Test.ipynb

{
 "cells": [
  {
   "cell_type": "code",
   "execution_count": 7,
   "metadata": {
    "collapsed": false,
    "scrolled": false
   },
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>sepal_length</th>\n",
       "      <th>sepal_width</th>\n",
       "      <th>petal_length</th>\n",
       "      <th>petal_width</th>\n",
       "      <th>species</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>5.1</td>\n",
       "      <td>3.5</td>\n",
       "      <td>1.4</td>\n",
       "      <td>0.2</td>\n",
       "      <td>setosa</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>4.9</td>\n",
       "      <td>3.0</td>\n",
       "      <td>1.4</td>\n",
       "      <td>0.2</td>\n",
       "      <td>setosa</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>4.7</td>\n",
       "      <td>3.2</td>\n",
       "      <td>1.3</td>\n",
       "      <td>0.2</td>\n",
       "      <td>setosa</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>4.6</td>\n",
       "      <td>3.1</td>\n",
       "      <td>1.5</td>\n",
       "      <td>0.2</td>\n",
       "      <td>setosa</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>5.0</td>\n",
       "      <td>3.6</td>\n",
       "      <td>1.4</td>\n",
       "      <td>0.2</td>\n",
       "      <td>setosa</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "   sepal_length  sepal_width  petal_length  petal_width species\n",
       "0           5.1          3.5           1.4          0.2  setosa\n",
       "1           4.9          3.0           1.4          0.2  setosa\n",
       "2           4.7          3.2           1.3          0.2  setosa\n",
       "3           4.6          3.1           1.5          0.2  setosa\n",
       "4           5.0          3.6           1.4          0.2  setosa"
      ]
     },
     "execution_count": 7,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "import pandas as pd\n",
    "import combine as com\n",
    "a  = pd.read_csv('iris.csv')\n",
    "a.head()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 8,
   "metadata": {
    "collapsed": false
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      " The complete summary with Graph \n",
      "sepal_length is discrete\n",
      "Sum is  876.5\n",
      "Average is  5.84333333333\n",
      "Median is  5.8\n",
      "Standard deviation is  0.828066127978\n",
      "Total number of values in the column us  150\n",
      "Number of unique values are 35\n",
      "sepal_length is of  float type \n"
     ]
    },
    {
     "data": {
      "image/png": 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      "text/plain": [
       "<matplotlib.figure.Figure at 0x1179a3790>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      " ITs discrete so you may not want to display this \n",
      "***************************\n",
      "sepal_width is discrete\n",
      "Sum is  458.1\n",
      "Average is  3.054\n",
      "Median is  3.0\n",
      "Standard deviation is  0.433594311362\n",
      "Total number of values in the column us  150\n",
      "Number of unique values are 23\n",
      "sepal_width is of  float type \n"
     ]
    },
    {
     "data": {
      "image/png": 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      "text/plain": [
       "<matplotlib.figure.Figure at 0x117f0bb90>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      " ITs discrete so you may not want to display this \n",
      "***************************\n",
      "petal_length is discrete\n",
      "Sum is  563.8\n",
      "Average is  3.75866666667\n",
      "Median is  4.35\n",
      "Standard deviation is  1.76442041995\n",
      "Total number of values in the column us  150\n",
      "Number of unique values are 43\n",
      "petal_length is of  float type \n"
     ]
    },
    {
     "data": {
      "image/png": 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      "text/plain": [
       "<matplotlib.figure.Figure at 0x11a646310>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      " ITs discrete so you may not want to display this \n",
      "***************************\n",
      "petal_width is discrete\n",
      "Sum is  179.8\n",
      "Average is  1.19866666667\n",
      "Median is  1.3\n",
      "Standard deviation is  0.763160741701\n",
      