Loan_Prediction.html

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}
.glyphicon-triangle-top:before {
  content: "\e253";
}
.glyphicon-console:before {
  content: "\e254";
}
.glyphicon-superscript:before {
  content: "\e255";
}
.glyphicon-subscript:before {
  content: "\e256";
}
.glyphicon-menu-left:before {
  content: "\e257";
}
.glyphicon-menu-right:before {
  content: "\e258";
}
.glyphicon-menu-down:before {
  content: "\e259";
}
.glyphicon-menu-up:before {
  content: "\e260";
}
* {
  -webkit-box-sizing: border-box;
  -moz-box-sizing: border-box;
  box-sizing: border-box;
}
*:before,
*:after {
  -webkit-box-sizing: border-box;
  -moz-box-sizing: border-box;
  box-sizing: border-box;
}
html {
  font-size: 10px;
  -webkit-tap-highlight-color: rgba(0, 0, 0, 0);
}
body {
  font-family: "Helvetica Neue", Helvetica, Arial, sans-serif;
  font-size: 13px;
  line-height: 1.42857143;
  color: #000;
  background-color: #fff;
}
input,
button,
select,
textarea {
  font-family: inherit;
  font-size: inherit;
  line-height: inherit;
}
a {
  color: #337ab7;
  text-decoration: none;
}
a:hover,
a:focus {
  color: #23527c;
  text-decoration: underline;
}
a:focus {
  outline: 5px auto -webkit-focus-ring-color;
  outline-offset: -2px;
}
figure {
  margin: 0;
}
img {
  vertical-align: middle;
}
.img-responsive,
.thumbnail > img,
.thumbnail a > img,
.carousel-inner > .item > img,
.carousel-inner > .item > a > img {
  display: block;
  max-width: 100%;
  height: auto;
}
.img-rounded {
  border-radius: 3px;
}
.img-thumbnail {
  padding: 4px;
  line-height: 1.42857143;
  background-color: #fff;
  border: 1px solid #ddd;
  border-radius: 2px;
  -webkit-transition: all 0.2s ease-in-out;
  -o-transition: all 0.2s ease-in-out;
  transition: all 0.2s ease-in-out;
  display: inline-block;
  max-width: 100%;
  height: auto;
}
.img-circle {
  border-radius: 50%;
}
hr {
  margin-top: 18px;
  margin-bottom: 18px;
  border: 0;
  border-top: 1px solid #eeeeee;
}
.sr-only {
  position: absolute;
  width: 1px;
  height: 1px;
  margin: -1px;
  padding: 0;
  overflow: hidden;
  clip: rect(0, 0, 0, 0);
  border: 0;
}
.sr-only-focusable:active,
.sr-only-focusable:focus {
  position: static;
  width: auto;
  height: auto;
  margin: 0;
  overflow: visible;
  clip: auto;
}
[role="button"] {
  cursor: pointer;
}
h1,
h2,
h3,
h4,
h5,
h6,
.h1,
.h2,
.h3,
.h4,
.h5,
.h6 {
  font-family: inherit;
  font-weight: 500;
  line-height: 1.1;
  color: inherit;
}
h1 small,
h2 small,
h3 small,
h4 small,
h5 small,
h6 small,
.h1 small,
.h2 small,
.h3 small,
.h4 small,
.h5 small,
.h6 small,
h1 .small,
h2 .small,
h3 .small,
h4 .small,
h5 .small,
h6 .small,
.h1 .small,
.h2 .small,
.h3 .small,
.h4 .small,
.h5 .small,
.h6 .small {
  font-weight: normal;
  line-height: 1;
  color: #777777;
}
h1,
.h1,
h2,
.h2,
h3,
.h3 {
  margin-top: 18px;
  margin-bottom: 9px;
}
h1 small,
.h1 small,
h2 small,
.h2 small,
h3 small,
.h3 small,
h1 .small,
.h1 .small,
h2 .small,
.h2 .small,
h3 .small,
.h3 .small {
  font-size: 65%;
}
h4,
.h4,
h5,
.h5,
h6,
.h6 {
  margin-top: 9px;
  margin-bottom: 9px;
}
h4 small,
.h4 small,
h5 small,
.h5 small,
h6 small,
.h6 small,
h4 .small,
.h4 .small,
h5 .small,
.h5 .small,
h6 .small,
.h6 .small {
  font-size: 75%;
}
h1,
.h1 {
  font-size: 33px;
}
h2,
.h2 {
  font-size: 27px;
}
h3,
.h3 {
  font-size: 23px;
}
h4,
.h4 {
  font-size: 17px;
}
h5,
.h5 {
  font-size: 13px;
}
h6,
.h6 {
  font-size: 12px;
}
p {
  margin: 0 0 9px;
}
.lead {
  margin-bottom: 18px;
  font-size: 14px;
  font-weight: 300;
  line-height: 1.4;
}
@media (min-width: 768px) {
  .lead {
    font-size: 19.5px;
  }
}
small,
.small {
  font-size: 92%;
}
mark,
.mark {
  background-color: #fcf8e3;
  padding: .2em;
}
.text-left {
  text-align: left;
}
.text-right {
  text-align: right;
}
.text-center {
  text-align: center;
}
.text-justify {
  text-align: justify;
}
.text-nowrap {
  white-space: nowrap;
}
.text-lowercase {
  text-transform: lowercase;
}
.text-uppercase {
  text-transform: uppercase;
}
.text-capitalize {
  text-transform: capitalize;
}
.text-muted {
  color: #777777;
}
.text-primary {
  color: #337ab7;
}
a.text-primary:hover,
a.text-primary:focus {
  color: #286090;
}
.text-success {
  color: #3c763d;
}
a.text-success:hover,
a.text-success:focus {
  color: #2b542c;
}
.text-info {
  color: #31708f;
}
a.text-info:hover,
a.text-info:focus {
  color: #245269;
}
.text-warning {
  color: #8a6d3b;
}
a.text-warning:hover,
a.text-warning:focus {
  color: #66512c;
}
.text-danger {
  color: #a94442;
}
a.text-danger:hover,
a.text-danger:focus {
  color: #843534;
}
.bg-primary {
  color: #fff;
  background-color: #337ab7;
}
a.bg-primary:hover,
a.bg-primary:focus {
  background-color: #286090;
}
.bg-success {
  background-color: #dff0d8;
}
a.bg-success:hover,
a.bg-success:focus {
  background-color: #c1e2b3;
}
.bg-info {
  background-color: #d9edf7;
}
a.bg-info:hover,
a.bg-info:focus {
  background-color: #afd9ee;
}
.bg-warning {
  background-color: #fcf8e3;
}
a.bg-warning:hover,
a.bg-warning:focus {
  background-color: #f7ecb5;
}
.bg-danger {
  background-color: #f2dede;
}
a.bg-danger:hover,
a.bg-danger:focus {
  background-color: #e4b9b9;
}
.page-header {
  padding-bottom: 8px;
  margin: 36px 0 18px;
  border-bottom: 1px solid #eeeeee;
}
ul,
ol {
  margin-top: 0;
  margin-bottom: 9px;
}
ul ul,
ol ul,
ul ol,
ol ol {
  margin-bottom: 0;
}
.list-unstyled {
  padding-left: 0;
  list-style: none;
}
.list-inline {
  padding-left: 0;
  list-style: none;
  margin-left: -5px;
}
.list-inline > li {
  display: inline-block;
  padding-left: 5px;
  padding-right: 5px;
}
dl {
  margin-top: 0;
  margin-bottom: 18px;
}
dt,
dd {
  line-height: 1.42857143;
}
dt {
  font-weight: bold;
}
dd {
  margin-left: 0;
}
@media (min-width: 541px) {
  .dl-horizontal dt {
    float: left;
    width: 160px;
    clear: left;
    text-align: right;
    overflow: hidden;
    text-overflow: ellipsis;
    white-space: nowrap;
  }
  .dl-horizontal dd {
    margin-left: 180px;
  }
}
abbr[title],
abbr[data-original-title] {
  cursor: help;
  border-bottom: 1px dotted #777777;
}
.initialism {
  font-size: 90%;
  text-transform: uppercase;
}
blockquote {
  padding: 9px 18px;
  margin: 0 0 18px;
  font-size: inherit;
  border-left: 5px solid #eeeeee;
}
blockquote p:last-child,
blockquote ul:last-child,
blockquote ol:last-child {
  margin-bottom: 0;
}
blockquote footer,
blockquote small,
blockquote .small {
  display: block;
  font-size: 80%;
  line-height: 1.42857143;
  color: #777777;
}
blockquote footer:before,
blockquote small:before,
blockquote .small:before {
  content: '\2014 \00A0';
}
.blockquote-reverse,
blockquote.pull-right {
  padding-right: 15px;
  padding-left: 0;
  border-right: 5px solid #eeeeee;
  border-left: 0;
  text-align: right;
}
.blockquote-reverse footer:before,
blockquote.pull-right footer:before,
.blockquote-reverse small:before,
blockquote.pull-right small:before,
.blockquote-reverse .small:before,
blockquote.pull-right .small:before {
  content: '';
}
.blockquote-reverse footer:after,
blockquote.pull-right footer:after,
.blockquote-reverse small:after,
blockquote.pull-right small:after,
.blockquote-reverse .small:after,
blockquote.pull-right .small:after {
  content: '\00A0 \2014';
}
address {
  margin-bottom: 18px;
  font-style: normal;
  line-height: 1.42857143;
}
code,
kbd,
pre,
samp {
  font-family: monospace;
}
code {
  padding: 2px 4px;
  font-size: 90%;
  color: #c7254e;
  background-color: #f9f2f4;
  border-radius: 2px;
}
kbd {
  padding: 2px 4px;
  font-size: 90%;
  color: #888;
  background-color: transparent;
  border-radius: 1px;
  box-shadow: inset 0 -1px 0 rgba(0, 0, 0, 0.25);
}
kbd kbd {
  padding: 0;
  font-size: 100%;
  font-weight: bold;
  box-shadow: none;
}
pre {
  display: block;
  padding: 8.5px;
  margin: 0 0 9px;
  font-size: 12px;
  line-height: 1.42857143;
  word-break: break-all;
  word-wrap: break-word;
  color: #333333;
  background-color: #f5f5f5;
  border: 1px solid #ccc;
  border-radius: 2px;
}
pre code {
  padding: 0;
  font-size: inherit;
  color: inherit;
  white-space: pre-wrap;
  background-color: transparent;
  border-radius: 0;
}
.pre-scrollable {
  max-height: 340px;
  overflow-y: scroll;
}
.container {
  margin-right: auto;
  margin-left: auto;
  padding-left: 0px;
  padding-right: 0px;
}
@media (min-width: 768px) {
  .container {
    width: 768px;
  }
}
@media (min-width: 992px) {
  .container {
    width: 940px;
  }
}
@media (min-width: 1200px) {
  .container {
    width: 1140px;
  }
}
.container-fluid {
  margin-right: auto;
  margin-left: auto;
  padding-left: 0px;
  padding-right: 0px;
}
.row {
  margin-left: 0px;
  margin-right: 0px;
}
.col-xs-1, .col-sm-1, .col-md-1, .col-lg-1, .col-xs-2, .col-sm-2, .col-md-2, .col-lg-2, .col-xs-3, .col-sm-3, .col-md-3, .col-lg-3, .col-xs-4, .col-sm-4, .col-md-4, .col-lg-4, .col-xs-5, .col-sm-5, .col-md-5, .col-lg-5, .col-xs-6, .col-sm-6, .col-md-6, .col-lg-6, .col-xs-7, .col-sm-7, .col-md-7, .col-lg-7, .col-xs-8, .col-sm-8, .col-md-8, .col-lg-8, .col-xs-9, .col-sm-9, .col-md-9, .col-lg-9, .col-xs-10, .col-sm-10, .col-md-10, .col-lg-10, .col-xs-11, .col-sm-11, .col-md-11, .col-lg-11, .col-xs-12, .col-sm-12, .col-md-12, .col-lg-12 {
  position: relative;
  min-height: 1px;
  padding-left: 0px;
  padding-right: 0px;
}
.col-xs-1, .col-xs-2, .col-xs-3, .col-xs-4, .col-xs-5, .col-xs-6, .col-xs-7, .col-xs-8, .col-xs-9, .col-xs-10, .col-xs-11, .col-xs-12 {
  float: left;
}
.col-xs-12 {
  width: 100%;
}
.col-xs-11 {
  width: 91.66666667%;
}
.col-xs-10 {
  width: 83.33333333%;
}
.col-xs-9 {
  width: 75%;
}
.col-xs-8 {
  width: 66.66666667%;
}
.col-xs-7 {
  width: 58.33333333%;
}
.col-xs-6 {
  width: 50%;
}
.col-xs-5 {
  width: 41.66666667%;
}
.col-xs-4 {
  width: 33.33333333%;
}
.col-xs-3 {
  width: 25%;
}
.col-xs-2 {
  width: 16.66666667%;
}
.col-xs-1 {
  width: 8.33333333%;
}
.col-xs-pull-12 {
  right: 100%;
}
.col-xs-pull-11 {
  right: 91.66666667%;
}
.col-xs-pull-10 {
  right: 83.33333333%;
}
.col-xs-pull-9 {
  right: 75%;
}
.col-xs-pull-8 {
  right: 66.66666667%;
}
.col-xs-pull-7 {
  right: 58.33333333%;
}
.col-xs-pull-6 {
  right: 50%;
}
.col-xs-pull-5 {
  right: 41.66666667%;
}
.col-xs-pull-4 {
  right: 33.33333333%;
}
.col-xs-pull-3 {
  right: 25%;
}
.col-xs-pull-2 {
  right: 16.66666667%;
}
.col-xs-pull-1 {
  right: 8.33333333%;
}
.col-xs-pull-0 {
  right: auto;
}
.col-xs-push-12 {
  left: 100%;
}
.col-xs-push-11 {
  left: 91.66666667%;
}
.col-xs-push-10 {
  left: 83.33333333%;
}
.col-xs-push-9 {
  left: 75%;
}
.col-xs-push-8 {
  left: 66.66666667%;
}
.col-xs-push-7 {
  left: 58.33333333%;
}
.col-xs-push-6 {
  left: 50%;
}
.col-xs-push-5 {
  left: 41.66666667%;
}
.col-xs-push-4 {
  left: 33.33333333%;
}
.col-xs-push-3 {
  left: 25%;
}
.col-xs-push-2 {
  left: 16.66666667%;
}
.col-xs-push-1 {
  left: 8.33333333%;
}
.col-xs-push-0 {
  left: auto;
}
.col-xs-offset-12 {
  margin-left: 100%;
}
.col-xs-offset-11 {
  margin-left: 91.66666667%;
}
.col-xs-offset-10 {
  margin-left: 83.33333333%;
}
.col-xs-offset-9 {
  margin-left: 75%;
}
.col-xs-offset-8 {
  margin-left: 66.66666667%;
}
.col-xs-offset-7 {
  margin-left: 58.33333333%;
}
.col-xs-offset-6 {
  margin-left: 50%;
}
.col-xs-offset-5 {
  margin-left: 41.66666667%;
}
.col-xs-offset-4 {
  margin-left: 33.33333333%;
}
.col-xs-offset-3 {
  margin-left: 25%;
}
.col-xs-offset-2 {
  margin-left: 16.66666667%;
}
.col-xs-offset-1 {
  margin-left: 8.33333333%;
}
.col-xs-offset-0 {
  margin-left: 0%;
}
@media (min-width: 768px) {
  .col-sm-1, .col-sm-2, .col-sm-3, .col-sm-4, .col-sm-5, .col-sm-6, .col-sm-7, .col-sm-8, .col-sm-9, .col-sm-10, .col-sm-11, .col-sm-12 {
    float: left;
  }
  .col-sm-12 {
    width: 100%;
  }
  .col-sm-11 {
    width: 91.66666667%;
  }
  .col-sm-10 {
    width: 83.33333333%;
  }
  .col-sm-9 {
    width: 75%;
  }
  .col-sm-8 {
    width: 66.66666667%;
  }
  .col-sm-7 {
    width: 58.33333333%;
  }
  .col-sm-6 {
    width: 50%;
  }
  .col-sm-5 {
    width: 41.66666667%;
  }
  .col-sm-4 {
    width: 33.33333333%;
  }
  .col-sm-3 {
    width: 25%;
  }
  .col-sm-2 {
    width: 16.66666667%;
  }
  .col-sm-1 {
    width: 8.33333333%;
  }
  .col-sm-pull-12 {
    right: 100%;
  }
  .col-sm-pull-11 {
    right: 91.66666667%;
  }
  .col-sm-pull-10 {
    right: 83.33333333%;
  }
  .col-sm-pull-9 {
    right: 75%;
  }
  .col-sm-pull-8 {
    right: 66.66666667%;
  }
  .col-sm-pull-7 {
    right: 58.33333333%;
  }
  .col-sm-pull-6 {
    right: 50%;
  }
  .col-sm-pull-5 {
    right: 41.66666667%;
  }
  .col-sm-pull-4 {
    right: 33.33333333%;
  }
  .col-sm-pull-3 {
    right: 25%;
  }
  .col-sm-pull-2 {
    right: 16.66666667%;
  }
  .col-sm-pull-1 {
    right: 8.33333333%;
  }
  .col-sm-pull-0 {
    right: auto;
  }
  .col-sm-push-12 {
    left: 100%;
  }
  .col-sm-push-11 {
    left: 91.66666667%;
  }
  .col-sm-push-10 {
    left: 83.33333333%;
  }
  .col-sm-push-9 {
    left: 75%;
  }
  .col-sm-push-8 {
    left: 66.66666667%;
  }
  .col-sm-push-7 {
    left: 58.33333333%;
  }
  .col-sm-push-6 {
    left: 50%;
  }
  .col-sm-push-5 {
    left: 41.66666667%;
  }
  .col-sm-push-4 {
    left: 33.33333333%;
  }
  .col-sm-push-3 {
    left: 25%;
  }
  .col-sm-push-2 {
    left: 16.66666667%;
  }
  .col-sm-push-1 {
    left: 8.33333333%;
  }
  .col-sm-push-0 {
    left: auto;
  }
  .col-sm-offset-12 {
    margin-left: 100%;
  }
  .col-sm-offset-11 {
    margin-left: 91.66666667%;
  }
  .col-sm-offset-10 {
    margin-left: 83.33333333%;
  }
  .col-sm-offset-9 {
    margin-left: 75%;
  }
  .col-sm-offset-8 {
    margin-left: 66.66666667%;
  }
  .col-sm-offset-7 {
    margin-left: 58.33333333%;
  }
  .col-sm-offset-6 {
    margin-left: 50%;
  }
  .col-sm-offset-5 {
    margin-left: 41.66666667%;
  }
  .col-sm-offset-4 {
    margin-left: 33.33333333%;
  }
  .col-sm-offset-3 {
    margin-left: 25%;
  }
  .col-sm-offset-2 {
    margin-left: 16.66666667%;
  }
  .col-sm-offset-1 {
    margin-left: 8.33333333%;
  }
  .col-sm-offset-0 {
    margin-left: 0%;
  }
}
@media (min-width: 992px) {
  .col-md-1, .col-md-2, .col-md-3, .col-md-4, .col-md-5, .col-md-6, .col-md-7, .col-md-8, .col-md-9, .col-md-10, .col-md-11, .col-md-12 {
    float: left;
  }
  .col-md-12 {
    width: 100%;
  }
  .col-md-11 {
    width: 91.66666667%;
  }
  .col-md-10 {
    width: 83.33333333%;
  }
  .col-md-9 {
    width: 75%;
  }
  .col-md-8 {
    width: 66.66666667%;
  }
  .col-md-7 {
    width: 58.33333333%;
  }
  .col-md-6 {
    width: 50%;
  }
  .col-md-5 {
    width: 41.66666667%;
  }
  .col-md-4 {
    width: 33.33333333%;
  }
  .col-md-3 {
    width: 25%;
  }
  .col-md-2 {
    width: 16.66666667%;
  }
  .col-md-1 {
    width: 8.33333333%;
  }
  .col-md-pull-12 {
    right: 100%;
  }
  .col-md-pull-11 {
    right: 91.66666667%;
  }
  .col-md-pull-10 {
    right: 83.33333333%;
  }
  .col-md-pull-9 {
    right: 75%;
  }
  .col-md-pull-8 {
    right: 66.66666667%;
  }
  .col-md-pull-7 {
    right: 58.33333333%;
  }
  .col-md-pull-6 {
    right: 50%;
  }
  .col-md-pull-5 {
    right: 41.66666667%;
  }
  .col-md-pull-4 {
    right: 33.33333333%;
  }
  .col-md-pull-3 {
    right: 25%;
  }
  .col-md-pull-2 {
    right: 16.66666667%;
  }
  .col-md-pull-1 {
    right: 8.33333333%;
  }
  .col-md-pull-0 {
    right: auto;
  }
  .col-md-push-12 {
    left: 100%;
  }
  .col-md-push-11 {
    left: 91.66666667%;
  }
  .col-md-push-10 {
    left: 83.33333333%;
  }
  .col-md-push-9 {
    left: 75%;
  }
  .col-md-push-8 {
    left: 66.66666667%;
  }
  .col-md-push-7 {
    left: 58.33333333%;
  }
  .col-md-push-6 {
    left: 50%;
  }
  .col-md-push-5 {
    left: 41.66666667%;
  }
  .col-md-push-4 {
    left: 33.33333333%;
  }
  .col-md-push-3 {
    left: 25%;
  }
  .col-md-push-2 {
    left: 16.66666667%;
  }
  .col-md-push-1 {
    left: 8.33333333%;
  }
  .col-md-push-0 {
    left: auto;
  }
  .col-md-offset-12 {
    margin-left: 100%;
  }
  .col-md-offset-11 {
    margin-left: 91.66666667%;
  }
  .col-md-offset-10 {
    margin-left: 83.33333333%;
  }
  .col-md-offset-9 {
    margin-left: 75%;
  }
  .col-md-offset-8 {
    margin-left: 66.66666667%;
  }
  .col-md-offset-7 {
    margin-left: 58.33333333%;
  }
  .col-md-offset-6 {
    margin-left: 50%;
  }
  .col-md-offset-5 {
    margin-left: 41.66666667%;
  }
  .col-md-offset-4 {
    margin-left: 33.33333333%;
  }
  .col-md-offset-3 {
    margin-left: 25%;
  }
  .col-md-offset-2 {
    margin-left: 16.66666667%;
  }
  .col-md-offset-1 {
    margin-left: 8.33333333%;
  }
  .col-md-offset-0 {
    margin-left: 0%;
  }
}
@media (min-width: 1200px) {
  .col-lg-1, .col-lg-2, .col-lg-3, .col-lg-4, .col-lg-5, .col-lg-6, .col-lg-7, .col-lg-8, .col-lg-9, .col-lg-10, .col-lg-11, .col-lg-12 {
    float: left;
  }
  .col-lg-12 {
    width: 100%;
  }
  .col-lg-11 {
    width: 91.66666667%;
  }
  .col-lg-10 {
    width: 83.33333333%;
  }
  .col-lg-9 {
    width: 75%;
  }
  .col-lg-8 {
    width: 66.66666667%;
  }
  .col-lg-7 {
    width: 58.33333333%;
  }
  .col-lg-6 {
    width: 50%;
  }
  .col-lg-5 {
    width: 41.66666667%;
  }
  .col-lg-4 {
    width: 33.33333333%;
  }
  .col-lg-3 {
    width: 25%;
  }
  .col-lg-2 {
    width: 16.66666667%;
  }
  .col-lg-1 {
    width: 8.33333333%;
  }
  .col-lg-pull-12 {
    right: 100%;
  }
  .col-lg-pull-11 {
    right: 91.66666667%;
  }
  .col-lg-pull-10 {
    right: 83.33333333%;
  }
  .col-lg-pull-9 {
    right: 75%;
  }
  .col-lg-pull-8 {
    right: 66.66666667%;
  }
  .col-lg-pull-7 {
    right: 58.33333333%;
  }
  .col-lg-pull-6 {
    right: 50%;
  }
  .col-lg-pull-5 {
    right: 41.66666667%;
  }
  .col-lg-pull-4 {
    right: 33.33333333%;
  }
  .col-lg-pull-3 {
    right: 25%;
  }
  .col-lg-pull-2 {
    right: 16.66666667%;
  }
  .col-lg-pull-1 {
    right: 8.33333333%;
  }
  .col-lg-pull-0 {
    right: auto;
  }
  .col-lg-push-12 {
    left: 100%;
  }
  .col-lg-push-11 {
    left: 91.66666667%;
  }
  .col-lg-push-10 {
    left: 83.33333333%;
  }
  .col-lg-push-9 {
    left: 75%;
  }
  .col-lg-push-8 {
    left: 66.66666667%;
  }
  .col-lg-push-7 {
    left: 58.33333333%;
  }
  .col-lg-push-6 {
    left: 50%;
  }
  .col-lg-push-5 {
    left: 41.66666667%;
  }
  .col-lg-push-4 {
    left: 33.33333333%;
  }
  .col-lg-push-3 {
    left: 25%;
  }
  .col-lg-push-2 {
    left: 16.66666667%;
  }
  .col-lg-push-1 {
    left: 8.33333333%;
  }
  .col-lg-push-0 {
    left: auto;
  }
  .col-lg-offset-12 {
    margin-left: 100%;
  }
  .col-lg-offset-11 {
    margin-left: 91.66666667%;
  }
  .col-lg-offset-10 {
    margin-left: 83.33333333%;
  }
  .col-lg-offset-9 {
    margin-left: 75%;
  }
  .col-lg-offset-8 {
    margin-left: 66.66666667%;
  }
  .col-lg-offset-7 {
    margin-left: 58.33333333%;
  }
  .col-lg-offset-6 {
    margin-left: 50%;
  }
  .col-lg-offset-5 {
    margin-left: 41.66666667%;
  }
  .col-lg-offset-4 {
    margin-left: 33.33333333%;
  }
  .col-lg-offset-3 {
    margin-left: 25%;
  }
  .col-lg-offset-2 {
    margin-left: 16.66666667%;
  }
  .col-lg-offset-1 {
    margin-left: 8.33333333%;
  }
  .col-lg-offset-0 {
    margin-left: 0%;
  }
}
table {
  background-color: transparent;
}
caption {
  padding-top: 8px;
  padding-bottom: 8px;
  color: #777777;
  text-align: left;
}
th {
  text-align: left;
}
.table {
  width: 100%;
  max-width: 100%;
  margin-bottom: 18px;
}
.table > thead > tr > th,
.table > tbody > tr > th,
.table > tfoot > tr > th,
.table > thead > tr > td,
.table > tbody > tr > td,
.table > tfoot > tr > td {
  padding: 8px;
  line-height: 1.42857143;
  vertical-align: top;
  border-top: 1px solid #ddd;
}
.table > thead > tr > th {
  vertical-align: bottom;
  border-bottom: 2px solid #ddd;
}
.table > caption + thead > tr:first-child > th,
.table > colgroup + thead > tr:first-child > th,
.table > thead:first-child > tr:first-child > th,
.table > caption + thead > tr:first-child > td,
.table > colgroup + thead > tr:first-child > td,
.table > thead:first-child > tr:first-child > td {
  border-top: 0;
}
.table > tbody + tbody {
  border-top: 2px solid #ddd;
}
.table .table {
  background-color: #fff;
}
.table-condensed > thead > tr > th,
.table-condensed > tbody > tr > th,
.table-condensed > tfoot > tr > th,
.table-condensed > thead > tr > td,
.table-condensed > tbody > tr > td,
.table-condensed > tfoot > tr > td {
  padding: 5px;
}
.table-bordered {
  border: 1px solid #ddd;
}
.table-bordered > thead > tr > th,
.table-bordered > tbody > tr > th,
.table-bordered > tfoot > tr > th,
.table-bordered > thead > tr > td,
.table-bordered > tbody > tr > td,
.table-bordered > tfoot > tr > td {
  border: 1px solid #ddd;
}
.table-bordered > thead > tr > th,
.table-bordered > thead > tr > td {
  border-bottom-width: 2px;
}
.table-striped > tbody > tr:nth-of-type(odd) {
  background-color: #f9f9f9;
}
.table-hover > tbody > tr:hover {
  background-color: #f5f5f5;
}
table col[class*="col-"] {
  position: static;
  float: none;
  display: table-column;
}
table td[class*="col-"],
table th[class*="col-"] {
  position: static;
  float: none;
  display: table-cell;
}
.table > thead > tr > td.active,
.table > tbody > tr > td.active,
.table > tfoot > tr > td.active,
.table > thead > tr > th.active,
.table > tbody > tr > th.active,
.table > tfoot > tr > th.active,
.table > thead > tr.active > td,
.table > tbody > tr.active > td,
.table > tfoot > tr.active > td,
.table > thead > tr.active > th,
.table > tbody > tr.active > th,
.table > tfoot > tr.active > th {
  background-color: #f5f5f5;
}
.table-hover > tbody > tr > td.active:hover,
.table-hover > tbody > tr > th.active:hover,
.table-hover > tbody > tr.active:hover > td,
.table-hover > tbody > tr:hover > .active,
.table-hover > tbody > tr.active:hover > th {
  background-color: #e8e8e8;
}
.table > thead > tr > td.success,
.table > tbody > tr > td.success,
.table > tfoot > tr > td.success,
.table > thead > tr > th.success,
.table > tbody > tr > th.success,
.table > tfoot > tr > th.success,
.table > thead > tr.success > td,
.table > tbody > tr.success > td,
.table > tfoot > tr.success > td,
.table > thead > tr.success > th,
.table > tbody > tr.success > th,
.table > tfoot > tr.success > th {
  background-color: #dff0d8;
}
.table-hover > tbody > tr > td.success:hover,
.table-hover > tbody > tr > th.success:hover,
.table-hover > tbody > tr.success:hover > td,
.table-hover > tbody > tr:hover > .success,
.table-hover > tbody > tr.success:hover > th {
  background-color: #d0e9c6;
}
.table > thead > tr > td.info,
.table > tbody > tr > td.info,
.table > tfoot > tr > td.info,
.table > thead > tr > th.info,
.table > tbody > tr > th.info,
.table > tfoot > tr > th.info,
.table > thead > tr.info > td,
.table > tbody > tr.info > td,
.table > tfoot > tr.info > td,
.table > thead > tr.info > th,
.table > tbody > tr.info > th,
.table > tfoot > tr.info > th {
  background-color: #d9edf7;
}
.table-hover > tbody > tr > td.info:hover,
.table-hover > tbody > tr > th.info:hover,
.table-hover > tbody > tr.info:hover > td,
.table-hover > tbody > tr:hover > .info,
.table-hover > tbody > tr.info:hover > th {
  background-color: #c4e3f3;
}
.table > thead > tr > td.warning,
.table > tbody > tr > td.warning,
.table > tfoot > tr > td.warning,
.table > thead > tr > th.warning,
.table > tbody > tr > th.warning,
.table > tfoot > tr > th.warning,
.table > thead > tr.warning > td,
.table > tbody > tr.warning > td,
.table > tfoot > tr.warning > td,
.table > thead > tr.warning > th,
.table > tbody > tr.warning > th,
.table > tfoot > tr.warning > th {
  background-color: #fcf8e3;
}
.table-hover > tbody > tr > td.warning:hover,
.table-hover > tbody > tr > th.warning:hover,
.table-hover > tbody > tr.warning:hover > td,
.table-hover > tbody > tr:hover > .warning,
.table-hover > tbody > tr.warning:hover > th {
  background-color: #faf2cc;
}
.table > thead > tr > td.danger,
.table > tbody > tr > td.danger,
.table > tfoot > tr > td.danger,
.table > thead > tr > th.danger,
.table > tbody > tr > th.danger,
.table > tfoot > tr > th.danger,
.table > thead > tr.danger > td,
.table > tbody > tr.danger > td,
.table > tfoot > tr.danger > td,
.table > thead > tr.danger > th,
.table > tbody > tr.danger > th,
.table > tfoot > tr.danger > th {
  background-color: #f2dede;
}
.table-hover > tbody > tr > td.danger:hover,
.table-hover > tbody > tr > th.danger:hover,
.table-hover > tbody > tr.danger:hover > td,
.table-hover > tbody > tr:hover > .danger,
.table-hover > tbody > tr.danger:hover > th {
  background-color: #ebcccc;
}
.table-responsive {
  overflow-x: auto;
  min-height: 0.01%;
}
@media screen and (max-width: 767px) {
  .table-responsive {
    width: 100%;
    margin-bottom: 13.5px;
    overflow-y: hidden;
    -ms-overflow-style: -ms-autohiding-scrollbar;
    border: 1px solid #ddd;
  }
  .table-responsive > .table {
    margin-bottom: 0;
  }
  .table-responsive > .table > thead > tr > th,
  .table-responsive > .table > tbody > tr > th,
  .table-responsive > .table > tfoot > tr > th,
  .table-responsive > .table > thead > tr > td,
  .table-responsive > .table > tbody > tr > td,
  .table-responsive > .table > tfoot > tr > td {
    white-space: nowrap;
  }
  .table-responsive > .table-bordered {
    border: 0;
  }
  .table-responsive > .table-bordered > thead > tr > th:first-child,
  .table-responsive > .table-bordered > tbody > tr > th:first-child,
  .table-responsive > .table-bordered > tfoot > tr > th:first-child,
  .table-responsive > .table-bordered > thead > tr > td:first-child,
  .table-responsive > .table-bordered > tbody > tr > td:first-child,
  .table-responsive > .table-bordered > tfoot > tr > td:first-child {
    border-left: 0;
  }
  .table-responsive > .table-bordered > thead > tr > th:last-child,
  .table-responsive > .table-bordered > tbody > tr > th:last-child,
  .table-responsive > .table-bordered > tfoot > tr > th:last-child,
  .table-responsive > .table-bordered > thead > tr > td:last-child,
  .table-responsive > .table-bordered > tbody > tr > td:last-child,
  .table-responsive > .table-bordered > tfoot > tr > td:last-child {
    border-right: 0;
  }
  .table-responsive > .table-bordered > tbody > tr:last-child > th,
  .table-responsive > .table-bordered > tfoot > tr:last-child > th,
  .table-responsive > .table-bordered > tbody > tr:last-child > td,
  .table-responsive > .table-bordered > tfoot > tr:last-child > td {
    border-bottom: 0;
  }
}
fieldset {
  padding: 0;
  margin: 0;
  border: 0;
  min-width: 0;
}
legend {
  display: block;
  width: 100%;
  padding: 0;
  margin-bottom: 18px;
  font-size: 19.5px;
  line-height: inherit;
  color: #333333;
  border: 0;
  border-bottom: 1px solid #e5e5e5;
}
label {
  display: inline-block;
  max-width: 100%;
  margin-bottom: 5px;
  font-weight: bold;
}
input[type="search"] {
  -webkit-box-sizing: border-box;
  -moz-box-sizing: border-box;
  box-sizing: border-box;
}
input[type="radio"],
input[type="checkbox"] {
  margin: 4px 0 0;
  margin-top: 1px \9;
  line-height: normal;
}
input[type="file"] {
  display: block;
}
input[type="range"] {
  display: block;
  width: 100%;
}
select[multiple],
select[size] {
  height: auto;
}
input[type="file"]:focus,
input[type="radio"]:focus,
input[type="checkbox"]:focus {
  outline: 5px auto -webkit-focus-ring-color;
  outline-offset: -2px;
}
output {
  display: block;
  padding-top: 7px;
  font-size: 13px;
  line-height: 1.42857143;
  color: #555555;
}
.form-control {
  display: block;
  width: 100%;
  height: 32px;
  padding: 6px 12px;
  font-size: 13px;
  line-height: 1.42857143;
  color: #555555;
  background-color: #fff;
  background-image: none;
  border: 1px solid #ccc;
  border-radius: 2px;
  -webkit-box-shadow: inset 0 1px 1px rgba(0, 0, 0, 0.075);
  box-shadow: inset 0 1px 1px rgba(0, 0, 0, 0.075);
  -webkit-transition: border-color ease-in-out .15s, box-shadow ease-in-out .15s;
  -o-transition: border-color ease-in-out .15s, box-shadow ease-in-out .15s;
  transition: border-color ease-in-out .15s, box-shadow ease-in-out .15s;
}
.form-control:focus {
  border-color: #66afe9;
  outline: 0;
  -webkit-box-shadow: inset 0 1px 1px rgba(0,0,0,.075), 0 0 8px rgba(102, 175, 233, 0.6);
  box-shadow: inset 0 1px 1px rgba(0,0,0,.075), 0 0 8px rgba(102, 175, 233, 0.6);
}
.form-control::-moz-placeholder {
  color: #999;
  opacity: 1;
}
.form-control:-ms-input-placeholder {
  color: #999;
}
.form-control::-webkit-input-placeholder {
  color: #999;
}
.form-control::-ms-expand {
  border: 0;
  background-color: transparent;
}
.form-control[disabled],
.form-control[readonly],
fieldset[disabled] .form-control {
  background-color: #eeeeee;
  opacity: 1;
}
.form-control[disabled],
fieldset[disabled] .form-control {
  cursor: not-allowed;
}
textarea.form-control {
  height: auto;
}
input[type="search"] {
  -webkit-appearance: none;
}
@media screen and (-webkit-min-device-pixel-ratio: 0) {
  input[type="date"].form-control,
  input[type="time"].form-control,
  input[type="datetime-local"].form-control,
  input[type="month"].form-control {
    line-height: 32px;
  }
  input[type="date"].input-sm,
  input[type="time"].input-sm,
  input[type="datetime-local"].input-sm,
  input[type="month"].input-sm,
  .input-group-sm input[type="date"],
  .input-group-sm input[type="time"],
  .input-group-sm input[type="datetime-local"],
  .input-group-sm input[type="month"] {
    line-height: 30px;
  }
  input[type="date"].input-lg,
  input[type="time"].input-lg,
  input[type="datetime-local"].input-lg,
  input[type="month"].input-lg,
  .input-group-lg input[type="date"],
  .input-group-lg input[type="time"],
  .input-group-lg input[type="datetime-local"],
  .input-group-lg input[type="month"] {
    line-height: 45px;
  }
}
.form-group {
  margin-bottom: 15px;
}
.radio,
.checkbox {
  position: relative;
  display: block;
  margin-top: 10px;
  margin-bottom: 10px;
}
.radio label,
.checkbox label {
  min-height: 18px;
  padding-left: 20px;
  margin-bottom: 0;
  font-weight: normal;
  cursor: pointer;
}
.radio input[type="radio"],
.radio-inline input[type="radio"],
.checkbox input[type="checkbox"],
.checkbox-inline input[type="checkbox"] {
  position: absolute;
  margin-left: -20px;
  margin-top: 4px \9;
}
.radio + .radio,
.checkbox + .checkbox {
  margin-top: -5px;
}
.radio-inline,
.checkbox-inline {
  position: relative;
  display: inline-block;
  padding-left: 20px;
  margin-bottom: 0;
  vertical-align: middle;
  font-weight: normal;
  cursor: pointer;
}
.radio-inline + .radio-inline,
.checkbox-inline + .checkbox-inline {
  margin-top: 0;
  margin-left: 10px;
}
input[type="radio"][disabled],
input[type="checkbox"][disabled],
input[type="radio"].disabled,
input[type="checkbox"].disabled,
fieldset[disabled] input[type="radio"],
fieldset[disabled] input[type="checkbox"] {
  cursor: not-allowed;
}
.radio-inline.disabled,
.checkbox-inline.disabled,
fieldset[disabled] .radio-inline,
fieldset[disabled] .checkbox-inline {
  cursor: not-allowed;
}
.radio.disabled label,
.checkbox.disabled label,
fieldset[disabled] .radio label,
fieldset[disabled] .checkbox label {
  cursor: not-allowed;
}
.form-control-static {
  padding-top: 7px;
  padding-bottom: 7px;
  margin-bottom: 0;
  min-height: 31px;
}
.form-control-static.input-lg,
.form-control-static.input-sm {
  padding-left: 0;
  padding-right: 0;
}
.input-sm {
  height: 30px;
  padding: 5px 10px;
  font-size: 12px;
  line-height: 1.5;
  border-radius: 1px;
}
select.input-sm {
  height: 30px;
  line-height: 30px;
}
textarea.input-sm,
select[multiple].input-sm {
  height: auto;
}
.form-group-sm .form-control {
  height: 30px;
  padding: 5px 10px;
  font-size: 12px;
  line-height: 1.5;
  border-radius: 1px;
}
.form-group-sm select.form-control {
  height: 30px;
  line-height: 30px;
}
.form-group-sm textarea.form-control,
.form-group-sm select[multiple].form-control {
  height: auto;
}
.form-group-sm .form-control-static {
  height: 30px;
  min-height: 30px;
  padding: 6px 10px;
  font-size: 12px;
  line-height: 1.5;
}
.input-lg {
  height: 45px;
  padding: 10px 16px;
  font-size: 17px;
  line-height: 1.3333333;
  border-radius: 3px;
}
select.input-lg {
  height: 45px;
  line-height: 45px;
}
textarea.input-lg,
select[multiple].input-lg {
  height: auto;
}
.form-group-lg .form-control {
  height: 45px;
  padding: 10px 16px;
  font-size: 17px;
  line-height: 1.3333333;
  border-radius: 3px;
}
.form-group-lg select.form-control {
  height: 45px;
  line-height: 45px;
}
.form-group-lg textarea.form-control,
.form-group-lg select[multiple].form-control {
  height: auto;
}
.form-group-lg .form-control-static {
  height: 45px;
  min-height: 35px;
  padding: 11px 16px;
  font-size: 17px;
  line-height: 1.3333333;
}
.has-feedback {
  position: relative;
}
.has-feedback .form-control {
  padding-right: 40px;
}
.form-control-feedback {
  position: absolute;
  top: 0;
  right: 0;
  z-index: 2;
  display: block;
  width: 32px;
  height: 32px;
  line-height: 32px;
  text-align: center;
  pointer-events: none;
}
.input-lg + .form-control-feedback,
.input-group-lg + .form-control-feedback,
.form-group-lg .form-control + .form-control-feedback {
  width: 45px;
  height: 45px;
  line-height: 45px;
}
.input-sm + .form-control-feedback,
.input-group-sm + .form-control-feedback,
.form-group-sm .form-control + .form-control-feedback {
  width: 30px;
  height: 30px;
  line-height: 30px;
}
.has-success .help-block,
.has-success .control-label,
.has-success .radio,
.has-success .checkbox,
.has-success .radio-inline,
.has-success .checkbox-inline,
.has-success.radio label,
.has-success.checkbox label,
.has-success.radio-inline label,
.has-success.checkbox-inline label {
  color: #3c763d;
}
.has-success .form-control {
  border-color: #3c763d;
  -webkit-box-shadow: inset 0 1px 1px rgba(0, 0, 0, 0.075);
  box-shadow: inset 0 1px 1px rgba(0, 0, 0, 0.075);
}
.has-success .form-control:focus {
  border-color: #2b542c;
  -webkit-box-shadow: inset 0 1px 1px rgba(0, 0, 0, 0.075), 0 0 6px #67b168;
  box-shadow: inset 0 1px 1px rgba(0, 0, 0, 0.075), 0 0 6px #67b168;
}
.has-success .input-group-addon {
  color: #3c763d;
  border-color: #3c763d;
  background-color: #dff0d8;
}
.has-success .form-control-feedback {
  color: #3c763d;
}
.has-warning .help-block,
.has-warning .control-label,
.has-warning .radio,
.has-warning .checkbox,
.has-warning .radio-inline,
.has-warning .checkbox-inline,
.has-warning.radio label,
.has-warning.checkbox label,
.has-warning.radio-inline label,
.has-warning.checkbox-inline label {
  color: #8a6d3b;
}
.has-warning .form-control {
  border-color: #8a6d3b;
  -webkit-box-shadow: inset 0 1px 1px rgba(0, 0, 0, 0.075);
  box-shadow: inset 0 1px 1px rgba(0, 0, 0, 0.075);
}
.has-warning .form-control:focus {
  border-color: #66512c;
  -webkit-box-shadow: inset 0 1px 1px rgba(0, 0, 0, 0.075), 0 0 6px #c0a16b;
  box-shadow: inset 0 1px 1px rgba(0, 0, 0, 0.075), 0 0 6px #c0a16b;
}
.has-warning .input-group-addon {
  color: #8a6d3b;
  border-color: #8a6d3b;
  background-color: #fcf8e3;
}
.has-warning .form-control-feedback {
  color: #8a6d3b;
}
.has-error .help-block,
.has-error .control-label,
.has-error .radio,
.has-error .checkbox,
.has-error .radio-inline,
.has-error .checkbox-inline,
.has-error.radio label,
.has-error.checkbox label,
.has-error.radio-inline label,
.has-error.checkbox-inline label {
  color: #a94442;
}
.has-error .form-control {
  border-color: #a94442;
  -webkit-box-shadow: inset 0 1px 1px rgba(0, 0, 0, 0.075);
  box-shadow: inset 0 1px 1px rgba(0, 0, 0, 0.075);
}
.has-error .form-control:focus {
  border-color: #843534;
  -webkit-box-shadow: inset 0 1px 1px rgba(0, 0, 0, 0.075), 0 0 6px #ce8483;
  box-shadow: inset 0 1px 1px rgba(0, 0, 0, 0.075), 0 0 6px #ce8483;
}
.has-error .input-group-addon {
  color: #a94442;
  border-color: #a94442;
  background-color: #f2dede;
}
.has-error .form-control-feedback {
  color: #a94442;
}
.has-feedback label ~ .form-control-feedback {
  top: 23px;
}
.has-feedback label.sr-only ~ .form-control-feedback {
  top: 0;
}
.help-block {
  display: block;
  margin-top: 5px;
  margin-bottom: 10px;
  color: #404040;
}
@media (min-width: 768px) {
  .form-inline .form-group {
    display: inline-block;
    margin-bottom: 0;
    vertical-align: middle;
  }
  .form-inline .form-control {
    display: inline-block;
    width: auto;
    vertical-align: middle;
  }
  .form-inline .form-control-static {
    display: inline-block;
  }
  .form-inline .input-group {
    display: inline-table;
    vertical-align: middle;
  }
  .form-inline .input-group .input-group-addon,
  .form-inline .input-group .input-group-btn,
  .form-inline .input-group .form-control {
    width: auto;
  }
  .form-inline .input-group > .form-control {
    width: 100%;
  }
  .form-inline .control-label {
    margin-bottom: 0;
    vertical-align: middle;
  }
  .form-inline .radio,
  .form-inline .checkbox {
    display: inline-block;
    margin-top: 0;
    margin-bottom: 0;
    vertical-align: middle;
  }
  .form-inline .radio label,
  .form-inline .checkbox label {
    padding-left: 0;
  }
  .form-inline .radio input[type="radio"],
  .form-inline .checkbox input[type="checkbox"] {
    position: relative;
    margin-left: 0;
  }
  .form-inline .has-feedback .form-control-feedback {
    top: 0;
  }
}
.form-horizontal .radio,
.form-horizontal .checkbox,
.form-horizontal .radio-inline,
.form-horizontal .checkbox-inline {
  margin-top: 0;
  margin-bottom: 0;
  padding-top: 7px;
}
.form-horizontal .radio,
.form-horizontal .checkbox {
  min-height: 25px;
}
.form-horizontal .form-group {
  margin-left: 0px;
  margin-right: 0px;
}
@media (min-width: 768px) {
  .form-horizontal .control-label {
    text-align: right;
    margin-bottom: 0;
    padding-top: 7px;
  }
}
.form-horizontal .has-feedback .form-control-feedback {
  right: 0px;
}
@media (min-width: 768px) {
  .form-horizontal .form-group-lg .control-label {
    padding-top: 11px;
    font-size: 17px;
  }
}
@media (min-width: 768px) {
  .form-horizontal .form-group-sm .control-label {
    padding-top: 6px;
    font-size: 12px;
  }
}
.btn {
  display: inline-block;
  margin-bottom: 0;
  font-weight: normal;
  text-align: center;
  vertical-align: middle;
  touch-action: manipulation;
  cursor: pointer;
  background-image: none;
  border: 1px solid transparent;
  white-space: nowrap;
  padding: 6px 12px;
  font-size: 13px;
  line-height: 1.42857143;
  border-radius: 2px;
  -webkit-user-select: none;
  -moz-user-select: none;
  -ms-user-select: none;
  user-select: none;
}
.btn:focus,
.btn:active:focus,
.btn.active:focus,
.btn.focus,
.btn:active.focus,
.btn.active.focus {
  outline: 5px auto -webkit-focus-ring-color;
  outline-offset: -2px;
}
.btn:hover,
.btn:focus,
.btn.focus {
  color: #333;
  text-decoration: none;
}
.btn:active,
.btn.active {
  outline: 0;
  background-image: none;
  -webkit-box-shadow: inset 0 3px 5px rgba(0, 0, 0, 0.125);
  box-shadow: inset 0 3px 5px rgba(0, 0, 0, 0.125);
}
.btn.disabled,
.btn[disabled],
fieldset[disabled] .btn {
  cursor: not-allowed;
  opacity: 0.65;
  filter: alpha(opacity=65);
  -webkit-box-shadow: none;
  box-shadow: none;
}
a.btn.disabled,
fieldset[disabled] a.btn {
  pointer-events: none;
}
.btn-default {
  color: #333;
  background-color: #fff;
  border-color: #ccc;
}
.btn-default:focus,
.btn-default.focus {
  color: #333;
  background-color: #e6e6e6;
  border-color: #8c8c8c;
}
.btn-default:hover {
  color: #333;
  background-color: #e6e6e6;
  border-color: #adadad;
}
.btn-default:active,
.btn-default.active,
.open > .dropdown-toggle.btn-default {
  color: #333;
  background-color: #e6e6e6;
  border-color: #adadad;
}
.btn-default:active:hover,
.btn-default.active:hover,
.open > .dropdown-toggle.btn-default:hover,
.btn-default:active:focus,
.btn-default.active:focus,
.open > .dropdown-toggle.btn-default:focus,
.btn-default:active.focus,
.btn-default.active.focus,
.open > .dropdown-toggle.btn-default.focus {
  color: #333;
  background-color: #d4d4d4;
  border-color: #8c8c8c;
}
.btn-default:active,
.btn-default.active,
.open > .dropdown-toggle.btn-default {
  background-image: none;
}
.btn-default.disabled:hover,
.btn-default[disabled]:hover,
fieldset[disabled] .btn-default:hover,
.btn-default.disabled:focus,
.btn-default[disabled]:focus,
fieldset[disabled] .btn-default:focus,
.btn-default.disabled.focus,
.btn-default[disabled].focus,
fieldset[disabled] .btn-default.focus {
  background-color: #fff;
  border-color: #ccc;
}
.btn-default .badge {
  color: #fff;
  background-color: #333;
}
.btn-primary {
  color: #fff;
  background-color: #337ab7;
  border-color: #2e6da4;
}
.btn-primary:focus,
.btn-primary.focus {
  color: #fff;
  background-color: #286090;
  border-color: #122b40;
}
.btn-primary:hover {
  color: #fff;
  background-color: #286090;
  border-color: #204d74;
}
.btn-primary:active,
.btn-primary.active,
.open > .dropdown-toggle.btn-primary {
  color: #fff;
  background-color: #286090;
  border-color: #204d74;
}
.btn-primary:active:hover,
.btn-primary.active:hover,
.open > .dropdown-toggle.btn-primary:hover,
.btn-primary:active:focus,
.btn-primary.active:focus,
.open > .dropdown-toggle.btn-primary:focus,
.btn-primary:active.focus,
.btn-primary.active.focus,
.open > .dropdown-toggle.btn-primary.focus {
  color: #fff;
  background-color: #204d74;
  border-color: #122b40;
}
.btn-primary:active,
.btn-primary.active,
.open > .dropdown-toggle.btn-primary {
  background-image: none;
}
.btn-primary.disabled:hover,
.btn-primary[disabled]:hover,
fieldset[disabled] .btn-primary:hover,
.btn-primary.disabled:focus,
.btn-primary[disabled]:focus,
fieldset[disabled] .btn-primary:focus,
.btn-primary.disabled.focus,
.btn-primary[disabled].focus,
fieldset[disabled] .btn-primary.focus {
  background-color: #337ab7;
  border-color: #2e6da4;
}
.btn-primary .badge {
  color: #337ab7;
  background-color: #fff;
}
.btn-success {
  color: #fff;
  background-color: #5cb85c;
  border-color: #4cae4c;
}
.btn-success:focus,
.btn-success.focus {
  color: #fff;
  background-color: #449d44;
  border-color: #255625;
}
.btn-success:hover {
  color: #fff;
  background-color: #449d44;
  border-color: #398439;
}
.btn-success:active,
.btn-success.active,
.open > .dropdown-toggle.btn-success {
  color: #fff;
  background-color: #449d44;
  border-color: #398439;
}
.btn-success:active:hover,
.btn-success.active:hover,
.open > .dropdown-toggle.btn-success:hover,
.btn-success:active:focus,
.btn-success.active:focus,
.open > .dropdown-toggle.btn-success:focus,
.btn-success:active.focus,
.btn-success.active.focus,
.open > .dropdown-toggle.btn-success.focus {
  color: #fff;
  background-color: #398439;
  border-color: #255625;
}
.btn-success:active,
.btn-success.active,
.open > .dropdown-toggle.btn-success {
  background-image: none;
}
.btn-success.disabled:hover,
.btn-success[disabled]:hover,
fieldset[disabled] .btn-success:hover,
.btn-success.disabled:focus,
.btn-success[disabled]:focus,
fieldset[disabled] .btn-success:focus,
.btn-success.disabled.focus,
.btn-success[disabled].focus,
fieldset[disabled] .btn-success.focus {
  background-color: #5cb85c;
  border-color: #4cae4c;
}
.btn-success .badge {
  color: #5cb85c;
  background-color: #fff;
}
.btn-info {
  color: #fff;
  background-color: #5bc0de;
  border-color: #46b8da;
}
.btn-info:focus,
.btn-info.focus {
  color: #fff;
  background-color: #31b0d5;
  border-color: #1b6d85;
}
.btn-info:hover {
  color: #fff;
  background-color: #31b0d5;
  border-color: #269abc;
}
.btn-info:active,
.btn-info.active,
.open > .dropdown-toggle.btn-info {
  color: #fff;
  background-color: #31b0d5;
  border-color: #269abc;
}
.btn-info:active:hover,
.btn-info.active:hover,
.open > .dropdown-toggle.btn-info:hover,
.btn-info:active:focus,
.btn-info.active:focus,
.open > .dropdown-toggle.btn-info:focus,
.btn-info:active.focus,
.btn-info.active.focus,
.open > .dropdown-toggle.btn-info.focus {
  color: #fff;
  background-color: #269abc;
  border-color: #1b6d85;
}
.btn-info:active,
.btn-info.active,
.open > .dropdown-toggle.btn-info {
  background-image: none;
}
.btn-info.disabled:hover,
.btn-info[disabled]:hover,
fieldset[disabled] .btn-info:hover,
.btn-info.disabled:focus,
.btn-info[disabled]:focus,
fieldset[disabled] .btn-info:focus,
.btn-info.disabled.focus,
.btn-info[disabled].focus,
fieldset[disabled] .btn-info.focus {
  background-color: #5bc0de;
  border-color: #46b8da;
}
.btn-info .badge {
  color: #5bc0de;
  background-color: #fff;
}
.btn-warning {
  color: #fff;
  background-color: #f0ad4e;
  border-color: #eea236;
}
.btn-warning:focus,
.btn-warning.focus {
  color: #fff;
  background-color: #ec971f;
  border-color: #985f0d;
}
.btn-warning:hover {
  color: #fff;
  background-color: #ec971f;
  border-color: #d58512;
}
.btn-warning:active,
.btn-warning.active,
.open > .dropdown-toggle.btn-warning {
  color: #fff;
  background-color: #ec971f;
  border-color: #d58512;
}
.btn-warning:active:hover,
.btn-warning.active:hover,
.open > .dropdown-toggle.btn-warning:hover,
.btn-warning:active:focus,
.btn-warning.active:focus,
.open > .dropdown-toggle.btn-warning:focus,
.btn-warning:active.focus,
.btn-warning.active.focus,
.open > .dropdown-toggle.btn-warning.focus {
  color: #fff;
  background-color: #d58512;
  border-color: #985f0d;
}
.btn-warning:active,
.btn-warning.active,
.open > .dropdown-toggle.btn-warning {
  background-image: none;
}
.btn-warning.disabled:hover,
.btn-warning[disabled]:hover,
fieldset[disabled] .btn-warning:hover,
.btn-warning.disabled:focus,
.btn-warning[disabled]:focus,
fieldset[disabled] .btn-warning:focus,
.btn-warning.disabled.focus,
.btn-warning[disabled].focus,
fieldset[disabled] .btn-warning.focus {
  background-color: #f0ad4e;
  border-color: #eea236;
}
.btn-warning .badge {
  color: #f0ad4e;
  background-color: #fff;
}
.btn-danger {
  color: #fff;
  background-color: #d9534f;
  border-color: #d43f3a;
}
.btn-danger:focus,
.btn-danger.focus {
  color: #fff;
  background-color: #c9302c;
  border-color: #761c19;
}
.btn-danger:hover {
  color: #fff;
  background-color: #c9302c;
  border-color: #ac2925;
}
.btn-danger:active,
.btn-danger.active,
.open > .dropdown-toggle.btn-danger {
  color: #fff;
  background-color: #c9302c;
  border-color: #ac2925;
}
.btn-danger:active:hover,
.btn-danger.active:hover,
.open > .dropdown-toggle.btn-danger:hover,
.btn-danger:active:focus,
.btn-danger.active:focus,
.open > .dropdown-toggle.btn-danger:focus,
.btn-danger:active.focus,
.btn-danger.active.focus,
.open > .dropdown-toggle.btn-danger.focus {
  color: #fff;
  background-color: #ac2925;
  border-color: #761c19;
}
.btn-danger:active,
.btn-danger.active,
.open > .dropdown-toggle.btn-danger {
  background-image: none;
}
.btn-danger.disabled:hover,
.btn-danger[disabled]:hover,
fieldset[disabled] .btn-danger:hover,
.btn-danger.disabled:focus,
.btn-danger[disabled]:focus,
fieldset[disabled] .btn-danger:focus,
.btn-danger.disabled.focus,
.btn-danger[disabled].focus,
fieldset[disabled] .btn-danger.focus {
  background-color: #d9534f;
  border-color: #d43f3a;
}
.btn-danger .badge {
  color: #d9534f;
  background-color: #fff;
}
.btn-link {
  color: #337ab7;
  font-weight: normal;
  border-radius: 0;
}
.btn-link,
.btn-link:active,
.btn-link.active,
.btn-link[disabled],
fieldset[disabled] .btn-link {
  background-color: transparent;
  -webkit-box-shadow: none;
  box-shadow: none;
}
.btn-link,
.btn-link:hover,
.btn-link:focus,
.btn-link:active {
  border-color: transparent;
}
.btn-link:hover,
.btn-link:focus {
  color: #23527c;
  text-decoration: underline;
  background-color: transparent;
}
.btn-link[disabled]:hover,
fieldset[disabled] .btn-link:hover,
.btn-link[disabled]:focus,
fieldset[disabled] .btn-link:focus {
  color: #777777;
  text-decoration: none;
}
.btn-lg,
.btn-group-lg > .btn {
  padding: 10px 16px;
  font-size: 17px;
  line-height: 1.3333333;
  border-radius: 3px;
}
.btn-sm,
.btn-group-sm > .btn {
  padding: 5px 10px;
  font-size: 12px;
  line-height: 1.5;
  border-radius: 1px;
}
.btn-xs,
.btn-group-xs > .btn {
  padding: 1px 5px;
  font-size: 12px;
  line-height: 1.5;
  border-radius: 1px;
}
.btn-block {
  display: block;
  width: 100%;
}
.btn-block + .btn-block {
  margin-top: 5px;
}
input[type="submit"].btn-block,
input[type="reset"].btn-block,
input[type="button"].btn-block {
  width: 100%;
}
.fade {
  opacity: 0;
  -webkit-transition: opacity 0.15s linear;
  -o-transition: opacity 0.15s linear;
  transition: opacity 0.15s linear;
}
.fade.in {
  opacity: 1;
}
.collapse {
  display: none;
}
.collapse.in {
  display: block;
}
tr.collapse.in {
  display: table-row;
}
tbody.collapse.in {
  display: table-row-group;
}
.collapsing {
  position: relative;
  height: 0;
  overflow: hidden;
  -webkit-transition-property: height, visibility;
  transition-property: height, visibility;
  -webkit-transition-duration: 0.35s;
  transition-duration: 0.35s;
  -webkit-transition-timing-function: ease;
  transition-timing-function: ease;
}
.caret {
  display: inline-block;
  width: 0;
  height: 0;
  margin-left: 2px;
  vertical-align: middle;
  border-top: 4px dashed;
  border-top: 4px solid \9;
  border-right: 4px solid transparent;
  border-left: 4px solid transparent;
}
.dropup,
.dropdown {
  position: relative;
}
.dropdown-toggle:focus {
  outline: 0;
}
.dropdown-menu {
  position: absolute;
  top: 100%;
  left: 0;
  z-index: 1000;
  display: none;
  float: left;
  min-width: 160px;
  padding: 5px 0;
  margin: 2px 0 0;
  list-style: none;
  font-size: 13px;
  text-align: left;
  background-color: #fff;
  border: 1px solid #ccc;
  border: 1px solid rgba(0, 0, 0, 0.15);
  border-radius: 2px;
  -webkit-box-shadow: 0 6px 12px rgba(0, 0, 0, 0.175);
  box-shadow: 0 6px 12px rgba(0, 0, 0, 0.175);
  background-clip: padding-box;
}
.dropdown-menu.pull-right {
  right: 0;
  left: auto;
}
.dropdown-menu .divider {
  height: 1px;
  margin: 8px 0;
  overflow: hidden;
  background-color: #e5e5e5;
}
.dropdown-menu > li > a {
  display: block;
  padding: 3px 20px;
  clear: both;
  font-weight: normal;
  line-height: 1.42857143;
  color: #333333;
  white-space: nowrap;
}
.dropdown-menu > li > a:hover,
.dropdown-menu > li > a:focus {
  text-decoration: none;
  color: #262626;
  background-color: #f5f5f5;
}
.dropdown-menu > .active > a,
.dropdown-menu > .active > a:hover,
.dropdown-menu > .active > a:focus {
  color: #fff;
  text-decoration: none;
  outline: 0;
  background-color: #337ab7;
}
.dropdown-menu > .disabled > a,
.dropdown-menu > .disabled > a:hover,
.dropdown-menu > .disabled > a:focus {
  color: #777777;
}
.dropdown-menu > .disabled > a:hover,
.dropdown-menu > .disabled > a:focus {
  text-decoration: none;
  background-color: transparent;
  background-image: none;
  filter: progid:DXImageTransform.Microsoft.gradient(enabled = false);
  cursor: not-allowed;
}
.open > .dropdown-menu {
  display: block;
}
.open > a {
  outline: 0;
}
.dropdown-menu-right {
  left: auto;
  right: 0;
}
.dropdown-menu-left {
  left: 0;
  right: auto;
}
.dropdown-header {
  display: block;
  padding: 3px 20px;
  font-size: 12px;
  line-height: 1.42857143;
  color: #777777;
  white-space: nowrap;
}
.dropdown-backdrop {
  position: fixed;
  left: 0;
  right: 0;
  bottom: 0;
  top: 0;
  z-index: 990;
}
.pull-right > .dropdown-menu {
  right: 0;
  left: auto;
}
.dropup .caret,
.navbar-fixed-bottom .dropdown .caret {
  border-top: 0;
  border-bottom: 4px dashed;
  border-bottom: 4px solid \9;
  content: "";
}
.dropup .dropdown-menu,
.navbar-fixed-bottom .dropdown .dropdown-menu {
  top: auto;
  bottom: 100%;
  margin-bottom: 2px;
}
@media (min-width: 541px) {
  .navbar-right .dropdown-menu {
    left: auto;
    right: 0;
  }
  .navbar-right .dropdown-menu-left {
    left: 0;
    right: auto;
  }
}
.btn-group,
.btn-group-vertical {
  position: relative;
  display: inline-block;
  vertical-align: middle;
}
.btn-group > .btn,
.btn-group-vertical > .btn {
  position: relative;
  float: left;
}
.btn-group > .btn:hover,
.btn-group-vertical > .btn:hover,
.btn-group > .btn:focus,
.btn-group-vertical > .btn:focus,
.btn-group > .btn:active,
.btn-group-vertical > .btn:active,
.btn-group > .btn.active,
.btn-group-vertical > .btn.active {
  z-index: 2;
}
.btn-group .btn + .btn,
.btn-group .btn + .btn-group,
.btn-group .btn-group + .btn,
.btn-group .btn-group + .btn-group {
  margin-left: -1px;
}
.btn-toolbar {
  margin-left: -5px;
}
.btn-toolbar .btn,
.btn-toolbar .btn-group,
.btn-toolbar .input-group {
  float: left;
}
.btn-toolbar > .btn,
.btn-toolbar > .btn-group,
.btn-toolbar > .input-group {
  margin-left: 5px;
}
.btn-group > .btn:not(:first-child):not(:last-child):not(.dropdown-toggle) {
  border-radius: 0;
}
.btn-group > .btn:first-child {
  margin-left: 0;
}
.btn-group > .btn:first-child:not(:last-child):not(.dropdown-toggle) {
  border-bottom-right-radius: 0;
  border-top-right-radius: 0;
}
.btn-group > .btn:last-child:not(:first-child),
.btn-group > .dropdown-toggle:not(:first-child) {
  border-bottom-left-radius: 0;
  border-top-left-radius: 0;
}
.btn-group > .btn-group {
  float: left;
}
.btn-group > .btn-group:not(:first-child):not(:last-child) > .btn {
  border-radius: 0;
}
.btn-group > .btn-group:first-child:not(:last-child) > .btn:last-child,
.btn-group > .btn-group:first-child:not(:last-child) > .dropdown-toggle {
  border-bottom-right-radius: 0;
  border-top-right-radius: 0;
}
.btn-group > .btn-group:last-child:not(:first-child) > .btn:first-child {
  border-bottom-left-radius: 0;
  border-top-left-radius: 0;
}
.btn-group .dropdown-toggle:active,
.btn-group.open .dropdown-toggle {
  outline: 0;
}
.btn-group > .btn + .dropdown-toggle {
  padding-left: 8px;
  padding-right: 8px;
}
.btn-group > .btn-lg + .dropdown-toggle {
  padding-left: 12px;
  padding-right: 12px;
}
.btn-group.open .dropdown-toggle {
  -webkit-box-shadow: inset 0 3px 5px rgba(0, 0, 0, 0.125);
  box-shadow: inset 0 3px 5px rgba(0, 0, 0, 0.125);
}
.btn-group.open .dropdown-toggle.btn-link {
  -webkit-box-shadow: none;
  box-shadow: none;
}
.btn .caret {
  margin-left: 0;
}
.btn-lg .caret {
  border-width: 5px 5px 0;
  border-bottom-width: 0;
}
.dropup .btn-lg .caret {
  border-width: 0 5px 5px;
}
.btn-group-vertical > .btn,
.btn-group-vertical > .btn-group,
.btn-group-vertical > .btn-group > .btn {
  display: block;
  float: none;
  width: 100%;
  max-width: 100%;
}
.btn-group-vertical > .btn-group > .btn {
  float: none;
}
.btn-group-vertical > .btn + .btn,
.btn-group-vertical > .btn + .btn-group,
.btn-group-vertical > .btn-group + .btn,
.btn-group-vertical > .btn-group + .btn-group {
  margin-top: -1px;
  margin-left: 0;
}
.btn-group-vertical > .btn:not(:first-child):not(:last-child) {
  border-radius: 0;
}
.btn-group-vertical > .btn:first-child:not(:last-child) {
  border-top-right-radius: 2px;
  border-top-left-radius: 2px;
  border-bottom-right-radius: 0;
  border-bottom-left-radius: 0;
}
.btn-group-vertical > .btn:last-child:not(:first-child) {
  border-top-right-radius: 0;
  border-top-left-radius: 0;
  border-bottom-right-radius: 2px;
  border-bottom-left-radius: 2px;
}
.btn-group-vertical > .btn-group:not(:first-child):not(:last-child) > .btn {
  border-radius: 0;
}
.btn-group-vertical > .btn-group:first-child:not(:last-child) > .btn:last-child,
.btn-group-vertical > .btn-group:first-child:not(:last-child) > .dropdown-toggle {
  border-bottom-right-radius: 0;
  border-bottom-left-radius: 0;
}
.btn-group-vertical > .btn-group:last-child:not(:first-child) > .btn:first-child {
  border-top-right-radius: 0;
  border-top-left-radius: 0;
}
.btn-group-justified {
  display: table;
  width: 100%;
  table-layout: fixed;
  border-collapse: separate;
}
.btn-group-justified > .btn,
.btn-group-justified > .btn-group {
  float: none;
  display: table-cell;
  width: 1%;
}
.btn-group-justified > .btn-group .btn {
  width: 100%;
}
.btn-group-justified > .btn-group .dropdown-menu {
  left: auto;
}
[data-toggle="buttons"] > .btn input[type="radio"],
[data-toggle="buttons"] > .btn-group > .btn input[type="radio"],
[data-toggle="buttons"] > .btn input[type="checkbox"],
[data-toggle="buttons"] > .btn-group > .btn input[type="checkbox"] {
  position: absolute;
  clip: rect(0, 0, 0, 0);
  pointer-events: none;
}
.input-group {
  position: relative;
  display: table;
  border-collapse: separate;
}
.input-group[class*="col-"] {
  float: none;
  padding-left: 0;
  padding-right: 0;
}
.input-group .form-control {
  position: relative;
  z-index: 2;
  float: left;
  width: 100%;
  margin-bottom: 0;
}
.input-group .form-control:focus {
  z-index: 3;
}
.input-group-lg > .form-control,
.input-group-lg > .input-group-addon,
.input-group-lg > .input-group-btn > .btn {
  height: 45px;
  padding: 10px 16px;
  font-size: 17px;
  line-height: 1.3333333;
  border-radius: 3px;
}
select.input-group-lg > .form-control,
select.input-group-lg > .input-group-addon,
select.input-group-lg > .input-group-btn > .btn {
  height: 45px;
  line-height: 45px;
}
textarea.input-group-lg > .form-control,
textarea.input-group-lg > .input-group-addon,
textarea.input-group-lg > .input-group-btn > .btn,
select[multiple].input-group-lg > .form-control,
select[multiple].input-group-lg > .input-group-addon,
select[multiple].input-group-lg > .input-group-btn > .btn {
  height: auto;
}
.input-group-sm > .form-control,
.input-group-sm > .input-group-addon,
.input-group-sm > .input-group-btn > .btn {
  height: 30px;
  padding: 5px 10px;
  font-size: 12px;
  line-height: 1.5;
  border-radius: 1px;
}
select.input-group-sm > .form-control,
select.input-group-sm > .input-group-addon,
select.input-group-sm > .input-group-btn > .btn {
  height: 30px;
  line-height: 30px;
}
textarea.input-group-sm > .form-control,
textarea.input-group-sm > .input-group-addon,
textarea.input-group-sm > .input-group-btn > .btn,
select[multiple].input-group-sm > .form-control,
select[multiple].input-group-sm > .input-group-addon,
select[multiple].input-group-sm > .input-group-btn > .btn {
  height: auto;
}
.input-group-addon,
.input-group-btn,
.input-group .form-control {
  display: table-cell;
}
.input-group-addon:not(:first-child):not(:last-child),
.input-group-btn:not(:first-child):not(:last-child),
.input-group .form-control:not(:first-child):not(:last-child) {
  border-radius: 0;
}
.input-group-addon,
.input-group-btn {
  width: 1%;
  white-space: nowrap;
  vertical-align: middle;
}
.input-group-addon {
  padding: 6px 12px;
  font-size: 13px;
  font-weight: normal;
  line-height: 1;
  color: #555555;
  text-align: center;
  background-color: #eeeeee;
  border: 1px solid #ccc;
  border-radius: 2px;
}
.input-group-addon.input-sm {
  padding: 5px 10px;
  font-size: 12px;
  border-radius: 1px;
}
.input-group-addon.input-lg {
  padding: 10px 16px;
  font-size: 17px;
  border-radius: 3px;
}
.input-group-addon input[type="radio"],
.input-group-addon input[type="checkbox"] {
  margin-top: 0;
}
.input-group .form-control:first-child,
.input-group-addon:first-child,
.input-group-btn:first-child > .btn,
.input-group-btn:first-child > .btn-group > .btn,
.input-group-btn:first-child > .dropdown-toggle,
.input-group-btn:last-child > .btn:not(:last-child):not(.dropdown-toggle),
.input-group-btn:last-child > .btn-group:not(:last-child) > .btn {
  border-bottom-right-radius: 0;
  border-top-right-radius: 0;
}
.input-group-addon:first-child {
  border-right: 0;
}
.input-group .form-control:last-child,
.input-group-addon:last-child,
.input-group-btn:last-child > .btn,
.input-group-btn:last-child > .btn-group > .btn,
.input-group-btn:last-child > .dropdown-toggle,
.input-group-btn:first-child > .btn:not(:first-child),
.input-group-btn:first-child > .btn-group:not(:first-child) > .btn {
  border-bottom-left-radius: 0;
  border-top-left-radius: 0;
}
.input-group-addon:last-child {
  border-left: 0;
}
.input-group-btn {
  position: relative;
  font-size: 0;
  white-space: nowrap;
}
.input-group-btn > .btn {
  position: relative;
}
.input-group-btn > .btn + .btn {
  margin-left: -1px;
}
.input-group-btn > .btn:hover,
.input-group-btn > .btn:focus,
.input-group-btn > .btn:active {
  z-index: 2;
}
.input-group-btn:first-child > .btn,
.input-group-btn:first-child > .btn-group {
  margin-right: -1px;
}
.input-group-btn:last-child > .btn,
.input-group-btn:last-child > .btn-group {
  z-index: 2;
  margin-left: -1px;
}
.nav {
  margin-bottom: 0;
  padding-left: 0;
  list-style: none;
}
.nav > li {
  position: relative;
  display: block;
}
.nav > li > a {
  position: relative;
  display: block;
  padding: 10px 15px;
}
.nav > li > a:hover,
.nav > li > a:focus {
  text-decoration: none;
  background-color: #eeeeee;
}
.nav > li.disabled > a {
  color: #777777;
}
.nav > li.disabled > a:hover,
.nav > li.disabled > a:focus {
  color: #777777;
  text-decoration: none;
  background-color: transparent;
  cursor: not-allowed;
}
.nav .open > a,
.nav .open > a:hover,
.nav .open > a:focus {
  background-color: #eeeeee;
  border-color: #337ab7;
}
.nav .nav-divider {
  height: 1px;
  margin: 8px 0;
  overflow: hidden;
  background-color: #e5e5e5;
}
.nav > li > a > img {
  max-width: none;
}
.nav-tabs {
  border-bottom: 1px solid #ddd;
}
.nav-tabs > li {
  float: left;
  margin-bottom: -1px;
}
.nav-tabs > li > a {
  margin-right: 2px;
  line-height: 1.42857143;
  border: 1px solid transparent;
  border-radius: 2px 2px 0 0;
}
.nav-tabs > li > a:hover {
  border-color: #eeeeee #eeeeee #ddd;
}
.nav-tabs > li.active > a,
.nav-tabs > li.active > a:hover,
.nav-tabs > li.active > a:focus {
  color: #555555;
  background-color: #fff;
  border: 1px solid #ddd;
  border-bottom-color: transparent;
  cursor: default;
}
.nav-tabs.nav-justified {
  width: 100%;
  border-bottom: 0;
}
.nav-tabs.nav-justified > li {
  float: none;
}
.nav-tabs.nav-justified > li > a {
  text-align: center;
  margin-bottom: 5px;
}
.nav-tabs.nav-justified > .dropdown .dropdown-menu {
  top: auto;
  left: auto;
}
@media (min-width: 768px) {
  .nav-tabs.nav-justified > li {
    display: table-cell;
    width: 1%;
  }
  .nav-tabs.nav-justified > li > a {
    margin-bottom: 0;
  }
}
.nav-tabs.nav-justified > li > a {
  margin-right: 0;
  border-radius: 2px;
}
.nav-tabs.nav-justified > .active > a,
.nav-tabs.nav-justified > .active > a:hover,
.nav-tabs.nav-justified > .active > a:focus {
  border: 1px solid #ddd;
}
@media (min-width: 768px) {
  .nav-tabs.nav-justified > li > a {
    border-bottom: 1px solid #ddd;
    border-radius: 2px 2px 0 0;
  }
  .nav-tabs.nav-justified > .active > a,
  .nav-tabs.nav-justified > .active > a:hover,
  .nav-tabs.nav-justified > .active > a:focus {
    border-bottom-color: #fff;
  }
}
.nav-pills > li {
  float: left;
}
.nav-pills > li > a {
  border-radius: 2px;
}
.nav-pills > li + li {
  margin-left: 2px;
}
.nav-pills > li.active > a,
.nav-pills > li.active > a:hover,
.nav-pills > li.active > a:focus {
  color: #fff;
  background-color: #337ab7;
}
.nav-stacked > li {
  float: none;
}
.nav-stacked > li + li {
  margin-top: 2px;
  margin-left: 0;
}
.nav-justified {
  width: 100%;
}
.nav-justified > li {
  float: none;
}
.nav-justified > li > a {
  text-align: center;
  margin-bottom: 5px;
}
.nav-justified > .dropdown .dropdown-menu {
  top: auto;
  left: auto;
}
@media (min-width: 768px) {
  .nav-justified > li {
    display: table-cell;
    width: 1%;
  }
  .nav-justified > li > a {
    margin-bottom: 0;
  }
}
.nav-tabs-justified {
  border-bottom: 0;
}
.nav-tabs-justified > li > a {
  margin-right: 0;
  border-radius: 2px;
}
.nav-tabs-justified > .active > a,
.nav-tabs-justified > .active > a:hover,
.nav-tabs-justified > .active > a:focus {
  border: 1px solid #ddd;
}
@media (min-width: 768px) {
  .nav-tabs-justified > li > a {
    border-bottom: 1px solid #ddd;
    border-radius: 2px 2px 0 0;
  }
  .nav-tabs-justified > .active > a,
  .nav-tabs-justified > .active > a:hover,
  .nav-tabs-justified > .active > a:focus {
    border-bottom-color: #fff;
  }
}
.tab-content > .tab-pane {
  display: none;
}
.tab-content > .active {
  display: block;
}
.nav-tabs .dropdown-menu {
  margin-top: -1px;
  border-top-right-radius: 0;
  border-top-left-radius: 0;
}
.navbar {
  position: relative;
  min-height: 30px;
  margin-bottom: 18px;
  border: 1px solid transparent;
}
@media (min-width: 541px) {
  .navbar {
    border-radius: 2px;
  }
}
@media (min-width: 541px) {
  .navbar-header {
    float: left;
  }
}
.navbar-collapse {
  overflow-x: visible;
  padding-right: 0px;
  padding-left: 0px;
  border-top: 1px solid transparent;
  box-shadow: inset 0 1px 0 rgba(255, 255, 255, 0.1);
  -webkit-overflow-scrolling: touch;
}
.navbar-collapse.in {
  overflow-y: auto;
}
@media (min-width: 541px) {
  .navbar-collapse {
    width: auto;
    border-top: 0;
    box-shadow: none;
  }
  .navbar-collapse.collapse {
    display: block !important;
    height: auto !important;
    padding-bottom: 0;
    overflow: visible !important;
  }
  .navbar-collapse.in {
    overflow-y: visible;
  }
  .navbar-fixed-top .navbar-collapse,
  .navbar-static-top .navbar-collapse,
  .navbar-fixed-bottom .navbar-collapse {
    padding-left: 0;
    padding-right: 0;
  }
}
.navbar-fixed-top .navbar-collapse,
.navbar-fixed-bottom .navbar-collapse {
  max-height: 340px;
}
@media (max-device-width: 540px) and (orientation: landscape) {
  .navbar-fixed-top .navbar-collapse,
  .navbar-fixed-bottom .navbar-collapse {
    max-height: 200px;
  }
}
.container > .navbar-header,
.container-fluid > .navbar-header,
.container > .navbar-collapse,
.container-fluid > .navbar-collapse {
  margin-right: 0px;
  margin-left: 0px;
}
@media (min-width: 541px) {
  .container > .navbar-header,
  .container-fluid > .navbar-header,
  .container > .navbar-collapse,
  .container-fluid > .navbar-collapse {
    margin-right: 0;
    margin-left: 0;
  }
}
.navbar-static-top {
  z-index: 1000;
  border-width: 0 0 1px;
}
@media (min-width: 541px) {
  .navbar-static-top {
    border-radius: 0;
  }
}
.navbar-fixed-top,
.navbar-fixed-bottom {
  position: fixed;
  right: 0;
  left: 0;
  z-index: 1030;
}
@media (min-width: 541px) {
  .navbar-fixed-top,
  .navbar-fixed-bottom {
    border-radius: 0;
  }
}
.navbar-fixed-top {
  top: 0;
  border-width: 0 0 1px;
}
.navbar-fixed-bottom {
  bottom: 0;
  margin-bottom: 0;
  border-width: 1px 0 0;
}
.navbar-brand {
  float: left;
  padding: 6px 0px;
  font-size: 17px;
  line-height: 18px;
  height: 30px;
}
.navbar-brand:hover,
.navbar-brand:focus {
  text-decoration: none;
}
.navbar-brand > img {
  display: block;
}
@media (min-width: 541px) {
  .navbar > .container .navbar-brand,
  .navbar > .container-fluid .navbar-brand {
    margin-left: 0px;
  }
}
.navbar-toggle {
  position: relative;
  float: right;
  margin-right: 0px;
  padding: 9px 10px;
  margin-top: -2px;
  margin-bottom: -2px;
  background-color: transparent;
  background-image: none;
  border: 1px solid transparent;
  border-radius: 2px;
}
.navbar-toggle:focus {
  outline: 0;
}
.navbar-toggle .icon-bar {
  display: block;
  width: 22px;
  height: 2px;
  border-radius: 1px;
}
.navbar-toggle .icon-bar + .icon-bar {
  margin-top: 4px;
}
@media (min-width: 541px) {
  .navbar-toggle {
    display: none;
  }
}
.navbar-nav {
  margin: 3px 0px;
}
.navbar-nav > li > a {
  padding-top: 10px;
  padding-bottom: 10px;
  line-height: 18px;
}
@media (max-width: 540px) {
  .navbar-nav .open .dropdown-menu {
    position: static;
    float: none;
    width: auto;
    margin-top: 0;
    background-color: transparent;
    border: 0;
    box-shadow: none;
  }
  .navbar-nav .open .dropdown-menu > li > a,
  .navbar-nav .open .dropdown-menu .dropdown-header {
    padding: 5px 15px 5px 25px;
  }
  .navbar-nav .open .dropdown-menu > li > a {
    line-height: 18px;
  }
  .navbar-nav .open .dropdown-menu > li > a:hover,
  .navbar-nav .open .dropdown-menu > li > a:focus {
    background-image: none;
  }
}
@media (min-width: 541px) {
  .navbar-nav {
    float: left;
    margin: 0;
  }
  .navbar-nav > li {
    float: left;
  }
  .navbar-nav > li > a {
    padding-top: 6px;
    padding-bottom: 6px;
  }
}
.navbar-form {
  margin-left: 0px;
  margin-right: 0px;
  padding: 10px 0px;
  border-top: 1px solid transparent;
  border-bottom: 1px solid transparent;
  -webkit-box-shadow: inset 0 1px 0 rgba(255, 255, 255, 0.1), 0 1px 0 rgba(255, 255, 255, 0.1);
  box-shadow: inset 0 1px 0 rgba(255, 255, 255, 0.1), 0 1px 0 rgba(255, 255, 255, 0.1);
  margin-top: -1px;
  margin-bottom: -1px;
}
@media (min-width: 768px) {
  .navbar-form .form-group {
    display: inline-block;
    margin-bottom: 0;
    vertical-align: middle;
  }
  .navbar-form .form-control {
    display: inline-block;
    width: auto;
    vertical-align: middle;
  }
  .navbar-form .form-control-static {
    display: inline-block;
  }
  .navbar-form .input-group {
    display: inline-table;
    vertical-align: middle;
  }
  .navbar-form .input-group .input-group-addon,
  .navbar-form .input-group .input-group-btn,
  .navbar-form .input-group .form-control {
    width: auto;
  }
  .navbar-form .input-group > .form-control {
    width: 100%;
  }
  .navbar-form .control-label {
    margin-bottom: 0;
    vertical-align: middle;
  }
  .navbar-form .radio,
  .navbar-form .checkbox {
    display: inline-block;
    margin-top: 0;
    margin-bottom: 0;
    vertical-align: middle;
  }
  .navbar-form .radio label,
  .navbar-form .checkbox label {
    padding-left: 0;
  }
  .navbar-form .radio input[type="radio"],
  .navbar-form .checkbox input[type="checkbox"] {
    position: relative;
    margin-left: 0;
  }
  .navbar-form .has-feedback .form-control-feedback {
    top: 0;
  }
}
@media (max-width: 540px) {
  .navbar-form .form-group {
    margin-bottom: 5px;
  }
  .navbar-form .form-group:last-child {
    margin-bottom: 0;
  }
}
@media (min-width: 541px) {
  .navbar-form {
    width: auto;
    border: 0;
    margin-left: 0;
    margin-right: 0;
    padding-top: 0;
    padding-bottom: 0;
    -webkit-box-shadow: none;
    box-shadow: none;
  }
}
.navbar-nav > li > .dropdown-menu {
  margin-top: 0;
  border-top-right-radius: 0;
  border-top-left-radius: 0;
}
.navbar-fixed-bottom .navbar-nav > li > .dropdown-menu {
  margin-bottom: 0;
  border-top-right-radius: 2px;
  border-top-left-radius: 2px;
  border-bottom-right-radius: 0;
  border-bottom-left-radius: 0;
}
.navbar-btn {
  margin-top: -1px;
  margin-bottom: -1px;
}
.navbar-btn.btn-sm {
  margin-top: 0px;
  margin-bottom: 0px;
}
.navbar-btn.btn-xs {
  margin-top: 4px;
  margin-bottom: 4px;
}
.navbar-text {
  margin-top: 6px;
  margin-bottom: 6px;
}
@media (min-width: 541px) {
  .navbar-text {
    float: left;
    margin-left: 0px;
    margin-right: 0px;
  }
}
@media (min-width: 541px) {
  .navbar-left {
    float: left !important;
    float: left;
  }
  .navbar-right {
    float: right !important;
    float: right;
    margin-right: 0px;
  }
  .navbar-right ~ .navbar-right {
    margin-right: 0;
  }
}
.navbar-default {
  background-color: #f8f8f8;
  border-color: #e7e7e7;
}
.navbar-default .navbar-brand {
  color: #777;
}
.navbar-default .navbar-brand:hover,
.navbar-default .navbar-brand:focus {
  color: #5e5e5e;
  background-color: transparent;
}
.navbar-default .navbar-text {
  color: #777;
}
.navbar-default .navbar-nav > li > a {
  color: #777;
}
.navbar-default .navbar-nav > li > a:hover,
.navbar-default .navbar-nav > li > a:focus {
  color: #333;
  background-color: transparent;
}
.navbar-default .navbar-nav > .active > a,
.navbar-default .navbar-nav > .active > a:hover,
.navbar-default .navbar-nav > .active > a:focus {
  color: #555;
  background-color: #e7e7e7;
}
.navbar-default .navbar-nav > .disabled > a,
.navbar-default .navbar-nav > .disabled > a:hover,
.navbar-default .navbar-nav > .disabled > a:focus {
  color: #ccc;
  background-color: transparent;
}
.navbar-default .navbar-toggle {
  border-color: #ddd;
}
.navbar-default .navbar-toggle:hover,
.navbar-default .navbar-toggle:focus {
  background-color: #ddd;
}
.navbar-default .navbar-toggle .icon-bar {
  background-color: #888;
}
.navbar-default .navbar-collapse,
.navbar-default .navbar-form {
  border-color: #e7e7e7;
}
.navbar-default .navbar-nav > .open > a,
.navbar-default .navbar-nav > .open > a:hover,
.navbar-default .navbar-nav > .open > a:focus {
  background-color: #e7e7e7;
  color: #555;
}
@media (max-width: 540px) {
  .navbar-default .navbar-nav .open .dropdown-menu > li > a {
    color: #777;
  }
  .navbar-default .navbar-nav .open .dropdown-menu > li > a:hover,
  .navbar-default .navbar-nav .open .dropdown-menu > li > a:focus {
    color: #333;
    background-color: transparent;
  }
  .navbar-default .navbar-nav .open .dropdown-menu > .active > a,
  .navbar-default .navbar-nav .open .dropdown-menu > .active > a:hover,
  .navbar-default .navbar-nav .open .dropdown-menu > .active > a:focus {
    color: #555;
    background-color: #e7e7e7;
  }
  .navbar-default .navbar-nav .open .dropdown-menu > .disabled > a,
  .navbar-default .navbar-nav .open .dropdown-menu > .disabled > a:hover,
  .navbar-default .navbar-nav .open .dropdown-menu > .disabled > a:focus {
    color: #ccc;
    background-color: transparent;
  }
}
.navbar-default .navbar-link {
  color: #777;
}
.navbar-default .navbar-link:hover {
  color: #333;
}
.navbar-default .btn-link {
  color: #777;
}
.navbar-default .btn-link:hover,
.navbar-default .btn-link:focus {
  color: #333;
}
.navbar-default .btn-link[disabled]:hover,
fieldset[disabled] .navbar-default .btn-link:hover,
.navbar-default .btn-link[disabled]:focus,
fieldset[disabled] .navbar-default .btn-link:focus {
  color: #ccc;
}
.navbar-inverse {
  background-color: #222;
  border-color: #080808;
}
.navbar-inverse .navbar-brand {
  color: #9d9d9d;
}
.navbar-inverse .navbar-brand:hover,
.navbar-inverse .navbar-brand:focus {
  color: #fff;
  background-color: transparent;
}
.navbar-inverse .navbar-text {
  color: #9d9d9d;
}
.navbar-inverse .navbar-nav > li > a {
  color: #9d9d9d;
}
.navbar-inverse .navbar-nav > li > a:hover,
.navbar-inverse .navbar-nav > li > a:focus {
  color: #fff;
  background-color: transparent;
}
.navbar-inverse .navbar-nav > .active > a,
.navbar-inverse .navbar-nav > .active > a:hover,
.navbar-inverse .navbar-nav > .active > a:focus {
  color: #fff;
  background-color: #080808;
}
.navbar-inverse .navbar-nav > .disabled > a,
.navbar-inverse .navbar-nav > .disabled > a:hover,
.navbar-inverse .navbar-nav > .disabled > a:focus {
  color: #444;
  background-color: transparent;
}
.navbar-inverse .navbar-toggle {
  border-color: #333;
}
.navbar-inverse .navbar-toggle:hover,
.navbar-inverse .navbar-toggle:focus {
  background-color: #333;
}
.navbar-inverse .navbar-toggle .icon-bar {
  background-color: #fff;
}
.navbar-inverse .navbar-collapse,
.navbar-inverse .navbar-form {
  border-color: #101010;
}
.navbar-inverse .navbar-nav > .open > a,
.navbar-inverse .navbar-nav > .open > a:hover,
.navbar-inverse .navbar-nav > .open > a:focus {
  background-color: #080808;
  color: #fff;
}
@media (max-width: 540px) {
  .navbar-inverse .navbar-nav .open .dropdown-menu > .dropdown-header {
    border-color: #080808;
  }
  .navbar-inverse .navbar-nav .open .dropdown-menu .divider {
    background-color: #080808;
  }
  .navbar-inverse .navbar-nav .open .dropdown-menu > li > a {
    color: #9d9d9d;
  }
  .navbar-inverse .navbar-nav .open .dropdown-menu > li > a:hover,
  .navbar-inverse .navbar-nav .open .dropdown-menu > li > a:focus {
    color: #fff;
    background-color: transparent;
  }
  .navbar-inverse .navbar-nav .open .dropdown-menu > .active > a,
  .navbar-inverse .navbar-nav .open .dropdown-menu > .active > a:hover,
  .navbar-inverse .navbar-nav .open .dropdown-menu > .active > a:focus {
    color: #fff;
    background-color: #080808;
  }
  .navbar-inverse .navbar-nav .open .dropdown-menu > .disabled > a,
  .navbar-inverse .navbar-nav .open .dropdown-menu > .disabled > a:hover,
  .navbar-inverse .navbar-nav .open .dropdown-menu > .disabled > a:focus {
    color: #444;
    background-color: transparent;
  }
}
.navbar-inverse .navbar-link {
  color: #9d9d9d;
}
.navbar-inverse .navbar-link:hover {
  color: #fff;
}
.navbar-inverse .btn-link {
  color: #9d9d9d;
}
.navbar-inverse .btn-link:hover,
.navbar-inverse .btn-link:focus {
  color: #fff;
}
.navbar-inverse .btn-link[disabled]:hover,
fieldset[disabled] .navbar-inverse .btn-link:hover,
.navbar-inverse .btn-link[disabled]:focus,
fieldset[disabled] .navbar-inverse .btn-link:focus {
  color: #444;
}
.breadcrumb {
  padding: 8px 15px;
  margin-bottom: 18px;
  list-style: none;
  background-color: #f5f5f5;
  border-radius: 2px;
}
.breadcrumb > li {
  display: inline-block;
}
.breadcrumb > li + li:before {
  content: "/\00a0";
  padding: 0 5px;
  color: #5e5e5e;
}
.breadcrumb > .active {
  color: #777777;
}
.pagination {
  display: inline-block;
  padding-left: 0;
  margin: 18px 0;
  border-radius: 2px;
}
.pagination > li {
  display: inline;
}
.pagination > li > a,
.pagination > li > span {
  position: relative;
  float: left;
  padding: 6px 12px;
  line-height: 1.42857143;
  text-decoration: none;
  color: #337ab7;
  background-color: #fff;
  border: 1px solid #ddd;
  margin-left: -1px;
}
.pagination > li:first-child > a,
.pagination > li:first-child > span {
  margin-left: 0;
  border-bottom-left-radius: 2px;
  border-top-left-radius: 2px;
}
.pagination > li:last-child > a,
.pagination > li:last-child > span {
  border-bottom-right-radius: 2px;
  border-top-right-radius: 2px;
}
.pagination > li > a:hover,
.pagination > li > span:hover,
.pagination > li > a:focus,
.pagination > li > span:focus {
  z-index: 2;
  color: #23527c;
  background-color: #eeeeee;
  border-color: #ddd;
}
.pagination > .active > a,
.pagination > .active > span,
.pagination > .active > a:hover,
.pagination > .active > span:hover,
.pagination > .active > a:focus,
.pagination > .active > span:focus {
  z-index: 3;
  color: #fff;
  background-color: #337ab7;
  border-color: #337ab7;
  cursor: default;
}
.pagination > .disabled > span,
.pagination > .disabled > span:hover,
.pagination > .disabled > span:focus,
.pagination > .disabled > a,
.pagination > .disabled > a:hover,
.pagination > .disabled > a:focus {
  color: #777777;
  background-color: #fff;
  border-color: #ddd;
  cursor: not-allowed;
}
.pagination-lg > li > a,
.pagination-lg > li > span {
  padding: 10px 16px;
  font-size: 17px;
  line-height: 1.3333333;
}
.pagination-lg > li:first-child > a,
.pagination-lg > li:first-child > span {
  border-bottom-left-radius: 3px;
  border-top-left-radius: 3px;
}
.pagination-lg > li:last-child > a,
.pagination-lg > li:last-child > span {
  border-bottom-right-radius: 3px;
  border-top-right-radius: 3px;
}
.pagination-sm > li > a,
.pagination-sm > li > span {
  padding: 5px 10px;
  font-size: 12px;
  line-height: 1.5;
}
.pagination-sm > li:first-child > a,
.pagination-sm > li:first-child > span {
  border-bottom-left-radius: 1px;
  border-top-left-radius: 1px;
}
.pagination-sm > li:last-child > a,
.pagination-sm > li:last-child > span {
  border-bottom-right-radius: 1px;
  border-top-right-radius: 1px;
}
.pager {
  padding-left: 0;
  margin: 18px 0;
  list-style: none;
  text-align: center;
}
.pager li {
  display: inline;
}
.pager li > a,
.pager li > span {
  display: inline-block;
  padding: 5px 14px;
  background-color: #fff;
  border: 1px solid #ddd;
  border-radius: 15px;
}
.pager li > a:hover,
.pager li > a:focus {
  text-decoration: none;
  background-color: #eeeeee;
}
.pager .next > a,
.pager .next > span {
  float: right;
}
.pager .previous > a,
.pager .previous > span {
  float: left;
}
.pager .disabled > a,
.pager .disabled > a:hover,
.pager .disabled > a:focus,
.pager .disabled > span {
  color: #777777;
  background-color: #fff;
  cursor: not-allowed;
}
.label {
  display: inline;
  padding: .2em .6em .3em;
  font-size: 75%;
  font-weight: bold;
  line-height: 1;
  color: #fff;
  text-align: center;
  white-space: nowrap;
  vertical-align: baseline;
  border-radius: .25em;
}
a.label:hover,
a.label:focus {
  color: #fff;
  text-decoration: none;
  cursor: pointer;
}
.label:empty {
  display: none;
}
.btn .label {
  position: relative;
  top: -1px;
}
.label-default {
  background-color: #777777;
}
.label-default[href]:hover,
.label-default[href]:focus {
  background-color: #5e5e5e;
}
.label-primary {
  background-color: #337ab7;
}
.label-primary[href]:hover,
.label-primary[href]:focus {
  background-color: #286090;
}
.label-success {
  background-color: #5cb85c;
}
.label-success[href]:hover,
.label-success[href]:focus {
  background-color: #449d44;
}
.label-info {
  background-color: #5bc0de;
}
.label-info[href]:hover,
.label-info[href]:focus {
  background-color: #31b0d5;
}
.label-warning {
  background-color: #f0ad4e;
}
.label-warning[href]:hover,
.label-warning[href]:focus {
  background-color: #ec971f;
}
.label-danger {
  background-color: #d9534f;
}
.label-danger[href]:hover,
.label-danger[href]:focus {
  background-color: #c9302c;
}
.badge {
  display: inline-block;
  min-width: 10px;
  padding: 3px 7px;
  font-size: 12px;
  font-weight: bold;
  color: #fff;
  line-height: 1;
  vertical-align: middle;
  white-space: nowrap;
  text-align: center;
  background-color: #777777;
  border-radius: 10px;
}
.badge:empty {
  display: none;
}
.btn .badge {
  position: relative;
  top: -1px;
}
.btn-xs .badge,
.btn-group-xs > .btn .badge {
  top: 0;
  padding: 1px 5px;
}
a.badge:hover,
a.badge:focus {
  color: #fff;
  text-decoration: none;
  cursor: pointer;
}
.list-group-item.active > .badge,
.nav-pills > .active > a > .badge {
  color: #337ab7;
  background-color: #fff;
}
.list-group-item > .badge {
  float: right;
}
.list-group-item > .badge + .badge {
  margin-right: 5px;
}
.nav-pills > li > a > .badge {
  margin-left: 3px;
}
.jumbotron {
  padding-top: 30px;
  padding-bottom: 30px;
  margin-bottom: 30px;
  color: inherit;
  background-color: #eeeeee;
}
.jumbotron h1,
.jumbotron .h1 {
  color: inherit;
}
.jumbotron p {
  margin-bottom: 15px;
  font-size: 20px;
  font-weight: 200;
}
.jumbotron > hr {
  border-top-color: #d5d5d5;
}
.container .jumbotron,
.container-fluid .jumbotron {
  border-radius: 3px;
  padding-left: 0px;
  padding-right: 0px;
}
.jumbotron .container {
  max-width: 100%;
}
@media screen and (min-width: 768px) {
  .jumbotron {
    padding-top: 48px;
    padding-bottom: 48px;
  }
  .container .jumbotron,
  .container-fluid .jumbotron {
    padding-left: 60px;
    padding-right: 60px;
  }
  .jumbotron h1,
  .jumbotron .h1 {
    font-size: 59px;
  }
}
.thumbnail {
  display: block;
  padding: 4px;
  margin-bottom: 18px;
  line-height: 1.42857143;
  background-color: #fff;
  border: 1px solid #ddd;
  border-radius: 2px;
  -webkit-transition: border 0.2s ease-in-out;
  -o-transition: border 0.2s ease-in-out;
  transition: border 0.2s ease-in-out;
}
.thumbnail > img,
.thumbnail a > img {
  margin-left: auto;
  margin-right: auto;
}
a.thumbnail:hover,
a.thumbnail:focus,
a.thumbnail.active {
  border-color: #337ab7;
}
.thumbnail .caption {
  padding: 9px;
  color: #000;
}
.alert {
  padding: 15px;
  margin-bottom: 18px;
  border: 1px solid transparent;
  border-radius: 2px;
}
.alert h4 {
  margin-top: 0;
  color: inherit;
}
.alert .alert-link {
  font-weight: bold;
}
.alert > p,
.alert > ul {
  margin-bottom: 0;
}
.alert > p + p {
  margin-top: 5px;
}
.alert-dismissable,
.alert-dismissible {
  padding-right: 35px;
}
.alert-dismissable .close,
.alert-dismissible .close {
  position: relative;
  top: -2px;
  right: -21px;
  color: inherit;
}
.alert-success {
  background-color: #dff0d8;
  border-color: #d6e9c6;
  color: #3c763d;
}
.alert-success hr {
  border-top-color: #c9e2b3;
}
.alert-success .alert-link {
  color: #2b542c;
}
.alert-info {
  background-color: #d9edf7;
  border-color: #bce8f1;
  color: #31708f;
}
.alert-info hr {
  border-top-color: #a6e1ec;
}
.alert-info .alert-link {
  color: #245269;
}
.alert-warning {
  background-color: #fcf8e3;
  border-color: #faebcc;
  color: #8a6d3b;
}
.alert-warning hr {
  border-top-color: #f7e1b5;
}
.alert-warning .alert-link {
  color: #66512c;
}
.alert-danger {
  background-color: #f2dede;
  border-color: #ebccd1;
  color: #a94442;
}
.alert-danger hr {
  border-top-color: #e4b9c0;
}
.alert-danger .alert-link {
  color: #843534;
}
@-webkit-keyframes progress-bar-stripes {
  from {
    background-position: 40px 0;
  }
  to {
    background-position: 0 0;
  }
}
@keyframes progress-bar-stripes {
  from {
    background-position: 40px 0;
  }
  to {
    background-position: 0 0;
  }
}
.progress {
  overflow: hidden;
  height: 18px;
  margin-bottom: 18px;
  background-color: #f5f5f5;
  border-radius: 2px;
  -webkit-box-shadow: inset 0 1px 2px rgba(0, 0, 0, 0.1);
  box-shadow: inset 0 1px 2px rgba(0, 0, 0, 0.1);
}
.progress-bar {
  float: left;
  width: 0%;
  height: 100%;
  font-size: 12px;
  line-height: 18px;
  color: #fff;
  text-align: center;
  background-color: #337ab7;
  -webkit-box-shadow: inset 0 -1px 0 rgba(0, 0, 0, 0.15);
  box-shadow: inset 0 -1px 0 rgba(0, 0, 0, 0.15);
  -webkit-transition: width 0.6s ease;
  -o-transition: width 0.6s ease;
  transition: width 0.6s ease;
}
.progress-striped .progress-bar,
.progress-bar-striped {
  background-image: -webkit-linear-gradient(45deg, rgba(255, 255, 255, 0.15) 25%, transparent 25%, transparent 50%, rgba(255, 255, 255, 0.15) 50%, rgba(255, 255, 255, 0.15) 75%, transparent 75%, transparent);
  background-image: -o-linear-gradient(45deg, rgba(255, 255, 255, 0.15) 25%, transparent 25%, transparent 50%, rgba(255, 255, 255, 0.15) 50%, rgba(255, 255, 255, 0.15) 75%, transparent 75%, transparent);
  background-image: linear-gradient(45deg, rgba(255, 255, 255, 0.15) 25%, transparent 25%, transparent 50%, rgba(255, 255, 255, 0.15) 50%, rgba(255, 255, 255, 0.15) 75%, transparent 75%, transparent);
  background-size: 40px 40px;
}
.progress.active .progress-bar,
.progress-bar.active {
  -webkit-animation: progress-bar-stripes 2s linear infinite;
  -o-animation: progress-bar-stripes 2s linear infinite;
  animation: progress-bar-stripes 2s linear infinite;
}
.progress-bar-success {
  background-color: #5cb85c;
}
.progress-striped .progress-bar-success {
  background-image: -webkit-linear-gradient(45deg, rgba(255, 255, 255, 0.15) 25%, transparent 25%, transparent 50%, rgba(255, 255, 255, 0.15) 50%, rgba(255, 255, 255, 0.15) 75%, transparent 75%, transparent);
  background-image: -o-linear-gradient(45deg, rgba(255, 255, 255, 0.15) 25%, transparent 25%, transparent 50%, rgba(255, 255, 255, 0.15) 50%, rgba(255, 255, 255, 0.15) 75%, transparent 75%, transparent);
  background-image: linear-gradient(45deg, rgba(255, 255, 255, 0.15) 25%, transparent 25%, transparent 50%, rgba(255, 255, 255, 0.15) 50%, rgba(255, 255, 255, 0.15) 75%, transparent 75%, transparent);
}
.progress-bar-info {
  background-color: #5bc0de;
}
.progress-striped .progress-bar-info {
  background-image: -webkit-linear-gradient(45deg, rgba(255, 255, 255, 0.15) 25%, transparent 25%, transparent 50%, rgba(255, 255, 255, 0.15) 50%, rgba(255, 255, 255, 0.15) 75%, transparent 75%, transparent);
  background-image: -o-linear-gradient(45deg, rgba(255, 255, 255, 0.15) 25%, transparent 25%, transparent 50%, rgba(255, 255, 255, 0.15) 50%, rgba(255, 255, 255, 0.15) 75%, transparent 75%, transparent);
  background-image: linear-gradient(45deg, rgba(255, 255, 255, 0.15) 25%, transparent 25%, transparent 50%, rgba(255, 255, 255, 0.15) 50%, rgba(255, 255, 255, 0.15) 75%, transparent 75%, transparent);
}
.progress-bar-warning {
  background-color: #f0ad4e;
}
.progress-striped .progress-bar-warning {
  background-image: -webkit-linear-gradient(45deg, rgba(255, 255, 255, 0.15) 25%, transparent 25%, transparent 50%, rgba(255, 255, 255, 0.15) 50%, rgba(255, 255, 255, 0.15) 75%, transparent 75%, transparent);
  background-image: -o-linear-gradient(45deg, rgba(255, 255, 255, 0.15) 25%, transparent 25%, transparent 50%, rgba(255, 255, 255, 0.15) 50%, rgba(255, 255, 255, 0.15) 75%, transparent 75%, transparent);
  background-image: linear-gradient(45deg, rgba(255, 255, 255, 0.15) 25%, transparent 25%, transparent 50%, rgba(255, 255, 255, 0.15) 50%, rgba(255, 255, 255, 0.15) 75%, transparent 75%, transparent);
}
.progress-bar-danger {
  background-color: #d9534f;
}
.progress-striped .progress-bar-danger {
  background-image: -webkit-linear-gradient(45deg, rgba(255, 255, 255, 0.15) 25%, transparent 25%, transparent 50%, rgba(255, 255, 255, 0.15) 50%, rgba(255, 255, 255, 0.15) 75%, transparent 75%, transparent);
  background-image: -o-linear-gradient(45deg, rgba(255, 255, 255, 0.15) 25%, transparent 25%, transparent 50%, rgba(255, 255, 255, 0.15) 50%, rgba(255, 255, 255, 0.15) 75%, transparent 75%, transparent);
  background-image: linear-gradient(45deg, rgba(255, 255, 255, 0.15) 25%, transparent 25%, transparent 50%, rgba(255, 255, 255, 0.15) 50%, rgba(255, 255, 255, 0.15) 75%, transparent 75%, transparent);
}
.media {
  margin-top: 15px;
}
.media:first-child {
  margin-top: 0;
}
.media,
.media-body {
  zoom: 1;
  overflow: hidden;
}
.media-body {
  width: 10000px;
}
.media-object {
  display: block;
}
.media-object.img-thumbnail {
  max-width: none;
}
.media-right,
.media > .pull-right {
  padding-left: 10px;
}
.media-left,
.media > .pull-left {
  padding-right: 10px;
}
.media-left,
.media-right,
.media-body {
  display: table-cell;
  vertical-align: top;
}
.media-middle {
  vertical-align: middle;
}
.media-bottom {
  vertical-align: bottom;
}
.media-heading {
  margin-top: 0;
  margin-bottom: 5px;
}
.media-list {
  padding-left: 0;
  list-style: none;
}
.list-group {
  margin-bottom: 20px;
  padding-left: 0;
}
.list-group-item {
  position: relative;
  display: block;
  padding: 10px 15px;
  margin-bottom: -1px;
  background-color: #fff;
  border: 1px solid #ddd;
}
.list-group-item:first-child {
  border-top-right-radius: 2px;
  border-top-left-radius: 2px;
}
.list-group-item:last-child {
  margin-bottom: 0;
  border-bottom-right-radius: 2px;
  border-bottom-left-radius: 2px;
}
a.list-group-item,
button.list-group-item {
  color: #555;
}
a.list-group-item .list-group-item-heading,
button.list-group-item .list-group-item-heading {
  color: #333;
}
a.list-group-item:hover,
button.list-group-item:hover,
a.list-group-item:focus,
button.list-group-item:focus {
  text-decoration: none;
  color: #555;
  background-color: #f5f5f5;
}
button.list-group-item {
  width: 100%;
  text-align: left;
}
.list-group-item.disabled,
.list-group-item.disabled:hover,
.list-group-item.disabled:focus {
  background-color: #eeeeee;
  color: #777777;
  cursor: not-allowed;
}
.list-group-item.disabled .list-group-item-heading,
.list-group-item.disabled:hover .list-group-item-heading,
.list-group-item.disabled:focus .list-group-item-heading {
  color: inherit;
}
.list-group-item.disabled .list-group-item-text,
.list-group-item.disabled:hover .list-group-item-text,
.list-group-item.disabled:focus .list-group-item-text {
  color: #777777;
}
.list-group-item.active,
.list-group-item.active:hover,
.list-group-item.active:focus {
  z-index: 2;
  color: #fff;
  background-color: #337ab7;
  border-color: #337ab7;
}
.list-group-item.active .list-group-item-heading,
.list-group-item.active:hover .list-group-item-heading,
.list-group-item.active:focus .list-group-item-heading,
.list-group-item.active .list-group-item-heading > small,
.list-group-item.active:hover .list-group-item-heading > small,
.list-group-item.active:focus .list-group-item-heading > small,
.list-group-item.active .list-group-item-heading > .small,
.list-group-item.active:hover .list-group-item-heading > .small,
.list-group-item.active:focus .list-group-item-heading > .small {
  color: inherit;
}
.list-group-item.active .list-group-item-text,
.list-group-item.active:hover .list-group-item-text,
.list-group-item.active:focus .list-group-item-text {
  color: #c7ddef;
}
.list-group-item-success {
  color: #3c763d;
  background-color: #dff0d8;
}
a.list-group-item-success,
button.list-group-item-success {
  color: #3c763d;
}
a.list-group-item-success .list-group-item-heading,
button.list-group-item-success .list-group-item-heading {
  color: inherit;
}
a.list-group-item-success:hover,
button.list-group-item-success:hover,
a.list-group-item-success:focus,
button.list-group-item-success:focus {
  color: #3c763d;
  background-color: #d0e9c6;
}
a.list-group-item-success.active,
button.list-group-item-success.active,
a.list-group-item-success.active:hover,
button.list-group-item-success.active:hover,
a.list-group-item-success.active:focus,
button.list-group-item-success.active:focus {
  color: #fff;
  background-color: #3c763d;
  border-color: #3c763d;
}
.list-group-item-info {
  color: #31708f;
  background-color: #d9edf7;
}
a.list-group-item-info,
button.list-group-item-info {
  color: #31708f;
}
a.list-group-item-info .list-group-item-heading,
button.list-group-item-info .list-group-item-heading {
  color: inherit;
}
a.list-group-item-info:hover,
button.list-group-item-info:hover,
a.list-group-item-info:focus,
button.list-group-item-info:focus {
  color: #31708f;
  background-color: #c4e3f3;
}
a.list-group-item-info.active,
button.list-group-item-info.active,
a.list-group-item-info.active:hover,
button.list-group-item-info.active:hover,
a.list-group-item-info.active:focus,
button.list-group-item-info.active:focus {
  color: #fff;
  background-color: #31708f;
  border-color: #31708f;
}
.list-group-item-warning {
  color: #8a6d3b;
  background-color: #fcf8e3;
}
a.list-group-item-warning,
button.list-group-item-warning {
  color: #8a6d3b;
}
a.list-group-item-warning .list-group-item-heading,
button.list-group-item-warning .list-group-item-heading {
  color: inherit;
}
a.list-group-item-warning:hover,
button.list-group-item-warning:hover,
a.list-group-item-warning:focus,
button.list-group-item-warning:focus {
  color: #8a6d3b;
  background-color: #faf2cc;
}
a.list-group-item-warning.active,
button.list-group-item-warning.active,
a.list-group-item-warning.active:hover,
button.list-group-item-warning.active:hover,
a.list-group-item-warning.active:focus,
button.list-group-item-warning.active:focus {
  color: #fff;
  background-color: #8a6d3b;
  border-color: #8a6d3b;
}
.list-group-item-danger {
  color: #a94442;
  background-color: #f2dede;
}
a.list-group-item-danger,
button.list-group-item-danger {
  color: #a94442;
}
a.list-group-item-danger .list-group-item-heading,
button.list-group-item-danger .list-group-item-heading {
  color: inherit;
}
a.list-group-item-danger:hover,
button.list-group-item-danger:hover,
a.list-group-item-danger:focus,
button.list-group-item-danger:focus {
  color: #a94442;
  background-color: #ebcccc;
}
a.list-group-item-danger.active,
button.list-group-item-danger.active,
a.list-group-item-danger.active:hover,
button.list-group-item-danger.active:hover,
a.list-group-item-danger.active:focus,
button.list-group-item-danger.active:focus {
  color: #fff;
  background-color: #a94442;
  border-color: #a94442;
}
.list-group-item-heading {
  margin-top: 0;
  margin-bottom: 5px;
}
.list-group-item-text {
  margin-bottom: 0;
  line-height: 1.3;
}
.panel {
  margin-bottom: 18px;
  background-color: #fff;
  border: 1px solid transparent;
  border-radius: 2px;
  -webkit-box-shadow: 0 1px 1px rgba(0, 0, 0, 0.05);
  box-shadow: 0 1px 1px rgba(0, 0, 0, 0.05);
}
.panel-body {
  padding: 15px;
}
.panel-heading {
  padding: 10px 15px;
  border-bottom: 1px solid transparent;
  border-top-right-radius: 1px;
  border-top-left-radius: 1px;
}
.panel-heading > .dropdown .dropdown-toggle {
  color: inherit;
}
.panel-title {
  margin-top: 0;
  margin-bottom: 0;
  font-size: 15px;
  color: inherit;
}
.panel-title > a,
.panel-title > small,
.panel-title > .small,
.panel-title > small > a,
.panel-title > .small > a {
  color: inherit;
}
.panel-footer {
  padding: 10px 15px;
  background-color: #f5f5f5;
  border-top: 1px solid #ddd;
  border-bottom-right-radius: 1px;
  border-bottom-left-radius: 1px;
}
.panel > .list-group,
.panel > .panel-collapse > .list-group {
  margin-bottom: 0;
}
.panel > .list-group .list-group-item,
.panel > .panel-collapse > .list-group .list-group-item {
  border-width: 1px 0;
  border-radius: 0;
}
.panel > .list-group:first-child .list-group-item:first-child,
.panel > .panel-collapse > .list-group:first-child .list-group-item:first-child {
  border-top: 0;
  border-top-right-radius: 1px;
  border-top-left-radius: 1px;
}
.panel > .list-group:last-child .list-group-item:last-child,
.panel > .panel-collapse > .list-group:last-child .list-group-item:last-child {
  border-bottom: 0;
  border-bottom-right-radius: 1px;
  border-bottom-left-radius: 1px;
}
.panel > .panel-heading + .panel-collapse > .list-group .list-group-item:first-child {
  border-top-right-radius: 0;
  border-top-left-radius: 0;
}
.panel-heading + .list-group .list-group-item:first-child {
  border-top-width: 0;
}
.list-group + .panel-footer {
  border-top-width: 0;
}
.panel > .table,
.panel > .table-responsive > .table,
.panel > .panel-collapse > .table {
  margin-bottom: 0;
}
.panel > .table caption,
.panel > .table-responsive > .table caption,
.panel > .panel-collapse > .table caption {
  padding-left: 15px;
  padding-right: 15px;
}
.panel > .table:first-child,
.panel > .table-responsive:first-child > .table:first-child {
  border-top-right-radius: 1px;
  border-top-left-radius: 1px;
}
.panel > .table:first-child > thead:first-child > tr:first-child,
.panel > .table-responsive:first-child > .table:first-child > thead:first-child > tr:first-child,
.panel > .table:first-child > tbody:first-child > tr:first-child,
.panel > .table-responsive:first-child > .table:first-child > tbody:first-child > tr:first-child {
  border-top-left-radius: 1px;
  border-top-right-radius: 1px;
}
.panel > .table:first-child > thead:first-child > tr:first-child td:first-child,
.panel > .table-responsive:first-child > .table:first-child > thead:first-child > tr:first-child td:first-child,
.panel > .table:first-child > tbody:first-child > tr:first-child td:first-child,
.panel > .table-responsive:first-child > .table:first-child > tbody:first-child > tr:first-child td:first-child,
.panel > .table:first-child > thead:first-child > tr:first-child th:first-child,
.panel > .table-responsive:first-child > .table:first-child > thead:first-child > tr:first-child th:first-child,
.panel > .table:first-child > tbody:first-child > tr:first-child th:first-child,
.panel > .table-responsive:first-child > .table:first-child > tbody:first-child > tr:first-child th:first-child {
  border-top-left-radius: 1px;
}
.panel > .table:first-child > thead:first-child > tr:first-child td:last-child,
.panel > .table-responsive:first-child > .table:first-child > thead:first-child > tr:first-child td:last-child,
.panel > .table:first-child > tbody:first-child > tr:first-child td:last-child,
.panel > .table-responsive:first-child > .table:first-child > tbody:first-child > tr:first-child td:last-child,
.panel > .table:first-child > thead:first-child > tr:first-child th:last-child,
.panel > .table-responsive:first-child > .table:first-child > thead:first-child > tr:first-child th:last-child,
.panel > .table:first-child > tbody:first-child > tr:first-child th:last-child,
.panel > .table-responsive:first-child > .table:first-child > tbody:first-child > tr:first-child th:last-child {
  border-top-right-radius: 1px;
}
.panel > .table:last-child,
.panel > .table-responsive:last-child > .table:last-child {
  border-bottom-right-radius: 1px;
  border-bottom-left-radius: 1px;
}
.panel > .table:last-child > tbody:last-child > tr:last-child,
.panel > .table-responsive:last-child > .table:last-child > tbody:last-child > tr:last-child,
.panel > .table:last-child > tfoot:last-child > tr:last-child,
.panel > .table-responsive:last-child > .table:last-child > tfoot:last-child > tr:last-child {
  border-bottom-left-radius: 1px;
  border-bottom-right-radius: 1px;
}
.panel > .table:last-child > tbody:last-child > tr:last-child td:first-child,
.panel > .table-responsive:last-child > .table:last-child > tbody:last-child > tr:last-child td:first-child,
.panel > .table:last-child > tfoot:last-child > tr:last-child td:first-child,
.panel > .table-responsive:last-child > .table:last-child > tfoot:last-child > tr:last-child td:first-child,
.panel > .table:last-child > tbody:last-child > tr:last-child th:first-child,
.panel > .table-responsive:last-child > .table:last-child > tbody:last-child > tr:last-child th:first-child,
.panel > .table:last-child > tfoot:last-child > tr:last-child th:first-child,
.panel > .table-responsive:last-child > .table:last-child > tfoot:last-child > tr:last-child th:first-child {
  border-bottom-left-radius: 1px;
}
.panel > .table:last-child > tbody:last-child > tr:last-child td:last-child,
.panel > .table-responsive:last-child > .table:last-child > tbody:last-child > tr:last-child td:last-child,
.panel > .table:last-child > tfoot:last-child > tr:last-child td:last-child,
.panel > .table-responsive:last-child > .table:last-child > tfoot:last-child > tr:last-child td:last-child,
.panel > .table:last-child > tbody:last-child > tr:last-child th:last-child,
.panel > .table-responsive:last-child > .table:last-child > tbody:last-child > tr:last-child th:last-child,
.panel > .table:last-child > tfoot:last-child > tr:last-child th:last-child,
.panel > .table-responsive:last-child > .table:last-child > tfoot:last-child > tr:last-child th:last-child {
  border-bottom-right-radius: 1px;
}
.panel > .panel-body + .table,
.panel > .panel-body + .table-responsive,
.panel > .table + .panel-body,
.panel > .table-responsive + .panel-body {
  border-top: 1px solid #ddd;
}
.panel > .table > tbody:first-child > tr:first-child th,
.panel > .table > tbody:first-child > tr:first-child td {
  border-top: 0;
}
.panel > .table-bordered,
.panel > .table-responsive > .table-bordered {
  border: 0;
}
.panel > .table-bordered > thead > tr > th:first-child,
.panel > .table-responsive > .table-bordered > thead > tr > th:first-child,
.panel > .table-bordered > tbody > tr > th:first-child,
.panel > .table-responsive > .table-bordered > tbody > tr > th:first-child,
.panel > .table-bordered > tfoot > tr > th:first-child,
.panel > .table-responsive > .table-bordered > tfoot > tr > th:first-child,
.panel > .table-bordered > thead > tr > td:first-child,
.panel > .table-responsive > .table-bordered > thead > tr > td:first-child,
.panel > .table-bordered > tbody > tr > td:first-child,
.panel > .table-responsive > .table-bordered > tbody > tr > td:first-child,
.panel > .table-bordered > tfoot > tr > td:first-child,
.panel > .table-responsive > .table-bordered > tfoot > tr > td:first-child {
  border-left: 0;
}
.panel > .table-bordered > thead > tr > th:last-child,
.panel > .table-responsive > .table-bordered > thead > tr > th:last-child,
.panel > .table-bordered > tbody > tr > th:last-child,
.panel > .table-responsive > .table-bordered > tbody > tr > th:last-child,
.panel > .table-bordered > tfoot > tr > th:last-child,
.panel > .table-responsive > .table-bordered > tfoot > tr > th:last-child,
.panel > .table-bordered > thead > tr > td:last-child,
.panel > .table-responsive > .table-bordered > thead > tr > td:last-child,
.panel > .table-bordered > tbody > tr > td:last-child,
.panel > .table-responsive > .table-bordered > tbody > tr > td:last-child,
.panel > .table-bordered > tfoot > tr > td:last-child,
.panel > .table-responsive > .table-bordered > tfoot > tr > td:last-child {
  border-right: 0;
}
.panel > .table-bordered > thead > tr:first-child > td,
.panel > .table-responsive > .table-bordered > thead > tr:first-child > td,
.panel > .table-bordered > tbody > tr:first-child > td,
.panel > .table-responsive > .table-bordered > tbody > tr:first-child > td,
.panel > .table-bordered > thead > tr:first-child > th,
.panel > .table-responsive > .table-bordered > thead > tr:first-child > th,
.panel > .table-bordered > tbody > tr:first-child > th,
.panel > .table-responsive > .table-bordered > tbody > tr:first-child > th {
  border-bottom: 0;
}
.panel > .table-bordered > tbody > tr:last-child > td,
.panel > .table-responsive > .table-bordered > tbody > tr:last-child > td,
.panel > .table-bordered > tfoot > tr:last-child > td,
.panel > .table-responsive > .table-bordered > tfoot > tr:last-child > td,
.panel > .table-bordered > tbody > tr:last-child > th,
.panel > .table-responsive > .table-bordered > tbody > tr:last-child > th,
.panel > .table-bordered > tfoot > tr:last-child > th,
.panel > .table-responsive > .table-bordered > tfoot > tr:last-child > th {
  border-bottom: 0;
}
.panel > .table-responsive {
  border: 0;
  margin-bottom: 0;
}
.panel-group {
  margin-bottom: 18px;
}
.panel-group .panel {
  margin-bottom: 0;
  border-radius: 2px;
}
.panel-group .panel + .panel {
  margin-top: 5px;
}
.panel-group .panel-heading {
  border-bottom: 0;
}
.panel-group .panel-heading + .panel-collapse > .panel-body,
.panel-group .panel-heading + .panel-collapse > .list-group {
  border-top: 1px solid #ddd;
}
.panel-group .panel-footer {
  border-top: 0;
}
.panel-group .panel-footer + .panel-collapse .panel-body {
  border-bottom: 1px solid #ddd;
}
.panel-default {
  border-color: #ddd;
}
.panel-default > .panel-heading {
  color: #333333;
  background-color: #f5f5f5;
  border-color: #ddd;
}
.panel-default > .panel-heading + .panel-collapse > .panel-body {
  border-top-color: #ddd;
}
.panel-default > .panel-heading .badge {
  color: #f5f5f5;
  background-color: #333333;
}
.panel-default > .panel-footer + .panel-collapse > .panel-body {
  border-bottom-color: #ddd;
}
.panel-primary {
  border-color: #337ab7;
}
.panel-primary > .panel-heading {
  color: #fff;
  background-color: #337ab7;
  border-color: #337ab7;
}
.panel-primary > .panel-heading + .panel-collapse > .panel-body {
  border-top-color: #337ab7;
}
.panel-primary > .panel-heading .badge {
  color: #337ab7;
  background-color: #fff;
}
.panel-primary > .panel-footer + .panel-collapse > .panel-body {
  border-bottom-color: #337ab7;
}
.panel-success {
  border-color: #d6e9c6;
}
.panel-success > .panel-heading {
  color: #3c763d;
  background-color: #dff0d8;
  border-color: #d6e9c6;
}
.panel-success > .panel-heading + .panel-collapse > .panel-body {
  border-top-color: #d6e9c6;
}
.panel-success > .panel-heading .badge {
  color: #dff0d8;
  background-color: #3c763d;
}
.panel-success > .panel-footer + .panel-collapse > .panel-body {
  border-bottom-color: #d6e9c6;
}
.panel-info {
  border-color: #bce8f1;
}
.panel-info > .panel-heading {
  color: #31708f;
  background-color: #d9edf7;
  border-color: #bce8f1;
}
.panel-info > .panel-heading + .panel-collapse > .panel-body {
  border-top-color: #bce8f1;
}
.panel-info > .panel-heading .badge {
  color: #d9edf7;
  background-color: #31708f;
}
.panel-info > .panel-footer + .panel-collapse > .panel-body {
  border-bottom-color: #bce8f1;
}
.panel-warning {
  border-color: #faebcc;
}
.panel-warning > .panel-heading {
  color: #8a6d3b;
  background-color: #fcf8e3;
  border-color: #faebcc;
}
.panel-warning > .panel-heading + .panel-collapse > .panel-body {
  border-top-color: #faebcc;
}
.panel-warning > .panel-heading .badge {
  color: #fcf8e3;
  background-color: #8a6d3b;
}
.panel-warning > .panel-footer + .panel-collapse > .panel-body {
  border-bottom-color: #faebcc;
}
.panel-danger {
  border-color: #ebccd1;
}
.panel-danger > .panel-heading {
  color: #a94442;
  background-color: #f2dede;
  border-color: #ebccd1;
}
.panel-danger > .panel-heading + .panel-collapse > .panel-body {
  border-top-color: #ebccd1;
}
.panel-danger > .panel-heading .badge {
  color: #f2dede;
  background-color: #a94442;
}
.panel-danger > .panel-footer + .panel-collapse > .panel-body {
  border-bottom-color: #ebccd1;
}
.embed-responsive {
  position: relative;
  display: block;
  height: 0;
  padding: 0;
  overflow: hidden;
}
.embed-responsive .embed-responsive-item,
.embed-responsive iframe,
.embed-responsive embed,
.embed-responsive object,
.embed-responsive video {
  position: absolute;
  top: 0;
  left: 0;
  bottom: 0;
  height: 100%;
  width: 100%;
  border: 0;
}
.embed-responsive-16by9 {
  padding-bottom: 56.25%;
}
.embed-responsive-4by3 {
  padding-bottom: 75%;
}
.well {
  min-height: 20px;
  padding: 19px;
  margin-bottom: 20px;
  background-color: #f5f5f5;
  border: 1px solid #e3e3e3;
  border-radius: 2px;
  -webkit-box-shadow: inset 0 1px 1px rgba(0, 0, 0, 0.05);
  box-shadow: inset 0 1px 1px rgba(0, 0, 0, 0.05);
}
.well blockquote {
  border-color: #ddd;
  border-color: rgba(0, 0, 0, 0.15);
}
.well-lg {
  padding: 24px;
  border-radius: 3px;
}
.well-sm {
  padding: 9px;
  border-radius: 1px;
}
.close {
  float: right;
  font-size: 19.5px;
  font-weight: bold;
  line-height: 1;
  color: #000;
  text-shadow: 0 1px 0 #fff;
  opacity: 0.2;
  filter: alpha(opacity=20);
}
.close:hover,
.close:focus {
  color: #000;
  text-decoration: none;
  cursor: pointer;
  opacity: 0.5;
  filter: alpha(opacity=50);
}
button.close {
  padding: 0;
  cursor: pointer;
  background: transparent;
  border: 0;
  -webkit-appearance: none;
}
.modal-open {
  overflow: hidden;
}
.modal {
  display: none;
  overflow: hidden;
  position: fixed;
  top: 0;
  right: 0;
  bottom: 0;
  left: 0;
  z-index: 1050;
  -webkit-overflow-scrolling: touch;
  outline: 0;
}
.modal.fade .modal-dialog {
  -webkit-transform: translate(0, -25%);
  -ms-transform: translate(0, -25%);
  -o-transform: translate(0, -25%);
  transform: translate(0, -25%);
  -webkit-transition: -webkit-transform 0.3s ease-out;
  -moz-transition: -moz-transform 0.3s ease-out;
  -o-transition: -o-transform 0.3s ease-out;
  transition: transform 0.3s ease-out;
}
.modal.in .modal-dialog {
  -webkit-transform: translate(0, 0);
  -ms-transform: translate(0, 0);
  -o-transform: translate(0, 0);
  transform: translate(0, 0);
}
.modal-open .modal {
  overflow-x: hidden;
  overflow-y: auto;
}
.modal-dialog {
  position: relative;
  width: auto;
  margin: 10px;
}
.modal-content {
  position: relative;
  background-color: #fff;
  border: 1px solid #999;
  border: 1px solid rgba(0, 0, 0, 0.2);
  border-radius: 3px;
  -webkit-box-shadow: 0 3px 9px rgba(0, 0, 0, 0.5);
  box-shadow: 0 3px 9px rgba(0, 0, 0, 0.5);
  background-clip: padding-box;
  outline: 0;
}
.modal-backdrop {
  position: fixed;
  top: 0;
  right: 0;
  bottom: 0;
  left: 0;
  z-index: 1040;
  background-color: #000;
}
.modal-backdrop.fade {
  opacity: 0;
  filter: alpha(opacity=0);
}
.modal-backdrop.in {
  opacity: 0.5;
  filter: alpha(opacity=50);
}
.modal-header {
  padding: 15px;
  border-bottom: 1px solid #e5e5e5;
}
.modal-header .close {
  margin-top: -2px;
}
.modal-title {
  margin: 0;
  line-height: 1.42857143;
}
.modal-body {
  position: relative;
  padding: 15px;
}
.modal-footer {
  padding: 15px;
  text-align: right;
  border-top: 1px solid #e5e5e5;
}
.modal-footer .btn + .btn {
  margin-left: 5px;
  margin-bottom: 0;
}
.modal-footer .btn-group .btn + .btn {
  margin-left: -1px;
}
.modal-footer .btn-block + .btn-block {
  margin-left: 0;
}
.modal-scrollbar-measure {
  position: absolute;
  top: -9999px;
  width: 50px;
  height: 50px;
  overflow: scroll;
}
@media (min-width: 768px) {
  .modal-dialog {
    width: 600px;
    margin: 30px auto;
  }
  .modal-content {
    -webkit-box-shadow: 0 5px 15px rgba(0, 0, 0, 0.5);
    box-shadow: 0 5px 15px rgba(0, 0, 0, 0.5);
  }
  .modal-sm {
    width: 300px;
  }
}
@media (min-width: 992px) {
  .modal-lg {
    width: 900px;
  }
}
.tooltip {
  position: absolute;
  z-index: 1070;
  display: block;
  font-family: "Helvetica Neue", Helvetica, Arial, sans-serif;
  font-style: normal;
  font-weight: normal;
  letter-spacing: normal;
  line-break: auto;
  line-height: 1.42857143;
  text-align: left;
  text-align: start;
  text-decoration: none;
  text-shadow: none;
  text-transform: none;
  white-space: normal;
  word-break: normal;
  word-spacing: normal;
  word-wrap: normal;
  font-size: 12px;
  opacity: 0;
  filter: alpha(opacity=0);
}
.tooltip.in {
  opacity: 0.9;
  filter: alpha(opacity=90);
}
.tooltip.top {
  margin-top: -3px;
  padding: 5px 0;
}
.tooltip.right {
  margin-left: 3px;
  padding: 0 5px;
}
.tooltip.bottom {
  margin-top: 3px;
  padding: 5px 0;
}
.tooltip.left {
  margin-left: -3px;
  padding: 0 5px;
}
.tooltip-inner {
  max-width: 200px;
  padding: 3px 8px;
  color: #fff;
  text-align: center;
  background-color: #000;
  border-radius: 2px;
}
.tooltip-arrow {
  position: absolute;
  width: 0;
  height: 0;
  border-color: transparent;
  border-style: solid;
}
.tooltip.top .tooltip-arrow {
  bottom: 0;
  left: 50%;
  margin-left: -5px;
  border-width: 5px 5px 0;
  border-top-color: #000;
}
.tooltip.top-left .tooltip-arrow {
  bottom: 0;
  right: 5px;
  margin-bottom: -5px;
  border-width: 5px 5px 0;
  border-top-color: #000;
}
.tooltip.top-right .tooltip-arrow {
  bottom: 0;
  left: 5px;
  margin-bottom: -5px;
  border-width: 5px 5px 0;
  border-top-color: #000;
}
.tooltip.right .tooltip-arrow {
  top: 50%;
  left: 0;
  margin-top: -5px;
  border-width: 5px 5px 5px 0;
  border-right-color: #000;
}
.tooltip.left .tooltip-arrow {
  top: 50%;
  right: 0;
  margin-top: -5px;
  border-width: 5px 0 5px 5px;
  border-left-color: #000;
}
.tooltip.bottom .tooltip-arrow {
  top: 0;
  left: 50%;
  margin-left: -5px;
  border-width: 0 5px 5px;
  border-bottom-color: #000;
}
.tooltip.bottom-left .tooltip-arrow {
  top: 0;
  right: 5px;
  margin-top: -5px;
  border-width: 0 5px 5px;
  border-bottom-color: #000;
}
.tooltip.bottom-right .tooltip-arrow {
  top: 0;
  left: 5px;
  margin-top: -5px;
  border-width: 0 5px 5px;
  border-bottom-color: #000;
}
.popover {
  position: absolute;
  top: 0;
  left: 0;
  z-index: 1060;
  display: none;
  max-width: 276px;
  padding: 1px;
  font-family: "Helvetica Neue", Helvetica, Arial, sans-serif;
  font-style: normal;
  font-weight: normal;
  letter-spacing: normal;
  line-break: auto;
  line-height: 1.42857143;
  text-align: left;
  text-align: start;
  text-decoration: none;
  text-shadow: none;
  text-transform: none;
  white-space: normal;
  word-break: normal;
  word-spacing: normal;
  word-wrap: normal;
  font-size: 13px;
  background-color: #fff;
  background-clip: padding-box;
  border: 1px solid #ccc;
  border: 1px solid rgba(0, 0, 0, 0.2);
  border-radius: 3px;
  -webkit-box-shadow: 0 5px 10px rgba(0, 0, 0, 0.2);
  box-shadow: 0 5px 10px rgba(0, 0, 0, 0.2);
}
.popover.top {
  margin-top: -10px;
}
.popover.right {
  margin-left: 10px;
}
.popover.bottom {
  margin-top: 10px;
}
.popover.left {
  margin-left: -10px;
}
.popover-title {
  margin: 0;
  padding: 8px 14px;
  font-size: 13px;
  background-color: #f7f7f7;
  border-bottom: 1px solid #ebebeb;
  border-radius: 2px 2px 0 0;
}
.popover-content {
  padding: 9px 14px;
}
.popover > .arrow,
.popover > .arrow:after {
  position: absolute;
  display: block;
  width: 0;
  height: 0;
  border-color: transparent;
  border-style: solid;
}
.popover > .arrow {
  border-width: 11px;
}
.popover > .arrow:after {
  border-width: 10px;
  content: "";
}
.popover.top > .arrow {
  left: 50%;
  margin-left: -11px;
  border-bottom-width: 0;
  border-top-color: #999999;
  border-top-color: rgba(0, 0, 0, 0.25);
  bottom: -11px;
}
.popover.top > .arrow:after {
  content: " ";
  bottom: 1px;
  margin-left: -10px;
  border-bottom-width: 0;
  border-top-color: #fff;
}
.popover.right > .arrow {
  top: 50%;
  left: -11px;
  margin-top: -11px;
  border-left-width: 0;
  border-right-color: #999999;
  border-right-color: rgba(0, 0, 0, 0.25);
}
.popover.right > .arrow:after {
  content: " ";
  left: 1px;
  bottom: -10px;
  border-left-width: 0;
  border-right-color: #fff;
}
.popover.bottom > .arrow {
  left: 50%;
  margin-left: -11px;
  border-top-width: 0;
  border-bottom-color: #999999;
  border-bottom-color: rgba(0, 0, 0, 0.25);
  top: -11px;
}
.popover.bottom > .arrow:after {
  content: " ";
  top: 1px;
  margin-left: -10px;
  border-top-width: 0;
  border-bottom-color: #fff;
}
.popover.left > .arrow {
  top: 50%;
  right: -11px;
  margin-top: -11px;
  border-right-width: 0;
  border-left-color: #999999;
  border-left-color: rgba(0, 0, 0, 0.25);
}
.popover.left > .arrow:after {
  content: " ";
  right: 1px;
  border-right-width: 0;
  border-left-color: #fff;
  bottom: -10px;
}
.carousel {
  position: relative;
}
.carousel-inner {
  position: relative;
  overflow: hidden;
  width: 100%;
}
.carousel-inner > .item {
  display: none;
  position: relative;
  -webkit-transition: 0.6s ease-in-out left;
  -o-transition: 0.6s ease-in-out left;
  transition: 0.6s ease-in-out left;
}
.carousel-inner > .item > img,
.carousel-inner > .item > a > img {
  line-height: 1;
}
@media all and (transform-3d), (-webkit-transform-3d) {
  .carousel-inner > .item {
    -webkit-transition: -webkit-transform 0.6s ease-in-out;
    -moz-transition: -moz-transform 0.6s ease-in-out;
    -o-transition: -o-transform 0.6s ease-in-out;
    transition: transform 0.6s ease-in-out;
    -webkit-backface-visibility: hidden;
    -moz-backface-visibility: hidden;
    backface-visibility: hidden;
    -webkit-perspective: 1000px;
    -moz-perspective: 1000px;
    perspective: 1000px;
  }
  .carousel-inner > .item.next,
  .carousel-inner > .item.active.right {
    -webkit-transform: translate3d(100%, 0, 0);
    transform: translate3d(100%, 0, 0);
    left: 0;
  }
  .carousel-inner > .item.prev,
  .carousel-inner > .item.active.left {
    -webkit-transform: translate3d(-100%, 0, 0);
    transform: translate3d(-100%, 0, 0);
    left: 0;
  }
  .carousel-inner > .item.next.left,
  .carousel-inner > .item.prev.right,
  .carousel-inner > .item.active {
    -webkit-transform: translate3d(0, 0, 0);
    transform: translate3d(0, 0, 0);
    left: 0;
  }
}
.carousel-inner > .active,
.carousel-inner > .next,
.carousel-inner > .prev {
  display: block;
}
.carousel-inner > .active {
  left: 0;
}
.carousel-inner > .next,
.carousel-inner > .prev {
  position: absolute;
  top: 0;
  width: 100%;
}
.carousel-inner > .next {
  left: 100%;
}
.carousel-inner > .prev {
  left: -100%;
}
.carousel-inner > .next.left,
.carousel-inner > .prev.right {
  left: 0;
}
.carousel-inner > .active.left {
  left: -100%;
}
.carousel-inner > .active.right {
  left: 100%;
}
.carousel-control {
  position: absolute;
  top: 0;
  left: 0;
  bottom: 0;
  width: 15%;
  opacity: 0.5;
  filter: alpha(opacity=50);
  font-size: 20px;
  color: #fff;
  text-align: center;
  text-shadow: 0 1px 2px rgba(0, 0, 0, 0.6);
  background-color: rgba(0, 0, 0, 0);
}
.carousel-control.left {
  background-image: -webkit-linear-gradient(left, rgba(0, 0, 0, 0.5) 0%, rgba(0, 0, 0, 0.0001) 100%);
  background-image: -o-linear-gradient(left, rgba(0, 0, 0, 0.5) 0%, rgba(0, 0, 0, 0.0001) 100%);
  background-image: linear-gradient(to right, rgba(0, 0, 0, 0.5) 0%, rgba(0, 0, 0, 0.0001) 100%);
  background-repeat: repeat-x;
  filter: progid:DXImageTransform.Microsoft.gradient(startColorstr='#80000000', endColorstr='#00000000', GradientType=1);
}
.carousel-control.right {
  left: auto;
  right: 0;
  background-image: -webkit-linear-gradient(left, rgba(0, 0, 0, 0.0001) 0%, rgba(0, 0, 0, 0.5) 100%);
  background-image: -o-linear-gradient(left, rgba(0, 0, 0, 0.0001) 0%, rgba(0, 0, 0, 0.5) 100%);
  background-image: linear-gradient(to right, rgba(0, 0, 0, 0.0001) 0%, rgba(0, 0, 0, 0.5) 100%);
  background-repeat: repeat-x;
  filter: progid:DXImageTransform.Microsoft.gradient(startColorstr='#00000000', endColorstr='#80000000', GradientType=1);
}
.carousel-control:hover,
.carousel-control:focus {
  outline: 0;
  color: #fff;
  text-decoration: none;
  opacity: 0.9;
  filter: alpha(opacity=90);
}
.carousel-control .icon-prev,
.carousel-control .icon-next,
.carousel-control .glyphicon-chevron-left,
.carousel-control .glyphicon-chevron-right {
  position: absolute;
  top: 50%;
  margin-top: -10px;
  z-index: 5;
  display: inline-block;
}
.carousel-control .icon-prev,
.carousel-control .glyphicon-chevron-left {
  left: 50%;
  margin-left: -10px;
}
.carousel-control .icon-next,
.carousel-control .glyphicon-chevron-right {
  right: 50%;
  margin-right: -10px;
}
.carousel-control .icon-prev,
.carousel-control .icon-next {
  width: 20px;
  height: 20px;
  line-height: 1;
  font-family: serif;
}
.carousel-control .icon-prev:before {
  content: '\2039';
}
.carousel-control .icon-next:before {
  content: '\203a';
}
.carousel-indicators {
  position: absolute;
  bottom: 10px;
  left: 50%;
  z-index: 15;
  width: 60%;
  margin-left: -30%;
  padding-left: 0;
  list-style: none;
  text-align: center;
}
.carousel-indicators li {
  display: inline-block;
  width: 10px;
  height: 10px;
  margin: 1px;
  text-indent: -999px;
  border: 1px solid #fff;
  border-radius: 10px;
  cursor: pointer;
  background-color: #000 \9;
  background-color: rgba(0, 0, 0, 0);
}
.carousel-indicators .active {
  margin: 0;
  width: 12px;
  height: 12px;
  background-color: #fff;
}
.carousel-caption {
  position: absolute;
  left: 15%;
  right: 15%;
  bottom: 20px;
  z-index: 10;
  padding-top: 20px;
  padding-bottom: 20px;
  color: #fff;
  text-align: center;
  text-shadow: 0 1px 2px rgba(0, 0, 0, 0.6);
}
.carousel-caption .btn {
  text-shadow: none;
}
@media screen and (min-width: 768px) {
  .carousel-control .glyphicon-chevron-left,
  .carousel-control .glyphicon-chevron-right,
  .carousel-control .icon-prev,
  .carousel-control .icon-next {
    width: 30px;
    height: 30px;
    margin-top: -10px;
    font-size: 30px;
  }
  .carousel-control .glyphicon-chevron-left,
  .carousel-control .icon-prev {
    margin-left: -10px;
  }
  .carousel-control .glyphicon-chevron-right,
  .carousel-control .icon-next {
    margin-right: -10px;
  }
  .carousel-caption {
    left: 20%;
    right: 20%;
    padding-bottom: 30px;
  }
  .carousel-indicators {
    bottom: 20px;
  }
}
.clearfix:before,
.clearfix:after,
.dl-horizontal dd:before,
.dl-horizontal dd:after,
.container:before,
.container:after,
.container-fluid:before,
.container-fluid:after,
.row:before,
.row:after,
.form-horizontal .form-group:before,
.form-horizontal .form-group:after,
.btn-toolbar:before,
.btn-toolbar:after,
.btn-group-vertical > .btn-group:before,
.btn-group-vertical > .btn-group:after,
.nav:before,
.nav:after,
.navbar:before,
.navbar:after,
.navbar-header:before,
.navbar-header:after,
.navbar-collapse:before,
.navbar-collapse:after,
.pager:before,
.pager:after,
.panel-body:before,
.panel-body:after,
.modal-header:before,
.modal-header:after,
.modal-footer:before,
.modal-footer:after,
.item_buttons:before,
.item_buttons:after {
  content: " ";
  display: table;
}
.clearfix:after,
.dl-horizontal dd:after,
.container:after,
.container-fluid:after,
.row:after,
.form-horizontal .form-group:after,
.btn-toolbar:after,
.btn-group-vertical > .btn-group:after,
.nav:after,
.navbar:after,
.navbar-header:after,
.navbar-collapse:after,
.pager:after,
.panel-body:after,
.modal-header:after,
.modal-footer:after,
.item_buttons:after {
  clear: both;
}
.center-block {
  display: block;
  margin-left: auto;
  margin-right: auto;
}
.pull-right {
  float: right !important;
}
.pull-left {
  float: left !important;
}
.hide {
  display: none !important;
}
.show {
  display: block !important;
}
.invisible {
  visibility: hidden;
}
.text-hide {
  font: 0/0 a;
  color: transparent;
  text-shadow: none;
  background-color: transparent;
  border: 0;
}
.hidden {
  display: none !important;
}
.affix {
  position: fixed;
}
@-ms-viewport {
  width: device-width;
}
.visible-xs,
.visible-sm,
.visible-md,
.visible-lg {
  display: none !important;
}
.visible-xs-block,
.visible-xs-inline,
.visible-xs-inline-block,
.visible-sm-block,
.visible-sm-inline,
.visible-sm-inline-block,
.visible-md-block,
.visible-md-inline,
.visible-md-inline-block,
.visible-lg-block,
.visible-lg-inline,
.visible-lg-inline-block {
  display: none !important;
}
@media (max-width: 767px) {
  .visible-xs {
    display: block !important;
  }
  table.visible-xs {
    display: table !important;
  }
  tr.visible-xs {
    display: table-row !important;
  }
  th.visible-xs,
  td.visible-xs {
    display: table-cell !important;
  }
}
@media (max-width: 767px) {
  .visible-xs-block {
    display: block !important;
  }
}
@media (max-width: 767px) {
  .visible-xs-inline {
    display: inline !important;
  }
}
@media (max-width: 767px) {
  .visible-xs-inline-block {
    display: inline-block !important;
  }
}
@media (min-width: 768px) and (max-width: 991px) {
  .visible-sm {
    display: block !important;
  }
  table.visible-sm {
    display: table !important;
  }
  tr.visible-sm {
    display: table-row !important;
  }
  th.visible-sm,
  td.visible-sm {
    display: table-cell !important;
  }
}
@media (min-width: 768px) and (max-width: 991px) {
  .visible-sm-block {
    display: block !important;
  }
}
@media (min-width: 768px) and (max-width: 991px) {
  .visible-sm-inline {
    display: inline !important;
  }
}
@media (min-width: 768px) and (max-width: 991px) {
  .visible-sm-inline-block {
    display: inline-block !important;
  }
}
@media (min-width: 992px) and (max-width: 1199px) {
  .visible-md {
    display: block !important;
  }
  table.visible-md {
    display: table !important;
  }
  tr.visible-md {
    display: table-row !important;
  }
  th.visible-md,
  td.visible-md {
    display: table-cell !important;
  }
}
@media (min-width: 992px) and (max-width: 1199px) {
  .visible-md-block {
    display: block !important;
  }
}
@media (min-width: 992px) and (max-width: 1199px) {
  .visible-md-inline {
    display: inline !important;
  }
}
@media (min-width: 992px) and (max-width: 1199px) {
  .visible-md-inline-block {
    display: inline-block !important;
  }
}
@media (min-width: 1200px) {
  .visible-lg {
    display: block !important;
  }
  table.visible-lg {
    display: table !important;
  }
  tr.visible-lg {
    display: table-row !important;
  }
  th.visible-lg,
  td.visible-lg {
    display: table-cell !important;
  }
}
@media (min-width: 1200px) {
  .visible-lg-block {
    display: block !important;
  }
}
@media (min-width: 1200px) {
  .visible-lg-inline {
    display: inline !important;
  }
}
@media (min-width: 1200px) {
  .visible-lg-inline-block {
    display: inline-block !important;
  }
}
@media (max-width: 767px) {
  .hidden-xs {
    display: none !important;
  }
}
@media (min-width: 768px) and (max-width: 991px) {
  .hidden-sm {
    display: none !important;
  }
}
@media (min-width: 992px) and (max-width: 1199px) {
  .hidden-md {
    display: none !important;
  }
}
@media (min-width: 1200px) {
  .hidden-lg {
    display: none !important;
  }
}
.visible-print {
  display: none !important;
}
@media print {
  .visible-print {
    display: block !important;
  }
  table.visible-print {
    display: table !important;
  }
  tr.visible-print {
    display: table-row !important;
  }
  th.visible-print,
  td.visible-print {
    display: table-cell !important;
  }
}
.visible-print-block {
  display: none !important;
}
@media print {
  .visible-print-block {
    display: block !important;
  }
}
.visible-print-inline {
  display: none !important;
}
@media print {
  .visible-print-inline {
    display: inline !important;
  }
}
.visible-print-inline-block {
  display: none !important;
}
@media print {
  .visible-print-inline-block {
    display: inline-block !important;
  }
}
@media print {
  .hidden-print {
    display: none !important;
  }
}
/*!
*
* Font Awesome
*
*/
/*!
 *  Font Awesome 4.2.0 by @davegandy - http://fontawesome.io - @fontawesome
 *  License - http://fontawesome.io/license (Font: SIL OFL 1.1, CSS: MIT License)
 */
/* FONT PATH
 * -------------------------- */
@font-face {
  font-family: 'FontAwesome';
  src: url('../components/font-awesome/fonts/fontawesome-webfont.eot?v=4.2.0');
  src: url('../components/font-awesome/fonts/fontawesome-webfont.eot?#iefix&v=4.2.0') format('embedded-opentype'), url('../components/font-awesome/fonts/fontawesome-webfont.woff?v=4.2.0') format('woff'), url('../components/font-awesome/fonts/fontawesome-webfont.ttf?v=4.2.0') format('truetype'), url('../components/font-awesome/fonts/fontawesome-webfont.svg?v=4.2.0#fontawesomeregular') format('svg');
  font-weight: normal;
  font-style: normal;
}
.fa {
  display: inline-block;
  font: normal normal normal 14px/1 FontAwesome;
  font-size: inherit;
  text-rendering: auto;
  -webkit-font-smoothing: antialiased;
  -moz-osx-font-smoothing: grayscale;
}
/* makes the font 33% larger relative to the icon container */
.fa-lg {
  font-size: 1.33333333em;
  line-height: 0.75em;
  vertical-align: -15%;
}
.fa-2x {
  font-size: 2em;
}
.fa-3x {
  font-size: 3em;
}
.fa-4x {
  font-size: 4em;
}
.fa-5x {
  font-size: 5em;
}
.fa-fw {
  width: 1.28571429em;
  text-align: center;
}
.fa-ul {
  padding-left: 0;
  margin-left: 2.14285714em;
  list-style-type: none;
}
.fa-ul > li {
  position: relative;
}
.fa-li {
  position: absolute;
  left: -2.14285714em;
  width: 2.14285714em;
  top: 0.14285714em;
  text-align: center;
}
.fa-li.fa-lg {
  left: -1.85714286em;
}
.fa-border {
  padding: .2em .25em .15em;
  border: solid 0.08em #eee;
  border-radius: .1em;
}
.pull-right {
  float: right;
}
.pull-left {
  float: left;
}
.fa.pull-left {
  margin-right: .3em;
}
.fa.pull-right {
  margin-left: .3em;
}
.fa-spin {
  -webkit-animation: fa-spin 2s infinite linear;
  animation: fa-spin 2s infinite linear;
}
@-webkit-keyframes fa-spin {
  0% {
    -webkit-transform: rotate(0deg);
    transform: rotate(0deg);
  }
  100% {
    -webkit-transform: rotate(359deg);
    transform: rotate(359deg);
  }
}
@keyframes fa-spin {
  0% {
    -webkit-transform: rotate(0deg);
    transform: rotate(0deg);
  }
  100% {
    -webkit-transform: rotate(359deg);
    transform: rotate(359deg);
  }
}
.fa-rotate-90 {
  filter: progid:DXImageTransform.Microsoft.BasicImage(rotation=1);
  -webkit-transform: rotate(90deg);
  -ms-transform: rotate(90deg);
  transform: rotate(90deg);
}
.fa-rotate-180 {
  filter: progid:DXImageTransform.Microsoft.BasicImage(rotation=2);
  -webkit-transform: rotate(180deg);
  -ms-transform: rotate(180deg);
  transform: rotate(180deg);
}
.fa-rotate-270 {
  filter: progid:DXImageTransform.Microsoft.BasicImage(rotation=3);
  -webkit-transform: rotate(270deg);
  -ms-transform: rotate(270deg);
  transform: rotate(270deg);
}
.fa-flip-horizontal {
  filter: progid:DXImageTransform.Microsoft.BasicImage(rotation=0, mirror=1);
  -webkit-transform: scale(-1, 1);
  -ms-transform: scale(-1, 1);
  transform: scale(-1, 1);
}
.fa-flip-vertical {
  filter: progid:DXImageTransform.Microsoft.BasicImage(rotation=2, mirror=1);
  -webkit-transform: scale(1, -1);
  -ms-transform: scale(1, -1);
  transform: scale(1, -1);
}
:root .fa-rotate-90,
:root .fa-rotate-180,
:root .fa-rotate-270,
:root .fa-flip-horizontal,
:root .fa-flip-vertical {
  filter: none;
}
.fa-stack {
  position: relative;
  display: inline-block;
  width: 2em;
  height: 2em;
  line-height: 2em;
  vertical-align: middle;
}
.fa-stack-1x,
.fa-stack-2x {
  position: absolute;
  left: 0;
  width: 100%;
  text-align: center;
}
.fa-stack-1x {
  line-height: inherit;
}
.fa-stack-2x {
  font-size: 2em;
}
.fa-inverse {
  color: #fff;
}
/* Font Awesome uses the Unicode Private Use Area (PUA) to ensure screen
   readers do not read off random characters that represent icons */
.fa-glass:before {
  content: "\f000";
}
.fa-music:before {
  content: "\f001";
}
.fa-search:before {
  content: "\f002";
}
.fa-envelope-o:before {
  content: "\f003";
}
.fa-heart:before {
  content: "\f004";
}
.fa-star:before {
  content: "\f005";
}
.fa-star-o:before {
  content: "\f006";
}
.fa-user:before {
  content: "\f007";
}
.fa-film:before {
  content: "\f008";
}
.fa-th-large:before {
  content: "\f009";
}
.fa-th:before {
  content: "\f00a";
}
.fa-th-list:before {
  content: "\f00b";
}
.fa-check:before {
  content: "\f00c";
}
.fa-remove:before,
.fa-close:before,
.fa-times:before {
  content: "\f00d";
}
.fa-search-plus:before {
  content: "\f00e";
}
.fa-search-minus:before {
  content: "\f010";
}
.fa-power-off:before {
  content: "\f011";
}
.fa-signal:before {
  content: "\f012";
}
.fa-gear:before,
.fa-cog:before {
  content: "\f013";
}
.fa-trash-o:before {
  content: "\f014";
}
.fa-home:before {
  content: "\f015";
}
.fa-file-o:before {
  content: "\f016";
}
.fa-clock-o:before {
  content: "\f017";
}
.fa-road:before {
  content: "\f018";
}
.fa-download:before {
  content: "\f019";
}
.fa-arrow-circle-o-down:before {
  content: "\f01a";
}
.fa-arrow-circle-o-up:before {
  content: "\f01b";
}
.fa-inbox:before {
  content: "\f01c";
}
.fa-play-circle-o:before {
  content: "\f01d";
}
.fa-rotate-right:before,
.fa-repeat:before {
  content: "\f01e";
}
.fa-refresh:before {
  content: "\f021";
}
.fa-list-alt:before {
  content: "\f022";
}
.fa-lock:before {
  content: "\f023";
}
.fa-flag:before {
  content: "\f024";
}
.fa-headphones:before {
  content: "\f025";
}
.fa-volume-off:before {
  content: "\f026";
}
.fa-volume-down:before {
  content: "\f027";
}
.fa-volume-up:before {
  content: "\f028";
}
.fa-qrcode:before {
  content: "\f029";
}
.fa-barcode:before {
  content: "\f02a";
}
.fa-tag:before {
  content: "\f02b";
}
.fa-tags:before {
  content: "\f02c";
}
.fa-book:before {
  content: "\f02d";
}
.fa-bookmark:before {
  content: "\f02e";
}
.fa-print:before {
  content: "\f02f";
}
.fa-camera:before {
  content: "\f030";
}
.fa-font:before {
  content: "\f031";
}
.fa-bold:before {
  content: "\f032";
}
.fa-italic:before {
  content: "\f033";
}
.fa-text-height:before {
  content: "\f034";
}
.fa-text-width:before {
  content: "\f035";
}
.fa-align-left:before {
  content: "\f036";
}
.fa-align-center:before {
  content: "\f037";
}
.fa-align-right:before {
  content: "\f038";
}
.fa-align-justify:before {
  content: "\f039";
}
.fa-list:before {
  content: "\f03a";
}
.fa-dedent:before,
.fa-outdent:before {
  content: "\f03b";
}
.fa-indent:before {
  content: "\f03c";
}
.fa-video-camera:before {
  content: "\f03d";
}
.fa-photo:before,
.fa-image:before,
.fa-picture-o:before {
  content: "\f03e";
}
.fa-pencil:before {
  content: "\f040";
}
.fa-map-marker:before {
  content: "\f041";
}
.fa-adjust:before {
  content: "\f042";
}
.fa-tint:before {
  content: "\f043";
}
.fa-edit:before,
.fa-pencil-square-o:before {
  content: "\f044";
}
.fa-share-square-o:before {
  content: "\f045";
}
.fa-check-square-o:before {
  content: "\f046";
}
.fa-arrows:before {
  content: "\f047";
}
.fa-step-backward:before {
  content: "\f048";
}
.fa-fast-backward:before {
  content: "\f049";
}
.fa-backward:before {
  content: "\f04a";
}
.fa-play:before {
  content: "\f04b";
}
.fa-pause:before {
  content: "\f04c";
}
.fa-stop:before {
  content: "\f04d";
}
.fa-forward:before {
  content: "\f04e";
}
.fa-fast-forward:before {
  content: "\f050";
}
.fa-step-forward:before {
  content: "\f051";
}
.fa-eject:before {
  content: "\f052";
}
.fa-chevron-left:before {
  content: "\f053";
}
.fa-chevron-right:before {
  content: "\f054";
}
.fa-plus-circle:before {
  content: "\f055";
}
.fa-minus-circle:before {
  content: "\f056";
}
.fa-times-circle:before {
  content: "\f057";
}
.fa-check-circle:before {
  content: "\f058";
}
.fa-question-circle:before {
  content: "\f059";
}
.fa-info-circle:before {
  content: "\f05a";
}
.fa-crosshairs:before {
  content: "\f05b";
}
.fa-times-circle-o:before {
  content: "\f05c";
}
.fa-check-circle-o:before {
  content: "\f05d";
}
.fa-ban:before {
  content: "\f05e";
}
.fa-arrow-left:before {
  content: "\f060";
}
.fa-arrow-right:before {
  content: "\f061";
}
.fa-arrow-up:before {
  content: "\f062";
}
.fa-arrow-down:before {
  content: "\f063";
}
.fa-mail-forward:before,
.fa-share:before {
  content: "\f064";
}
.fa-expand:before {
  content: "\f065";
}
.fa-compress:before {
  content: "\f066";
}
.fa-plus:before {
  content: "\f067";
}
.fa-minus:before {
  content: "\f068";
}
.fa-asterisk:before {
  content: "\f069";
}
.fa-exclamation-circle:before {
  content: "\f06a";
}
.fa-gift:before {
  content: "\f06b";
}
.fa-leaf:before {
  content: "\f06c";
}
.fa-fire:before {
  content: "\f06d";
}
.fa-eye:before {
  content: "\f06e";
}
.fa-eye-slash:before {
  content: "\f070";
}
.fa-warning:before,
.fa-exclamation-triangle:before {
  content: "\f071";
}
.fa-plane:before {
  content: "\f072";
}
.fa-calendar:before {
  content: "\f073";
}
.fa-random:before {
  content: "\f074";
}
.fa-comment:before {
  content: "\f075";
}
.fa-magnet:before {
  content: "\f076";
}
.fa-chevron-up:before {
  content: "\f077";
}
.fa-chevron-down:before {
  content: "\f078";
}
.fa-retweet:before {
  content: "\f079";
}
.fa-shopping-cart:before {
  content: "\f07a";
}
.fa-folder:before {
  content: "\f07b";
}
.fa-folder-open:before {
  content: "\f07c";
}
.fa-arrows-v:before {
  content: "\f07d";
}
.fa-arrows-h:before {
  content: "\f07e";
}
.fa-bar-chart-o:before,
.fa-bar-chart:before {
  content: "\f080";
}
.fa-twitter-square:before {
  content: "\f081";
}
.fa-facebook-square:before {
  content: "\f082";
}
.fa-camera-retro:before {
  content: "\f083";
}
.fa-key:before {
  content: "\f084";
}
.fa-gears:before,
.fa-cogs:before {
  content: "\f085";
}
.fa-comments:before {
  content: "\f086";
}
.fa-thumbs-o-up:before {
  content: "\f087";
}
.fa-thumbs-o-down:before {
  content: "\f088";
}
.fa-star-half:before {
  content: "\f089";
}
.fa-heart-o:before {
  content: "\f08a";
}
.fa-sign-out:before {
  content: "\f08b";
}
.fa-linkedin-square:before {
  content: "\f08c";
}
.fa-thumb-tack:before {
  content: "\f08d";
}
.fa-external-link:before {
  content: "\f08e";
}
.fa-sign-in:before {
  content: "\f090";
}
.fa-trophy:before {
  content: "\f091";
}
.fa-github-square:before {
  content: "\f092";
}
.fa-upload:before {
  content: "\f093";
}
.fa-lemon-o:before {
  content: "\f094";
}
.fa-phone:before {
  content: "\f095";
}
.fa-square-o:before {
  content: "\f096";
}
.fa-bookmark-o:before {
  content: "\f097";
}
.fa-phone-square:before {
  content: "\f098";
}
.fa-twitter:before {
  content: "\f099";
}
.fa-facebook:before {
  content: "\f09a";
}
.fa-github:before {
  content: "\f09b";
}
.fa-unlock:before {
  content: "\f09c";
}
.fa-credit-card:before {
  content: "\f09d";
}
.fa-rss:before {
  content: "\f09e";
}
.fa-hdd-o:before {
  content: "\f0a0";
}
.fa-bullhorn:before {
  content: "\f0a1";
}
.fa-bell:before {
  content: "\f0f3";
}
.fa-certificate:before {
  content: "\f0a3";
}
.fa-hand-o-right:before {
  content: "\f0a4";
}
.fa-hand-o-left:before {
  content: "\f0a5";
}
.fa-hand-o-up:before {
  content: "\f0a6";
}
.fa-hand-o-down:before {
  content: "\f0a7";
}
.fa-arrow-circle-left:before {
  content: "\f0a8";
}
.fa-arrow-circle-right:before {
  content: "\f0a9";
}
.fa-arrow-circle-up:before {
  content: "\f0aa";
}
.fa-arrow-circle-down:before {
  content: "\f0ab";
}
.fa-globe:before {
  content: "\f0ac";
}
.fa-wrench:before {
  content: "\f0ad";
}
.fa-tasks:before {
  content: "\f0ae";
}
.fa-filter:before {
  content: "\f0b0";
}
.fa-briefcase:before {
  content: "\f0b1";
}
.fa-arrows-alt:before {
  content: "\f0b2";
}
.fa-group:before,
.fa-users:before {
  content: "\f0c0";
}
.fa-chain:before,
.fa-link:before {
  content: "\f0c1";
}
.fa-cloud:before {
  content: "\f0c2";
}
.fa-flask:before {
  content: "\f0c3";
}
.fa-cut:before,
.fa-scissors:before {
  content: "\f0c4";
}
.fa-copy:before,
.fa-files-o:before {
  content: "\f0c5";
}
.fa-paperclip:before {
  content: "\f0c6";
}
.fa-save:before,
.fa-floppy-o:before {
  content: "\f0c7";
}
.fa-square:before {
  content: "\f0c8";
}
.fa-navicon:before,
.fa-reorder:before,
.fa-bars:before {
  content: "\f0c9";
}
.fa-list-ul:before {
  content: "\f0ca";
}
.fa-list-ol:before {
  content: "\f0cb";
}
.fa-strikethrough:before {
  content: "\f0cc";
}
.fa-underline:before {
  content: "\f0cd";
}
.fa-table:before {
  content: "\f0ce";
}
.fa-magic:before {
  content: "\f0d0";
}
.fa-truck:before {
  content: "\f0d1";
}
.fa-pinterest:before {
  content: "\f0d2";
}
.fa-pinterest-square:before {
  content: "\f0d3";
}
.fa-google-plus-square:before {
  content: "\f0d4";
}
.fa-google-plus:before {
  content: "\f0d5";
}
.fa-money:before {
  content: "\f0d6";
}
.fa-caret-down:before {
  content: "\f0d7";
}
.fa-caret-up:before {
  content: "\f0d8";
}
.fa-caret-left:before {
  content: "\f0d9";
}
.fa-caret-right:before {
  content: "\f0da";
}
.fa-columns:before {
  content: "\f0db";
}
.fa-unsorted:before,
.fa-sort:before {
  content: "\f0dc";
}
.fa-sort-down:before,
.fa-sort-desc:before {
  content: "\f0dd";
}
.fa-sort-up:before,
.fa-sort-asc:before {
  content: "\f0de";
}
.fa-envelope:before {
  content: "\f0e0";
}
.fa-linkedin:before {
  content: "\f0e1";
}
.fa-rotate-left:before,
.fa-undo:before {
  content: "\f0e2";
}
.fa-legal:before,
.fa-gavel:before {
  content: "\f0e3";
}
.fa-dashboard:before,
.fa-tachometer:before {
  content: "\f0e4";
}
.fa-comment-o:before {
  content: "\f0e5";
}
.fa-comments-o:before {
  content: "\f0e6";
}
.fa-flash:before,
.fa-bolt:before {
  content: "\f0e7";
}
.fa-sitemap:before {
  content: "\f0e8";
}
.fa-umbrella:before {
  content: "\f0e9";
}
.fa-paste:before,
.fa-clipboard:before {
  content: "\f0ea";
}
.fa-lightbulb-o:before {
  content: "\f0eb";
}
.fa-exchange:before {
  content: "\f0ec";
}
.fa-cloud-download:before {
  content: "\f0ed";
}
.fa-cloud-upload:before {
  content: "\f0ee";
}
.fa-user-md:before {
  content: "\f0f0";
}
.fa-stethoscope:before {
  content: "\f0f1";
}
.fa-suitcase:before {
  content: "\f0f2";
}
.fa-bell-o:before {
  content: "\f0a2";
}
.fa-coffee:before {
  content: "\f0f4";
}
.fa-cutlery:before {
  content: "\f0f5";
}
.fa-file-text-o:before {
  content: "\f0f6";
}
.fa-building-o:before {
  content: "\f0f7";
}
.fa-hospital-o:before {
  content: "\f0f8";
}
.fa-ambulance:before {
  content: "\f0f9";
}
.fa-medkit:before {
  content: "\f0fa";
}
.fa-fighter-jet:before {
  content: "\f0fb";
}
.fa-beer:before {
  content: "\f0fc";
}
.fa-h-square:before {
  content: "\f0fd";
}
.fa-plus-square:before {
  content: "\f0fe";
}
.fa-angle-double-left:before {
  content: "\f100";
}
.fa-angle-double-right:before {
  content: "\f101";
}
.fa-angle-double-up:before {
  content: "\f102";
}
.fa-angle-double-down:before {
  content: "\f103";
}
.fa-angle-left:before {
  content: "\f104";
}
.fa-angle-right:before {
  content: "\f105";
}
.fa-angle-up:before {
  content: "\f106";
}
.fa-angle-down:before {
  content: "\f107";
}
.fa-desktop:before {
  content: "\f108";
}
.fa-laptop:before {
  content: "\f109";
}
.fa-tablet:before {
  content: "\f10a";
}
.fa-mobile-phone:before,
.fa-mobile:before {
  content: "\f10b";
}
.fa-circle-o:before {
  content: "\f10c";
}
.fa-quote-left:before {
  content: "\f10d";
}
.fa-quote-right:before {
  content: "\f10e";
}
.fa-spinner:before {
  content: "\f110";
}
.fa-circle:before {
  content: "\f111";
}
.fa-mail-reply:before,
.fa-reply:before {
  content: "\f112";
}
.fa-github-alt:before {
  content: "\f113";
}
.fa-folder-o:before {
  content: "\f114";
}
.fa-folder-open-o:before {
  content: "\f115";
}
.fa-smile-o:before {
  content: "\f118";
}
.fa-frown-o:before {
  content: "\f119";
}
.fa-meh-o:before {
  content: "\f11a";
}
.fa-gamepad:before {
  content: "\f11b";
}
.fa-keyboard-o:before {
  content: "\f11c";
}
.fa-flag-o:before {
  content: "\f11d";
}
.fa-flag-checkered:before {
  content: "\f11e";
}
.fa-terminal:before {
  content: "\f120";
}
.fa-code:before {
  content: "\f121";
}
.fa-mail-reply-all:before,
.fa-reply-all:before {
  content: "\f122";
}
.fa-star-half-empty:before,
.fa-star-half-full:before,
.fa-star-half-o:before {
  content: "\f123";
}
.fa-location-arrow:before {
  content: "\f124";
}
.fa-crop:before {
  content: "\f125";
}
.fa-code-fork:before {
  content: "\f126";
}
.fa-unlink:before,
.fa-chain-broken:before {
  content: "\f127";
}
.fa-question:before {
  content: "\f128";
}
.fa-info:before {
  content: "\f129";
}
.fa-exclamation:before {
  content: "\f12a";
}
.fa-superscript:before {
  content: "\f12b";
}
.fa-subscript:before {
  content: "\f12c";
}
.fa-eraser:before {
  content: "\f12d";
}
.fa-puzzle-piece:before {
  content: "\f12e";
}
.fa-microphone:before {
  content: "\f130";
}
.fa-microphone-slash:before {
  content: "\f131";
}
.fa-shield:before {
  content: "\f132";
}
.fa-calendar-o:before {
  content: "\f133";
}
.fa-fire-extinguisher:before {
  content: "\f134";
}
.fa-rocket:before {
  content: "\f135";
}
.fa-maxcdn:before {
  content: "\f136";
}
.fa-chevron-circle-left:before {
  content: "\f137";
}
.fa-chevron-circle-right:before {
  content: "\f138";
}
.fa-chevron-circle-up:before {
  content: "\f139";
}
.fa-chevron-circle-down:before {
  content: "\f13a";
}
.fa-html5:before {
  content: "\f13b";
}
.fa-css3:before {
  content: "\f13c";
}
.fa-anchor:before {
  content: "\f13d";
}
.fa-unlock-alt:before {
  content: "\f13e";
}
.fa-bullseye:before {
  content: "\f140";
}
.fa-ellipsis-h:before {
  content: "\f141";
}
.fa-ellipsis-v:before {
  content: "\f142";
}
.fa-rss-square:before {
  content: "\f143";
}
.fa-play-circle:before {
  content: "\f144";
}
.fa-ticket:before {
  content: "\f145";
}
.fa-minus-square:before {
  content: "\f146";
}
.fa-minus-square-o:before {
  content: "\f147";
}
.fa-level-up:before {
  content: "\f148";
}
.fa-level-down:before {
  content: "\f149";
}
.fa-check-square:before {
  content: "\f14a";
}
.fa-pencil-square:before {
  content: "\f14b";
}
.fa-external-link-square:before {
  content: "\f14c";
}
.fa-share-square:before {
  content: "\f14d";
}
.fa-compass:before {
  content: "\f14e";
}
.fa-toggle-down:before,
.fa-caret-square-o-down:before {
  content: "\f150";
}
.fa-toggle-up:before,
.fa-caret-square-o-up:before {
  content: "\f151";
}
.fa-toggle-right:before,
.fa-caret-square-o-right:before {
  content: "\f152";
}
.fa-euro:before,
.fa-eur:before {
  content: "\f153";
}
.fa-gbp:before {
  content: "\f154";
}
.fa-dollar:before,
.fa-usd:before {
  content: "\f155";
}
.fa-rupee:before,
.fa-inr:before {
  content: "\f156";
}
.fa-cny:before,
.fa-rmb:before,
.fa-yen:before,
.fa-jpy:before {
  content: "\f157";
}
.fa-ruble:before,
.fa-rouble:before,
.fa-rub:before {
  content: "\f158";
}
.fa-won:before,
.fa-krw:before {
  content: "\f159";
}
.fa-bitcoin:before,
.fa-btc:before {
  content: "\f15a";
}
.fa-file:before {
  content: "\f15b";
}
.fa-file-text:before {
  content: "\f15c";
}
.fa-sort-alpha-asc:before {
  content: "\f15d";
}
.fa-sort-alpha-desc:before {
  content: "\f15e";
}
.fa-sort-amount-asc:before {
  content: "\f160";
}
.fa-sort-amount-desc:before {
  content: "\f161";
}
.fa-sort-numeric-asc:before {
  content: "\f162";
}
.fa-sort-numeric-desc:before {
  content: "\f163";
}
.fa-thumbs-up:before {
  content: "\f164";
}
.fa-thumbs-down:before {
  content: "\f165";
}
.fa-youtube-square:before {
  content: "\f166";
}
.fa-youtube:before {
  content: "\f167";
}
.fa-xing:before {
  content: "\f168";
}
.fa-xing-square:before {
  content: "\f169";
}
.fa-youtube-play:before {
  content: "\f16a";
}
.fa-dropbox:before {
  content: "\f16b";
}
.fa-stack-overflow:before {
  content: "\f16c";
}
.fa-instagram:before {
  content: "\f16d";
}
.fa-flickr:before {
  content: "\f16e";
}
.fa-adn:before {
  content: "\f170";
}
.fa-bitbucket:before {
  content: "\f171";
}
.fa-bitbucket-square:before {
  content: "\f172";
}
.fa-tumblr:before {
  content: "\f173";
}
.fa-tumblr-square:before {
  content: "\f174";
}
.fa-long-arrow-down:before {
  content: "\f175";
}
.fa-long-arrow-up:before {
  content: "\f176";
}
.fa-long-arrow-left:before {
  content: "\f177";
}
.fa-long-arrow-right:before {
  content: "\f178";
}
.fa-apple:before {
  content: "\f179";
}
.fa-windows:before {
  content: "\f17a";
}
.fa-android:before {
  content: "\f17b";
}
.fa-linux:before {
  content: "\f17c";
}
.fa-dribbble:before {
  content: "\f17d";
}
.fa-skype:before {
  content: "\f17e";
}
.fa-foursquare:before {
  content: "\f180";
}
.fa-trello:before {
  content: "\f181";
}
.fa-female:before {
  content: "\f182";
}
.fa-male:before {
  content: "\f183";
}
.fa-gittip:before {
  content: "\f184";
}
.fa-sun-o:before {
  content: "\f185";
}
.fa-moon-o:before {
  content: "\f186";
}
.fa-archive:before {
  content: "\f187";
}
.fa-bug:before {
  content: "\f188";
}
.fa-vk:before {
  content: "\f189";
}
.fa-weibo:before {
  content: "\f18a";
}
.fa-renren:before {
  content: "\f18b";
}
.fa-pagelines:before {
  content: "\f18c";
}
.fa-stack-exchange:before {
  content: "\f18d";
}
.fa-arrow-circle-o-right:before {
  content: "\f18e";
}
.fa-arrow-circle-o-left:before {
  content: "\f190";
}
.fa-toggle-left:before,
.fa-caret-square-o-left:before {
  content: "\f191";
}
.fa-dot-circle-o:before {
  content: "\f192";
}
.fa-wheelchair:before {
  content: "\f193";
}
.fa-vimeo-square:before {
  content: "\f194";
}
.fa-turkish-lira:before,
.fa-try:before {
  content: "\f195";
}
.fa-plus-square-o:before {
  content: "\f196";
}
.fa-space-shuttle:before {
  content: "\f197";
}
.fa-slack:before {
  content: "\f198";
}
.fa-envelope-square:before {
  content: "\f199";
}
.fa-wordpress:before {
  content: "\f19a";
}
.fa-openid:before {
  content: "\f19b";
}
.fa-institution:before,
.fa-bank:before,
.fa-university:before {
  content: "\f19c";
}
.fa-mortar-board:before,
.fa-graduation-cap:before {
  content: "\f19d";
}
.fa-yahoo:before {
  content: "\f19e";
}
.fa-google:before {
  content: "\f1a0";
}
.fa-reddit:before {
  content: "\f1a1";
}
.fa-reddit-square:before {
  content: "\f1a2";
}
.fa-stumbleupon-circle:before {
  content: "\f1a3";
}
.fa-stumbleupon:before {
  content: "\f1a4";
}
.fa-delicious:before {
  content: "\f1a5";
}
.fa-digg:before {
  content: "\f1a6";
}
.fa-pied-piper:before {
  content: "\f1a7";
}
.fa-pied-piper-alt:before {
  content: "\f1a8";
}
.fa-drupal:before {
  content: "\f1a9";
}
.fa-joomla:before {
  content: "\f1aa";
}
.fa-language:before {
  content: "\f1ab";
}
.fa-fax:before {
  content: "\f1ac";
}
.fa-building:before {
  content: "\f1ad";
}
.fa-child:before {
  content: "\f1ae";
}
.fa-paw:before {
  content: "\f1b0";
}
.fa-spoon:before {
  content: "\f1b1";
}
.fa-cube:before {
  content: "\f1b2";
}
.fa-cubes:before {
  content: "\f1b3";
}
.fa-behance:before {
  content: "\f1b4";
}
.fa-behance-square:before {
  content: "\f1b5";
}
.fa-steam:before {
  content: "\f1b6";
}
.fa-steam-square:before {
  content: "\f1b7";
}
.fa-recycle:before {
  content: "\f1b8";
}
.fa-automobile:before,
.fa-car:before {
  content: "\f1b9";
}
.fa-cab:before,
.fa-taxi:before {
  content: "\f1ba";
}
.fa-tree:before {
  content: "\f1bb";
}
.fa-spotify:before {
  content: "\f1bc";
}
.fa-deviantart:before {
  content: "\f1bd";
}
.fa-soundcloud:before {
  content: "\f1be";
}
.fa-database:before {
  content: "\f1c0";
}
.fa-file-pdf-o:before {
  content: "\f1c1";
}
.fa-file-word-o:before {
  content: "\f1c2";
}
.fa-file-excel-o:before {
  content: "\f1c3";
}
.fa-file-powerpoint-o:before {
  content: "\f1c4";
}
.fa-file-photo-o:before,
.fa-file-picture-o:before,
.fa-file-image-o:before {
  content: "\f1c5";
}
.fa-file-zip-o:before,
.fa-file-archive-o:before {
  content: "\f1c6";
}
.fa-file-sound-o:before,
.fa-file-audio-o:before {
  content: "\f1c7";
}
.fa-file-movie-o:before,
.fa-file-video-o:before {
  content: "\f1c8";
}
.fa-file-code-o:before {
  content: "\f1c9";
}
.fa-vine:before {
  content: "\f1ca";
}
.fa-codepen:before {
  content: "\f1cb";
}
.fa-jsfiddle:before {
  content: "\f1cc";
}
.fa-life-bouy:before,
.fa-life-buoy:before,
.fa-life-saver:before,
.fa-support:before,
.fa-life-ring:before {
  content: "\f1cd";
}
.fa-circle-o-notch:before {
  content: "\f1ce";
}
.fa-ra:before,
.fa-rebel:before {
  content: "\f1d0";
}
.fa-ge:before,
.fa-empire:before {
  content: "\f1d1";
}
.fa-git-square:before {
  content: "\f1d2";
}
.fa-git:before {
  content: "\f1d3";
}
.fa-hacker-news:before {
  content: "\f1d4";
}
.fa-tencent-weibo:before {
  content: "\f1d5";
}
.fa-qq:before {
  content: "\f1d6";
}
.fa-wechat:before,
.fa-weixin:before {
  content: "\f1d7";
}
.fa-send:before,
.fa-paper-plane:before {
  content: "\f1d8";
}
.fa-send-o:before,
.fa-paper-plane-o:before {
  content: "\f1d9";
}
.fa-history:before {
  content: "\f1da";
}
.fa-circle-thin:before {
  content: "\f1db";
}
.fa-header:before {
  content: "\f1dc";
}
.fa-paragraph:before {
  content: "\f1dd";
}
.fa-sliders:before {
  content: "\f1de";
}
.fa-share-alt:before {
  content: "\f1e0";
}
.fa-share-alt-square:before {
  content: "\f1e1";
}
.fa-bomb:before {
  content: "\f1e2";
}
.fa-soccer-ball-o:before,
.fa-futbol-o:before {
  content: "\f1e3";
}
.fa-tty:before {
  content: "\f1e4";
}
.fa-binoculars:before {
  content: "\f1e5";
}
.fa-plug:before {
  content: "\f1e6";
}
.fa-slideshare:before {
  content: "\f1e7";
}
.fa-twitch:before {
  content: "\f1e8";
}
.fa-yelp:before {
  content: "\f1e9";
}
.fa-newspaper-o:before {
  content: "\f1ea";
}
.fa-wifi:before {
  content: "\f1eb";
}
.fa-calculator:before {
  content: "\f1ec";
}
.fa-paypal:before {
  content: "\f1ed";
}
.fa-google-wallet:before {
  content: "\f1ee";
}
.fa-cc-visa:before {
  content: "\f1f0";
}
.fa-cc-mastercard:before {
  content: "\f1f1";
}
.fa-cc-discover:before {
  content: "\f1f2";
}
.fa-cc-amex:before {
  content: "\f1f3";
}
.fa-cc-paypal:before {
  content: "\f1f4";
}
.fa-cc-stripe:before {
  content: "\f1f5";
}
.fa-bell-slash:before {
  content: "\f1f6";
}
.fa-bell-slash-o:before {
  content: "\f1f7";
}
.fa-trash:before {
  content: "\f1f8";
}
.fa-copyright:before {
  content: "\f1f9";
}
.fa-at:before {
  content: "\f1fa";
}
.fa-eyedropper:before {
  content: "\f1fb";
}
.fa-paint-brush:before {
  content: "\f1fc";
}
.fa-birthday-cake:before {
  content: "\f1fd";
}
.fa-area-chart:before {
  content: "\f1fe";
}
.fa-pie-chart:before {
  content: "\f200";
}
.fa-line-chart:before {
  content: "\f201";
}
.fa-lastfm:before {
  content: "\f202";
}
.fa-lastfm-square:before {
  content: "\f203";
}
.fa-toggle-off:before {
  content: "\f204";
}
.fa-toggle-on:before {
  content: "\f205";
}
.fa-bicycle:before {
  content: "\f206";
}
.fa-bus:before {
  content: "\f207";
}
.fa-ioxhost:before {
  content: "\f208";
}
.fa-angellist:before {
  content: "\f209";
}
.fa-cc:before {
  content: "\f20a";
}
.fa-shekel:before,
.fa-sheqel:before,
.fa-ils:before {
  content: "\f20b";
}
.fa-meanpath:before {
  content: "\f20c";
}
/*!
*
* IPython base
*
*/
.modal.fade .modal-dialog {
  -webkit-transform: translate(0, 0);
  -ms-transform: translate(0, 0);
  -o-transform: translate(0, 0);
  transform: translate(0, 0);
}
code {
  color: #000;
}
pre {
  font-size: inherit;
  line-height: inherit;
}
label {
  font-weight: normal;
}
/* Make the page background atleast 100% the height of the view port */
/* Make the page itself atleast 70% the height of the view port */
.border-box-sizing {
  box-sizing: border-box;
  -moz-box-sizing: border-box;
  -webkit-box-sizing: border-box;
}
.corner-all {
  border-radius: 2px;
}
.no-padding {
  padding: 0px;
}
/* Flexible box model classes */
/* Taken from Alex Russell http://infrequently.org/2009/08/css-3-progress/ */
/* This file is a compatability layer.  It allows the usage of flexible box 
model layouts accross multiple browsers, including older browsers.  The newest,
universal implementation of the flexible box model is used when available (see
`Modern browsers` comments below).  Browsers that are known to implement this 
new spec completely include:

    Firefox 28.0+
    Chrome 29.0+
    Internet Explorer 11+ 
    Opera 17.0+

Browsers not listed, including Safari, are supported via the styling under the
`Old browsers` comments below.
*/
.hbox {
  /* Old browsers */
  display: -webkit-box;
  -webkit-box-orient: horizontal;
  -webkit-box-align: stretch;
  display: -moz-box;
  -moz-box-orient: horizontal;
  -moz-box-align: stretch;
  display: box;
  box-orient: horizontal;
  box-align: stretch;
  /* Modern browsers */
  display: flex;
  flex-direction: row;
  align-items: stretch;
}
.hbox > * {
  /* Old browsers */
  -webkit-box-flex: 0;
  -moz-box-flex: 0;
  box-flex: 0;
  /* Modern browsers */
  flex: none;
}
.vbox {
  /* Old browsers */
  display: -webkit-box;
  -webkit-box-orient: vertical;
  -webkit-box-align: stretch;
  display: -moz-box;
  -moz-box-orient: vertical;
  -moz-box-align: stretch;
  display: box;
  box-orient: vertical;
  box-align: stretch;
  /* Modern browsers */
  display: flex;
  flex-direction: column;
  align-items: stretch;
}
.vbox > * {
  /* Old browsers */
  -webkit-box-flex: 0;
  -moz-box-flex: 0;
  box-flex: 0;
  /* Modern browsers */
  flex: none;
}
.hbox.reverse,
.vbox.reverse,
.reverse {
  /* Old browsers */
  -webkit-box-direction: reverse;
  -moz-box-direction: reverse;
  box-direction: reverse;
  /* Modern browsers */
  flex-direction: row-reverse;
}
.hbox.box-flex0,
.vbox.box-flex0,
.box-flex0 {
  /* Old browsers */
  -webkit-box-flex: 0;
  -moz-box-flex: 0;
  box-flex: 0;
  /* Modern browsers */
  flex: none;
  width: auto;
}
.hbox.box-flex1,
.vbox.box-flex1,
.box-flex1 {
  /* Old browsers */
  -webkit-box-flex: 1;
  -moz-box-flex: 1;
  box-flex: 1;
  /* Modern browsers */
  flex: 1;
}
.hbox.box-flex,
.vbox.box-flex,
.box-flex {
  /* Old browsers */
  /* Old browsers */
  -webkit-box-flex: 1;
  -moz-box-flex: 1;
  box-flex: 1;
  /* Modern browsers */
  flex: 1;
}
.hbox.box-flex2,
.vbox.box-flex2,
.box-flex2 {
  /* Old browsers */
  -webkit-box-flex: 2;
  -moz-box-flex: 2;
  box-flex: 2;
  /* Modern browsers */
  flex: 2;
}
.box-group1 {
  /*  Deprecated */
  -webkit-box-flex-group: 1;
  -moz-box-flex-group: 1;
  box-flex-group: 1;
}
.box-group2 {
  /* Deprecated */
  -webkit-box-flex-group: 2;
  -moz-box-flex-group: 2;
  box-flex-group: 2;
}
.hbox.start,
.vbox.start,
.start {
  /* Old browsers */
  -webkit-box-pack: start;
  -moz-box-pack: start;
  box-pack: start;
  /* Modern browsers */
  justify-content: flex-start;
}
.hbox.end,
.vbox.end,
.end {
  /* Old browsers */
  -webkit-box-pack: end;
  -moz-box-pack: end;
  box-pack: end;
  /* Modern browsers */
  justify-content: flex-end;
}
.hbox.center,
.vbox.center,
.center {
  /* Old browsers */
  -webkit-box-pack: center;
  -moz-box-pack: center;
  box-pack: center;
  /* Modern browsers */
  justify-content: center;
}
.hbox.baseline,
.vbox.baseline,
.baseline {
  /* Old browsers */
  -webkit-box-pack: baseline;
  -moz-box-pack: baseline;
  box-pack: baseline;
  /* Modern browsers */
  justify-content: baseline;
}
.hbox.stretch,
.vbox.stretch,
.stretch {
  /* Old browsers */
  -webkit-box-pack: stretch;
  -moz-box-pack: stretch;
  box-pack: stretch;
  /* Modern browsers */
  justify-content: stretch;
}
.hbox.align-start,
.vbox.align-start,
.align-start {
  /* Old browsers */
  -webkit-box-align: start;
  -moz-box-align: start;
  box-align: start;
  /* Modern browsers */
  align-items: flex-start;
}
.hbox.align-end,
.vbox.align-end,
.align-end {
  /* Old browsers */
  -webkit-box-align: end;
  -moz-box-align: end;
  box-align: end;
  /* Modern browsers */
  align-items: flex-end;
}
.hbox.align-center,
.vbox.align-center,
.align-center {
  /* Old browsers */
  -webkit-box-align: center;
  -moz-box-align: center;
  box-align: center;
  /* Modern browsers */
  align-items: center;
}
.hbox.align-baseline,
.vbox.align-baseline,
.align-baseline {
  /* Old browsers */
  -webkit-box-align: baseline;
  -moz-box-align: baseline;
  box-align: baseline;
  /* Modern browsers */
  align-items: baseline;
}
.hbox.align-stretch,
.vbox.align-stretch,
.align-stretch {
  /* Old browsers */
  -webkit-box-align: stretch;
  -moz-box-align: stretch;
  box-align: stretch;
  /* Modern browsers */
  align-items: stretch;
}
div.error {
  margin: 2em;
  text-align: center;
}
div.error > h1 {
  font-size: 500%;
  line-height: normal;
}
div.error > p {
  font-size: 200%;
  line-height: normal;
}
div.traceback-wrapper {
  text-align: left;
  max-width: 800px;
  margin: auto;
}
/**
 * Primary styles
 *
 * Author: Jupyter Development Team
 */
body {
  background-color: #fff;
  /* This makes sure that the body covers the entire window and needs to
       be in a different element than the display: box in wrapper below */
  position: absolute;
  left: 0px;
  right: 0px;
  top: 0px;
  bottom: 0px;
  overflow: visible;
}
body > #header {
  /* Initially hidden to prevent FLOUC */
  display: none;
  background-color: #fff;
  /* Display over codemirror */
  position: relative;
  z-index: 100;
}
body > #header #header-container {
  padding-bottom: 5px;
  padding-top: 5px;
  box-sizing: border-box;
  -moz-box-sizing: border-box;
  -webkit-box-sizing: border-box;
}
body > #header .header-bar {
  width: 100%;
  height: 1px;
  background: #e7e7e7;
  margin-bottom: -1px;
}
@media print {
  body > #header {
    display: none !important;
  }
}
#header-spacer {
  width: 100%;
  visibility: hidden;
}
@media print {
  #header-spacer {
    display: none;
  }
}
#ipython_notebook {
  padding-left: 0px;
  padding-top: 1px;
  padding-bottom: 1px;
}
@media (max-width: 991px) {
  #ipython_notebook {
    margin-left: 10px;
  }
}
[dir="rtl"] #ipython_notebook {
  float: right !important;
}
#noscript {
  width: auto;
  padding-top: 16px;
  padding-bottom: 16px;
  text-align: center;
  font-size: 22px;
  color: red;
  font-weight: bold;
}
#ipython_notebook img {
  height: 28px;
}
#site {
  width: 100%;
  display: none;
  box-sizing: border-box;
  -moz-box-sizing: border-box;
  -webkit-box-sizing: border-box;
  overflow: auto;
}
@media print {
  #site {
    height: auto !important;
  }
}
/* Smaller buttons */
.ui-button .ui-button-text {
  padding: 0.2em 0.8em;
  font-size: 77%;
}
input.ui-button {
  padding: 0.3em 0.9em;
}
span#login_widget {
  float: right;
}
span#login_widget > .button,
#logout {
  color: #333;
  background-color: #fff;
  border-color: #ccc;
}
span#login_widget > .button:focus,
#logout:focus,
span#login_widget > .button.focus,
#logout.focus {
  color: #333;
  background-color: #e6e6e6;
  border-color: #8c8c8c;
}
span#login_widget > .button:hover,
#logout:hover {
  color: #333;
  background-color: #e6e6e6;
  border-color: #adadad;
}
span#login_widget > .button:active,
#logout:active,
span#login_widget > .button.active,
#logout.active,
.open > .dropdown-togglespan#login_widget > .button,
.open > .dropdown-toggle#logout {
  color: #333;
  background-color: #e6e6e6;
  border-color: #adadad;
}
span#login_widget > .button:active:hover,
#logout:active:hover,
span#login_widget > .button.active:hover,
#logout.active:hover,
.open > .dropdown-togglespan#login_widget > .button:hover,
.open > .dropdown-toggle#logout:hover,
span#login_widget > .button:active:focus,
#logout:active:focus,
span#login_widget > .button.active:focus,
#logout.active:focus,
.open > .dropdown-togglespan#login_widget > .button:focus,
.open > .dropdown-toggle#logout:focus,
span#login_widget > .button:active.focus,
#logout:active.focus,
span#login_widget > .button.active.focus,
#logout.active.focus,
.open > .dropdown-togglespan#login_widget > .button.focus,
.open > .dropdown-toggle#logout.focus {
  color: #333;
  background-color: #d4d4d4;
  border-color: #8c8c8c;
}
span#login_widget > .button:active,
#logout:active,
span#login_widget > .button.active,
#logout.active,
.open > .dropdown-togglespan#login_widget > .button,
.open > .dropdown-toggle#logout {
  background-image: none;
}
span#login_widget > .button.disabled:hover,
#logout.disabled:hover,
span#login_widget > .button[disabled]:hover,
#logout[disabled]:hover,
fieldset[disabled] span#login_widget > .button:hover,
fieldset[disabled] #logout:hover,
span#login_widget > .button.disabled:focus,
#logout.disabled:focus,
span#login_widget > .button[disabled]:focus,
#logout[disabled]:focus,
fieldset[disabled] span#login_widget > .button:focus,
fieldset[disabled] #logout:focus,
span#login_widget > .button.disabled.focus,
#logout.disabled.focus,
span#login_widget > .button[disabled].focus,
#logout[disabled].focus,
fieldset[disabled] span#login_widget > .button.focus,
fieldset[disabled] #logout.focus {
  background-color: #fff;
  border-color: #ccc;
}
span#login_widget > .button .badge,
#logout .badge {
  color: #fff;
  background-color: #333;
}
.nav-header {
  text-transform: none;
}
#header > span {
  margin-top: 10px;
}
.modal_stretch .modal-dialog {
  /* Old browsers */
  display: -webkit-box;
  -webkit-box-orient: vertical;
  -webkit-box-align: stretch;
  display: -moz-box;
  -moz-box-orient: vertical;
  -moz-box-align: stretch;
  display: box;
  box-orient: vertical;
  box-align: stretch;
  /* Modern browsers */
  display: flex;
  flex-direction: column;
  align-items: stretch;
  min-height: 80vh;
}
.modal_stretch .modal-dialog .modal-body {
  max-height: calc(100vh - 200px);
  overflow: auto;
  flex: 1;
}
@media (min-width: 768px) {
  .modal .modal-dialog {
    width: 700px;
  }
}
@media (min-width: 768px) {
  select.form-control {
    margin-left: 12px;
    margin-right: 12px;
  }
}
/*!
*
* IPython auth
*
*/
.center-nav {
  display: inline-block;
  margin-bottom: -4px;
}
/*!
*
* IPython tree view
*
*/
/* We need an invisible input field on top of the sentense*/
/* "Drag file onto the list ..." */
.alternate_upload {
  background-color: none;
  display: inline;
}
.alternate_upload.form {
  padding: 0;
  margin: 0;
}
.alternate_upload input.fileinput {
  text-align: center;
  vertical-align: middle;
  display: inline;
  opacity: 0;
  z-index: 2;
  width: 12ex;
  margin-right: -12ex;
}
.alternate_upload .btn-upload {
  height: 22px;
}
/**
 * Primary styles
 *
 * Author: Jupyter Development Team
 */
[dir="rtl"] #tabs li {
  float: right;
}
ul#tabs {
  margin-bottom: 4px;
}
[dir="rtl"] ul#tabs {
  margin-right: 0px;
}
ul#tabs a {
  padding-top: 6px;
  padding-bottom: 4px;
}
ul.breadcrumb a:focus,
ul.breadcrumb a:hover {
  text-decoration: none;
}
ul.breadcrumb i.icon-home {
  font-size: 16px;
  margin-right: 4px;
}
ul.breadcrumb span {
  color: #5e5e5e;
}
.list_toolbar {
  padding: 4px 0 4px 0;
  vertical-align: middle;
}
.list_toolbar .tree-buttons {
  padding-top: 1px;
}
[dir="rtl"] .list_toolbar .tree-buttons {
  float: left !important;
}
[dir="rtl"] .list_toolbar .pull-right {
  padding-top: 1px;
  float: left !important;
}
[dir="rtl"] .list_toolbar .pull-left {
  float: right !important;
}
.dynamic-buttons {
  padding-top: 3px;
  display: inline-block;
}
.list_toolbar [class*="span"] {
  min-height: 24px;
}
.list_header {
  font-weight: bold;
  background-color: #EEE;
}
.list_placeholder {
  font-weight: bold;
  padding-top: 4px;
  padding-bottom: 4px;
  padding-left: 7px;
  padding-right: 7px;
}
.list_container {
  margin-top: 4px;
  margin-bottom: 20px;
  border: 1px solid #ddd;
  border-radius: 2px;
}
.list_container > div {
  border-bottom: 1px solid #ddd;
}
.list_container > div:hover .list-item {
  background-color: red;
}
.list_container > div:last-child {
  border: none;
}
.list_item:hover .list_item {
  background-color: #ddd;
}
.list_item a {
  text-decoration: none;
}
.list_item:hover {
  background-color: #fafafa;
}
.list_header > div,
.list_item > div {
  padding-top: 4px;
  padding-bottom: 4px;
  padding-left: 7px;
  padding-right: 7px;
  line-height: 22px;
}
.list_header > div input,
.list_item > div input {
  margin-right: 7px;
  margin-left: 14px;
  vertical-align: baseline;
  line-height: 22px;
  position: relative;
  top: -1px;
}
.list_header > div .item_link,
.list_item > div .item_link {
  margin-left: -1px;
  vertical-align: baseline;
  line-height: 22px;
}
.new-file input[type=checkbox] {
  visibility: hidden;
}
.item_name {
  line-height: 22px;
  height: 24px;
}
.item_icon {
  font-size: 14px;
  color: #5e5e5e;
  margin-right: 7px;
  margin-left: 7px;
  line-height: 22px;
  vertical-align: baseline;
}
.item_buttons {
  line-height: 1em;
  margin-left: -5px;
}
.item_buttons .btn,
.item_buttons .btn-group,
.item_buttons .input-group {
  float: left;
}
.item_buttons > .btn,
.item_buttons > .btn-group,
.item_buttons > .input-group {
  margin-left: 5px;
}
.item_buttons .btn {
  min-width: 13ex;
}
.item_buttons .running-indicator {
  padding-top: 4px;
  color: #5cb85c;
}
.item_buttons .kernel-name {
  padding-top: 4px;
  color: #5bc0de;
  margin-right: 7px;
  float: left;
}
.toolbar_info {
  height: 24px;
  line-height: 24px;
}
.list_item input:not([type=checkbox]) {
  padding-top: 3px;
  padding-bottom: 3px;
  height: 22px;
  line-height: 14px;
  margin: 0px;
}
.highlight_text {
  color: blue;
}
#project_name {
  display: inline-block;
  padding-left: 7px;
  margin-left: -2px;
}
#project_name > .breadcrumb {
  padding: 0px;
  margin-bottom: 0px;
  background-color: transparent;
  font-weight: bold;
}
#tree-selector {
  padding-right: 0px;
}
[dir="rtl"] #tree-selector a {
  float: right;
}
#button-select-all {
  min-width: 50px;
}
#select-all {
  margin-left: 7px;
  margin-right: 2px;
}
.menu_icon {
  margin-right: 2px;
}
.tab-content .row {
  margin-left: 0px;
  margin-right: 0px;
}
.folder_icon:before {
  display: inline-block;
  font: normal normal normal 14px/1 FontAwesome;
  font-size: inherit;
  text-rendering: auto;
  -webkit-font-smoothing: antialiased;
  -moz-osx-font-smoothing: grayscale;
  content: "\f114";
}
.folder_icon:before.pull-left {
  margin-right: .3em;
}
.folder_icon:before.pull-right {
  margin-left: .3em;
}
.notebook_icon:before {
  display: inline-block;
  font: normal normal normal 14px/1 FontAwesome;
  font-size: inherit;
  text-rendering: auto;
  -webkit-font-smoothing: antialiased;
  -moz-osx-font-smoothing: grayscale;
  content: "\f02d";
  position: relative;
  top: -1px;
}
.notebook_icon:before.pull-left {
  margin-right: .3em;
}
.notebook_icon:before.pull-right {
  margin-left: .3em;
}
.running_notebook_icon:before {
  display: inline-block;
  font: normal normal normal 14px/1 FontAwesome;
  font-size: inherit;
  text-rendering: auto;
  -webkit-font-smoothing: antialiased;
  -moz-osx-font-smoothing: grayscale;
  content: "\f02d";
  position: relative;
  top: -1px;
  color: #5cb85c;
}
.running_notebook_icon:before.pull-left {
  margin-right: .3em;
}
.running_notebook_icon:before.pull-right {
  margin-left: .3em;
}
.file_icon:before {
  display: inline-block;
  font: normal normal normal 14px/1 FontAwesome;
  font-size: inherit;
  text-rendering: auto;
  -webkit-font-smoothing: antialiased;
  -moz-osx-font-smoothing: grayscale;
  content: "\f016";
  position: relative;
  top: -2px;
}
.file_icon:before.pull-left {
  margin-right: .3em;
}
.file_icon:before.pull-right {
  margin-left: .3em;
}
#notebook_toolbar .pull-right {
  padding-top: 0px;
  margin-right: -1px;
}
ul#new-menu {
  left: auto;
  right: 0;
}
[dir="rtl"] #new-menu {
  text-align: right;
}
.kernel-menu-icon {
  padding-right: 12px;
  width: 24px;
  content: "\f096";
}
.kernel-menu-icon:before {
  content: "\f096";
}
.kernel-menu-icon-current:before {
  content: "\f00c";
}
#tab_content {
  padding-top: 20px;
}
#running .panel-group .panel {
  margin-top: 3px;
  margin-bottom: 1em;
}
#running .panel-group .panel .panel-heading {
  background-color: #EEE;
  padding-top: 4px;
  padding-bottom: 4px;
  padding-left: 7px;
  padding-right: 7px;
  line-height: 22px;
}
#running .panel-group .panel .panel-heading a:focus,
#running .panel-group .panel .panel-heading a:hover {
  text-decoration: none;
}
#running .panel-group .panel .panel-body {
  padding: 0px;
}
#running .panel-group .panel .panel-body .list_container {
  margin-top: 0px;
  margin-bottom: 0px;
  border: 0px;
  border-radius: 0px;
}
#running .panel-group .panel .panel-body .list_container .list_item {
  border-bottom: 1px solid #ddd;
}
#running .panel-group .panel .panel-body .list_container .list_item:last-child {
  border-bottom: 0px;
}
[dir="rtl"] #running .col-sm-8 {
  float: right !important;
}
.delete-button {
  display: none;
}
.duplicate-button {
  display: none;
}
.rename-button {
  display: none;
}
.shutdown-button {
  display: none;
}
.dynamic-instructions {
  display: inline-block;
  padding-top: 4px;
}
/*!
*
* IPython text editor webapp
*
*/
.selected-keymap i.fa {
  padding: 0px 5px;
}
.selected-keymap i.fa:before {
  content: "\f00c";
}
#mode-menu {
  overflow: auto;
  max-height: 20em;
}
.edit_app #header {
  -webkit-box-shadow: 0px 0px 12px 1px rgba(87, 87, 87, 0.2);
  box-shadow: 0px 0px 12px 1px rgba(87, 87, 87, 0.2);
}
.edit_app #menubar .navbar {
  /* Use a negative 1 bottom margin, so the border overlaps the border of the
    header */
  margin-bottom: -1px;
}
.dirty-indicator {
  display: inline-block;
  font: normal normal normal 14px/1 FontAwesome;
  font-size: inherit;
  text-rendering: auto;
  -webkit-font-smoothing: antialiased;
  -moz-osx-font-smoothing: grayscale;
  width: 20px;
}
.dirty-indicator.pull-left {
  margin-right: .3em;
}
.dirty-indicator.pull-right {
  margin-left: .3em;
}
.dirty-indicator-dirty {
  display: inline-block;
  font: normal normal normal 14px/1 FontAwesome;
  font-size: inherit;
  text-rendering: auto;
  -webkit-font-smoothing: antialiased;
  -moz-osx-font-smoothing: grayscale;
  width: 20px;
}
.dirty-indicator-dirty.pull-left {
  margin-right: .3em;
}
.dirty-indicator-dirty.pull-right {
  margin-left: .3em;
}
.dirty-indicator-clean {
  display: inline-block;
  font: normal normal normal 14px/1 FontAwesome;
  font-size: inherit;
  text-rendering: auto;
  -webkit-font-smoothing: antialiased;
  -moz-osx-font-smoothing: grayscale;
  width: 20px;
}
.dirty-indicator-clean.pull-left {
  margin-right: .3em;
}
.dirty-indicator-clean.pull-right {
  margin-left: .3em;
}
.dirty-indicator-clean:before {
  display: inline-block;
  font: normal normal normal 14px/1 FontAwesome;
  font-size: inherit;
  text-rendering: auto;
  -webkit-font-smoothing: antialiased;
  -moz-osx-font-smoothing: grayscale;
  content: "\f00c";
}
.dirty-indicator-clean:before.pull-left {
  margin-right: .3em;
}
.dirty-indicator-clean:before.pull-right {
  margin-left: .3em;
}
#filename {
  font-size: 16pt;
  display: table;
  padding: 0px 5px;
}
#current-mode {
  padding-left: 5px;
  padding-right: 5px;
}
#texteditor-backdrop {
  padding-top: 20px;
  padding-bottom: 20px;
}
@media not print {
  #texteditor-backdrop {
    background-color: #EEE;
  }
}
@media print {
  #texteditor-backdrop #texteditor-container .CodeMirror-gutter,
  #texteditor-backdrop #texteditor-container .CodeMirror-gutters {
    background-color: #fff;
  }
}
@media not print {
  #texteditor-backdrop #texteditor-container .CodeMirror-gutter,
  #texteditor-backdrop #texteditor-container .CodeMirror-gutters {
    background-color: #fff;
  }
}
@media not print {
  #texteditor-backdrop #texteditor-container {
    padding: 0px;
    background-color: #fff;
    -webkit-box-shadow: 0px 0px 12px 1px rgba(87, 87, 87, 0.2);
    box-shadow: 0px 0px 12px 1px rgba(87, 87, 87, 0.2);
  }
}
/*!
*
* IPython notebook
*
*/
/* CSS font colors for translated ANSI colors. */
.ansibold {
  font-weight: bold;
}
/* use dark versions for foreground, to improve visibility */
.ansiblack {
  color: black;
}
.ansired {
  color: darkred;
}
.ansigreen {
  color: darkgreen;
}
.ansiyellow {
  color: #c4a000;
}
.ansiblue {
  color: darkblue;
}
.ansipurple {
  color: darkviolet;
}
.ansicyan {
  color: steelblue;
}
.ansigray {
  color: gray;
}
/* and light for background, for the same reason */
.ansibgblack {
  background-color: black;
}
.ansibgred {
  background-color: red;
}
.ansibggreen {
  background-color: green;
}
.ansibgyellow {
  background-color: yellow;
}
.ansibgblue {
  background-color: blue;
}
.ansibgpurple {
  background-color: magenta;
}
.ansibgcyan {
  background-color: cyan;
}
.ansibggray {
  background-color: gray;
}
div.cell {
  /* Old browsers */
  display: -webkit-box;
  -webkit-box-orient: vertical;
  -webkit-box-align: stretch;
  display: -moz-box;
  -moz-box-orient: vertical;
  -moz-box-align: stretch;
  display: box;
  box-orient: vertical;
  box-align: stretch;
  /* Modern browsers */
  display: flex;
  flex-direction: column;
  align-items: stretch;
  border-radius: 2px;
  box-sizing: border-box;
  -moz-box-sizing: border-box;
  -webkit-box-sizing: border-box;
  border-width: 1px;
  border-style: solid;
  border-color: transparent;
  width: 100%;
  padding: 5px;
  /* This acts as a spacer between cells, that is outside the border */
  margin: 0px;
  outline: none;
  border-left-width: 1px;
  padding-left: 5px;
  background: linear-gradient(to right, transparent -40px, transparent 1px, transparent 1px, transparent 100%);
}
div.cell.jupyter-soft-selected {
  border-left-color: #90CAF9;
  border-left-color: #E3F2FD;
  border-left-width: 1px;
  padding-left: 5px;
  border-right-color: #E3F2FD;
  border-right-width: 1px;
  background: #E3F2FD;
}
@media print {
  div.cell.jupyter-soft-selected {
    border-color: transparent;
  }
}
div.cell.selected {
  border-color: #ababab;
  border-left-width: 0px;
  padding-left: 6px;
  background: linear-gradient(to right, #42A5F5 -40px, #42A5F5 5px, transparent 5px, transparent 100%);
}
@media print {
  div.cell.selected {
    border-color: transparent;
  }
}
div.cell.selected.jupyter-soft-selected {
  border-left-width: 0;
  padding-left: 6px;
  background: linear-gradient(to right, #42A5F5 -40px, #42A5F5 7px, #E3F2FD 7px, #E3F2FD 100%);
}
.edit_mode div.cell.selected {
  border-color: #66BB6A;
  border-left-width: 0px;
  padding-left: 6px;
  background: linear-gradient(to right, #66BB6A -40px, #66BB6A 5px, transparent 5px, transparent 100%);
}
@media print {
  .edit_mode div.cell.selected {
    border-color: transparent;
  }
}
.prompt {
  /* This needs to be wide enough for 3 digit prompt numbers: In[100]: */
  min-width: 14ex;
  /* This padding is tuned to match the padding on the CodeMirror editor. */
  padding: 0.4em;
  margin: 0px;
  font-family: monospace;
  text-align: right;
  /* This has to match that of the the CodeMirror class line-height below */
  line-height: 1.21429em;
  /* Don't highlight prompt number selection */
  -webkit-touch-callout: none;
  -webkit-user-select: none;
  -khtml-user-select: none;
  -moz-user-select: none;
  -ms-user-select: none;
  user-select: none;
  /* Use default cursor */
  cursor: default;
}
@media (max-width: 540px) {
  .prompt {
    text-align: left;
  }
}
div.inner_cell {
  min-width: 0;
  /* Old browsers */
  display: -webkit-box;
  -webkit-box-orient: vertical;
  -webkit-box-align: stretch;
  display: -moz-box;
  -moz-box-orient: vertical;
  -moz-box-align: stretch;
  display: box;
  box-orient: vertical;
  box-align: stretch;
  /* Modern browsers */
  display: flex;
  flex-direction: column;
  align-items: stretch;
  /* Old browsers */
  -webkit-box-flex: 1;
  -moz-box-flex: 1;
  box-flex: 1;
  /* Modern browsers */
  flex: 1;
}
/* input_area and input_prompt must match in top border and margin for alignment */
div.input_area {
  border: 1px solid #cfcfcf;
  border-radius: 2px;
  background: #f7f7f7;
  line-height: 1.21429em;
}
/* This is needed so that empty prompt areas can collapse to zero height when there
   is no content in the output_subarea and the prompt. The main purpose of this is
   to make sure that empty JavaScript output_subareas have no height. */
div.prompt:empty {
  padding-top: 0;
  padding-bottom: 0;
}
div.unrecognized_cell {
  padding: 5px 5px 5px 0px;
  /* Old browsers */
  display: -webkit-box;
  -webkit-box-orient: horizontal;
  -webkit-box-align: stretch;
  display: -moz-box;
  -moz-box-orient: horizontal;
  -moz-box-align: stretch;
  display: box;
  box-orient: horizontal;
  box-align: stretch;
  /* Modern browsers */
  display: flex;
  flex-direction: row;
  align-items: stretch;
}
div.unrecognized_cell .inner_cell {
  border-radius: 2px;
  padding: 5px;
  font-weight: bold;
  color: red;
  border: 1px solid #cfcfcf;
  background: #eaeaea;
}
div.unrecognized_cell .inner_cell a {
  color: inherit;
  text-decoration: none;
}
div.unrecognized_cell .inner_cell a:hover {
  color: inherit;
  text-decoration: none;
}
@media (max-width: 540px) {
  div.unrecognized_cell > div.prompt {
    display: none;
  }
}
div.code_cell {
  /* avoid page breaking on code cells when printing */
}
@media print {
  div.code_cell {
    page-break-inside: avoid;
  }
}
/* any special styling for code cells that are currently running goes here */
div.input {
  page-break-inside: avoid;
  /* Old browsers */
  display: -webkit-box;
  -webkit-box-orient: horizontal;
  -webkit-box-align: stretch;
  display: -moz-box;
  -moz-box-orient: horizontal;
  -moz-box-align: stretch;
  display: box;
  box-orient: horizontal;
  box-align: stretch;
  /* Modern browsers */
  display: flex;
  flex-direction: row;
  align-items: stretch;
}
@media (max-width: 540px) {
  div.input {
    /* Old browsers */
    display: -webkit-box;
    -webkit-box-orient: vertical;
    -webkit-box-align: stretch;
    display: -moz-box;
    -moz-box-orient: vertical;
    -moz-box-align: stretch;
    display: box;
    box-orient: vertical;
    box-align: stretch;
    /* Modern browsers */
    display: flex;
    flex-direction: column;
    align-items: stretch;
  }
}
/* input_area and input_prompt must match in top border and margin for alignment */
div.input_prompt {
  color: #303F9F;
  border-top: 1px solid transparent;
}
div.input_area > div.highlight {
  margin: 0.4em;
  border: none;
  padding: 0px;
  background-color: transparent;
}
div.input_area > div.highlight > pre {
  margin: 0px;
  border: none;
  padding: 0px;
  background-color: transparent;
}
/* The following gets added to the <head> if it is detected that the user has a
 * monospace font with inconsistent normal/bold/italic height.  See
 * notebookmain.js.  Such fonts will have keywords vertically offset with
 * respect to the rest of the text.  The user should select a better font.
 * See: https://github.com/ipython/ipython/issues/1503
 *
 * .CodeMirror span {
 *      vertical-align: bottom;
 * }
 */
.CodeMirror {
  line-height: 1.21429em;
  /* Changed from 1em to our global default */
  font-size: 14px;
  height: auto;
  /* Changed to auto to autogrow */
  background: none;
  /* Changed from white to allow our bg to show through */
}
.CodeMirror-scroll {
  /*  The CodeMirror docs are a bit fuzzy on if overflow-y should be hidden or visible.*/
  /*  We have found that if it is visible, vertical scrollbars appear with font size changes.*/
  overflow-y: hidden;
  overflow-x: auto;
}
.CodeMirror-lines {
  /* In CM2, this used to be 0.4em, but in CM3 it went to 4px. We need the em value because */
  /* we have set a different line-height and want this to scale with that. */
  padding: 0.4em;
}
.CodeMirror-linenumber {
  padding: 0 8px 0 4px;
}
.CodeMirror-gutters {
  border-bottom-left-radius: 2px;
  border-top-left-radius: 2px;
}
.CodeMirror pre {
  /* In CM3 this went to 4px from 0 in CM2. We need the 0 value because of how we size */
  /* .CodeMirror-lines */
  padding: 0;
  border: 0;
  border-radius: 0;
}
/*

Original style from softwaremaniacs.org (c) Ivan Sagalaev <Maniac@SoftwareManiacs.Org>
Adapted from GitHub theme

*/
.highlight-base {
  color: #000;
}
.highlight-variable {
  color: #000;
}
.highlight-variable-2 {
  color: #1a1a1a;
}
.highlight-variable-3 {
  color: #333333;
}
.highlight-string {
  color: #BA2121;
}
.highlight-comment {
  color: #408080;
  font-style: italic;
}
.highlight-number {
  color: #080;
}
.highlight-atom {
  color: #88F;
}
.highlight-keyword {
  color: #008000;
  font-weight: bold;
}
.highlight-builtin {
  color: #008000;
}
.highlight-error {
  color: #f00;
}
.highlight-operator {
  color: #AA22FF;
  font-weight: bold;
}
.highlight-meta {
  color: #AA22FF;
}
/* previously not defined, copying from default codemirror */
.highlight-def {
  color: #00f;
}
.highlight-string-2 {
  color: #f50;
}
.highlight-qualifier {
  color: #555;
}
.highlight-bracket {
  color: #997;
}
.highlight-tag {
  color: #170;
}
.highlight-attribute {
  color: #00c;
}
.highlight-header {
  color: blue;
}
.highlight-quote {
  color: #090;
}
.highlight-link {
  color: #00c;
}
/* apply the same style to codemirror */
.cm-s-ipython span.cm-keyword {
  color: #008000;
  font-weight: bold;
}
.cm-s-ipython span.cm-atom {
  color: #88F;
}
.cm-s-ipython span.cm-number {
  color: #080;
}
.cm-s-ipython span.cm-def {
  color: #00f;
}
.cm-s-ipython span.cm-variable {
  color: #000;
}
.cm-s-ipython span.cm-operator {
  color: #AA22FF;
  font-weight: bold;
}
.cm-s-ipython span.cm-variable-2 {
  color: #1a1a1a;
}
.cm-s-ipython span.cm-variable-3 {
  color: #333333;
}
.cm-s-ipython span.cm-comment {
  color: #408080;
  font-style: italic;
}
.cm-s-ipython span.cm-string {
  color: #BA2121;
}
.cm-s-ipython span.cm-string-2 {
  color: #f50;
}
.cm-s-ipython span.cm-meta {
  color: #AA22FF;
}
.cm-s-ipython span.cm-qualifier {
  color: #555;
}
.cm-s-ipython span.cm-builtin {
  color: #008000;
}
.cm-s-ipython span.cm-bracket {
  color: #997;
}
.cm-s-ipython span.cm-tag {
  color: #170;
}
.cm-s-ipython span.cm-attribute {
  color: #00c;
}
.cm-s-ipython span.cm-header {
  color: blue;
}
.cm-s-ipython span.cm-quote {
  color: #090;
}
.cm-s-ipython span.cm-link {
  color: #00c;
}
.cm-s-ipython span.cm-error {
  color: #f00;
}
.cm-s-ipython span.cm-tab {
  background: url(data:image/png;base64,iVBORw0KGgoAAAANSUhEUgAAADAAAAAMCAYAAAAkuj5RAAAAAXNSR0IArs4c6QAAAGFJREFUSMft1LsRQFAQheHPowAKoACx3IgEKtaEHujDjORSgWTH/ZOdnZOcM/sgk/kFFWY0qV8foQwS4MKBCS3qR6ixBJvElOobYAtivseIE120FaowJPN75GMu8j/LfMwNjh4HUpwg4LUAAAAASUVORK5CYII=);
  background-position: right;
  background-repeat: no-repeat;
}
div.output_wrapper {
  /* this position must be relative to enable descendents to be absolute within it */
  position: relative;
  /* Old browsers */
  display: -webkit-box;
  -webkit-box-orient: vertical;
  -webkit-box-align: stretch;
  display: -moz-box;
  -moz-box-orient: vertical;
  -moz-box-align: stretch;
  display: box;
  box-orient: vertical;
  box-align: stretch;
  /* Modern browsers */
  display: flex;
  flex-direction: column;
  align-items: stretch;
  z-index: 1;
}
/* class for the output area when it should be height-limited */
div.output_scroll {
  /* ideally, this would be max-height, but FF barfs all over that */
  height: 24em;
  /* FF needs this *and the wrapper* to specify full width, or it will shrinkwrap */
  width: 100%;
  overflow: auto;
  border-radius: 2px;
  -webkit-box-shadow: inset 0 2px 8px rgba(0, 0, 0, 0.8);
  box-shadow: inset 0 2px 8px rgba(0, 0, 0, 0.8);
  display: block;
}
/* output div while it is collapsed */
div.output_collapsed {
  margin: 0px;
  padding: 0px;
  /* Old browsers */
  display: -webkit-box;
  -webkit-box-orient: vertical;
  -webkit-box-align: stretch;
  display: -moz-box;
  -moz-box-orient: vertical;
  -moz-box-align: stretch;
  display: box;
  box-orient: vertical;
  box-align: stretch;
  /* Modern browsers */
  display: flex;
  flex-direction: column;
  align-items: stretch;
}
div.out_prompt_overlay {
  height: 100%;
  padding: 0px 0.4em;
  position: absolute;
  border-radius: 2px;
}
div.out_prompt_overlay:hover {
  /* use inner shadow to get border that is computed the same on WebKit/FF */
  -webkit-box-shadow: inset 0 0 1px #000;
  box-shadow: inset 0 0 1px #000;
  background: rgba(240, 240, 240, 0.5);
}
div.output_prompt {
  color: #D84315;
}
/* This class is the outer container of all output sections. */
div.output_area {
  padding: 0px;
  page-break-inside: avoid;
  /* Old browsers */
  display: -webkit-box;
  -webkit-box-orient: horizontal;
  -webkit-box-align: stretch;
  display: -moz-box;
  -moz-box-orient: horizontal;
  -moz-box-align: stretch;
  display: box;
  box-orient: horizontal;
  box-align: stretch;
  /* Modern browsers */
  display: flex;
  flex-direction: row;
  align-items: stretch;
}
div.output_area .MathJax_Display {
  text-align: left !important;
}
div.output_area .rendered_html table {
  margin-left: 0;
  margin-right: 0;
}
div.output_area .rendered_html img {
  margin-left: 0;
  margin-right: 0;
}
div.output_area img,
div.output_area svg {
  max-width: 100%;
  height: auto;
}
div.output_area img.unconfined,
div.output_area svg.unconfined {
  max-width: none;
}
/* This is needed to protect the pre formating from global settings such
   as that of bootstrap */
.output {
  /* Old browsers */
  display: -webkit-box;
  -webkit-box-orient: vertical;
  -webkit-box-align: stretch;
  display: -moz-box;
  -moz-box-orient: vertical;
  -moz-box-align: stretch;
  display: box;
  box-orient: vertical;
  box-align: stretch;
  /* Modern browsers */
  display: flex;
  flex-direction: column;
  align-items: stretch;
}
@media (max-width: 540px) {
  div.output_area {
    /* Old browsers */
    display: -webkit-box;
    -webkit-box-orient: vertical;
    -webkit-box-align: stretch;
    display: -moz-box;
    -moz-box-orient: vertical;
    -moz-box-align: stretch;
    display: box;
    box-orient: vertical;
    box-align: stretch;
    /* Modern browsers */
    display: flex;
    flex-direction: column;
    align-items: stretch;
  }
}
div.output_area pre {
  margin: 0;
  padding: 0;
  border: 0;
  vertical-align: baseline;
  color: black;
  background-color: transparent;
  border-radius: 0;
}
/* This class is for the output subarea inside the output_area and after
   the prompt div. */
div.output_subarea {
  overflow-x: auto;
  padding: 0.4em;
  /* Old browsers */
  -webkit-box-flex: 1;
  -moz-box-flex: 1;
  box-flex: 1;
  /* Modern browsers */
  flex: 1;
  max-width: calc(100% - 14ex);
}
div.output_scroll div.output_subarea {
  overflow-x: visible;
}
/* The rest of the output_* classes are for special styling of the different
   output types */
/* all text output has this class: */
div.output_text {
  text-align: left;
  color: #000;
  /* This has to match that of the the CodeMirror class line-height below */
  line-height: 1.21429em;
}
/* stdout/stderr are 'text' as well as 'stream', but execute_result/error are *not* streams */
div.output_stderr {
  background: #fdd;
  /* very light red background for stderr */
}
div.output_latex {
  text-align: left;
}
/* Empty output_javascript divs should have no height */
div.output_javascript:empty {
  padding: 0;
}
.js-error {
  color: darkred;
}
/* raw_input styles */
div.raw_input_container {
  line-height: 1.21429em;
  padding-top: 5px;
}
pre.raw_input_prompt {
  /* nothing needed here. */
}
input.raw_input {
  font-family: monospace;
  font-size: inherit;
  color: inherit;
  width: auto;
  /* make sure input baseline aligns with prompt */
  vertical-align: baseline;
  /* padding + margin = 0.5em between prompt and cursor */
  padding: 0em 0.25em;
  margin: 0em 0.25em;
}
input.raw_input:focus {
  box-shadow: none;
}
p.p-space {
  margin-bottom: 10px;
}
div.output_unrecognized {
  padding: 5px;
  font-weight: bold;
  color: red;
}
div.output_unrecognized a {
  color: inherit;
  text-decoration: none;
}
div.output_unrecognized a:hover {
  color: inherit;
  text-decoration: none;
}
.rendered_html {
  color: #000;
  /* any extras will just be numbers: */
}
.rendered_html em {
  font-style: italic;
}
.rendered_html strong {
  font-weight: bold;
}
.rendered_html u {
  text-decoration: underline;
}
.rendered_html :link {
  text-decoration: underline;
}
.rendered_html :visited {
  text-decoration: underline;
}
.rendered_html h1 {
  font-size: 185.7%;
  margin: 1.08em 0 0 0;
  font-weight: bold;
  line-height: 1.0;
}
.rendered_html h2 {
  font-size: 157.1%;
  margin: 1.27em 0 0 0;
  font-weight: bold;
  line-height: 1.0;
}
.rendered_html h3 {
  font-size: 128.6%;
  margin: 1.55em 0 0 0;
  font-weight: bold;
  line-height: 1.0;
}
.rendered_html h4 {
  font-size: 100%;
  margin: 2em 0 0 0;
  font-weight: bold;
  line-height: 1.0;
}
.rendered_html h5 {
  font-size: 100%;
  margin: 2em 0 0 0;
  font-weight: bold;
  line-height: 1.0;
  font-style: italic;
}
.rendered_html h6 {
  font-size: 100%;
  margin: 2em 0 0 0;
  font-weight: bold;
  line-height: 1.0;
  font-style: italic;
}
.rendered_html h1:first-child {
  margin-top: 0.538em;
}
.rendered_html h2:first-child {
  margin-top: 0.636em;
}
.rendered_html h3:first-child {
  margin-top: 0.777em;
}
.rendered_html h4:first-child {
  margin-top: 1em;
}
.rendered_html h5:first-child {
  margin-top: 1em;
}
.rendered_html h6:first-child {
  margin-top: 1em;
}
.rendered_html ul {
  list-style: disc;
  margin: 0em 2em;
  padding-left: 0px;
}
.rendered_html ul ul {
  list-style: square;
  margin: 0em 2em;
}
.rendered_html ul ul ul {
  list-style: circle;
  margin: 0em 2em;
}
.rendered_html ol {
  list-style: decimal;
  margin: 0em 2em;
  padding-left: 0px;
}
.rendered_html ol ol {
  list-style: upper-alpha;
  margin: 0em 2em;
}
.rendered_html ol ol ol {
  list-style: lower-alpha;
  margin: 0em 2em;
}
.rendered_html ol ol ol ol {
  list-style: lower-roman;
  margin: 0em 2em;
}
.rendered_html ol ol ol ol ol {
  list-style: decimal;
  margin: 0em 2em;
}
.rendered_html * + ul {
  margin-top: 1em;
}
.rendered_html * + ol {
  margin-top: 1em;
}
.rendered_html hr {
  color: black;
  background-color: black;
}
.rendered_html pre {
  margin: 1em 2em;
}
.rendered_html pre,
.rendered_html code {
  border: 0;
  background-color: #fff;
  color: #000;
  font-size: 100%;
  padding: 0px;
}
.rendered_html blockquote {
  margin: 1em 2em;
}
.rendered_html table {
  margin-left: auto;
  margin-right: auto;
  border: 1px solid black;
  border-collapse: collapse;
}
.rendered_html tr,
.rendered_html th,
.rendered_html td {
  border: 1px solid black;
  border-collapse: collapse;
  margin: 1em 2em;
}
.rendered_html td,
.rendered_html th {
  text-align: left;
  vertical-align: middle;
  padding: 4px;
}
.rendered_html th {
  font-weight: bold;
}
.rendered_html * + table {
  margin-top: 1em;
}
.rendered_html p {
  text-align: left;
}
.rendered_html * + p {
  margin-top: 1em;
}
.rendered_html img {
  display: block;
  margin-left: auto;
  margin-right: auto;
}
.rendered_html * + img {
  margin-top: 1em;
}
.rendered_html img,
.rendered_html svg {
  max-width: 100%;
  height: auto;
}
.rendered_html img.unconfined,
.rendered_html svg.unconfined {
  max-width: none;
}
div.text_cell {
  /* Old browsers */
  display: -webkit-box;
  -webkit-box-orient: horizontal;
  -webkit-box-align: stretch;
  display: -moz-box;
  -moz-box-orient: horizontal;
  -moz-box-align: stretch;
  display: box;
  box-orient: horizontal;
  box-align: stretch;
  /* Modern browsers */
  display: flex;
  flex-direction: row;
  align-items: stretch;
}
@media (max-width: 540px) {
  div.text_cell > div.prompt {
    display: none;
  }
}
div.text_cell_render {
  /*font-family: "Helvetica Neue", Arial, Helvetica, Geneva, sans-serif;*/
  outline: none;
  resize: none;
  width: inherit;
  border-style: none;
  padding: 0.5em 0.5em 0.5em 0.4em;
  color: #000;
  box-sizing: border-box;
  -moz-box-sizing: border-box;
  -webkit-box-sizing: border-box;
}
a.anchor-link:link {
  text-decoration: none;
  padding: 0px 20px;
  visibility: hidden;
}
h1:hover .anchor-link,
h2:hover .anchor-link,
h3:hover .anchor-link,
h4:hover .anchor-link,
h5:hover .anchor-link,
h6:hover .anchor-link {
  visibility: visible;
}
.text_cell.rendered .input_area {
  display: none;
}
.text_cell.rendered .rendered_html {
  overflow-x: auto;
  overflow-y: hidden;
}
.text_cell.unrendered .text_cell_render {
  display: none;
}
.cm-header-1,
.cm-header-2,
.cm-header-3,
.cm-header-4,
.cm-header-5,
.cm-header-6 {
  font-weight: bold;
  font-family: "Helvetica Neue", Helvetica, Arial, sans-serif;
}
.cm-header-1 {
  font-size: 185.7%;
}
.cm-header-2 {
  font-size: 157.1%;
}
.cm-header-3 {
  font-size: 128.6%;
}
.cm-header-4 {
  font-size: 110%;
}
.cm-header-5 {
  font-size: 100%;
  font-style: italic;
}
.cm-header-6 {
  font-size: 100%;
  font-style: italic;
}
/*!
*
* IPython notebook webapp
*
*/
@media (max-width: 767px) {
  .notebook_app {
    padding-left: 0px;
    padding-right: 0px;
  }
}
#ipython-main-app {
  box-sizing: border-box;
  -moz-box-sizing: border-box;
  -webkit-box-sizing: border-box;
  height: 100%;
}
div#notebook_panel {
  margin: 0px;
  padding: 0px;
  box-sizing: border-box;
  -moz-box-sizing: border-box;
  -webkit-box-sizing: border-box;
  height: 100%;
}
div#notebook {
  font-size: 14px;
  line-height: 20px;
  overflow-y: hidden;
  overflow-x: auto;
  width: 100%;
  /* This spaces the page away from the edge of the notebook area */
  padding-top: 20px;
  margin: 0px;
  outline: none;
  box-sizing: border-box;
  -moz-box-sizing: border-box;
  -webkit-box-sizing: border-box;
  min-height: 100%;
}
@media not print {
  #notebook-container {
    padding: 15px;
    background-color: #fff;
    min-height: 0;
    -webkit-box-shadow: 0px 0px 12px 1px rgba(87, 87, 87, 0.2);
    box-shadow: 0px 0px 12px 1px rgba(87, 87, 87, 0.2);
  }
}
@media print {
  #notebook-container {
    width: 100%;
  }
}
div.ui-widget-content {
  border: 1px solid #ababab;
  outline: none;
}
pre.dialog {
  background-color: #f7f7f7;
  border: 1px solid #ddd;
  border-radius: 2px;
  padding: 0.4em;
  padding-left: 2em;
}
p.dialog {
  padding: 0.2em;
}
/* Word-wrap output correctly.  This is the CSS3 spelling, though Firefox seems
   to not honor it correctly.  Webkit browsers (Chrome, rekonq, Safari) do.
 */
pre,
code,
kbd,
samp {
  white-space: pre-wrap;
}
#fonttest {
  font-family: monospace;
}
p {
  margin-bottom: 0;
}
.end_space {
  min-height: 100px;
  transition: height .2s ease;
}
.notebook_app > #header {
  -webkit-box-shadow: 0px 0px 12px 1px rgba(87, 87, 87, 0.2);
  box-shadow: 0px 0px 12px 1px rgba(87, 87, 87, 0.2);
}
@media not print {
  .notebook_app {
    background-color: #EEE;
  }
}
kbd {
  border-style: solid;
  border-width: 1px;
  box-shadow: none;
  margin: 2px;
  padding-left: 2px;
  padding-right: 2px;
  padding-top: 1px;
  padding-bottom: 1px;
}
/* CSS for the cell toolbar */
.celltoolbar {
  border: thin solid #CFCFCF;
  border-bottom: none;
  background: #EEE;
  border-radius: 2px 2px 0px 0px;
  width: 100%;
  height: 29px;
  padding-right: 4px;
  /* Old browsers */
  display: -webkit-box;
  -webkit-box-orient: horizontal;
  -webkit-box-align: stretch;
  display: -moz-box;
  -moz-box-orient: horizontal;
  -moz-box-align: stretch;
  display: box;
  box-orient: horizontal;
  box-align: stretch;
  /* Modern browsers */
  display: flex;
  flex-direction: row;
  align-items: stretch;
  /* Old browsers */
  -webkit-box-pack: end;
  -moz-box-pack: end;
  box-pack: end;
  /* Modern browsers */
  justify-content: flex-end;
  display: -webkit-flex;
}
@media print {
  .celltoolbar {
    display: none;
  }
}
.ctb_hideshow {
  display: none;
  vertical-align: bottom;
}
/* ctb_show is added to the ctb_hideshow div to show the cell toolbar.
   Cell toolbars are only shown when the ctb_global_show class is also set.
*/
.ctb_global_show .ctb_show.ctb_hideshow {
  display: block;
}
.ctb_global_show .ctb_show + .input_area,
.ctb_global_show .ctb_show + div.text_cell_input,
.ctb_global_show .ctb_show ~ div.text_cell_render {
  border-top-right-radius: 0px;
  border-top-left-radius: 0px;
}
.ctb_global_show .ctb_show ~ div.text_cell_render {
  border: 1px solid #cfcfcf;
}
.celltoolbar {
  font-size: 87%;
  padding-top: 3px;
}
.celltoolbar select {
  display: block;
  width: 100%;
  height: 32px;
  padding: 6px 12px;
  font-size: 13px;
  line-height: 1.42857143;
  color: #555555;
  background-color: #fff;
  background-image: none;
  border: 1px solid #ccc;
  border-radius: 2px;
  -webkit-box-shadow: inset 0 1px 1px rgba(0, 0, 0, 0.075);
  box-shadow: inset 0 1px 1px rgba(0, 0, 0, 0.075);
  -webkit-transition: border-color ease-in-out .15s, box-shadow ease-in-out .15s;
  -o-transition: border-color ease-in-out .15s, box-shadow ease-in-out .15s;
  transition: border-color ease-in-out .15s, box-shadow ease-in-out .15s;
  height: 30px;
  padding: 5px 10px;
  font-size: 12px;
  line-height: 1.5;
  border-radius: 1px;
  width: inherit;
  font-size: inherit;
  height: 22px;
  padding: 0px;
  display: inline-block;
}
.celltoolbar select:focus {
  border-color: #66afe9;
  outline: 0;
  -webkit-box-shadow: inset 0 1px 1px rgba(0,0,0,.075), 0 0 8px rgba(102, 175, 233, 0.6);
  box-shadow: inset 0 1px 1px rgba(0,0,0,.075), 0 0 8px rgba(102, 175, 233, 0.6);
}
.celltoolbar select::-moz-placeholder {
  color: #999;
  opacity: 1;
}
.celltoolbar select:-ms-input-placeholder {
  color: #999;
}
.celltoolbar select::-webkit-input-placeholder {
  color: #999;
}
.celltoolbar select::-ms-expand {
  border: 0;
  background-color: transparent;
}
.celltoolbar select[disabled],
.celltoolbar select[readonly],
fieldset[disabled] .celltoolbar select {
  background-color: #eeeeee;
  opacity: 1;
}
.celltoolbar select[disabled],
fieldset[disabled] .celltoolbar select {
  cursor: not-allowed;
}
textarea.celltoolbar select {
  height: auto;
}
select.celltoolbar select {
  height: 30px;
  line-height: 30px;
}
textarea.celltoolbar select,
select[multiple].celltoolbar select {
  height: auto;
}
.celltoolbar label {
  margin-left: 5px;
  margin-right: 5px;
}
.completions {
  position: absolute;
  z-index: 110;
  overflow: hidden;
  border: 1px solid #ababab;
  border-radius: 2px;
  -webkit-box-shadow: 0px 6px 10px -1px #adadad;
  box-shadow: 0px 6px 10px -1px #adadad;
  line-height: 1;
}
.completions select {
  background: white;
  outline: none;
  border: none;
  padding: 0px;
  margin: 0px;
  overflow: auto;
  font-family: monospace;
  font-size: 110%;
  color: #000;
  width: auto;
}
.completions select option.context {
  color: #286090;
}
#kernel_logo_widget {
  float: right !important;
  float: right;
}
#kernel_logo_widget .current_kernel_logo {
  display: none;
  margin-top: -1px;
  margin-bottom: -1px;
  width: 32px;
  height: 32px;
}
#menubar {
  box-sizing: border-box;
  -moz-box-sizing: border-box;
  -webkit-box-sizing: border-box;
  margin-top: 1px;
}
#menubar .navbar {
  border-top: 1px;
  border-radius: 0px 0px 2px 2px;
  margin-bottom: 0px;
}
#menubar .navbar-toggle {
  float: left;
  padding-top: 7px;
  padding-bottom: 7px;
  border: none;
}
#menubar .navbar-collapse {
  clear: left;
}
.nav-wrapper {
  border-bottom: 1px solid #e7e7e7;
}
i.menu-icon {
  padding-top: 4px;
}
ul#help_menu li a {
  overflow: hidden;
  padding-right: 2.2em;
}
ul#help_menu li a i {
  margin-right: -1.2em;
}
.dropdown-submenu {
  position: relative;
}
.dropdown-submenu > .dropdown-menu {
  top: 0;
  left: 100%;
  margin-top: -6px;
  margin-left: -1px;
}
.dropdown-submenu:hover > .dropdown-menu {
  display: block;
}
.dropdown-submenu > a:after {
  display: inline-block;
  font: normal normal normal 14px/1 FontAwesome;
  font-size: inherit;
  text-rendering: auto;
  -webkit-font-smoothing: antialiased;
  -moz-osx-font-smoothing: grayscale;
  display: block;
  content: "\f0da";
  float: right;
  color: #333333;
  margin-top: 2px;
  margin-right: -10px;
}
.dropdown-submenu > a:after.pull-left {
  margin-right: .3em;
}
.dropdown-submenu > a:after.pull-right {
  margin-left: .3em;
}
.dropdown-submenu:hover > a:after {
  color: #262626;
}
.dropdown-submenu.pull-left {
  float: none;
}
.dropdown-submenu.pull-left > .dropdown-menu {
  left: -100%;
  margin-left: 10px;
}
#notification_area {
  float: right !important;
  float: right;
  z-index: 10;
}
.indicator_area {
  float: right !important;
  float: right;
  color: #777;
  margin-left: 5px;
  margin-right: 5px;
  width: 11px;
  z-index: 10;
  text-align: center;
  width: auto;
}
#kernel_indicator {
  float: right !important;
  float: right;
  color: #777;
  margin-left: 5px;
  margin-right: 5px;
  width: 11px;
  z-index: 10;
  text-align: center;
  width: auto;
  border-left: 1px solid;
}
#kernel_indicator .kernel_indicator_name {
  padding-left: 5px;
  padding-right: 5px;
}
#modal_indicator {
  float: right !important;
  float: right;
  color: #777;
  margin-left: 5px;
  margin-right: 5px;
  width: 11px;
  z-index: 10;
  text-align: center;
  width: auto;
}
#readonly-indicator {
  float: right !important;
  float: right;
  color: #777;
  margin-left: 5px;
  margin-right: 5px;
  width: 11px;
  z-index: 10;
  text-align: center;
  width: auto;
  margin-top: 2px;
  margin-bottom: 0px;
  margin-left: 0px;
  margin-right: 0px;
  display: none;
}
.modal_indicator:before {
  width: 1.28571429em;
  text-align: center;
}
.edit_mode .modal_indicator:before {
  display: inline-block;
  font: normal normal normal 14px/1 FontAwesome;
  font-size: inherit;
  text-rendering: auto;
  -webkit-font-smoothing: antialiased;
  -moz-osx-font-smoothing: grayscale;
  content: "\f040";
}
.edit_mode .modal_indicator:before.pull-left {
  margin-right: .3em;
}
.edit_mode .modal_indicator:before.pull-right {
  margin-left: .3em;
}
.command_mode .modal_indicator:before {
  display: inline-block;
  font: normal normal normal 14px/1 FontAwesome;
  font-size: inherit;
  text-rendering: auto;
  -webkit-font-smoothing: antialiased;
  -moz-osx-font-smoothing: grayscale;
  content: ' ';
}
.command_mode .modal_indicator:before.pull-left {
  margin-right: .3em;
}
.command_mode .modal_indicator:before.pull-right {
  margin-left: .3em;
}
.kernel_idle_icon:before {
  display: inline-block;
  font: normal normal normal 14px/1 FontAwesome;
  font-size: inherit;
  text-rendering: auto;
  -webkit-font-smoothing: antialiased;
  -moz-osx-font-smoothing: grayscale;
  content: "\f10c";
}
.kernel_idle_icon:before.pull-left {
  margin-right: .3em;
}
.kernel_idle_icon:before.pull-right {
  margin-left: .3em;
}
.kernel_busy_icon:before {
  display: inline-block;
  font: normal normal normal 14px/1 FontAwesome;
  font-size: inherit;
  text-rendering: auto;
  -webkit-font-smoothing: antialiased;
  -moz-osx-font-smoothing: grayscale;
  content: "\f111";
}
.kernel_busy_icon:before.pull-left {
  margin-right: .3em;
}
.kernel_busy_icon:before.pull-right {
  margin-left: .3em;
}
.kernel_dead_icon:before {
  display: inline-block;
  font: normal normal normal 14px/1 FontAwesome;
  font-size: inherit;
  text-rendering: auto;
  -webkit-font-smoothing: antialiased;
  -moz-osx-font-smoothing: grayscale;
  content: "\f1e2";
}
.kernel_dead_icon:before.pull-left {
  margin-right: .3em;
}
.kernel_dead_icon:before.pull-right {
  margin-left: .3em;
}
.kernel_disconnected_icon:before {
  display: inline-block;
  font: normal normal normal 14px/1 FontAwesome;
  font-size: inherit;
  text-rendering: auto;
  -webkit-font-smoothing: antialiased;
  -moz-osx-font-smoothing: grayscale;
  content: "\f127";
}
.kernel_disconnected_icon:before.pull-left {
  margin-right: .3em;
}
.kernel_disconnected_icon:before.pull-right {
  margin-left: .3em;
}
.notification_widget {
  color: #777;
  z-index: 10;
  background: rgba(240, 240, 240, 0.5);
  margin-right: 4px;
  color: #333;
  background-color: #fff;
  border-color: #ccc;
}
.notification_widget:focus,
.notification_widget.focus {
  color: #333;
  background-color: #e6e6e6;
  border-color: #8c8c8c;
}
.notification_widget:hover {
  color: #333;
  background-color: #e6e6e6;
  border-color: #adadad;
}
.notification_widget:active,
.notification_widget.active,
.open > .dropdown-toggle.notification_widget {
  color: #333;
  background-color: #e6e6e6;
  border-color: #adadad;
}
.notification_widget:active:hover,
.notification_widget.active:hover,
.open > .dropdown-toggle.notification_widget:hover,
.notification_widget:active:focus,
.notification_widget.active:focus,
.open > .dropdown-toggle.notification_widget:focus,
.notification_widget:active.focus,
.notification_widget.active.focus,
.open > .dropdown-toggle.notification_widget.focus {
  color: #333;
  background-color: #d4d4d4;
  border-color: #8c8c8c;
}
.notification_widget:active,
.notification_widget.active,
.open > .dropdown-toggle.notification_widget {
  background-image: none;
}
.notification_widget.disabled:hover,
.notification_widget[disabled]:hover,
fieldset[disabled] .notification_widget:hover,
.notification_widget.disabled:focus,
.notification_widget[disabled]:focus,
fieldset[disabled] .notification_widget:focus,
.notification_widget.disabled.focus,
.notification_widget[disabled].focus,
fieldset[disabled] .notification_widget.focus {
  background-color: #fff;
  border-color: #ccc;
}
.notification_widget .badge {
  color: #fff;
  background-color: #333;
}
.notification_widget.warning {
  color: #fff;
  background-color: #f0ad4e;
  border-color: #eea236;
}
.notification_widget.warning:focus,
.notification_widget.warning.focus {
  color: #fff;
  background-color: #ec971f;
  border-color: #985f0d;
}
.notification_widget.warning:hover {
  color: #fff;
  background-color: #ec971f;
  border-color: #d58512;
}
.notification_widget.warning:active,
.notification_widget.warning.active,
.open > .dropdown-toggle.notification_widget.warning {
  color: #fff;
  background-color: #ec971f;
  border-color: #d58512;
}
.notification_widget.warning:active:hover,
.notification_widget.warning.active:hover,
.open > .dropdown-toggle.notification_widget.warning:hover,
.notification_widget.warning:active:focus,
.notification_widget.warning.active:focus,
.open > .dropdown-toggle.notification_widget.warning:focus,
.notification_widget.warning:active.focus,
.notification_widget.warning.active.focus,
.open > .dropdown-toggle.notification_widget.warning.focus {
  color: #fff;
  background-color: #d58512;
  border-color: #985f0d;
}
.notification_widget.warning:active,
.notification_widget.warning.active,
.open > .dropdown-toggle.notification_widget.warning {
  background-image: none;
}
.notification_widget.warning.disabled:hover,
.notification_widget.warning[disabled]:hover,
fieldset[disabled] .notification_widget.warning:hover,
.notification_widget.warning.disabled:focus,
.notification_widget.warning[disabled]:focus,
fieldset[disabled] .notification_widget.warning:focus,
.notification_widget.warning.disabled.focus,
.notification_widget.warning[disabled].focus,
fieldset[disabled] .notification_widget.warning.focus {
  background-color: #f0ad4e;
  border-color: #eea236;
}
.notification_widget.warning .badge {
  color: #f0ad4e;
  background-color: #fff;
}
.notification_widget.success {
  color: #fff;
  background-color: #5cb85c;
  border-color: #4cae4c;
}
.notification_widget.success:focus,
.notification_widget.success.focus {
  color: #fff;
  background-color: #449d44;
  border-color: #255625;
}
.notification_widget.success:hover {
  color: #fff;
  background-color: #449d44;
  border-color: #398439;
}
.notification_widget.success:active,
.notification_widget.success.active,
.open > .dropdown-toggle.notification_widget.success {
  color: #fff;
  background-color: #449d44;
  border-color: #398439;
}
.notification_widget.success:active:hover,
.notification_widget.success.active:hover,
.open > .dropdown-toggle.notification_widget.success:hover,
.notification_widget.success:active:focus,
.notification_widget.success.active:focus,
.open > .dropdown-toggle.notification_widget.success:focus,
.notification_widget.success:active.focus,
.notification_widget.success.active.focus,
.open > .dropdown-toggle.notification_widget.success.focus {
  color: #fff;
  background-color: #398439;
  border-color: #255625;
}
.notification_widget.success:active,
.notification_widget.success.active,
.open > .dropdown-toggle.notification_widget.success {
  background-image: none;
}
.notification_widget.success.disabled:hover,
.notification_widget.success[disabled]:hover,
fieldset[disabled] .notification_widget.success:hover,
.notification_widget.success.disabled:focus,
.notification_widget.success[disabled]:focus,
fieldset[disabled] .notification_widget.success:focus,
.notification_widget.success.disabled.focus,
.notification_widget.success[disabled].focus,
fieldset[disabled] .notification_widget.success.focus {
  background-color: #5cb85c;
  border-color: #4cae4c;
}
.notification_widget.success .badge {
  color: #5cb85c;
  background-color: #fff;
}
.notification_widget.info {
  color: #fff;
  background-color: #5bc0de;
  border-color: #46b8da;
}
.notification_widget.info:focus,
.notification_widget.info.focus {
  color: #fff;
  background-color: #31b0d5;
  border-color: #1b6d85;
}
.notification_widget.info:hover {
  color: #fff;
  background-color: #31b0d5;
  border-color: #269abc;
}
.notification_widget.info:active,
.notification_widget.info.active,
.open > .dropdown-toggle.notification_widget.info {
  color: #fff;
  background-color: #31b0d5;
  border-color: #269abc;
}
.notification_widget.info:active:hover,
.notification_widget.info.active:hover,
.open > .dropdown-toggle.notification_widget.info:hover,
.notification_widget.info:active:focus,
.notification_widget.info.active:focus,
.open > .dropdown-toggle.notification_widget.info:focus,
.notification_widget.info:active.focus,
.notification_widget.info.active.focus,
.open > .dropdown-toggle.notification_widget.info.focus {
  color: #fff;
  background-color: #269abc;
  border-color: #1b6d85;
}
.notification_widget.info:active,
.notification_widget.info.active,
.open > .dropdown-toggle.notification_widget.info {
  background-image: none;
}
.notification_widget.info.disabled:hover,
.notification_widget.info[disabled]:hover,
fieldset[disabled] .notification_widget.info:hover,
.notification_widget.info.disabled:focus,
.notification_widget.info[disabled]:focus,
fieldset[disabled] .notification_widget.info:focus,
.notification_widget.info.disabled.focus,
.notification_widget.info[disabled].focus,
fieldset[disabled] .notification_widget.info.focus {
  background-color: #5bc0de;
  border-color: #46b8da;
}
.notification_widget.info .badge {
  color: #5bc0de;
  background-color: #fff;
}
.notification_widget.danger {
  color: #fff;
  background-color: #d9534f;
  border-color: #d43f3a;
}
.notification_widget.danger:focus,
.notification_widget.danger.focus {
  color: #fff;
  background-color: #c9302c;
  border-color: #761c19;
}
.notification_widget.danger:hover {
  color: #fff;
  background-color: #c9302c;
  border-color: #ac2925;
}
.notification_widget.danger:active,
.notification_widget.danger.active,
.open > .dropdown-toggle.notification_widget.danger {
  color: #fff;
  background-color: #c9302c;
  border-color: #ac2925;
}
.notification_widget.danger:active:hover,
.notification_widget.danger.active:hover,
.open > .dropdown-toggle.notification_widget.danger:hover,
.notification_widget.danger:active:focus,
.notification_widget.danger.active:focus,
.open > .dropdown-toggle.notification_widget.danger:focus,
.notification_widget.danger:active.focus,
.notification_widget.danger.active.focus,
.open > .dropdown-toggle.notification_widget.danger.focus {
  color: #fff;
  background-color: #ac2925;
  border-color: #761c19;
}
.notification_widget.danger:active,
.notification_widget.danger.active,
.open > .dropdown-toggle.notification_widget.danger {
  background-image: none;
}
.notification_widget.danger.disabled:hover,
.notification_widget.danger[disabled]:hover,
fieldset[disabled] .notification_widget.danger:hover,
.notification_widget.danger.disabled:focus,
.notification_widget.danger[disabled]:focus,
fieldset[disabled] .notification_widget.danger:focus,
.notification_widget.danger.disabled.focus,
.notification_widget.danger[disabled].focus,
fieldset[disabled] .notification_widget.danger.focus {
  background-color: #d9534f;
  border-color: #d43f3a;
}
.notification_widget.danger .badge {
  color: #d9534f;
  background-color: #fff;
}
div#pager {
  background-color: #fff;
  font-size: 14px;
  line-height: 20px;
  overflow: hidden;
  display: none;
  position: fixed;
  bottom: 0px;
  width: 100%;
  max-height: 50%;
  padding-top: 8px;
  -webkit-box-shadow: 0px 0px 12px 1px rgba(87, 87, 87, 0.2);
  box-shadow: 0px 0px 12px 1px rgba(87, 87, 87, 0.2);
  /* Display over codemirror */
  z-index: 100;
  /* Hack which prevents jquery ui resizable from changing top. */
  top: auto !important;
}
div#pager pre {
  line-height: 1.21429em;
  color: #000;
  background-color: #f7f7f7;
  padding: 0.4em;
}
div#pager #pager-button-area {
  position: absolute;
  top: 8px;
  right: 20px;
}
div#pager #pager-contents {
  position: relative;
  overflow: auto;
  width: 100%;
  height: 100%;
}
div#pager #pager-contents #pager-container {
  position: relative;
  padding: 15px 0px;
  box-sizing: border-box;
  -moz-box-sizing: border-box;
  -webkit-box-sizing: border-box;
}
div#pager .ui-resizable-handle {
  top: 0px;
  height: 8px;
  background: #f7f7f7;
  border-top: 1px solid #cfcfcf;
  border-bottom: 1px solid #cfcfcf;
  /* This injects handle bars (a short, wide = symbol) for 
        the resize handle. */
}
div#pager .ui-resizable-handle::after {
  content: '';
  top: 2px;
  left: 50%;
  height: 3px;
  width: 30px;
  margin-left: -15px;
  position: absolute;
  border-top: 1px solid #cfcfcf;
}
.quickhelp {
  /* Old browsers */
  display: -webkit-box;
  -webkit-box-orient: horizontal;
  -webkit-box-align: stretch;
  display: -moz-box;
  -moz-box-orient: horizontal;
  -moz-box-align: stretch;
  display: box;
  box-orient: horizontal;
  box-align: stretch;
  /* Modern browsers */
  display: flex;
  flex-direction: row;
  align-items: stretch;
  line-height: 1.8em;
}
.shortcut_key {
  display: inline-block;
  width: 21ex;
  text-align: right;
  font-family: monospace;
}
.shortcut_descr {
  display: inline-block;
  /* Old browsers */
  -webkit-box-flex: 1;
  -moz-box-flex: 1;
  box-flex: 1;
  /* Modern browsers */
  flex: 1;
}
span.save_widget {
  margin-top: 6px;
}
span.save_widget span.filename {
  height: 1em;
  line-height: 1em;
  padding: 3px;
  margin-left: 16px;
  border: none;
  font-size: 146.5%;
  border-radius: 2px;
}
span.save_widget span.filename:hover {
  background-color: #e6e6e6;
}
span.checkpoint_status,
span.autosave_status {
  font-size: small;
}
@media (max-width: 767px) {
  span.save_widget {
    font-size: small;
  }
  span.checkpoint_status,
  span.autosave_status {
    display: none;
  }
}
@media (min-width: 768px) and (max-width: 991px) {
  span.checkpoint_status {
    display: none;
  }
  span.autosave_status {
    font-size: x-small;
  }
}
.toolbar {
  padding: 0px;
  margin-left: -5px;
  margin-top: 2px;
  margin-bottom: 5px;
  box-sizing: border-box;
  -moz-box-sizing: border-box;
  -webkit-box-sizing: border-box;
}
.toolbar select,
.toolbar label {
  width: auto;
  vertical-align: middle;
  margin-right: 2px;
  margin-bottom: 0px;
  display: inline;
  font-size: 92%;
  margin-left: 0.3em;
  margin-right: 0.3em;
  padding: 0px;
  padding-top: 3px;
}
.toolbar .btn {
  padding: 2px 8px;
}
.toolbar .btn-group {
  margin-top: 0px;
  margin-left: 5px;
}
#maintoolbar {
  margin-bottom: -3px;
  margin-top: -8px;
  border: 0px;
  min-height: 27px;
  margin-left: 0px;
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<h1 id="Lending-Club-Data-Analysis">Lending Club Data Analysis<a class="anchor-link" href="#Lending-Club-Data-Analysis">&#182;</a></h1><p>The basic aim of this data analysis project is to predict the loan_status of the applicant and for that we will be using Random Forest Ensemble cladssifier to predict the loan status of the applicant.</p>

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<h2 id="Importing-the-data">Importing the data<a class="anchor-link" href="#Importing-the-data">&#182;</a></h2>
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<div class=" highlight hl-ipython3"><pre><span></span><span class="kn">import</span> <span class="nn">pandas</span> <span class="k">as</span> <span class="nn">pd</span>
<span class="kn">import</span> <span class="nn">seaborn</span> <span class="k">as</span> <span class="nn">sns</span>
<span class="kn">import</span> <span class="nn">numpy</span> <span class="k">as</span> <span class="nn">np</span>
<span class="kn">import</span> <span class="nn">matplotlib.pyplot</span> <span class="k">as</span> <span class="nn">plt</span>
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<div class=" highlight hl-ipython3"><pre><span></span><span class="o">%</span> <span class="n">matplotlib</span> <span class="n">inline</span>
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<div class=" highlight hl-ipython3"><pre><span></span><span class="n">start_df</span> <span class="o">=</span> <span class="n">pd</span><span class="o">.</span><span class="n">read_csv</span><span class="p">(</span><span class="s1">&#39;C://Users/Saurabh/Desktop/Home Work/IDS Assignments/data/Dataset/loan.csv&#39;</span><span class="p">,</span> <span class="n">low_memory</span><span class="o">=</span><span class="kc">False</span><span class="p">)</span>
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<div class=" highlight hl-ipython3"><pre><span></span><span class="n">start_df</span><span class="o">.</span><span class="n">head</span><span class="p">()</span>
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<style scoped>
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      <th></th>
      <th>id</th>
      <th>member_id</th>
      <th>loan_amnt</th>
      <th>funded_amnt</th>
      <th>funded_amnt_inv</th>
      <th>term</th>
      <th>int_rate</th>
      <th>installment</th>
      <th>grade</th>
      <th>sub_grade</th>
      <th>...</th>
      <th>total_bal_il</th>
      <th>il_util</th>
      <th>open_rv_12m</th>
      <th>open_rv_24m</th>
      <th>max_bal_bc</th>
      <th>all_util</th>
      <th>total_rev_hi_lim</th>
      <th>inq_fi</th>
      <th>total_cu_tl</th>
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  </thead>
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      <th>0</th>
      <td>1077501</td>
      <td>1296599</td>
      <td>5000.0</td>
      <td>5000.0</td>
      <td>4975.0</td>
      <td>36 months</td>
      <td>10.65</td>
      <td>162.87</td>
      <td>B</td>
      <td>B2</td>
      <td>...</td>
      <td>NaN</td>
      <td>NaN</td>
      <td>NaN</td>
      <td>NaN</td>
      <td>NaN</td>
      <td>NaN</td>
      <td>NaN</td>
      <td>NaN</td>
      <td>NaN</td>
      <td>NaN</td>
    </tr>
    <tr>
      <th>1</th>
      <td>1077430</td>
      <td>1314167</td>
      <td>2500.0</td>
      <td>2500.0</td>
      <td>2500.0</td>
      <td>60 months</td>
      <td>15.27</td>
      <td>59.83</td>
      <td>C</td>
      <td>C4</td>
      <td>...</td>
      <td>NaN</td>
      <td>NaN</td>
      <td>NaN</td>
      <td>NaN</td>
      <td>NaN</td>
      <td>NaN</td>
      <td>NaN</td>
      <td>NaN</td>
      <td>NaN</td>
      <td>NaN</td>
    </tr>
    <tr>
      <th>2</th>
      <td>1077175</td>
      <td>1313524</td>
      <td>2400.0</td>
      <td>2400.0</td>
      <td>2400.0</td>
      <td>36 months</td>
      <td>15.96</td>
      <td>84.33</td>
      <td>C</td>
      <td>C5</td>
      <td>...</td>
      <td>NaN</td>
      <td>NaN</td>
      <td>NaN</td>
      <td>NaN</td>
      <td>NaN</td>
      <td>NaN</td>
      <td>NaN</td>
      <td>NaN</td>
      <td>NaN</td>
      <td>NaN</td>
    </tr>
    <tr>
      <th>3</th>
      <td>1076863</td>
      <td>1277178</td>
      <td>10000.0</td>
      <td>10000.0</td>
      <td>10000.0</td>
      <td>36 months</td>
      <td>13.49</td>
      <td>339.31</td>
      <td>C</td>
      <td>C1</td>
      <td>...</td>
      <td>NaN</td>
      <td>NaN</td>
      <td>NaN</td>
      <td>NaN</td>
      <td>NaN</td>
      <td>NaN</td>
      <td>NaN</td>
      <td>NaN</td>
      <td>NaN</td>
      <td>NaN</td>
    </tr>
    <tr>
      <th>4</th>
      <td>1075358</td>
      <td>1311748</td>
      <td>3000.0</td>
      <td>3000.0</td>
      <td>3000.0</td>
      <td>60 months</td>
      <td>12.69</td>
      <td>67.79</td>
      <td>B</td>
      <td>B5</td>
      <td>...</td>
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      <td>NaN</td>
      <td>NaN</td>
      <td>NaN</td>
      <td>NaN</td>
      <td>NaN</td>
      <td>NaN</td>
      <td>NaN</td>
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  </tbody>
</table>
<p>5 rows × 74 columns</p>
</div>
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<div class=" highlight hl-ipython3"><pre><span></span><span class="c1">#Making a copy of the dataframe</span>
<span class="n">df</span> <span class="o">=</span> <span class="n">start_df</span><span class="o">.</span><span class="n">copy</span><span class="p">()</span>
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<div class=" highlight hl-ipython3"><pre><span></span><span class="n">df</span><span class="o">.</span><span class="n">head</span><span class="p">()</span>
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<table border="1" class="dataframe">
  <thead>
    <tr style="text-align: right;">
      <th></th>
      <th>id</th>
      <th>member_id</th>
      <th>loan_amnt</th>
      <th>funded_amnt</th>
      <th>funded_amnt_inv</th>
      <th>term</th>
      <th>int_rate</th>
      <th>installment</th>
      <th>grade</th>
      <th>sub_grade</th>
      <th>...</th>
      <th>total_bal_il</th>
      <th>il_util</th>
      <th>open_rv_12m</th>
      <th>open_rv_24m</th>
      <th>max_bal_bc</th>
      <th>all_util</th>
      <th>total_rev_hi_lim</th>
      <th>inq_fi</th>
      <th>total_cu_tl</th>
      <th>inq_last_12m</th>
    </tr>
  </thead>
  <tbody>
    <tr>
      <th>0</th>
      <td>1077501</td>
      <td>1296599</td>
      <td>5000.0</td>
      <td>5000.0</td>
      <td>4975.0</td>
      <td>0</td>
      <td>10.65</td>
      <td>162.87</td>
      <td>B</td>
      <td>B2</td>
      <td>...</td>
      <td>NaN</td>
      <td>NaN</td>
      <td>NaN</td>
      <td>NaN</td>
      <td>NaN</td>
      <td>NaN</td>
      <td>NaN</td>
      <td>NaN</td>
      <td>NaN</td>
      <td>NaN</td>
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    <tr>
      <th>1</th>
      <td>1077430</td>
      <td>1314167</td>
      <td>2500.0</td>
      <td>2500.0</td>
      <td>2500.0</td>
      <td>1</td>
      <td>15.27</td>
      <td>59.83</td>
      <td>C</td>
      <td>C4</td>
      <td>...</td>
      <td>NaN</td>
      <td>NaN</td>
      <td>NaN</td>
      <td>NaN</td>
      <td>NaN</td>
      <td>NaN</td>
      <td>NaN</td>
      <td>NaN</td>
      <td>NaN</td>
      <td>NaN</td>
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    <tr>
      <th>2</th>
      <td>1077175</td>
      <td>1313524</td>
      <td>2400.0</td>
      <td>2400.0</td>
      <td>2400.0</td>
      <td>0</td>
      <td>15.96</td>
      <td>84.33</td>
      <td>C</td>
      <td>C5</td>
      <td>...</td>
      <td>NaN</td>
      <td>NaN</td>
      <td>NaN</td>
      <td>NaN</td>
      <td>NaN</td>
      <td>NaN</td>
      <td>NaN</td>
      <td>NaN</td>
      <td>NaN</td>
      <td>NaN</td>
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    <tr>
      <th>3</th>
      <td>1076863</td>
      <td>1277178</td>
      <td>10000.0</td>
      <td>10000.0</td>
      <td>10000.0</td>
      <td>0</td>
      <td>13.49</td>
      <td>339.31</td>
      <td>C</td>
      <td>C1</td>
      <td>...</td>
      <td>NaN</td>
      <td>NaN</td>
      <td>NaN</td>
      <td>NaN</td>
      <td>NaN</td>
      <td>NaN</td>
      <td>NaN</td>
      <td>NaN</td>
      <td>NaN</td>
      <td>NaN</td>
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    <tr>
      <th>4</th>
      <td>1075358</td>
      <td>1311748</td>
      <td>3000.0</td>
      <td>3000.0</td>
      <td>3000.0</td>
      <td>1</td>
      <td>12.69</td>
      <td>67.79</td>
      <td>B</td>
      <td>B5</td>
      <td>...</td>
      <td>NaN</td>
      <td>NaN</td>
      <td>NaN</td>
      <td>NaN</td>
      <td>NaN</td>
      <td>NaN</td>
      <td>NaN</td>
      <td>NaN</td>
      <td>NaN</td>
      <td>NaN</td>
    </tr>
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<p>5 rows × 74 columns</p>
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<div class=" highlight hl-ipython3"><pre><span></span><span class="c1">#Checking the dimensions</span>
<span class="n">df</span><span class="o">.</span><span class="n">shape</span>
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<pre>(887379, 74)</pre>
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<div class=" highlight hl-ipython3"><pre><span></span><span class="n">df</span><span class="o">.</span><span class="n">columns</span>
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<pre>Index([&#39;id&#39;, &#39;member_id&#39;, &#39;loan_amnt&#39;, &#39;funded_amnt&#39;, &#39;funded_amnt_inv&#39;,
       &#39;term&#39;, &#39;int_rate&#39;, &#39;installment&#39;, &#39;grade&#39;, &#39;sub_grade&#39;, &#39;emp_title&#39;,
       &#39;emp_length&#39;, &#39;home_ownership&#39;, &#39;annual_inc&#39;, &#39;verification_status&#39;,
       &#39;issue_d&#39;, &#39;loan_status&#39;, &#39;pymnt_plan&#39;, &#39;url&#39;, &#39;desc&#39;, &#39;purpose&#39;,
       &#39;title&#39;, &#39;zip_code&#39;, &#39;addr_state&#39;, &#39;dti&#39;, &#39;delinq_2yrs&#39;,
       &#39;earliest_cr_line&#39;, &#39;inq_last_6mths&#39;, &#39;mths_since_last_delinq&#39;,
       &#39;mths_since_last_record&#39;, &#39;open_acc&#39;, &#39;pub_rec&#39;, &#39;revol_bal&#39;,
       &#39;revol_util&#39;, &#39;total_acc&#39;, &#39;initial_list_status&#39;, &#39;out_prncp&#39;,
       &#39;out_prncp_inv&#39;, &#39;total_pymnt&#39;, &#39;total_pymnt_inv&#39;, &#39;total_rec_prncp&#39;,
       &#39;total_rec_int&#39;, &#39;total_rec_late_fee&#39;, &#39;recoveries&#39;,
       &#39;collection_recovery_fee&#39;, &#39;last_pymnt_d&#39;, &#39;last_pymnt_amnt&#39;,
       &#39;next_pymnt_d&#39;, &#39;last_credit_pull_d&#39;, &#39;collections_12_mths_ex_med&#39;,
       &#39;mths_since_last_major_derog&#39;, &#39;policy_code&#39;, &#39;application_type&#39;,
       &#39;annual_inc_joint&#39;, &#39;dti_joint&#39;, &#39;verification_status_joint&#39;,
       &#39;acc_now_delinq&#39;, &#39;tot_coll_amt&#39;, &#39;tot_cur_bal&#39;, &#39;open_acc_6m&#39;,
       &#39;open_il_6m&#39;, &#39;open_il_12m&#39;, &#39;open_il_24m&#39;, &#39;mths_since_rcnt_il&#39;,
       &#39;total_bal_il&#39;, &#39;il_util&#39;, &#39;open_rv_12m&#39;, &#39;open_rv_24m&#39;, &#39;max_bal_bc&#39;,
       &#39;all_util&#39;, &#39;total_rev_hi_lim&#39;, &#39;inq_fi&#39;, &#39;total_cu_tl&#39;,
       &#39;inq_last_12m&#39;],
      dtype=&#39;object&#39;)</pre>
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<h2 id="Understanding-the-data">Understanding the data<a class="anchor-link" href="#Understanding-the-data">&#182;</a></h2><p>Lets check the description of the data provided on the kernal</p>

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<div class=" highlight hl-ipython3"><pre><span></span><span class="n">df_description</span> <span class="o">=</span> <span class="n">pd</span><span class="o">.</span><span class="n">read_excel</span><span class="p">(</span><span class="s2">&quot;C://Users/Saurabh/Desktop/Home Work/IDS Assignments/data/Dataset/LCDataDictionary.xlsx&quot;</span><span class="p">)</span><span class="o">.</span><span class="n">dropna</span><span class="p">()</span>
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<div class=" highlight hl-ipython3"><pre><span></span><span class="n">df_description</span><span class="o">.</span><span class="n">style</span><span class="o">.</span><span class="n">set_properties</span><span class="p">(</span><span class="n">subset</span><span class="o">=</span><span class="p">[</span><span class="s1">&#39;Description&#39;</span><span class="p">],</span> <span class="o">**</span><span class="p">{</span><span class="s1">&#39;width&#39;</span><span class="p">:</span> <span class="s1">&#39;1000px&#39;</span><span class="p">})</span>
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<thead>    <tr> 
        <th class="blank level0" ></th> 
        <th class="col_heading level0 col0" >LoanStatNew</th> 
        <th class="col_heading level0 col1" >Description</th> 
    </tr></thead> 
<tbody>    <tr> 
        <th id="T_6ba8be34_fa4d_11e8_8db5_28c63fc57d3elevel0_row0" class="row_heading level0 row0" >0</th> 
        <td id="T_6ba8be34_fa4d_11e8_8db5_28c63fc57d3erow0_col0" class="data row0 col0" >addr_state</td> 
        <td id="T_6ba8be34_fa4d_11e8_8db5_28c63fc57d3erow0_col1" class="data row0 col1" >The state provided by the borrower in the loan application</td> 
    </tr>    <tr> 
        <th id="T_6ba8be34_fa4d_11e8_8db5_28c63fc57d3elevel0_row1" class="row_heading level0 row1" >1</th> 
        <td id="T_6ba8be34_fa4d_11e8_8db5_28c63fc57d3erow1_col0" class="data row1 col0" >annual_inc</td> 
        <td id="T_6ba8be34_fa4d_11e8_8db5_28c63fc57d3erow1_col1" class="data row1 col1" >The self-reported annual income provided by the borrower during registration.</td> 
    </tr>    <tr> 
        <th id="T_6ba8be34_fa4d_11e8_8db5_28c63fc57d3elevel0_row2" class="row_heading level0 row2" >2</th> 
        <td id="T_6ba8be34_fa4d_11e8_8db5_28c63fc57d3erow2_col0" class="data row2 col0" >annual_inc_joint</td> 
        <td id="T_6ba8be34_fa4d_11e8_8db5_28c63fc57d3erow2_col1" class="data row2 col1" >The combined self-reported annual income provided by the co-borrowers during registration</td> 
    </tr>    <tr> 
        <th id="T_6ba8be34_fa4d_11e8_8db5_28c63fc57d3elevel0_row3" class="row_heading level0 row3" >3</th> 
        <td id="T_6ba8be34_fa4d_11e8_8db5_28c63fc57d3erow3_col0" class="data row3 col0" >application_type</td> 
        <td id="T_6ba8be34_fa4d_11e8_8db5_28c63fc57d3erow3_col1" class="data row3 col1" >Indicates whether the loan is an individual application or a joint application with two co-borrowers</td> 
    </tr>    <tr> 
        <th id="T_6ba8be34_fa4d_11e8_8db5_28c63fc57d3elevel0_row4" class="row_heading level0 row4" >4</th> 
        <td id="T_6ba8be34_fa4d_11e8_8db5_28c63fc57d3erow4_col0" class="data row4 col0" >collection_recovery_fee</td> 
        <td id="T_6ba8be34_fa4d_11e8_8db5_28c63fc57d3erow4_col1" class="data row4 col1" >post charge off collection fee</td> 
    </tr>    <tr> 
        <th id="T_6ba8be34_fa4d_11e8_8db5_28c63fc57d3elevel0_row5" class="row_heading level0 row5" >5</th> 
        <td id="T_6ba8be34_fa4d_11e8_8db5_28c63fc57d3erow5_col0" class="data row5 col0" >collections_12_mths_ex_med</td> 
        <td id="T_6ba8be34_fa4d_11e8_8db5_28c63fc57d3erow5_col1" class="data row5 col1" >Number of collections in 12 months excluding medical collections</td> 
    </tr>    <tr> 
        <th id="T_6ba8be34_fa4d_11e8_8db5_28c63fc57d3elevel0_row6" class="row_heading level0 row6" >6</th> 
        <td id="T_6ba8be34_fa4d_11e8_8db5_28c63fc57d3erow6_col0" class="data row6 col0" >delinq_2yrs</td> 
        <td id="T_6ba8be34_fa4d_11e8_8db5_28c63fc57d3erow6_col1" class="data row6 col1" >The number of 30+ days past-due incidences of delinquency in the borrower's credit file for the past 2 years</td> 
    </tr>    <tr> 
        <th id="T_6ba8be34_fa4d_11e8_8db5_28c63fc57d3elevel0_row7" class="row_heading level0 row7" >7</th> 
        <td id="T_6ba8be34_fa4d_11e8_8db5_28c63fc57d3erow7_col0" class="data row7 col0" >desc</td> 
        <td id="T_6ba8be34_fa4d_11e8_8db5_28c63fc57d3erow7_col1" class="data row7 col1" >Loan description provided by the borrower</td> 
    </tr>    <tr> 
        <th id="T_6ba8be34_fa4d_11e8_8db5_28c63fc57d3elevel0_row8" class="row_heading level0 row8" >8</th> 
        <td id="T_6ba8be34_fa4d_11e8_8db5_28c63fc57d3erow8_col0" class="data row8 col0" >dti</td> 
        <td id="T_6ba8be34_fa4d_11e8_8db5_28c63fc57d3erow8_col1" class="data row8 col1" >A ratio calculated using the borrower’s total monthly debt payments on the total debt obligations, excluding mortgage and the requested LC loan, divided by the borrower’s self-reported monthly income.</td> 
    </tr>    <tr> 
        <th id="T_6ba8be34_fa4d_11e8_8db5_28c63fc57d3elevel0_row9" class="row_heading level0 row9" >9</th> 
        <td id="T_6ba8be34_fa4d_11e8_8db5_28c63fc57d3erow9_col0" class="data row9 col0" >dti_joint</td> 
        <td id="T_6ba8be34_fa4d_11e8_8db5_28c63fc57d3erow9_col1" class="data row9 col1" >A ratio calculated using the co-borrowers' total monthly payments on the total debt obligations, excluding mortgages and the requested LC loan, divided by the co-borrowers' combined self-reported monthly income</td> 
    </tr>    <tr> 
        <th id="T_6ba8be34_fa4d_11e8_8db5_28c63fc57d3elevel0_row10" class="row_heading level0 row10" >10</th> 
        <td id="T_6ba8be34_fa4d_11e8_8db5_28c63fc57d3erow10_col0" class="data row10 col0" >earliest_cr_line</td> 
        <td id="T_6ba8be34_fa4d_11e8_8db5_28c63fc57d3erow10_col1" class="data row10 col1" >The month the borrower's earliest reported credit line was opened</td> 
    </tr>    <tr> 
        <th id="T_6ba8be34_fa4d_11e8_8db5_28c63fc57d3elevel0_row11" class="row_heading level0 row11" >11</th> 
        <td id="T_6ba8be34_fa4d_11e8_8db5_28c63fc57d3erow11_col0" class="data row11 col0" >emp_length</td> 
        <td id="T_6ba8be34_fa4d_11e8_8db5_28c63fc57d3erow11_col1" class="data row11 col1" >Employment length in years. Possible values are between 0 and 10 where 0 means less than one year and 10 means ten or more years. </td> 
    </tr>    <tr> 
        <th id="T_6ba8be34_fa4d_11e8_8db5_28c63fc57d3elevel0_row12" class="row_heading level0 row12" >12</th> 
        <td id="T_6ba8be34_fa4d_11e8_8db5_28c63fc57d3erow12_col0" class="data row12 col0" >emp_title</td> 
        <td id="T_6ba8be34_fa4d_11e8_8db5_28c63fc57d3erow12_col1" class="data row12 col1" >The job title supplied by the Borrower when applying for the loan.*</td> 
    </tr>    <tr> 
        <th id="T_6ba8be34_fa4d_11e8_8db5_28c63fc57d3elevel0_row13" class="row_heading level0 row13" >13</th> 
        <td id="T_6ba8be34_fa4d_11e8_8db5_28c63fc57d3erow13_col0" class="data row13 col0" >fico_range_high</td> 
        <td id="T_6ba8be34_fa4d_11e8_8db5_28c63fc57d3erow13_col1" class="data row13 col1" >The upper boundary range the borrower’s FICO at loan origination belongs to.</td> 
    </tr>    <tr> 
        <th id="T_6ba8be34_fa4d_11e8_8db5_28c63fc57d3elevel0_row14" class="row_heading level0 row14" >14</th> 
        <td id="T_6ba8be34_fa4d_11e8_8db5_28c63fc57d3erow14_col0" class="data row14 col0" >fico_range_low</td> 
        <td id="T_6ba8be34_fa4d_11e8_8db5_28c63fc57d3erow14_col1" class="data row14 col1" >The lower boundary range the borrower’s FICO at loan origination belongs to.</td> 
    </tr>    <tr> 
        <th id="T_6ba8be34_fa4d_11e8_8db5_28c63fc57d3elevel0_row15" class="row_heading level0 row15" >15</th> 
        <td id="T_6ba8be34_fa4d_11e8_8db5_28c63fc57d3erow15_col0" class="data row15 col0" >funded_amnt</td> 
        <td id="T_6ba8be34_fa4d_11e8_8db5_28c63fc57d3erow15_col1" class="data row15 col1" >The total amount committed to that loan at that point in time.</td> 
    </tr>    <tr> 
        <th id="T_6ba8be34_fa4d_11e8_8db5_28c63fc57d3elevel0_row16" class="row_heading level0 row16" >16</th> 
        <td id="T_6ba8be34_fa4d_11e8_8db5_28c63fc57d3erow16_col0" class="data row16 col0" >funded_amnt_inv</td> 
        <td id="T_6ba8be34_fa4d_11e8_8db5_28c63fc57d3erow16_col1" class="data row16 col1" >The total amount committed by investors for that loan at that point in time.</td> 
    </tr>    <tr> 
        <th id="T_6ba8be34_fa4d_11e8_8db5_28c63fc57d3elevel0_row17" class="row_heading level0 row17" >17</th> 
        <td id="T_6ba8be34_fa4d_11e8_8db5_28c63fc57d3erow17_col0" class="data row17 col0" >grade</td> 
        <td id="T_6ba8be34_fa4d_11e8_8db5_28c63fc57d3erow17_col1" class="data row17 col1" >LC assigned loan grade</td> 
    </tr>    <tr> 
        <th id="T_6ba8be34_fa4d_11e8_8db5_28c63fc57d3elevel0_row18" class="row_heading level0 row18" >18</th> 
        <td id="T_6ba8be34_fa4d_11e8_8db5_28c63fc57d3erow18_col0" class="data row18 col0" >home_ownership</td> 
        <td id="T_6ba8be34_fa4d_11e8_8db5_28c63fc57d3erow18_col1" class="data row18 col1" >The home ownership status provided by the borrower during registration. Our values are: RENT, OWN, MORTGAGE, OTHER.</td> 
    </tr>    <tr> 
        <th id="T_6ba8be34_fa4d_11e8_8db5_28c63fc57d3elevel0_row19" class="row_heading level0 row19" >19</th> 
        <td id="T_6ba8be34_fa4d_11e8_8db5_28c63fc57d3erow19_col0" class="data row19 col0" >id</td> 
        <td id="T_6ba8be34_fa4d_11e8_8db5_28c63fc57d3erow19_col1" class="data row19 col1" >A unique LC assigned ID for the loan listing.</td> 
    </tr>    <tr> 
        <th id="T_6ba8be34_fa4d_11e8_8db5_28c63fc57d3elevel0_row20" class="row_heading level0 row20" >20</th> 
        <td id="T_6ba8be34_fa4d_11e8_8db5_28c63fc57d3erow20_col0" class="data row20 col0" >initial_list_status</td> 
        <td id="T_6ba8be34_fa4d_11e8_8db5_28c63fc57d3erow20_col1" class="data row20 col1" >The initial listing status of the loan. Possible values are – W, F</td> 
    </tr>    <tr> 
        <th id="T_6ba8be34_fa4d_11e8_8db5_28c63fc57d3elevel0_row21" class="row_heading level0 row21" >21</th> 
        <td id="T_6ba8be34_fa4d_11e8_8db5_28c63fc57d3erow21_col0" class="data row21 col0" >inq_last_6mths</td> 
        <td id="T_6ba8be34_fa4d_11e8_8db5_28c63fc57d3erow21_col1" class="data row21 col1" >The number of inquiries in past 6 months (excluding auto and mortgage inquiries)</td> 
    </tr>    <tr> 
        <th id="T_6ba8be34_fa4d_11e8_8db5_28c63fc57d3elevel0_row22" class="row_heading level0 row22" >22</th> 
        <td id="T_6ba8be34_fa4d_11e8_8db5_28c63fc57d3erow22_col0" class="data row22 col0" >installment</td> 
        <td id="T_6ba8be34_fa4d_11e8_8db5_28c63fc57d3erow22_col1" class="data row22 col1" >The monthly payment owed by the borrower if the loan originates.</td> 
    </tr>    <tr> 
        <th id="T_6ba8be34_fa4d_11e8_8db5_28c63fc57d3elevel0_row23" class="row_heading level0 row23" >23</th> 
        <td id="T_6ba8be34_fa4d_11e8_8db5_28c63fc57d3erow23_col0" class="data row23 col0" >int_rate</td> 
        <td id="T_6ba8be34_fa4d_11e8_8db5_28c63fc57d3erow23_col1" class="data row23 col1" >Interest Rate on the loan</td> 
    </tr>    <tr> 
        <th id="T_6ba8be34_fa4d_11e8_8db5_28c63fc57d3elevel0_row24" class="row_heading level0 row24" >24</th> 
        <td id="T_6ba8be34_fa4d_11e8_8db5_28c63fc57d3erow24_col0" class="data row24 col0" >is_inc_v</td> 
        <td id="T_6ba8be34_fa4d_11e8_8db5_28c63fc57d3erow24_col1" class="data row24 col1" >Indicates if income was verified by LC, not verified, or if the income source was verified</td> 
    </tr>    <tr> 
        <th id="T_6ba8be34_fa4d_11e8_8db5_28c63fc57d3elevel0_row25" class="row_heading level0 row25" >25</th> 
        <td id="T_6ba8be34_fa4d_11e8_8db5_28c63fc57d3erow25_col0" class="data row25 col0" >issue_d</td> 
        <td id="T_6ba8be34_fa4d_11e8_8db5_28c63fc57d3erow25_col1" class="data row25 col1" >The month which the loan was funded</td> 
    </tr>    <tr> 
        <th id="T_6ba8be34_fa4d_11e8_8db5_28c63fc57d3elevel0_row26" class="row_heading level0 row26" >26</th> 
        <td id="T_6ba8be34_fa4d_11e8_8db5_28c63fc57d3erow26_col0" class="data row26 col0" >last_credit_pull_d</td> 
        <td id="T_6ba8be34_fa4d_11e8_8db5_28c63fc57d3erow26_col1" class="data row26 col1" >The most recent month LC pulled credit for this loan</td> 
    </tr>    <tr> 
        <th id="T_6ba8be34_fa4d_11e8_8db5_28c63fc57d3elevel0_row27" class="row_heading level0 row27" >27</th> 
        <td id="T_6ba8be34_fa4d_11e8_8db5_28c63fc57d3erow27_col0" class="data row27 col0" >last_fico_range_high</td> 
        <td id="T_6ba8be34_fa4d_11e8_8db5_28c63fc57d3erow27_col1" class="data row27 col1" >The upper boundary range the borrower’s last FICO pulled belongs to.</td> 
    </tr>    <tr> 
        <th id="T_6ba8be34_fa4d_11e8_8db5_28c63fc57d3elevel0_row28" class="row_heading level0 row28" >28</th> 
        <td id="T_6ba8be34_fa4d_11e8_8db5_28c63fc57d3erow28_col0" class="data row28 col0" >last_fico_range_low</td> 
        <td id="T_6ba8be34_fa4d_11e8_8db5_28c63fc57d3erow28_col1" class="data row28 col1" >The lower boundary range the borrower’s last FICO pulled belongs to.</td> 
    </tr>    <tr> 
        <th id="T_6ba8be34_fa4d_11e8_8db5_28c63fc57d3elevel0_row29" class="row_heading level0 row29" >29</th> 
        <td id="T_6ba8be34_fa4d_11e8_8db5_28c63fc57d3erow29_col0" class="data row29 col0" >last_pymnt_amnt</td> 
        <td id="T_6ba8be34_fa4d_11e8_8db5_28c63fc57d3erow29_col1" class="data row29 col1" >Last total payment amount received</td> 
    </tr>    <tr> 
        <th id="T_6ba8be34_fa4d_11e8_8db5_28c63fc57d3elevel0_row30" class="row_heading level0 row30" >30</th> 
        <td id="T_6ba8be34_fa4d_11e8_8db5_28c63fc57d3erow30_col0" class="data row30 col0" >last_pymnt_d</td> 
        <td id="T_6ba8be34_fa4d_11e8_8db5_28c63fc57d3erow30_col1" class="data row30 col1" >Last month payment was received</td> 
    </tr>    <tr> 
        <th id="T_6ba8be34_fa4d_11e8_8db5_28c63fc57d3elevel0_row31" class="row_heading level0 row31" >31</th> 
        <td id="T_6ba8be34_fa4d_11e8_8db5_28c63fc57d3erow31_col0" class="data row31 col0" >loan_amnt</td> 
        <td id="T_6ba8be34_fa4d_11e8_8db5_28c63fc57d3erow31_col1" class="data row31 col1" >The listed amount of the loan applied for by the borrower. If at some point in time, the credit department reduces the loan amount, then it will be reflected in this value.</td> 
    </tr>    <tr> 
        <th id="T_6ba8be34_fa4d_11e8_8db5_28c63fc57d3elevel0_row32" class="row_heading level0 row32" >32</th> 
        <td id="T_6ba8be34_fa4d_11e8_8db5_28c63fc57d3erow32_col0" class="data row32 col0" >loan_status</td> 
        <td id="T_6ba8be34_fa4d_11e8_8db5_28c63fc57d3erow32_col1" class="data row32 col1" >Current status of the loan</td> 
    </tr>    <tr> 
        <th id="T_6ba8be34_fa4d_11e8_8db5_28c63fc57d3elevel0_row33" class="row_heading level0 row33" >33</th> 
        <td id="T_6ba8be34_fa4d_11e8_8db5_28c63fc57d3erow33_col0" class="data row33 col0" >member_id</td> 
        <td id="T_6ba8be34_fa4d_11e8_8db5_28c63fc57d3erow33_col1" class="data row33 col1" >A unique LC assigned Id for the borrower member.</td> 
    </tr>    <tr> 
        <th id="T_6ba8be34_fa4d_11e8_8db5_28c63fc57d3elevel0_row34" class="row_heading level0 row34" >34</th> 
        <td id="T_6ba8be34_fa4d_11e8_8db5_28c63fc57d3erow34_col0" class="data row34 col0" >mths_since_last_delinq</td> 
        <td id="T_6ba8be34_fa4d_11e8_8db5_28c63fc57d3erow34_col1" class="data row34 col1" >The number of months since the borrower's last delinquency.</td> 
    </tr>    <tr> 
        <th id="T_6ba8be34_fa4d_11e8_8db5_28c63fc57d3elevel0_row35" class="row_heading level0 row35" >35</th> 
        <td id="T_6ba8be34_fa4d_11e8_8db5_28c63fc57d3erow35_col0" class="data row35 col0" >mths_since_last_major_derog</td> 
        <td id="T_6ba8be34_fa4d_11e8_8db5_28c63fc57d3erow35_col1" class="data row35 col1" >Months since most recent 90-day or worse rating</td> 
    </tr>    <tr> 
        <th id="T_6ba8be34_fa4d_11e8_8db5_28c63fc57d3elevel0_row36" class="row_heading level0 row36" >36</th> 
        <td id="T_6ba8be34_fa4d_11e8_8db5_28c63fc57d3erow36_col0" class="data row36 col0" >mths_since_last_record</td> 
        <td id="T_6ba8be34_fa4d_11e8_8db5_28c63fc57d3erow36_col1" class="data row36 col1" >The number of months since the last public record.</td> 
    </tr>    <tr> 
        <th id="T_6ba8be34_fa4d_11e8_8db5_28c63fc57d3elevel0_row37" class="row_heading level0 row37" >37</th> 
        <td id="T_6ba8be34_fa4d_11e8_8db5_28c63fc57d3erow37_col0" class="data row37 col0" >next_pymnt_d</td> 
        <td id="T_6ba8be34_fa4d_11e8_8db5_28c63fc57d3erow37_col1" class="data row37 col1" >Next scheduled payment date</td> 
    </tr>    <tr> 
        <th id="T_6ba8be34_fa4d_11e8_8db5_28c63fc57d3elevel0_row38" class="row_heading level0 row38" >38</th> 
        <td id="T_6ba8be34_fa4d_11e8_8db5_28c63fc57d3erow38_col0" class="data row38 col0" >open_acc</td> 
        <td id="T_6ba8be34_fa4d_11e8_8db5_28c63fc57d3erow38_col1" class="data row38 col1" >The number of open credit lines in the borrower's credit file.</td> 
    </tr>    <tr> 
        <th id="T_6ba8be34_fa4d_11e8_8db5_28c63fc57d3elevel0_row39" class="row_heading level0 row39" >39</th> 
        <td id="T_6ba8be34_fa4d_11e8_8db5_28c63fc57d3erow39_col0" class="data row39 col0" >out_prncp</td> 
        <td id="T_6ba8be34_fa4d_11e8_8db5_28c63fc57d3erow39_col1" class="data row39 col1" >Remaining outstanding principal for total amount funded</td> 
    </tr>    <tr> 
        <th id="T_6ba8be34_fa4d_11e8_8db5_28c63fc57d3elevel0_row40" class="row_heading level0 row40" >40</th> 
        <td id="T_6ba8be34_fa4d_11e8_8db5_28c63fc57d3erow40_col0" class="data row40 col0" >out_prncp_inv</td> 
        <td id="T_6ba8be34_fa4d_11e8_8db5_28c63fc57d3erow40_col1" class="data row40 col1" >Remaining outstanding principal for portion of total amount funded by investors</td> 
    </tr>    <tr> 
        <th id="T_6ba8be34_fa4d_11e8_8db5_28c63fc57d3elevel0_row41" class="row_heading level0 row41" >41</th> 
        <td id="T_6ba8be34_fa4d_11e8_8db5_28c63fc57d3erow41_col0" class="data row41 col0" >policy_code</td> 
        <td id="T_6ba8be34_fa4d_11e8_8db5_28c63fc57d3erow41_col1" class="data row41 col1" >publicly available policy_code=1
new products not publicly available policy_code=2</td> 
    </tr>    <tr> 
        <th id="T_6ba8be34_fa4d_11e8_8db5_28c63fc57d3elevel0_row42" class="row_heading level0 row42" >42</th> 
        <td id="T_6ba8be34_fa4d_11e8_8db5_28c63fc57d3erow42_col0" class="data row42 col0" >pub_rec</td> 
        <td id="T_6ba8be34_fa4d_11e8_8db5_28c63fc57d3erow42_col1" class="data row42 col1" >Number of derogatory public records</td> 
    </tr>    <tr> 
        <th id="T_6ba8be34_fa4d_11e8_8db5_28c63fc57d3elevel0_row43" class="row_heading level0 row43" >43</th> 
        <td id="T_6ba8be34_fa4d_11e8_8db5_28c63fc57d3erow43_col0" class="data row43 col0" >purpose</td> 
        <td id="T_6ba8be34_fa4d_11e8_8db5_28c63fc57d3erow43_col1" class="data row43 col1" >A category provided by the borrower for the loan request. </td> 
    </tr>    <tr> 
        <th id="T_6ba8be34_fa4d_11e8_8db5_28c63fc57d3elevel0_row44" class="row_heading level0 row44" >44</th> 
        <td id="T_6ba8be34_fa4d_11e8_8db5_28c63fc57d3erow44_col0" class="data row44 col0" >pymnt_plan</td> 
        <td id="T_6ba8be34_fa4d_11e8_8db5_28c63fc57d3erow44_col1" class="data row44 col1" >Indicates if a payment plan has been put in place for the loan</td> 
    </tr>    <tr> 
        <th id="T_6ba8be34_fa4d_11e8_8db5_28c63fc57d3elevel0_row45" class="row_heading level0 row45" >45</th> 
        <td id="T_6ba8be34_fa4d_11e8_8db5_28c63fc57d3erow45_col0" class="data row45 col0" >recoveries</td> 
        <td id="T_6ba8be34_fa4d_11e8_8db5_28c63fc57d3erow45_col1" class="data row45 col1" >post charge off gross recovery</td> 
    </tr>    <tr> 
        <th id="T_6ba8be34_fa4d_11e8_8db5_28c63fc57d3elevel0_row46" class="row_heading level0 row46" >46</th> 
        <td id="T_6ba8be34_fa4d_11e8_8db5_28c63fc57d3erow46_col0" class="data row46 col0" >revol_bal</td> 
        <td id="T_6ba8be34_fa4d_11e8_8db5_28c63fc57d3erow46_col1" class="data row46 col1" >Total credit revolving balance</td> 
    </tr>    <tr> 
        <th id="T_6ba8be34_fa4d_11e8_8db5_28c63fc57d3elevel0_row47" class="row_heading level0 row47" >47</th> 
        <td id="T_6ba8be34_fa4d_11e8_8db5_28c63fc57d3erow47_col0" class="data row47 col0" >revol_util</td> 
        <td id="T_6ba8be34_fa4d_11e8_8db5_28c63fc57d3erow47_col1" class="data row47 col1" >Revolving line utilization rate, or the amount of credit the borrower is using relative to all available revolving credit.</td> 
    </tr>    <tr> 
        <th id="T_6ba8be34_fa4d_11e8_8db5_28c63fc57d3elevel0_row48" class="row_heading level0 row48" >48</th> 
        <td id="T_6ba8be34_fa4d_11e8_8db5_28c63fc57d3erow48_col0" class="data row48 col0" >sub_grade</td> 
        <td id="T_6ba8be34_fa4d_11e8_8db5_28c63fc57d3erow48_col1" class="data row48 col1" >LC assigned loan subgrade</td> 
    </tr>    <tr> 
        <th id="T_6ba8be34_fa4d_11e8_8db5_28c63fc57d3elevel0_row49" class="row_heading level0 row49" >49</th> 
        <td id="T_6ba8be34_fa4d_11e8_8db5_28c63fc57d3erow49_col0" class="data row49 col0" >term</td> 
        <td id="T_6ba8be34_fa4d_11e8_8db5_28c63fc57d3erow49_col1" class="data row49 col1" >The number of payments on the loan. Values are in months and can be either 36 or 60.</td> 
    </tr>    <tr> 
        <th id="T_6ba8be34_fa4d_11e8_8db5_28c63fc57d3elevel0_row50" class="row_heading level0 row50" >50</th> 
        <td id="T_6ba8be34_fa4d_11e8_8db5_28c63fc57d3erow50_col0" class="data row50 col0" >title</td> 
        <td id="T_6ba8be34_fa4d_11e8_8db5_28c63fc57d3erow50_col1" class="data row50 col1" >The loan title provided by the borrower</td> 
    </tr>    <tr> 
        <th id="T_6ba8be34_fa4d_11e8_8db5_28c63fc57d3elevel0_row51" class="row_heading level0 row51" >51</th> 
        <td id="T_6ba8be34_fa4d_11e8_8db5_28c63fc57d3erow51_col0" class="data row51 col0" >total_acc</td> 
        <td id="T_6ba8be34_fa4d_11e8_8db5_28c63fc57d3erow51_col1" class="data row51 col1" >The total number of credit lines currently in the borrower's credit file</td> 
    </tr>    <tr> 
        <th id="T_6ba8be34_fa4d_11e8_8db5_28c63fc57d3elevel0_row52" class="row_heading level0 row52" >52</th> 
        <td id="T_6ba8be34_fa4d_11e8_8db5_28c63fc57d3erow52_col0" class="data row52 col0" >total_pymnt</td> 
        <td id="T_6ba8be34_fa4d_11e8_8db5_28c63fc57d3erow52_col1" class="data row52 col1" >Payments received to date for total amount funded</td> 
    </tr>    <tr> 
        <th id="T_6ba8be34_fa4d_11e8_8db5_28c63fc57d3elevel0_row53" class="row_heading level0 row53" >53</th> 
        <td id="T_6ba8be34_fa4d_11e8_8db5_28c63fc57d3erow53_col0" class="data row53 col0" >total_pymnt_inv</td> 
        <td id="T_6ba8be34_fa4d_11e8_8db5_28c63fc57d3erow53_col1" class="data row53 col1" >Payments received to date for portion of total amount funded by investors</td> 
    </tr>    <tr> 
        <th id="T_6ba8be34_fa4d_11e8_8db5_28c63fc57d3elevel0_row54" class="row_heading level0 row54" >54</th> 
        <td id="T_6ba8be34_fa4d_11e8_8db5_28c63fc57d3erow54_col0" class="data row54 col0" >total_rec_int</td> 
        <td id="T_6ba8be34_fa4d_11e8_8db5_28c63fc57d3erow54_col1" class="data row54 col1" >Interest received to date</td> 
    </tr>    <tr> 
        <th id="T_6ba8be34_fa4d_11e8_8db5_28c63fc57d3elevel0_row55" class="row_heading level0 row55" >55</th> 
        <td id="T_6ba8be34_fa4d_11e8_8db5_28c63fc57d3erow55_col0" class="data row55 col0" >total_rec_late_fee</td> 
        <td id="T_6ba8be34_fa4d_11e8_8db5_28c63fc57d3erow55_col1" class="data row55 col1" >Late fees received to date</td> 
    </tr>    <tr> 
        <th id="T_6ba8be34_fa4d_11e8_8db5_28c63fc57d3elevel0_row56" class="row_heading level0 row56" >56</th> 
        <td id="T_6ba8be34_fa4d_11e8_8db5_28c63fc57d3erow56_col0" class="data row56 col0" >total_rec_prncp</td> 
        <td id="T_6ba8be34_fa4d_11e8_8db5_28c63fc57d3erow56_col1" class="data row56 col1" >Principal received to date</td> 
    </tr>    <tr> 
        <th id="T_6ba8be34_fa4d_11e8_8db5_28c63fc57d3elevel0_row57" class="row_heading level0 row57" >57</th> 
        <td id="T_6ba8be34_fa4d_11e8_8db5_28c63fc57d3erow57_col0" class="data row57 col0" >url</td> 
        <td id="T_6ba8be34_fa4d_11e8_8db5_28c63fc57d3erow57_col1" class="data row57 col1" >URL for the LC page with listing data.</td> 
    </tr>    <tr> 
        <th id="T_6ba8be34_fa4d_11e8_8db5_28c63fc57d3elevel0_row58" class="row_heading level0 row58" >58</th> 
        <td id="T_6ba8be34_fa4d_11e8_8db5_28c63fc57d3erow58_col0" class="data row58 col0" >verified_status_joint</td> 
        <td id="T_6ba8be34_fa4d_11e8_8db5_28c63fc57d3erow58_col1" class="data row58 col1" >Indicates if the co-borrowers' joint income was verified by LC, not verified, or if the income source was verified</td> 
    </tr>    <tr> 
        <th id="T_6ba8be34_fa4d_11e8_8db5_28c63fc57d3elevel0_row59" class="row_heading level0 row59" >59</th> 
        <td id="T_6ba8be34_fa4d_11e8_8db5_28c63fc57d3erow59_col0" class="data row59 col0" >zip_code</td> 
        <td id="T_6ba8be34_fa4d_11e8_8db5_28c63fc57d3erow59_col1" class="data row59 col1" >The first 3 numbers of the zip code provided by the borrower in the loan application.</td> 
    </tr>    <tr> 
        <th id="T_6ba8be34_fa4d_11e8_8db5_28c63fc57d3elevel0_row60" class="row_heading level0 row60" >60</th> 
        <td id="T_6ba8be34_fa4d_11e8_8db5_28c63fc57d3erow60_col0" class="data row60 col0" >open_acc_6m</td> 
        <td id="T_6ba8be34_fa4d_11e8_8db5_28c63fc57d3erow60_col1" class="data row60 col1" >Number of open trades in last 6 months</td> 
    </tr>    <tr> 
        <th id="T_6ba8be34_fa4d_11e8_8db5_28c63fc57d3elevel0_row61" class="row_heading level0 row61" >61</th> 
        <td id="T_6ba8be34_fa4d_11e8_8db5_28c63fc57d3erow61_col0" class="data row61 col0" >open_il_6m</td> 
        <td id="T_6ba8be34_fa4d_11e8_8db5_28c63fc57d3erow61_col1" class="data row61 col1" >Number of currently active installment trades</td> 
    </tr>    <tr> 
        <th id="T_6ba8be34_fa4d_11e8_8db5_28c63fc57d3elevel0_row62" class="row_heading level0 row62" >62</th> 
        <td id="T_6ba8be34_fa4d_11e8_8db5_28c63fc57d3erow62_col0" class="data row62 col0" >open_il_12m</td> 
        <td id="T_6ba8be34_fa4d_11e8_8db5_28c63fc57d3erow62_col1" class="data row62 col1" >Number of installment accounts opened in past 12 months</td> 
    </tr>    <tr> 
        <th id="T_6ba8be34_fa4d_11e8_8db5_28c63fc57d3elevel0_row63" class="row_heading level0 row63" >63</th> 
        <td id="T_6ba8be34_fa4d_11e8_8db5_28c63fc57d3erow63_col0" class="data row63 col0" >open_il_24m</td> 
        <td id="T_6ba8be34_fa4d_11e8_8db5_28c63fc57d3erow63_col1" class="data row63 col1" >Number of installment accounts opened in past 24 months</td> 
    </tr>    <tr> 
        <th id="T_6ba8be34_fa4d_11e8_8db5_28c63fc57d3elevel0_row64" class="row_heading level0 row64" >64</th> 
        <td id="T_6ba8be34_fa4d_11e8_8db5_28c63fc57d3erow64_col0" class="data row64 col0" >mths_since_rcnt_il</td> 
        <td id="T_6ba8be34_fa4d_11e8_8db5_28c63fc57d3erow64_col1" class="data row64 col1" >Months since most recent installment accounts opened</td> 
    </tr>    <tr> 
        <th id="T_6ba8be34_fa4d_11e8_8db5_28c63fc57d3elevel0_row65" class="row_heading level0 row65" >65</th> 
        <td id="T_6ba8be34_fa4d_11e8_8db5_28c63fc57d3erow65_col0" class="data row65 col0" >total_bal_il</td> 
        <td id="T_6ba8be34_fa4d_11e8_8db5_28c63fc57d3erow65_col1" class="data row65 col1" >Total current balance of all installment accounts</td> 
    </tr>    <tr> 
        <th id="T_6ba8be34_fa4d_11e8_8db5_28c63fc57d3elevel0_row66" class="row_heading level0 row66" >66</th> 
        <td id="T_6ba8be34_fa4d_11e8_8db5_28c63fc57d3erow66_col0" class="data row66 col0" >il_util</td> 
        <td id="T_6ba8be34_fa4d_11e8_8db5_28c63fc57d3erow66_col1" class="data row66 col1" >Ratio of total current balance to high credit/credit limit on all install acct</td> 
    </tr>    <tr> 
        <th id="T_6ba8be34_fa4d_11e8_8db5_28c63fc57d3elevel0_row67" class="row_heading level0 row67" >67</th> 
        <td id="T_6ba8be34_fa4d_11e8_8db5_28c63fc57d3erow67_col0" class="data row67 col0" >open_rv_12m</td> 
        <td id="T_6ba8be34_fa4d_11e8_8db5_28c63fc57d3erow67_col1" class="data row67 col1" >Number of revolving trades opened in past 12 months</td> 
    </tr>    <tr> 
        <th id="T_6ba8be34_fa4d_11e8_8db5_28c63fc57d3elevel0_row68" class="row_heading level0 row68" >68</th> 
        <td id="T_6ba8be34_fa4d_11e8_8db5_28c63fc57d3erow68_col0" class="data row68 col0" >open_rv_24m</td> 
        <td id="T_6ba8be34_fa4d_11e8_8db5_28c63fc57d3erow68_col1" class="data row68 col1" >Number of revolving trades opened in past 24 months</td> 
    </tr>    <tr> 
        <th id="T_6ba8be34_fa4d_11e8_8db5_28c63fc57d3elevel0_row69" class="row_heading level0 row69" >69</th> 
        <td id="T_6ba8be34_fa4d_11e8_8db5_28c63fc57d3erow69_col0" class="data row69 col0" >max_bal_bc</td> 
        <td id="T_6ba8be34_fa4d_11e8_8db5_28c63fc57d3erow69_col1" class="data row69 col1" >Maximum current balance owed on all revolving accounts</td> 
    </tr>    <tr> 
        <th id="T_6ba8be34_fa4d_11e8_8db5_28c63fc57d3elevel0_row70" class="row_heading level0 row70" >70</th> 
        <td id="T_6ba8be34_fa4d_11e8_8db5_28c63fc57d3erow70_col0" class="data row70 col0" >all_util</td> 
        <td id="T_6ba8be34_fa4d_11e8_8db5_28c63fc57d3erow70_col1" class="data row70 col1" >Balance to credit limit on all trades</td> 
    </tr>    <tr> 
        <th id="T_6ba8be34_fa4d_11e8_8db5_28c63fc57d3elevel0_row71" class="row_heading level0 row71" >71</th> 
        <td id="T_6ba8be34_fa4d_11e8_8db5_28c63fc57d3erow71_col0" class="data row71 col0" >total_rev_hi_lim  </td> 
        <td id="T_6ba8be34_fa4d_11e8_8db5_28c63fc57d3erow71_col1" class="data row71 col1" >Total revolving high credit/credit limit</td> 
    </tr>    <tr> 
        <th id="T_6ba8be34_fa4d_11e8_8db5_28c63fc57d3elevel0_row72" class="row_heading level0 row72" >72</th> 
        <td id="T_6ba8be34_fa4d_11e8_8db5_28c63fc57d3erow72_col0" class="data row72 col0" >inq_fi</td> 
        <td id="T_6ba8be34_fa4d_11e8_8db5_28c63fc57d3erow72_col1" class="data row72 col1" >Number of personal finance inquiries</td> 
    </tr>    <tr> 
        <th id="T_6ba8be34_fa4d_11e8_8db5_28c63fc57d3elevel0_row73" class="row_heading level0 row73" >73</th> 
        <td id="T_6ba8be34_fa4d_11e8_8db5_28c63fc57d3erow73_col0" class="data row73 col0" >total_cu_tl</td> 
        <td id="T_6ba8be34_fa4d_11e8_8db5_28c63fc57d3erow73_col1" class="data row73 col1" >Number of finance trades</td> 
    </tr>    <tr> 
        <th id="T_6ba8be34_fa4d_11e8_8db5_28c63fc57d3elevel0_row74" class="row_heading level0 row74" >74</th> 
        <td id="T_6ba8be34_fa4d_11e8_8db5_28c63fc57d3erow74_col0" class="data row74 col0" >inq_last_12m</td> 
        <td id="T_6ba8be34_fa4d_11e8_8db5_28c63fc57d3erow74_col1" class="data row74 col1" >Number of credit inquiries in past 12 months</td> 
    </tr>    <tr> 
        <th id="T_6ba8be34_fa4d_11e8_8db5_28c63fc57d3elevel0_row75" class="row_heading level0 row75" >75</th> 
        <td id="T_6ba8be34_fa4d_11e8_8db5_28c63fc57d3erow75_col0" class="data row75 col0" >acc_now_delinq</td> 
        <td id="T_6ba8be34_fa4d_11e8_8db5_28c63fc57d3erow75_col1" class="data row75 col1" >The number of accounts on which the borrower is now delinquent.</td> 
    </tr>    <tr> 
        <th id="T_6ba8be34_fa4d_11e8_8db5_28c63fc57d3elevel0_row76" class="row_heading level0 row76" >76</th> 
        <td id="T_6ba8be34_fa4d_11e8_8db5_28c63fc57d3erow76_col0" class="data row76 col0" >tot_coll_amt</td> 
        <td id="T_6ba8be34_fa4d_11e8_8db5_28c63fc57d3erow76_col1" class="data row76 col1" >Total collection amounts ever owed</td> 
    </tr>    <tr> 
        <th id="T_6ba8be34_fa4d_11e8_8db5_28c63fc57d3elevel0_row77" class="row_heading level0 row77" >77</th> 
        <td id="T_6ba8be34_fa4d_11e8_8db5_28c63fc57d3erow77_col0" class="data row77 col0" >tot_cur_bal</td> 
        <td id="T_6ba8be34_fa4d_11e8_8db5_28c63fc57d3erow77_col1" class="data row77 col1" >Total current balance of all accounts</td> 
    </tr></tbody> 
</table> 
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<div class=" highlight hl-ipython3"><pre><span></span><span class="n">df</span><span class="o">.</span><span class="n">isnull</span><span class="p">()</span><span class="o">.</span><span class="n">sum</span><span class="p">()</span>
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<pre>id                                  0
member_id                           0
loan_amnt                           0
funded_amnt                         0
funded_amnt_inv                     0
term                                0
int_rate                            0
installment                         0
grade                               0
sub_grade                           0
emp_title                       51462
emp_length                      44825
home_ownership                      0
annual_inc                          4
verification_status                 0
issue_d                             0
loan_status                         0
pymnt_plan                          0
url                                 0
desc                           761351
purpose                             0
title                             152
zip_code                            0
addr_state                          0
dti                                 0
delinq_2yrs                        29
earliest_cr_line                   29
inq_last_6mths                     29
mths_since_last_delinq         454312
mths_since_last_record         750326
                                ...  
collection_recovery_fee             0
last_pymnt_d                    17659
last_pymnt_amnt                     0
next_pymnt_d                   252971
last_credit_pull_d                 53
collections_12_mths_ex_med        145
mths_since_last_major_derog    665676
policy_code                         0
application_type                    0
annual_inc_joint               886868
dti_joint                      886870
verification_status_joint      886868
acc_now_delinq                     29
tot_coll_amt                    70276
tot_cur_bal                     70276
open_acc_6m                    866007
open_il_6m                     866007
open_il_12m                    866007
open_il_24m                    866007
mths_since_rcnt_il             866569
total_bal_il                   866007
il_util                        868762
open_rv_12m                    866007
open_rv_24m                    866007
max_bal_bc                     866007
all_util                       866007
total_rev_hi_lim                70276
inq_fi                         866007
total_cu_tl                    866007
inq_last_12m                   866007
Length: 74, dtype: int64</pre>
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<div class=" highlight hl-ipython3"><pre><span></span><span class="k">def</span> <span class="nf">null_values</span><span class="p">(</span><span class="n">df</span><span class="p">):</span>
    <span class="n">mis_val</span> <span class="o">=</span> <span class="n">df</span><span class="o">.</span><span class="n">isnull</span><span class="p">()</span><span class="o">.</span><span class="n">sum</span><span class="p">()</span>
    <span class="n">mis_val_percent</span> <span class="o">=</span> <span class="mi">100</span> <span class="o">*</span> <span class="n">df</span><span class="o">.</span><span class="n">isnull</span><span class="p">()</span><span class="o">.</span><span class="n">sum</span><span class="p">()</span><span class="o">/</span><span class="nb">len</span><span class="p">(</span><span class="n">df</span><span class="p">)</span>
    <span class="n">mis_val_table</span><span class="o">=</span><span class="n">pd</span><span class="o">.</span><span class="n">concat</span><span class="p">([</span><span class="n">mis_val</span><span class="p">,</span><span class="n">mis_val_percent</span><span class="p">],</span><span class="n">axis</span> <span class="o">=</span> <span class="mi">1</span><span class="p">)</span>
    <span class="n">mis_val_ren_columns</span> <span class="o">=</span> <span class="n">mis_val_table</span><span class="o">.</span><span class="n">rename</span><span class="p">(</span><span class="n">columns</span><span class="o">=</span><span class="p">{</span><span class="mi">0</span> <span class="p">:</span> <span class="s2">&quot;Missing Values&quot;</span><span class="p">,</span> <span class="mi">1</span> <span class="p">:</span> <span class="s2">&quot;</span><span class="si">% o</span><span class="s2">f Missing Values&quot;</span><span class="p">})</span>
    <span class="n">mis_val_ren_columns</span> <span class="o">=</span> <span class="n">mis_val_ren_columns</span><span class="p">[</span><span class="n">mis_val_ren_columns</span><span class="o">.</span><span class="n">iloc</span><span class="p">[:,</span><span class="mi">1</span><span class="p">]</span> <span class="o">!=</span> <span class="mi">0</span><span class="p">]</span><span class="o">.</span><span class="n">sort_values</span><span class="p">(</span><span class="s1">&#39;</span><span class="si">% o</span><span class="s1">f Missing Values&#39;</span><span class="p">,</span><span class="n">ascending</span><span class="o">=</span><span class="kc">False</span><span class="p">)</span><span class="o">.</span><span class="n">round</span><span class="p">(</span><span class="mi">1</span><span class="p">)</span>
    <span class="nb">print</span> <span class="p">(</span><span class="s2">&quot;Dataframe has &quot;</span> <span class="o">+</span> <span class="nb">str</span><span class="p">(</span><span class="n">df</span><span class="o">.</span><span class="n">shape</span><span class="p">[</span><span class="mi">1</span><span class="p">])</span> <span class="o">+</span> <span class="s2">&quot; columns.</span><span class="se">\n</span><span class="s2">&quot;</span>      
            <span class="s2">&quot;There are &quot;</span> <span class="o">+</span> <span class="nb">str</span><span class="p">(</span><span class="n">mis_val_ren_columns</span><span class="o">.</span><span class="n">shape</span><span class="p">[</span><span class="mi">0</span><span class="p">])</span> <span class="o">+</span>
              <span class="s2">&quot; columns that have missing values.&quot;</span><span class="p">)</span>
    <span class="k">return</span> <span class="n">mis_val_ren_columns</span>
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<div class=" highlight hl-ipython3"><pre><span></span><span class="c1"># Missing values statistics</span>
<span class="n">miss_values</span> <span class="o">=</span> <span class="n">null_values</span><span class="p">(</span><span class="n">df</span><span class="p">)</span>
<span class="n">miss_values</span><span class="o">.</span><span class="n">head</span><span class="p">(</span><span class="mi">20</span><span class="p">)</span>
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<pre>Dataframe has 74 columns.
There are 40 columns that have missing values.
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<style scoped>
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<table border="1" class="dataframe">
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      <th></th>
      <th>Missing Values</th>
      <th>% of Missing Values</th>
    </tr>
  </thead>
  <tbody>
    <tr>
      <th>dti_joint</th>
      <td>886870</td>
      <td>99.9</td>
    </tr>
    <tr>
      <th>annual_inc_joint</th>
      <td>886868</td>
      <td>99.9</td>
    </tr>
    <tr>
      <th>verification_status_joint</th>
      <td>886868</td>
      <td>99.9</td>
    </tr>
    <tr>
      <th>il_util</th>
      <td>868762</td>
      <td>97.9</td>
    </tr>
    <tr>
      <th>mths_since_rcnt_il</th>
      <td>866569</td>
      <td>97.7</td>
    </tr>
    <tr>
      <th>total_cu_tl</th>
      <td>866007</td>
      <td>97.6</td>
    </tr>
    <tr>
      <th>inq_fi</th>
      <td>866007</td>
      <td>97.6</td>
    </tr>
    <tr>
      <th>all_util</th>
      <td>866007</td>
      <td>97.6</td>
    </tr>
    <tr>
      <th>max_bal_bc</th>
      <td>866007</td>
      <td>97.6</td>
    </tr>
    <tr>
      <th>open_rv_24m</th>
      <td>866007</td>
      <td>97.6</td>
    </tr>
    <tr>
      <th>open_rv_12m</th>
      <td>866007</td>
      <td>97.6</td>
    </tr>
    <tr>
      <th>total_bal_il</th>
      <td>866007</td>
      <td>97.6</td>
    </tr>
    <tr>
      <th>open_il_24m</th>
      <td>866007</td>
      <td>97.6</td>
    </tr>
    <tr>
      <th>open_il_12m</th>
      <td>866007</td>
      <td>97.6</td>
    </tr>
    <tr>
      <th>open_il_6m</th>
      <td>866007</td>
      <td>97.6</td>
    </tr>
    <tr>
      <th>open_acc_6m</th>
      <td>866007</td>
      <td>97.6</td>
    </tr>
    <tr>
      <th>inq_last_12m</th>
      <td>866007</td>
      <td>97.6</td>
    </tr>
    <tr>
      <th>desc</th>
      <td>761351</td>
      <td>85.8</td>
    </tr>
    <tr>
      <th>mths_since_last_record</th>
      <td>750326</td>
      <td>84.6</td>
    </tr>
    <tr>
      <th>mths_since_last_major_derog</th>
      <td>665676</td>
      <td>75.0</td>
    </tr>
  </tbody>
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<p>Now if we have a look at the percentage of missing data in many columns is far more than we could work with . So it is better if we remove a certain columns by setting a threshold values in the further section.</p>

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<div class=" highlight hl-ipython3"><pre><span></span><span class="n">df</span><span class="p">[</span><span class="s1">&#39;loan_status&#39;</span><span class="p">]</span><span class="o">.</span><span class="n">value_counts</span><span class="p">()</span>
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<pre>Current                                                601779
Fully Paid                                             207723
Charged Off                                             45248
Late (31-120 days)                                      11591
Issued                                                   8460
In Grace Period                                          6253
Late (16-30 days)                                        2357
Does not meet the credit policy. Status:Fully Paid       1988
Default                                                  1219
Does not meet the credit policy. Status:Charged Off       761
Name: loan_status, dtype: int64</pre>
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<p>Here we are interested in the loan status with default value thus we assign 1 as default and 0 for any other category.</p>

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<div class=" highlight hl-ipython3"><pre><span></span><span class="n">target_list</span> <span class="o">=</span> <span class="p">[</span><span class="mi">1</span> <span class="k">if</span> <span class="n">i</span><span class="o">==</span><span class="s1">&#39;Default&#39;</span> <span class="k">else</span> <span class="mi">0</span> <span class="k">for</span> <span class="n">i</span> <span class="ow">in</span> <span class="n">df</span><span class="p">[</span><span class="s1">&#39;loan_status&#39;</span><span class="p">]]</span>

<span class="n">df</span><span class="p">[</span><span class="s1">&#39;TARGET&#39;</span><span class="p">]</span> <span class="o">=</span> <span class="n">target_list</span>
<span class="n">df</span><span class="p">[</span><span class="s1">&#39;TARGET&#39;</span><span class="p">]</span><span class="o">.</span><span class="n">value_counts</span><span class="p">()</span>
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<pre>0    886160
1      1219
Name: TARGET, dtype: int64</pre>
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<p>From the above output we can clearly see that this is the case of imbalance class problem where the value of class is far less than the other. There are cost function based approaches and sampling based approaches for handling this kind of problem which we will use later so that our model doesn't exhibit high bias while trying to predict if a loan will default or not. Now since we have modified the targer variable we will drop the loan_status variable</p>

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<div class=" highlight hl-ipython3"><pre><span></span><span class="n">df</span><span class="o">.</span><span class="n">drop</span><span class="p">(</span><span class="s1">&#39;loan_status&#39;</span><span class="p">,</span><span class="n">axis</span><span class="o">=</span><span class="mi">1</span><span class="p">,</span><span class="n">inplace</span><span class="o">=</span><span class="kc">True</span><span class="p">)</span>
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<p>Now let us visualize the datatypes that we will be working with</p>

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<div class=" highlight hl-ipython3"><pre><span></span><span class="n">df</span><span class="o">.</span><span class="n">dtypes</span><span class="o">.</span><span class="n">value_counts</span><span class="p">()</span><span class="o">.</span><span class="n">sort_values</span><span class="p">()</span><span class="o">.</span><span class="n">plot</span><span class="p">(</span><span class="n">kind</span><span class="o">=</span><span class="s1">&#39;barh&#39;</span><span class="p">)</span>
<span class="n">plt</span><span class="o">.</span><span class="n">title</span><span class="p">(</span><span class="s1">&#39;Number of columns distributed by Data Types&#39;</span><span class="p">,</span><span class="n">fontsize</span><span class="o">=</span><span class="mi">20</span><span class="p">)</span>
<span class="n">plt</span><span class="o">.</span><span class="n">xlabel</span><span class="p">(</span><span class="s1">&#39;Number of columns&#39;</span><span class="p">,</span><span class="n">fontsize</span><span class="o">=</span><span class="mi">15</span><span class="p">)</span>
<span class="n">plt</span><span class="o">.</span><span class="n">ylabel</span><span class="p">(</span><span class="s1">&#39;Data type&#39;</span><span class="p">,</span><span class="n">fontsize</span><span class="o">=</span><span class="mi">15</span><span class="p">)</span>
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<pre>Text(0,0.5,&#39;Data type&#39;)</pre>
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>
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<p>After looking at the above distribution we can say that there are quite a number of columns that have object as the datatype which will impose problem while modelling</p>

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<div class="prompt input_prompt">In&nbsp;[77]:</div>
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<div class=" highlight hl-ipython3"><pre><span></span><span class="n">df</span><span class="o">.</span><span class="n">select_dtypes</span><span class="p">(</span><span class="s1">&#39;object&#39;</span><span class="p">)</span><span class="o">.</span><span class="n">apply</span><span class="p">(</span><span class="n">pd</span><span class="o">.</span><span class="n">Series</span><span class="o">.</span><span class="n">nunique</span><span class="p">,</span> <span class="n">axis</span> <span class="o">=</span> <span class="mi">0</span><span class="p">)</span>
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<pre>grade                             7
sub_grade                        35
emp_title                    299271
emp_length                       11
home_ownership                    6
verification_status               3
issue_d                         103
url                          887379
desc                         124469
purpose                          14
title                         63144
zip_code                        935
addr_state                       51
earliest_cr_line                697
last_pymnt_d                     98
next_pymnt_d                    100
last_credit_pull_d              103
verification_status_joint         3
dtype: int64</pre>
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<p>We would want to label encode the columns having only 2 categorical data and one-hot encode columns with more than 2 categorical data. Also, columns like emp_title, url, desc, etc. should be dropped because there aren't any large number of unique data for any of the categories they contain. Also, Principal Component Analysis can be carried out for the one-hot encoded columns to bring the feature dimensions down.</p>

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<h1 id="Anomaly-Detection">Anomaly Detection<a class="anchor-link" href="#Anomaly-Detection">&#182;</a></h1>
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<div class=" highlight hl-ipython3"><pre><span></span><span class="n">df</span><span class="p">[</span><span class="s1">&#39;emp_length&#39;</span><span class="p">]</span><span class="o">.</span><span class="n">isnull</span><span class="p">()</span><span class="o">.</span><span class="n">sum</span><span class="p">()</span>
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<pre>44825</pre>
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<div class=" highlight hl-ipython3"><pre><span></span><span class="n">df</span><span class="p">[</span><span class="s1">&#39;emp_length&#39;</span><span class="p">]</span><span class="o">.</span><span class="n">value_counts</span><span class="p">()</span>
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<pre>10+ years    291569
2 years       78870
&lt; 1 year      70605
3 years       70026
1 year        57095
5 years       55704
4 years       52529
7 years       44594
8 years       43955
6 years       42950
9 years       34657
Name: emp_length, dtype: int64</pre>
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<p>Filling na values with 0 and fiotering numbers in place of year using a regular expression to extract the mumbers from a string</p>

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<div class=" highlight hl-ipython3"><pre><span></span><span class="n">df</span><span class="p">[</span><span class="s1">&#39;emp_length&#39;</span><span class="p">]</span><span class="o">.</span><span class="n">fillna</span><span class="p">(</span><span class="n">value</span><span class="o">=</span><span class="mi">0</span><span class="p">,</span><span class="n">inplace</span><span class="o">=</span><span class="kc">True</span><span class="p">)</span>

<span class="n">df</span><span class="p">[</span><span class="s1">&#39;emp_length&#39;</span><span class="p">]</span><span class="o">.</span><span class="n">replace</span><span class="p">(</span><span class="n">to_replace</span><span class="o">=</span><span class="s1">&#39;[^0-9]+&#39;</span><span class="p">,</span> <span class="n">value</span><span class="o">=</span><span class="s1">&#39;&#39;</span><span class="p">,</span> <span class="n">inplace</span><span class="o">=</span><span class="kc">True</span><span class="p">,</span> <span class="n">regex</span><span class="o">=</span><span class="kc">True</span><span class="p">)</span>
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<p>Checking the null values in the emp_length variable again to verify that there are no null values in the column</p>

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<div class=" highlight hl-ipython3"><pre><span></span><span class="n">df</span><span class="p">[</span><span class="s1">&#39;emp_length&#39;</span><span class="p">]</span><span class="o">.</span><span class="n">isnull</span><span class="p">()</span><span class="o">.</span><span class="n">sum</span><span class="p">()</span>
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<pre>0</pre>
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<div class=" highlight hl-ipython3"><pre><span></span><span class="n">df</span><span class="p">[</span><span class="s1">&#39;emp_length&#39;</span><span class="p">]</span><span class="o">.</span><span class="n">value_counts</span><span class="p">()</span>
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<pre>10    291569
1     127700
2      78870
3      70026
5      55704
4      52529
0      44825
7      44594
8      43955
6      42950
9      34657
Name: emp_length, dtype: int64</pre>
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<div class=" highlight hl-ipython3"><pre><span></span><span class="n">df</span><span class="p">[</span><span class="s1">&#39;emp_length&#39;</span><span class="p">]</span><span class="o">.</span><span class="n">value_counts</span><span class="p">()</span><span class="o">.</span><span class="n">sort_values</span><span class="p">()</span><span class="o">.</span><span class="n">plot</span><span class="p">(</span><span class="n">kind</span><span class="o">=</span><span class="s1">&#39;barh&#39;</span><span class="p">,</span><span class="n">figsize</span><span class="o">=</span><span class="p">(</span><span class="mi">18</span><span class="p">,</span><span class="mi">8</span><span class="p">))</span>
<span class="n">plt</span><span class="o">.</span><span class="n">title</span><span class="p">(</span><span class="s1">&#39;Number of loans distributed by Employment Years&#39;</span><span class="p">,</span><span class="n">fontsize</span><span class="o">=</span><span class="mi">20</span><span class="p">)</span>
<span class="n">plt</span><span class="o">.</span><span class="n">xlabel</span><span class="p">(</span><span class="s1">&#39;Number of loans&#39;</span><span class="p">,</span><span class="n">fontsize</span><span class="o">=</span><span class="mi">15</span><span class="p">)</span>
<span class="n">plt</span><span class="o">.</span><span class="n">ylabel</span><span class="p">(</span><span class="s1">&#39;Years worked&#39;</span><span class="p">,</span><span class="n">fontsize</span><span class="o">=</span><span class="mi">15</span><span class="p">);</span>
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<p>The column looks fine. Also, it can be seen that people who have worked for 10 or more years are more likely to take a loan.</p>

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<div class="prompt input_prompt">In&nbsp;[85]:</div>
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<div class=" highlight hl-ipython3"><pre><span></span><span class="n">fig</span> <span class="o">=</span> <span class="n">plt</span><span class="o">.</span><span class="n">figure</span><span class="p">(</span><span class="n">figsize</span><span class="o">=</span><span class="p">(</span><span class="mi">12</span><span class="p">,</span><span class="mi">6</span><span class="p">))</span>
<span class="n">sns</span><span class="o">.</span><span class="n">violinplot</span><span class="p">(</span><span class="n">x</span><span class="o">=</span><span class="s2">&quot;TARGET&quot;</span><span class="p">,</span><span class="n">y</span><span class="o">=</span><span class="s2">&quot;loan_amnt&quot;</span><span class="p">,</span><span class="n">data</span><span class="o">=</span><span class="n">df</span><span class="p">,</span> <span class="n">hue</span><span class="o">=</span><span class="s2">&quot;pymnt_plan&quot;</span><span class="p">,</span> <span class="n">split</span><span class="o">=</span><span class="kc">True</span><span class="p">)</span>
<span class="n">plt</span><span class="o">.</span><span class="n">title</span><span class="p">(</span><span class="s2">&quot;Payment plan - Loan Amount&quot;</span><span class="p">,</span> <span class="n">fontsize</span><span class="o">=</span><span class="mi">20</span><span class="p">)</span>
<span class="n">plt</span><span class="o">.</span><span class="n">xlabel</span><span class="p">(</span><span class="s2">&quot;TARGET&quot;</span><span class="p">,</span> <span class="n">fontsize</span><span class="o">=</span><span class="mi">15</span><span class="p">)</span>
<span class="n">plt</span><span class="o">.</span><span class="n">ylabel</span><span class="p">(</span><span class="s2">&quot;Loan Amount&quot;</span><span class="p">,</span> <span class="n">fontsize</span><span class="o">=</span><span class="mi">15</span><span class="p">);</span>
</pre></div>

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<p>Naturally, the defaulted loans had no payment plan</p>

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<h1 id="Exploratory-Data-Analysis">Exploratory Data Analysis<a class="anchor-link" href="#Exploratory-Data-Analysis">&#182;</a></h1><p>Let us remove all the columns with more than 70% missing data as they won't be helping for modelling and exploration.</p>

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<div class=" highlight hl-ipython3"><pre><span></span><span class="c1">#Storing TRUE if the count of that column is less than 70%</span>
<span class="n">temp</span> <span class="o">=</span> <span class="p">[</span><span class="n">i</span> <span class="k">for</span> <span class="n">i</span> <span class="ow">in</span> <span class="n">df</span><span class="o">.</span><span class="n">count</span><span class="p">()</span><span class="o">&lt;</span><span class="mi">887379</span> <span class="o">*</span><span class="mf">0.30</span><span class="p">]</span> 
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<div class=" highlight hl-ipython3"><pre><span></span><span class="c1">#Dropping the columns that have more than 70% of na values</span>
<span class="n">df</span><span class="o">.</span><span class="n">drop</span><span class="p">(</span><span class="n">df</span><span class="o">.</span><span class="n">columns</span><span class="p">[</span><span class="n">temp</span><span class="p">],</span><span class="n">axis</span><span class="o">=</span><span class="mi">1</span><span class="p">,</span><span class="n">inplace</span><span class="o">=</span><span class="kc">True</span><span class="p">)</span>
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<div class=" highlight hl-ipython3"><pre><span></span><span class="c1">#Finding the correlation of Target Vlaues and then sorting the correlation -1 to 1 </span>
<span class="n">corr</span> <span class="o">=</span> <span class="n">df</span><span class="o">.</span><span class="n">corr</span><span class="p">()[</span><span class="s1">&#39;TARGET&#39;</span><span class="p">]</span><span class="o">.</span><span class="n">sort_values</span><span class="p">()</span>
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<p>Let us now display the strong correlations between the targer variable and the columns that we found after filtering them</p>

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<div class=" highlight hl-ipython3"><pre><span></span><span class="c1">#Displaying the correlations</span>
<span class="nb">print</span><span class="p">(</span><span class="s1">&#39;Most Positive Correlations:</span><span class="se">\n</span><span class="s1">&#39;</span><span class="p">,</span> <span class="n">corr</span><span class="o">.</span><span class="n">tail</span><span class="p">(</span><span class="mi">10</span><span class="p">))</span>
<span class="nb">print</span><span class="p">(</span><span class="s1">&#39;</span><span class="se">\n</span><span class="s1">Most Negative Correlations:</span><span class="se">\n</span><span class="s1">&#39;</span><span class="p">,</span> <span class="n">corr</span><span class="o">.</span><span class="n">head</span><span class="p">(</span><span class="mi">10</span><span class="p">))</span>
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<pre>Most Positive Correlations:
 revol_util            0.004831
inq_last_6mths        0.006042
term                  0.009178
total_rec_int         0.010490
total_rec_late_fee    0.011758
out_prncp             0.013938
out_prncp_inv         0.013944
int_rate              0.024485
TARGET                1.000000
policy_code                NaN
Name: TARGET, dtype: float64

Most Negative Correlations:
 last_pymnt_amnt    -0.013132
total_rec_prncp    -0.012085
id                 -0.010041
member_id          -0.009836
total_pymnt        -0.007590
total_pymnt_inv    -0.007448
tot_cur_bal        -0.007036
annual_inc         -0.004743
total_rev_hi_lim   -0.004729
recoveries         -0.004157
Name: TARGET, dtype: float64
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<p>Besides from the perfect correlation of TARGET column with itself, columns like int_rate which is interest rate, out_prncp_inv which is remaining outstanding principal, etc. have high positive correlation with the TARGET column and these are quite true as higher the interest rate, higher it is harder for a borrower to pay back a loan. However, columns like out_prncp_inv, out_prncp, total_rec_int, total_rec_late_fee, inq_last_6mths and revol_util are bound to be higher when a borrower doesn't pay back a loan and thus doesn't carry much significance. So, the column of interest after int_rate could be the dti which is the Debt to Income ratio which understandably will affect if a borrower can pay back a loan or not.</p>
<p>Also, columns like recoveries, total_rev_hi_lim, etc. have negative correlation with the TARGET column as a borrower who has paid back money is more likely to repay the loan.</p>

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<p>Now we will examine debt to income ratio and interest rate against target variable</p>

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<div class=" highlight hl-ipython3"><pre><span></span><span class="n">df</span><span class="o">.</span><span class="n">corr</span><span class="p">()[</span><span class="s1">&#39;dti&#39;</span><span class="p">]</span><span class="o">.</span><span class="n">sort_values</span><span class="p">()</span><span class="o">.</span><span class="n">tail</span><span class="p">(</span><span class="mi">6</span><span class="p">)</span>
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<pre>int_rate       0.079903
revol_util     0.087844
total_acc      0.108056
open_acc       0.144250
dti            1.000000
policy_code         NaN
Name: dti, dtype: float64</pre>
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<p>We can conclude from the above output that higher the debt to income ratio higher will be the interest rate i.e it is positively correlated with dti ratio</p>

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<p>Now, we shall plot some Kernal Density Estimation plots to see how the interest rate  and debt to income ratio are ddistributed for the Target variable</p>

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<div class=" highlight hl-ipython3"><pre><span></span><span class="n">fig</span> <span class="o">=</span> <span class="n">plt</span><span class="o">.</span><span class="n">figure</span><span class="p">(</span><span class="n">figsize</span><span class="o">=</span><span class="p">(</span><span class="mi">22</span><span class="p">,</span><span class="mi">6</span><span class="p">))</span>
<span class="n">sns</span><span class="o">.</span><span class="n">kdeplot</span><span class="p">(</span><span class="n">df</span><span class="o">.</span><span class="n">loc</span><span class="p">[</span><span class="n">df</span><span class="p">[</span><span class="s1">&#39;TARGET&#39;</span><span class="p">]</span> <span class="o">==</span> <span class="mi">1</span><span class="p">,</span> <span class="s1">&#39;int_rate&#39;</span><span class="p">],</span> <span class="n">label</span> <span class="o">=</span> <span class="s1">&#39;target = 1&#39;</span><span class="p">)</span>
<span class="n">sns</span><span class="o">.</span><span class="n">kdeplot</span><span class="p">(</span><span class="n">df</span><span class="o">.</span><span class="n">loc</span><span class="p">[</span><span class="n">df</span><span class="p">[</span><span class="s1">&#39;TARGET&#39;</span><span class="p">]</span> <span class="o">==</span> <span class="mi">0</span><span class="p">,</span> <span class="s1">&#39;int_rate&#39;</span><span class="p">],</span> <span class="n">label</span> <span class="o">=</span> <span class="s1">&#39;target = 0&#39;</span><span class="p">);</span>
<span class="n">plt</span><span class="o">.</span><span class="n">xlabel</span><span class="p">(</span><span class="s1">&#39;Interest Rate (%)&#39;</span><span class="p">,</span><span class="n">fontsize</span><span class="o">=</span><span class="mi">15</span><span class="p">)</span>
<span class="n">plt</span><span class="o">.</span><span class="n">ylabel</span><span class="p">(</span><span class="s1">&#39;Density&#39;</span><span class="p">,</span><span class="n">fontsize</span><span class="o">=</span><span class="mi">15</span><span class="p">)</span>
<span class="n">plt</span><span class="o">.</span><span class="n">title</span><span class="p">(</span><span class="s1">&#39;Distribution of Interest Rate&#39;</span><span class="p">,</span><span class="n">fontsize</span><span class="o">=</span><span class="mi">20</span><span class="p">);</span>
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<p>Here by looking at the above kernal density plots we can say that interest rate follow kind of Gaussian distribution with more density rates between 12-18%</p>
<h3 id="Violin-plot-of-TARGET-classes-with-distribution-of-loan-amount-differentiated-by-the-terms.">Violin-plot of TARGET classes with distribution of loan amount differentiated by the terms.<a class="anchor-link" href="#Violin-plot-of-TARGET-classes-with-distribution-of-loan-amount-differentiated-by-the-terms.">&#182;</a></h3>
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<div class=" highlight hl-ipython3"><pre><span></span><span class="n">df</span><span class="p">[</span><span class="s2">&quot;term&quot;</span><span class="p">]</span><span class="o">.</span><span class="n">unique</span><span class="p">()</span>
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<pre>array([0, 1], dtype=int64)</pre>
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<div class=" highlight hl-ipython3"><pre><span></span><span class="n">fig</span> <span class="o">=</span> <span class="n">plt</span><span class="o">.</span><span class="n">figure</span><span class="p">(</span><span class="n">figsize</span><span class="o">=</span><span class="p">(</span><span class="mi">12</span><span class="p">,</span><span class="mi">6</span><span class="p">))</span>
<span class="n">sns</span><span class="o">.</span><span class="n">violinplot</span><span class="p">(</span><span class="n">x</span><span class="o">=</span><span class="s2">&quot;TARGET&quot;</span><span class="p">,</span> <span class="n">y</span><span class="o">=</span><span class="s2">&quot;loan_amnt&quot;</span><span class="p">,</span> <span class="n">data</span><span class="o">=</span><span class="n">df</span><span class="p">,</span> <span class="n">hue</span><span class="o">=</span><span class="s2">&quot;term&quot;</span><span class="p">,</span> <span class="n">split</span><span class="o">=</span><span class="kc">True</span><span class="p">,</span> <span class="n">color</span><span class="o">=</span><span class="s1">&#39;pink&#39;</span><span class="p">)</span>
<span class="n">plt</span><span class="o">.</span><span class="n">title</span><span class="p">(</span><span class="s2">&quot;Term - Loan Amount&quot;</span><span class="p">,</span> <span class="n">fontsize</span><span class="o">=</span><span class="mi">20</span><span class="p">)</span>
<span class="n">plt</span><span class="o">.</span><span class="n">xlabel</span><span class="p">(</span><span class="s2">&quot;TARGET&quot;</span><span class="p">,</span> <span class="n">fontsize</span><span class="o">=</span><span class="mi">15</span><span class="p">)</span>
<span class="n">plt</span><span class="o">.</span><span class="n">ylabel</span><span class="p">(</span><span class="s2">&quot;Loan Amount&quot;</span><span class="p">,</span> <span class="n">fontsize</span><span class="o">=</span><span class="mi">15</span><span class="p">);</span>
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<p>From the above visualization we can say that higher the term higher is the loan amount</p>
<h3 id="Violin-plot-of-TARGET-classes-with-distribution-of-loan-amount-differentiated-by-the-application-type.">Violin-plot of TARGET classes with distribution of loan amount differentiated by the application type.<a class="anchor-link" href="#Violin-plot-of-TARGET-classes-with-distribution-of-loan-amount-differentiated-by-the-application-type.">&#182;</a></h3>
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<div class="prompt input_prompt">In&nbsp;[94]:</div>
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<div class=" highlight hl-ipython3"><pre><span></span><span class="n">df</span><span class="p">[</span><span class="s2">&quot;application_type&quot;</span><span class="p">]</span><span class="o">.</span><span class="n">unique</span><span class="p">()</span>
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<pre>array([0, 1], dtype=int64)</pre>
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<p>Since we have 2 types of the application lets have a look at the distribution of loan amount for target variable with application type</p>

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<div class=" highlight hl-ipython3"><pre><span></span><span class="n">fig</span> <span class="o">=</span> <span class="n">plt</span><span class="o">.</span><span class="n">figure</span><span class="p">(</span><span class="n">figsize</span><span class="o">=</span><span class="p">(</span><span class="mi">12</span><span class="p">,</span><span class="mi">6</span><span class="p">))</span>
<span class="n">sns</span><span class="o">.</span><span class="n">violinplot</span><span class="p">(</span><span class="n">x</span><span class="o">=</span><span class="s2">&quot;TARGET&quot;</span><span class="p">,</span> <span class="n">y</span><span class="o">=</span><span class="s2">&quot;loan_amnt&quot;</span><span class="p">,</span> <span class="n">data</span><span class="o">=</span><span class="n">df</span><span class="p">,</span> <span class="n">hue</span><span class="o">=</span><span class="s2">&quot;application_type&quot;</span><span class="p">,</span> <span class="n">split</span><span class="o">=</span><span class="kc">True</span><span class="p">,</span> <span class="n">color</span><span class="o">=</span><span class="s2">&quot;green&quot;</span><span class="p">)</span>
<span class="n">plt</span><span class="o">.</span><span class="n">title</span><span class="p">(</span><span class="s2">&quot;Application Type - Loan Amount&quot;</span><span class="p">,</span> <span class="n">fontsize</span><span class="o">=</span><span class="mi">20</span><span class="p">)</span>
<span class="n">plt</span><span class="o">.</span><span class="n">xlabel</span><span class="p">(</span><span class="s2">&quot;TARGET&quot;</span><span class="p">,</span> <span class="n">fontsize</span><span class="o">=</span><span class="mi">15</span><span class="p">)</span>
<span class="n">plt</span><span class="o">.</span><span class="n">ylabel</span><span class="p">(</span><span class="s2">&quot;Loan Amount&quot;</span><span class="p">,</span> <span class="n">fontsize</span><span class="o">=</span><span class="mi">15</span><span class="p">);</span>
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<p>From the above violin plot we can say that all the loans that have been defaulted are from individuals rather than from two or more people</p>

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<div class=" highlight hl-ipython3"><pre><span></span><span class="n">df</span><span class="p">[</span><span class="s1">&#39;application_type&#39;</span><span class="p">]</span><span class="o">.</span><span class="n">value_counts</span><span class="p">()</span>
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<pre>0    886868
1       511
Name: application_type, dtype: int64</pre>
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<p>Also after seeing the number of count for application type we cant really infer that joint application status are completely safe from default loan status i.e  it isn't significant enough to conclude that the loan taken by all Joint applicants are paid back.</p>

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<h3 id="Violin-plot-of-TARGET-classes-with-distribution-of-interest-rate-differentiated-by-the-loan-grades">Violin-plot of TARGET classes with distribution of interest rate differentiated by the loan grades<a class="anchor-link" href="#Violin-plot-of-TARGET-classes-with-distribution-of-interest-rate-differentiated-by-the-loan-grades">&#182;</a></h3>
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<div class=" highlight hl-ipython3"><pre><span></span><span class="n">df</span><span class="p">[</span><span class="s2">&quot;grade&quot;</span><span class="p">]</span><span class="o">.</span><span class="n">value_counts</span><span class="p">()</span>
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<pre>B    254535
C    245860
A    148202
D    139542
E     70705
F     23046
G      5489
Name: grade, dtype: int64</pre>
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<div class=" highlight hl-ipython3"><pre><span></span><span class="n">fig</span> <span class="o">=</span> <span class="n">plt</span><span class="o">.</span><span class="n">figure</span><span class="p">(</span><span class="n">figsize</span><span class="o">=</span><span class="p">(</span><span class="mi">18</span><span class="p">,</span><span class="mi">8</span><span class="p">))</span>
<span class="n">sns</span><span class="o">.</span><span class="n">violinplot</span><span class="p">(</span><span class="n">x</span><span class="o">=</span><span class="s2">&quot;TARGET&quot;</span><span class="p">,</span><span class="n">y</span><span class="o">=</span><span class="s2">&quot;int_rate&quot;</span><span class="p">,</span><span class="n">data</span><span class="o">=</span><span class="n">df</span><span class="p">,</span> <span class="n">hue</span><span class="o">=</span><span class="s2">&quot;grade&quot;</span><span class="p">)</span>
<span class="n">plt</span><span class="o">.</span><span class="n">title</span><span class="p">(</span><span class="s2">&quot;Grade - Interest Rate&quot;</span><span class="p">,</span> <span class="n">fontsize</span><span class="o">=</span><span class="mi">20</span><span class="p">)</span>
<span class="n">plt</span><span class="o">.</span><span class="n">xlabel</span><span class="p">(</span><span class="s2">&quot;TARGET&quot;</span><span class="p">,</span> <span class="n">fontsize</span><span class="o">=</span><span class="mi">15</span><span class="p">)</span>
<span class="n">plt</span><span class="o">.</span><span class="n">ylabel</span><span class="p">(</span><span class="s2">&quot;Interest Rate&quot;</span><span class="p">,</span> <span class="n">fontsize</span><span class="o">=</span><span class="mi">15</span><span class="p">);</span>
</pre></div>

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<p>We can say that both target classes have similar kind of interest rates by grades.</p>

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<p>Let us also check the correlation of annual income with loan amount taken.</p>

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<div class=" highlight hl-ipython3"><pre><span></span><span class="n">df</span><span class="o">.</span><span class="n">corr</span><span class="p">()[</span><span class="s1">&#39;annual_inc&#39;</span><span class="p">]</span><span class="o">.</span><span class="n">sort_values</span><span class="p">()</span><span class="o">.</span><span class="n">tail</span><span class="p">(</span><span class="mi">10</span><span class="p">)</span>
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<pre>out_prncp_inv       0.211254
total_rev_hi_lim    0.268860
revol_bal           0.295784
installment         0.326182
funded_amnt_inv     0.331420
funded_amnt         0.332466
loan_amnt           0.332698
tot_cur_bal         0.418332
annual_inc          1.000000
policy_code              NaN
Name: annual_inc, dtype: float64</pre>
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<p>The annual income of the applicant has high positive correlation with the amount of loan they have taken.</p>

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<h3 id="From-where-do-most-of-the-loans-tend-to-be-defaulted?">From where do most of the loans tend to be defaulted?<a class="anchor-link" href="#From-where-do-most-of-the-loans-tend-to-be-defaulted?">&#182;</a></h3>
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<div class=" highlight hl-ipython3"><pre><span></span><span class="n">fig</span> <span class="o">=</span> <span class="n">plt</span><span class="o">.</span><span class="n">figure</span><span class="p">(</span><span class="n">figsize</span><span class="o">=</span><span class="p">(</span><span class="mi">18</span><span class="p">,</span><span class="mi">10</span><span class="p">))</span>
<span class="n">df</span><span class="p">[</span><span class="n">df</span><span class="p">[</span><span class="s1">&#39;TARGET&#39;</span><span class="p">]</span><span class="o">==</span><span class="mi">1</span><span class="p">]</span><span class="o">.</span><span class="n">groupby</span><span class="p">(</span><span class="s1">&#39;addr_state&#39;</span><span class="p">)[</span><span class="s1">&#39;TARGET&#39;</span><span class="p">]</span><span class="o">.</span><span class="n">count</span><span class="p">()</span><span class="o">.</span><span class="n">sort_values</span><span class="p">()</span><span class="o">.</span><span class="n">plot</span><span class="p">(</span><span class="n">kind</span><span class="o">=</span><span class="s1">&#39;barh&#39;</span><span class="p">)</span>
<span class="n">plt</span><span class="o">.</span><span class="n">ylabel</span><span class="p">(</span><span class="s1">&#39;State&#39;</span><span class="p">,</span><span class="n">fontsize</span><span class="o">=</span><span class="mi">15</span><span class="p">)</span>
<span class="n">plt</span><span class="o">.</span><span class="n">xlabel</span><span class="p">(</span><span class="s1">&#39;Number of loans&#39;</span><span class="p">,</span><span class="n">fontsize</span><span class="o">=</span><span class="mi">15</span><span class="p">)</span>
<span class="n">plt</span><span class="o">.</span><span class="n">title</span><span class="p">(</span><span class="s1">&#39;Number of defaulted loans per state&#39;</span><span class="p">,</span><span class="n">fontsize</span><span class="o">=</span><span class="mi">20</span><span class="p">);</span>
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<div class="prompt input_prompt">In&nbsp;[101]:</div>
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<div class=" highlight hl-ipython3"><pre><span></span><span class="n">fig</span> <span class="o">=</span> <span class="n">plt</span><span class="o">.</span><span class="n">figure</span><span class="p">(</span><span class="n">figsize</span><span class="o">=</span><span class="p">(</span><span class="mi">18</span><span class="p">,</span><span class="mi">10</span><span class="p">))</span>
<span class="n">df</span><span class="p">[</span><span class="n">df</span><span class="p">[</span><span class="s1">&#39;TARGET&#39;</span><span class="p">]</span><span class="o">==</span><span class="mi">0</span><span class="p">]</span><span class="o">.</span><span class="n">groupby</span><span class="p">(</span><span class="s1">&#39;addr_state&#39;</span><span class="p">)[</span><span class="s1">&#39;TARGET&#39;</span><span class="p">]</span><span class="o">.</span><span class="n">count</span><span class="p">()</span><span class="o">.</span><span class="n">sort_values</span><span class="p">()</span><span class="o">.</span><span class="n">plot</span><span class="p">(</span><span class="n">kind</span><span class="o">=</span><span class="s1">&#39;barh&#39;</span><span class="p">)</span>
<span class="n">plt</span><span class="o">.</span><span class="n">ylabel</span><span class="p">(</span><span class="s1">&#39;State&#39;</span><span class="p">)</span>
<span class="n">plt</span><span class="o">.</span><span class="n">xlabel</span><span class="p">(</span><span class="s1">&#39;Number of loans&#39;</span><span class="p">)</span>
<span class="n">plt</span><span class="o">.</span><span class="n">title</span><span class="p">(</span><span class="s1">&#39;Number of not-defaulted loans per state&#39;</span><span class="p">);</span>
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<p>It can be seen that there are more number of loans taken amount from the same states where there are more number of defaulted risk. This is why the state cannot be taken as a major feature for knowing if a loan will be defaulted or not.</p>

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<p>Let's see if we have any members taking multiple loans.</p>

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<div class="prompt input_prompt">In&nbsp;[102]:</div>
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<div class=" highlight hl-ipython3"><pre><span></span><span class="n">df</span><span class="p">[</span><span class="s1">&#39;member_id&#39;</span><span class="p">]</span><span class="o">.</span><span class="n">value_counts</span><span class="p">()</span><span class="o">.</span><span class="n">head</span><span class="p">(</span><span class="mi">2</span><span class="p">)</span>
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<pre>58732538    1
353782      1
Name: member_id, dtype: int64</pre>
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<p>From the results above we can state that not a single member has taken loan more than once thus we can drop the column</p>

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<h2 id="Cleaning-the-data">Cleaning the data<a class="anchor-link" href="#Cleaning-the-data">&#182;</a></h2>
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<p>As we had observe, some columns like annual_inc, int_rate, etc. may be much useful for building our model but on the other hand, some columns like id, member_id, etc. will not be helping.</p>
<p>Also, columns like 'title' and 'emp_title' are text which cannot be one-hot encoded / label encoded as they have arbitrary categorical text and very less unique data for each of their categories.</p>

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<div class=" highlight hl-ipython3"><pre><span></span><span class="n">df</span><span class="p">[</span><span class="s1">&#39;emp_title&#39;</span><span class="p">]</span><span class="o">.</span><span class="n">value_counts</span><span class="p">()</span><span class="o">.</span><span class="n">head</span><span class="p">()</span>
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<pre>Teacher             13469
Manager             11240
Registered Nurse     5525
Owner                5376
RN                   5355
Name: emp_title, dtype: int64</pre>
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<div class=" highlight hl-ipython3"><pre><span></span><span class="n">df</span><span class="o">.</span><span class="n">drop</span><span class="p">([</span><span class="s1">&#39;id&#39;</span><span class="p">,</span><span class="s1">&#39;member_id&#39;</span><span class="p">,</span><span class="s1">&#39;emp_title&#39;</span><span class="p">,</span><span class="s1">&#39;title&#39;</span><span class="p">,</span><span class="s1">&#39;zip_code&#39;</span><span class="p">,</span><span class="s1">&#39;url&#39;</span><span class="p">],</span><span class="n">axis</span><span class="o">=</span><span class="mi">1</span><span class="p">,</span><span class="n">inplace</span><span class="o">=</span><span class="kc">True</span><span class="p">)</span>
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<pre>(887379, 48)</pre>
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<p>Now we have reduced the data to 48 columns.Let's print them out to get a quick look of what we are dealing with,</p>

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<div class=" highlight hl-ipython3"><pre><span></span><span class="n">df</span><span class="o">.</span><span class="n">info</span><span class="p">()</span>
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<pre>&lt;class &#39;pandas.core.frame.DataFrame&#39;&gt;
RangeIndex: 887379 entries, 0 to 887378
Data columns (total 48 columns):
loan_amnt                     887379 non-null float64
funded_amnt                   887379 non-null float64
funded_amnt_inv               887379 non-null float64
term                          887379 non-null int64
int_rate                      887379 non-null float64
installment                   887379 non-null float64
grade                         887379 non-null object
sub_grade                     887379 non-null object
emp_length                    887379 non-null object
home_ownership                887379 non-null object
annual_inc                    887375 non-null float64
verification_status           887379 non-null object
issue_d                       887379 non-null object
pymnt_plan                    887379 non-null int64
purpose                       887379 non-null object
addr_state                    887379 non-null object
dti                           887379 non-null float64
delinq_2yrs                   887350 non-null float64
earliest_cr_line              887350 non-null object
inq_last_6mths                887350 non-null float64
mths_since_last_delinq        433067 non-null float64
open_acc                      887350 non-null float64
pub_rec                       887350 non-null float64
revol_bal                     887379 non-null float64
revol_util                    886877 non-null float64
total_acc                     887350 non-null float64
initial_list_status           887379 non-null int64
out_prncp                     887379 non-null float64
out_prncp_inv                 887379 non-null float64
total_pymnt                   887379 non-null float64
total_pymnt_inv               887379 non-null float64
total_rec_prncp               887379 non-null float64
total_rec_int                 887379 non-null float64
total_rec_late_fee            887379 non-null float64
recoveries                    887379 non-null float64
collection_recovery_fee       887379 non-null float64
last_pymnt_d                  869720 non-null object
last_pymnt_amnt               887379 non-null float64
next_pymnt_d                  634408 non-null object
last_credit_pull_d            887326 non-null object
collections_12_mths_ex_med    887234 non-null float64
policy_code                   887379 non-null float64
application_type              887379 non-null int64
acc_now_delinq                887350 non-null float64
tot_coll_amt                  817103 non-null float64
tot_cur_bal                   817103 non-null float64
total_rev_hi_lim              817103 non-null float64
TARGET                        887379 non-null int64
dtypes: float64(31), int64(5), object(12)
memory usage: 325.0+ MB
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<div class=" highlight hl-ipython3"><pre><span></span><span class="n">df</span><span class="o">.</span><span class="n">loc</span><span class="p">[:,(</span><span class="s1">&#39;issue_d&#39;</span><span class="p">,</span><span class="s1">&#39;TARGET&#39;</span><span class="p">)]</span><span class="o">.</span><span class="n">head</span><span class="p">(</span><span class="mi">10</span><span class="p">)</span>
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<div>
<style scoped>
    .dataframe tbody tr th:only-of-type {
        vertical-align: middle;
    }

    .dataframe tbody tr th {
        vertical-align: top;
    }

    .dataframe thead th {
        text-align: right;
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</style>
<table border="1" class="dataframe">
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      <th></th>
      <th>issue_d</th>
      <th>TARGET</th>
    </tr>
  </thead>
  <tbody>
    <tr>
      <th>0</th>
      <td>Dec-2011</td>
      <td>0</td>
    </tr>
    <tr>
      <th>1</th>
      <td>Dec-2011</td>
      <td>0</td>
    </tr>
    <tr>
      <th>2</th>
      <td>Dec-2011</td>
      <td>0</td>
    </tr>
    <tr>
      <th>3</th>
      <td>Dec-2011</td>
      <td>0</td>
    </tr>
    <tr>
      <th>4</th>
      <td>Dec-2011</td>
      <td>0</td>
    </tr>
    <tr>
      <th>5</th>
      <td>Dec-2011</td>
      <td>0</td>
    </tr>
    <tr>
      <th>6</th>
      <td>Dec-2011</td>
      <td>0</td>
    </tr>
    <tr>
      <th>7</th>
      <td>Dec-2011</td>
      <td>0</td>
    </tr>
    <tr>
      <th>8</th>
      <td>Dec-2011</td>
      <td>0</td>
    </tr>
    <tr>
      <th>9</th>
      <td>Dec-2011</td>
      <td>0</td>
    </tr>
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<p>First, We'll be converting the date object columns into integer number of years or months just because we do not want to blow up the number of feature columns by performing one-hot encoding on them. For filling the null values we have taken the dates with the highest number of counts.</p>

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<div class=" highlight hl-ipython3"><pre><span></span><span class="c1">#Converting the field to datetime and extracting the year and storing it in Integer format</span>
<span class="n">df</span><span class="p">[</span><span class="s1">&#39;issue_d&#39;</span><span class="p">]</span><span class="o">=</span> <span class="n">pd</span><span class="o">.</span><span class="n">to_datetime</span><span class="p">(</span><span class="n">df</span><span class="p">[</span><span class="s1">&#39;issue_d&#39;</span><span class="p">])</span><span class="o">.</span><span class="n">apply</span><span class="p">(</span><span class="k">lambda</span> <span class="n">x</span><span class="p">:</span> <span class="nb">int</span><span class="p">(</span><span class="n">x</span><span class="o">.</span><span class="n">strftime</span><span class="p">(</span><span class="s1">&#39;%Y&#39;</span><span class="p">)))</span>
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<div class=" highlight hl-ipython3"><pre><span></span><span class="c1">#Printing the datatype of the column we just formatted</span>
<span class="n">df</span><span class="p">[</span><span class="s1">&#39;issue_d&#39;</span><span class="p">]</span><span class="o">.</span><span class="n">dtype</span>
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<pre>dtype(&#39;int64&#39;)</pre>
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<div class=" highlight hl-ipython3"><pre><span></span><span class="c1">#Printing the mode of lastpayment date to fill in the  na values</span>
<span class="n">pd</span><span class="o">.</span><span class="n">to_datetime</span><span class="p">(</span><span class="n">df</span><span class="p">[</span><span class="s1">&#39;last_pymnt_d&#39;</span><span class="p">])</span><span class="o">.</span><span class="n">value_counts</span><span class="p">()</span><span class="o">.</span><span class="n">head</span><span class="p">(</span><span class="mi">1</span><span class="p">)</span>
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<pre>2016-01-01    470150
Name: last_pymnt_d, dtype: int64</pre>
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<div class=" highlight hl-ipython3"><pre><span></span><span class="c1">#Printing the mode of last credit pull date to fill in the  na values</span>
<span class="n">pd</span><span class="o">.</span><span class="n">to_datetime</span><span class="p">(</span><span class="n">df</span><span class="p">[</span><span class="s1">&#39;last_credit_pull_d&#39;</span><span class="p">])</span><span class="o">.</span><span class="n">value_counts</span><span class="p">()</span><span class="o">.</span><span class="n">head</span><span class="p">(</span><span class="mi">1</span><span class="p">)</span>
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<pre>2016-01-01    730574
Name: last_credit_pull_d, dtype: int64</pre>
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<div class=" highlight hl-ipython3"><pre><span></span><span class="c1">#Printing the mode of earliest credit line date to fill in the  na values</span>
<span class="n">pd</span><span class="o">.</span><span class="n">to_datetime</span><span class="p">(</span><span class="n">df</span><span class="p">[</span><span class="s1">&#39;earliest_cr_line&#39;</span><span class="p">])</span><span class="o">.</span><span class="n">value_counts</span><span class="p">()</span><span class="o">.</span><span class="n">head</span><span class="p">(</span><span class="mi">1</span><span class="p">)</span>
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<pre>2001-08-01    6659
Name: earliest_cr_line, dtype: int64</pre>
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<div class=" highlight hl-ipython3"><pre><span></span><span class="c1">#Printing the mode of next payment date to fill in the  na values</span>
<span class="n">pd</span><span class="o">.</span><span class="n">to_datetime</span><span class="p">(</span><span class="n">df</span><span class="p">[</span><span class="s1">&#39;next_pymnt_d&#39;</span><span class="p">])</span><span class="o">.</span><span class="n">value_counts</span><span class="p">()</span><span class="o">.</span><span class="n">head</span><span class="p">(</span><span class="mi">1</span><span class="p">)</span>
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<pre>2016-02-01    553406
Name: next_pymnt_d, dtype: int64</pre>
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<div class=" highlight hl-ipython3"><pre><span></span><span class="n">df</span><span class="p">[</span><span class="s1">&#39;last_pymnt_d&#39;</span><span class="p">]</span><span class="o">=</span> <span class="n">pd</span><span class="o">.</span><span class="n">to_datetime</span><span class="p">(</span><span class="n">df</span><span class="p">[</span><span class="s1">&#39;last_pymnt_d&#39;</span><span class="p">]</span><span class="o">.</span><span class="n">fillna</span><span class="p">(</span><span class="s1">&#39;2016-01-01&#39;</span><span class="p">))</span><span class="o">.</span><span class="n">apply</span><span class="p">(</span><span class="k">lambda</span> <span class="n">x</span><span class="p">:</span> <span class="nb">int</span><span class="p">(</span><span class="n">x</span><span class="o">.</span><span class="n">strftime</span><span class="p">(</span><span class="s1">&#39;%m&#39;</span><span class="p">)))</span>
<span class="n">df</span><span class="p">[</span><span class="s1">&#39;last_credit_pull_d&#39;</span><span class="p">]</span><span class="o">=</span> <span class="n">pd</span><span class="o">.</span><span class="n">to_datetime</span><span class="p">(</span><span class="n">df</span><span class="p">[</span><span class="s1">&#39;last_credit_pull_d&#39;</span><span class="p">]</span><span class="o">.</span><span class="n">fillna</span><span class="p">(</span><span class="s2">&quot;2016-01-01&quot;</span><span class="p">))</span><span class="o">.</span><span class="n">apply</span><span class="p">(</span><span class="k">lambda</span> <span class="n">x</span><span class="p">:</span> <span class="nb">int</span><span class="p">(</span><span class="n">x</span><span class="o">.</span><span class="n">strftime</span><span class="p">(</span><span class="s1">&#39;%m&#39;</span><span class="p">)))</span>
<span class="n">df</span><span class="p">[</span><span class="s1">&#39;earliest_cr_line&#39;</span><span class="p">]</span><span class="o">=</span> <span class="n">pd</span><span class="o">.</span><span class="n">to_datetime</span><span class="p">(</span><span class="n">df</span><span class="p">[</span><span class="s1">&#39;earliest_cr_line&#39;</span><span class="p">]</span><span class="o">.</span><span class="n">fillna</span><span class="p">(</span><span class="s1">&#39;2001-08-01&#39;</span><span class="p">))</span><span class="o">.</span><span class="n">apply</span><span class="p">(</span><span class="k">lambda</span> <span class="n">x</span><span class="p">:</span> <span class="nb">int</span><span class="p">(</span><span class="n">x</span><span class="o">.</span><span class="n">strftime</span><span class="p">(</span><span class="s1">&#39;%m&#39;</span><span class="p">)))</span>
<span class="n">df</span><span class="p">[</span><span class="s1">&#39;next_pymnt_d&#39;</span><span class="p">]</span> <span class="o">=</span> <span class="n">pd</span><span class="o">.</span><span class="n">to_datetime</span><span class="p">(</span><span class="n">df</span><span class="p">[</span><span class="s1">&#39;next_pymnt_d&#39;</span><span class="p">]</span><span class="o">.</span><span class="n">fillna</span><span class="p">(</span><span class="n">value</span> <span class="o">=</span> <span class="s1">&#39;2016-02-01&#39;</span><span class="p">))</span><span class="o">.</span><span class="n">apply</span><span class="p">(</span><span class="k">lambda</span> <span class="n">x</span><span class="p">:</span><span class="nb">int</span><span class="p">(</span><span class="n">x</span><span class="o">.</span><span class="n">strftime</span><span class="p">(</span><span class="s2">&quot;%Y&quot;</span><span class="p">)))</span>
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<p>`Let's see how we can handle our categorical data. Two methods we can use are Label Encoding and One Hot Encoding.</p>
<p>The problem with label encoding is that it gives the categories an arbitrary ordering. The value assigned to each of the categories is random and does not reflect any inherent aspect of the category. So, If we only have two unique values for a categorical variable (such as Yes/No), then label encoding is fine, but for more than 2 unique categories, one-hot encoding is the better option.</p>
<p>However, due to the large number of columns originated after One-Hot Encoding, we may have to conduct Principle Component Analysis (PCA) for dimensionality reduction.</p>

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<div class=" highlight hl-ipython3"><pre><span></span><span class="kn">from</span> <span class="nn">sklearn</span> <span class="k">import</span> <span class="n">preprocessing</span>
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<div class=" highlight hl-ipython3"><pre><span></span><span class="c1">#Performing label encoding on the object datatypes with 2or less than 2 unique categories</span>
<span class="n">count</span> <span class="o">=</span> <span class="mi">0</span>

<span class="k">for</span> <span class="n">col</span> <span class="ow">in</span> <span class="n">df</span><span class="p">:</span>
    <span class="k">if</span> <span class="n">df</span><span class="p">[</span><span class="n">col</span><span class="p">]</span><span class="o">.</span><span class="n">dtype</span> <span class="o">==</span> <span class="s1">&#39;object&#39;</span><span class="p">:</span>
        <span class="k">if</span> <span class="nb">len</span><span class="p">(</span><span class="nb">list</span><span class="p">(</span><span class="n">df</span><span class="p">[</span><span class="n">col</span><span class="p">]</span><span class="o">.</span><span class="n">unique</span><span class="p">()))</span> <span class="o">&lt;=</span> <span class="mi">2</span><span class="p">:</span>     
            <span class="n">le</span> <span class="o">=</span> <span class="n">preprocessing</span><span class="o">.</span><span class="n">LabelEncoder</span><span class="p">()</span>
            <span class="n">df</span><span class="p">[</span><span class="n">col</span><span class="p">]</span> <span class="o">=</span> <span class="n">le</span><span class="o">.</span><span class="n">fit_transform</span><span class="p">(</span><span class="n">df</span><span class="p">[</span><span class="n">col</span><span class="p">])</span>
            <span class="n">count</span> <span class="o">+=</span> <span class="mi">1</span>
            <span class="nb">print</span> <span class="p">(</span><span class="n">col</span><span class="p">)</span>
            
<span class="nb">print</span><span class="p">(</span><span class="s1">&#39;</span><span class="si">%d</span><span class="s1"> columns were label encoded.&#39;</span> <span class="o">%</span> <span class="n">count</span><span class="p">)</span>
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<pre>0 columns were label encoded.
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<p>And one-hot encoding the rest categorical columns.</p>

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<div class=" highlight hl-ipython3"><pre><span></span><span class="c1">#Changing the structure of the object datatypes by performing one hot encoding</span>
<span class="n">df</span><span class="o">=</span><span class="n">pd</span><span class="o">.</span><span class="n">get_dummies</span><span class="p">(</span><span class="n">df</span><span class="p">)</span>
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<pre>(887379, 168)
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<p>For the 'mths_since_last_delinq' column, We'll be filling in the missing value with the median of the columns as the data in the column is continuous.</p>

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<div class=" highlight hl-ipython3"><pre><span></span><span class="n">df</span><span class="p">[</span><span class="s1">&#39;mths_since_last_delinq&#39;</span><span class="p">]</span> <span class="o">=</span> <span class="n">df</span><span class="p">[</span><span class="s1">&#39;mths_since_last_delinq&#39;</span><span class="p">]</span><span class="o">.</span><span class="n">fillna</span><span class="p">(</span><span class="n">df</span><span class="p">[</span><span class="s1">&#39;mths_since_last_delinq&#39;</span><span class="p">]</span><span class="o">.</span><span class="n">median</span><span class="p">())</span>
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<p>However for columns like 'total_rev_hi_lim','tot_col_ammnt',etc. , We won't be filling in the missing data because they will certainly be of high feature importance due to their description. If they do not seem to be of high importance we can always re-iterate and fill the missing values later.</p>
<p>So, dropping all remaining null values,</p>

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<div class=" highlight hl-ipython3"><pre><span></span><span class="c1">#Dropping the NA values</span>
<span class="n">df</span><span class="o">.</span><span class="n">dropna</span><span class="p">(</span><span class="n">inplace</span><span class="o">=</span><span class="kc">True</span><span class="p">)</span>
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<p>Now we check the count of the dataset</p>

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<div class=" highlight hl-ipython3"><pre><span></span><span class="c1">#Printing the count of the data in columns and printing the head of the data</span>
<span class="n">df</span><span class="o">.</span><span class="n">count</span><span class="p">()</span><span class="o">.</span><span class="n">sort_values</span><span class="p">()</span><span class="o">.</span><span class="n">head</span><span class="p">(</span><span class="mi">3</span><span class="p">)</span>
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<pre>loan_amnt                   816722
purpose_home_improvement    816722
purpose_house               816722
dtype: int64</pre>
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<div class=" highlight hl-ipython3"><pre><span></span><span class="n">df</span><span class="p">[</span><span class="s1">&#39;TARGET&#39;</span><span class="p">]</span><span class="o">.</span><span class="n">value_counts</span><span class="p">()</span>
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<pre>0    815522
1      1200
Name: TARGET, dtype: int64</pre>
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<p>We are now left with a reasonable amount of data for modelling.</p>

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<h2 id="Modeling">Modeling<a class="anchor-link" href="#Modeling">&#182;</a></h2>
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<p>Now for modelling we will be using two ensemble methods and compare them</p>
<ol>
<li>Bagging</li>
<li>Boosting</li>
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<h2 id="1)-Bagging---Random-Forest">1) Bagging - Random Forest<a class="anchor-link" href="#1)-Bagging---Random-Forest">&#182;</a></h2><p>Ensemble of Decision Trees</p>
<p>Training via the bagging method (Repeated sampling with replacement)</p>
<p>Bagging: Sample from samples
RF: Sample from predictors.  m=sqrt(p)m=sqrt(p)  for classification and  m=p/3m=p/3  for regression problems.
Utilise uncorrelated trees</p>
<p>Tmporting the required libraries for performing the algorithm</p>

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<div class=" highlight hl-ipython3"><pre><span></span><span class="kn">from</span> <span class="nn">sklearn.ensemble</span> <span class="k">import</span> <span class="n">RandomForestClassifier</span>
<span class="kn">from</span> <span class="nn">sklearn.model_selection</span> <span class="k">import</span> <span class="n">cross_val_score</span><span class="p">,</span> <span class="n">cross_val_predict</span>
<span class="kn">from</span> <span class="nn">sklearn.metrics</span> <span class="k">import</span> <span class="n">accuracy_score</span><span class="p">,</span> <span class="n">classification_report</span><span class="p">,</span> <span class="n">confusion_matrix</span>
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<p>Now, we create a classification report function</p>

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<div class=" highlight hl-ipython3"><pre><span></span><span class="k">def</span> <span class="nf">print_score</span><span class="p">(</span><span class="n">clf</span><span class="p">,</span> <span class="n">X_train</span><span class="p">,</span> <span class="n">y_train</span><span class="p">,</span> <span class="n">X_test</span><span class="p">,</span> <span class="n">y_test</span><span class="p">,</span> <span class="n">train</span><span class="o">=</span><span class="kc">True</span><span class="p">):</span>
    <span class="k">if</span> <span class="n">train</span><span class="p">:</span>
        <span class="nb">print</span><span class="p">(</span><span class="s2">&quot;Train Result </span><span class="se">\n</span><span class="s2">&quot;</span><span class="p">)</span>
        <span class="nb">print</span><span class="p">(</span><span class="s2">&quot;accuracy score: </span><span class="si">{0:.4f}</span><span class="se">\n</span><span class="s2">&quot;</span><span class="o">.</span><span class="n">format</span><span class="p">(</span><span class="n">accuracy_score</span><span class="p">(</span><span class="n">y_train</span><span class="p">,</span><span class="n">clf</span><span class="o">.</span><span class="n">predict</span><span class="p">(</span><span class="n">X_train</span><span class="p">))))</span>
        <span class="nb">print</span><span class="p">(</span><span class="s2">&quot;Classification Report: </span><span class="se">\n</span><span class="s2"> </span><span class="si">{}</span><span class="se">\n</span><span class="s2">&quot;</span><span class="o">.</span><span class="n">format</span><span class="p">(</span><span class="n">classification_report</span><span class="p">(</span><span class="n">y_train</span><span class="p">,</span><span class="n">clf</span><span class="o">.</span><span class="n">predict</span><span class="p">(</span><span class="n">X_train</span><span class="p">))))</span>
        <span class="nb">print</span><span class="p">(</span><span class="s2">&quot;Confusion Matrix: </span><span class="se">\n</span><span class="s2">&quot;</span><span class="o">.</span><span class="n">format</span><span class="p">(</span><span class="n">confusion_matrix</span><span class="p">(</span><span class="n">y_train</span><span class="p">,</span><span class="n">clf</span><span class="o">.</span><span class="n">predict</span><span class="p">(</span><span class="n">X_train</span><span class="p">))))</span>

        <span class="n">res</span> <span class="o">=</span> <span class="n">cross_val_score</span><span class="p">(</span><span class="n">clf</span><span class="p">,</span> <span class="n">X_train</span><span class="p">,</span> <span class="n">y_train</span><span class="p">,</span> <span class="n">cv</span><span class="o">=</span><span class="mi">10</span><span class="p">,</span> <span class="n">scoring</span><span class="o">=</span><span class="s1">&#39;accuracy&#39;</span><span class="p">)</span>
        <span class="nb">print</span><span class="p">(</span><span class="s2">&quot;Average Accuracy: </span><span class="se">\t</span><span class="s2"> </span><span class="si">{0:.4f}</span><span class="s2">&quot;</span><span class="o">.</span><span class="n">format</span><span class="p">(</span><span class="n">np</span><span class="o">.</span><span class="n">mean</span><span class="p">(</span><span class="n">res</span><span class="p">)))</span>
        <span class="nb">print</span><span class="p">(</span><span class="s2">&quot;Accuracy SD: </span><span class="se">\t\t</span><span class="s2"> </span><span class="si">{0:.4f}</span><span class="s2">&quot;</span><span class="o">.</span><span class="n">format</span><span class="p">(</span><span class="n">np</span><span class="o">.</span><span class="n">std</span><span class="p">(</span><span class="n">res</span><span class="p">)))</span>
        
    <span class="k">elif</span> <span class="n">train</span><span class="o">==</span><span class="kc">False</span><span class="p">:</span>
        <span class="nb">print</span><span class="p">(</span><span class="s2">&quot;Test Result:</span><span class="se">\n</span><span class="s2">&quot;</span><span class="p">)</span>        
        <span class="nb">print</span><span class="p">(</span><span class="s2">&quot;accuracy score: </span><span class="si">{0:.4f}</span><span class="se">\n</span><span class="s2">&quot;</span><span class="o">.</span><span class="n">format</span><span class="p">(</span><span class="n">accuracy_score</span><span class="p">(</span><span class="n">y_test</span><span class="p">,</span> <span class="n">clf</span><span class="o">.</span><span class="n">predict</span><span class="p">(</span><span class="n">X_test</span><span class="p">))))</span>
        <span class="nb">print</span><span class="p">(</span><span class="s2">&quot;Classification Report: </span><span class="se">\n</span><span class="s2"> </span><span class="si">{}</span><span class="se">\n</span><span class="s2">&quot;</span><span class="o">.</span><span class="n">format</span><span class="p">(</span><span class="n">classification_report</span><span class="p">(</span><span class="n">y_test</span><span class="p">,</span> <span class="n">clf</span><span class="o">.</span><span class="n">predict</span><span class="p">(</span><span class="n">X_test</span><span class="p">))))</span>
        <span class="nb">print</span><span class="p">(</span><span class="s2">&quot;Confusion Matrix: </span><span class="se">\n</span><span class="s2"> </span><span class="si">{}</span><span class="se">\n</span><span class="s2">&quot;</span><span class="o">.</span><span class="n">format</span><span class="p">(</span><span class="n">confusion_matrix</span><span class="p">(</span><span class="n">y_test</span><span class="p">,</span> <span class="n">clf</span><span class="o">.</span><span class="n">predict</span><span class="p">(</span><span class="n">X_test</span><span class="p">))))</span>    
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<p>Now we shall conduct the train and the test split</p>

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<div class=" highlight hl-ipython3"><pre><span></span><span class="n">X_train</span><span class="p">,</span> <span class="n">X_test</span><span class="p">,</span> <span class="n">y_train</span><span class="p">,</span> <span class="n">y_test</span> <span class="o">=</span> <span class="n">train_test_split</span><span class="p">(</span><span class="n">df</span><span class="o">.</span><span class="n">drop</span><span class="p">(</span><span class="s1">&#39;TARGET&#39;</span><span class="p">,</span><span class="n">axis</span><span class="o">=</span><span class="mi">1</span><span class="p">),</span><span class="n">df</span><span class="p">[</span><span class="s1">&#39;TARGET&#39;</span><span class="p">],</span><span class="n">test_size</span><span class="o">=</span><span class="mf">0.15</span><span class="p">,</span><span class="n">random_state</span><span class="o">=</span><span class="mi">101</span><span class="p">)</span>
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<p>Standardizing features by removing the mean and scaling to unit variance</p>

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      <th></th>
      <th>loan_amnt</th>
      <th>funded_amnt</th>
      <th>funded_amnt_inv</th>
      <th>term</th>
      <th>int_rate</th>
      <th>installment</th>
      <th>annual_inc</th>
      <th>issue_d</th>
      <th>pymnt_plan</th>
      <th>dti</th>
      <th>...</th>
      <th>addr_state_SD</th>
      <th>addr_state_TN</th>
      <th>addr_state_TX</th>
      <th>addr_state_UT</th>
      <th>addr_state_VA</th>
      <th>addr_state_VT</th>
      <th>addr_state_WA</th>
      <th>addr_state_WI</th>
      <th>addr_state_WV</th>
      <th>addr_state_WY</th>
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  </thead>
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      <th>576085</th>
      <td>2000.0</td>
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      <td>0</td>
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      <td>67.71</td>
      <td>35000.0</td>
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      <td>472.25</td>
      <td>38101.0</td>
      <td>2015</td>
      <td>0</td>
      <td>16.06</td>
      <td>...</td>
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      <td>0</td>
      <td>0</td>
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      <td>0</td>
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    <tr>
      <th>335692</th>
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      <td>7800.0</td>
      <td>7800.0</td>
      <td>0</td>
      <td>7.12</td>
      <td>241.27</td>
      <td>75000.0</td>
      <td>2014</td>
      <td>0</td>
      <td>12.06</td>
      <td>...</td>
      <td>0</td>
      <td>0</td>
      <td>0</td>
      <td>0</td>
      <td>0</td>
      <td>0</td>
      <td>0</td>
      <td>0</td>
      <td>0</td>
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    <tr>
      <th>776669</th>
      <td>5250.0</td>
      <td>5250.0</td>
      <td>5250.0</td>
      <td>0</td>
      <td>13.33</td>
      <td>177.73</td>
      <td>48000.0</td>
      <td>2015</td>
      <td>0</td>
      <td>14.98</td>
      <td>...</td>
      <td>0</td>
      <td>0</td>
      <td>0</td>
      <td>0</td>
      <td>0</td>
      <td>0</td>
      <td>0</td>
      <td>0</td>
      <td>0</td>
      <td>0</td>
    </tr>
    <tr>
      <th>312594</th>
      <td>10000.0</td>
      <td>10000.0</td>
      <td>10000.0</td>
      <td>0</td>
      <td>12.49</td>
      <td>334.49</td>
      <td>65000.0</td>
      <td>2014</td>
      <td>0</td>
      <td>9.68</td>
      <td>...</td>
      <td>0</td>
      <td>0</td>
      <td>0</td>
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<p>5 rows × 167 columns</p>
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<div class=" highlight hl-ipython3"><pre><span></span><span class="n">X_test</span><span class="o">.</span><span class="n">head</span><span class="p">()</span>
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      <th></th>
      <th>loan_amnt</th>
      <th>funded_amnt</th>
      <th>funded_amnt_inv</th>
      <th>term</th>
      <th>int_rate</th>
      <th>installment</th>
      <th>annual_inc</th>
      <th>issue_d</th>
      <th>pymnt_plan</th>
      <th>dti</th>
      <th>...</th>
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      <th>addr_state_WA</th>
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      <th>addr_state_WY</th>
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  <tbody>
    <tr>
      <th>636039</th>
      <td>5000.0</td>
      <td>5000.0</td>
      <td>5000.0</td>
      <td>0</td>
      <td>8.18</td>
      <td>157.10</td>
      <td>45000.0</td>
      <td>2015</td>
      <td>0</td>
      <td>17.01</td>
      <td>...</td>
      <td>0</td>
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      <th>677915</th>
      <td>16500.0</td>
      <td>16500.0</td>
      <td>16500.0</td>
      <td>1</td>
      <td>8.18</td>
      <td>335.99</td>
      <td>60000.0</td>
      <td>2015</td>
      <td>0</td>
      <td>12.90</td>
      <td>...</td>
      <td>0</td>
      <td>0</td>
      <td>0</td>
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      <th>350397</th>
      <td>15350.0</td>
      <td>15350.0</td>
      <td>15350.0</td>
      <td>1</td>
      <td>16.29</td>
      <td>375.66</td>
      <td>35000.0</td>
      <td>2014</td>
      <td>0</td>
      <td>22.15</td>
      <td>...</td>
      <td>0</td>
      <td>0</td>
      <td>0</td>
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      <td>0</td>
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      <th>419565</th>
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      <td>13.65</td>
      <td>272.07</td>
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      <td>0</td>
      <td>9.18</td>
      <td>...</td>
      <td>0</td>
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      <th>281660</th>
      <td>15000.0</td>
      <td>15000.0</td>
      <td>15000.0</td>
      <td>0</td>
      <td>6.49</td>
      <td>459.67</td>
      <td>60000.0</td>
      <td>2014</td>
      <td>0</td>
      <td>25.43</td>
      <td>...</td>
      <td>0</td>
      <td>0</td>
      <td>0</td>
      <td>0</td>
      <td>0</td>
      <td>0</td>
      <td>0</td>
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<div class=" highlight hl-ipython3"><pre><span></span><span class="kn">from</span> <span class="nn">sklearn.preprocessing</span> <span class="k">import</span> <span class="n">StandardScaler</span>
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<div class=" highlight hl-ipython3"><pre><span></span><span class="n">sc</span> <span class="o">=</span> <span class="n">StandardScaler</span><span class="p">()</span>
<span class="n">X_train</span> <span class="o">=</span> <span class="n">sc</span><span class="o">.</span><span class="n">fit_transform</span><span class="p">(</span><span class="n">X_train</span><span class="p">)</span>
<span class="n">X_test</span><span class="o">=</span><span class="n">sc</span><span class="o">.</span><span class="n">transform</span><span class="p">(</span><span class="n">X_test</span><span class="p">)</span>
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<p>Oversampling only the training set using Synthetic Minority Oversampling Technique (SMOTE)</p>

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<div class=" highlight hl-ipython3"><pre><span></span><span class="n">y_train</span><span class="o">.</span><span class="n">value_counts</span><span class="p">()</span>
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<pre>0    693190
1      1023
Name: TARGET, dtype: int64</pre>
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<div class=" highlight hl-ipython3"><pre><span></span><span class="kn">from</span> <span class="nn">imblearn.over_sampling</span> <span class="k">import</span> <span class="n">SMOTE</span>
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<div class=" highlight hl-ipython3"><pre><span></span><span class="n">sm</span> <span class="o">=</span> <span class="n">SMOTE</span><span class="p">(</span><span class="n">random_state</span><span class="o">=</span><span class="mi">12</span><span class="p">,</span> <span class="n">ratio</span> <span class="o">=</span> <span class="mf">1.0</span><span class="p">)</span>
<span class="n">x_train_r</span><span class="p">,</span> <span class="n">y_train_r</span> <span class="o">=</span> <span class="n">sm</span><span class="o">.</span><span class="n">fit_sample</span><span class="p">(</span><span class="n">X_train</span><span class="p">,</span> <span class="n">y_train</span><span class="p">)</span>
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<pre>C:\Users\Saurabh\Anaconda3\lib\site-packages\sklearn\utils\deprecation.py:77: DeprecationWarning: Function _ratio_float is deprecated; Use a float for &#39;ratio&#39; is deprecated from version 0.2. The support will be removed in 0.4. Use a dict, str, or a callable instead.
  warnings.warn(msg, category=DeprecationWarning)
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<p>Let us check the count of output variables after appling the SMOTE function for imbalanced learning</p>

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<div class=" highlight hl-ipython3"><pre><span></span><span class="p">(</span><span class="n">y_train_r</span><span class="o">==</span><span class="mi">1</span><span class="p">)</span><span class="o">.</span><span class="n">sum</span><span class="p">()</span>
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<pre>693190</pre>
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<div class=" highlight hl-ipython3"><pre><span></span><span class="p">(</span><span class="n">y_train_r</span><span class="o">==</span><span class="mi">0</span><span class="p">)</span><span class="o">.</span><span class="n">sum</span><span class="p">()</span>
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<pre>693190</pre>
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<p>Now, we will bet trying out different models to get the best prediction score.</p>

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<h4 id="Creating-a-baseline-for-accuracy-and-recall-using-Logistic-Regression">Creating a baseline for accuracy and recall using Logistic Regression<a class="anchor-link" href="#Creating-a-baseline-for-accuracy-and-recall-using-Logistic-Regression">&#182;</a></h4>
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<div class=" highlight hl-ipython3"><pre><span></span><span class="kn">from</span> <span class="nn">sklearn.linear_model</span> <span class="k">import</span> <span class="n">LogisticRegression</span>

<span class="n">log_reg</span> <span class="o">=</span> <span class="n">LogisticRegression</span><span class="p">(</span><span class="n">C</span> <span class="o">=</span> <span class="mf">0.0001</span><span class="p">,</span><span class="n">random_state</span><span class="o">=</span><span class="mi">21</span><span class="p">)</span>

<span class="n">log_reg</span><span class="o">.</span><span class="n">fit</span><span class="p">(</span><span class="n">x_train_r</span><span class="p">,</span> <span class="n">y_train_r</span><span class="p">)</span>
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<pre>LogisticRegression(C=0.0001, class_weight=None, dual=False,
          fit_intercept=True, intercept_scaling=1, max_iter=100,
          multi_class=&#39;ovr&#39;, n_jobs=1, penalty=&#39;l2&#39;, random_state=21,
          solver=&#39;liblinear&#39;, tol=0.0001, verbose=0, warm_start=False)</pre>
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<div class=" highlight hl-ipython3"><pre><span></span><span class="n">print_score</span><span class="p">(</span><span class="n">log_reg</span><span class="p">,</span> <span class="n">x_train_r</span><span class="p">,</span> <span class="n">y_train_r</span><span class="p">,</span> <span class="n">X_test</span><span class="p">,</span> <span class="n">y_test</span><span class="p">,</span> <span class="n">train</span><span class="o">=</span><span class="kc">False</span><span class="p">)</span>
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<pre>Test Result:

accuracy score: 0.7933

Classification Report: 
              precision    recall  f1-score   support

          0       1.00      0.79      0.88    122332
          1       0.01      0.86      0.01       177

avg / total       1.00      0.79      0.88    122509


Confusion Matrix: 
 [[97036 25296]
 [   25   152]]

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<p>The accuracy came out to be satisfactory for the baseline along with the recall score. However, precision seems to be very off.</p>
<p>For our case, overfitting will be a huge concern. So, We are using Random Forest as it is known to decrease overfitting by selecting features at random.</p>

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<div class=" highlight hl-ipython3"><pre><span></span><span class="kn">from</span> <span class="nn">sklearn.ensemble</span> <span class="k">import</span> <span class="n">RandomForestClassifier</span>
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<div class=" highlight hl-ipython3"><pre><span></span><span class="n">clf_rf</span> <span class="o">=</span> <span class="n">RandomForestClassifier</span><span class="p">(</span><span class="n">n_estimators</span><span class="o">=</span><span class="mi">40</span><span class="p">,</span> <span class="n">random_state</span><span class="o">=</span><span class="mi">21</span><span class="p">)</span>
<span class="n">clf_rf</span><span class="o">.</span><span class="n">fit</span><span class="p">(</span><span class="n">x_train_r</span><span class="p">,</span> <span class="n">y_train_r</span><span class="p">)</span>
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<pre>RandomForestClassifier(bootstrap=True, class_weight=None, criterion=&#39;gini&#39;,
            max_depth=None, max_features=&#39;auto&#39;, max_leaf_nodes=None,
            min_impurity_decrease=0.0, min_impurity_split=None,
            min_samples_leaf=1, min_samples_split=2,
            min_weight_fraction_leaf=0.0, n_estimators=40, n_jobs=1,
            oob_score=False, random_state=21, verbose=0, warm_start=False)</pre>
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<div class=" highlight hl-ipython3"><pre><span></span><span class="n">print_score</span><span class="p">(</span><span class="n">clf_rf</span><span class="p">,</span> <span class="n">x_train_r</span><span class="p">,</span> <span class="n">y_train_r</span><span class="p">,</span> <span class="n">X_test</span><span class="p">,</span> <span class="n">y_test</span><span class="p">,</span> <span class="n">train</span><span class="o">=</span><span class="kc">False</span><span class="p">)</span>
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<pre>Test Result:

accuracy score: 0.9986

Classification Report: 
              precision    recall  f1-score   support

          0       1.00      1.00      1.00    122332
          1       1.00      0.06      0.11       177

avg / total       1.00      1.00      1.00    122509


Confusion Matrix: 
 [[122332      0]
 [   167     10]]

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<p>Hence, From the above results we can say that Logistic regression is able to predict the outcome with about 80% accuracy and Random Forest is able to predict the data with about 99% accuracy but with lower recall values as compared to Logistic Regression which has higher recall comparatively. In order to obtain higher precision and recall rates we need to improvise the model based on past mistakes which can be done with the help of boosting using LightGBM classifier.</p>

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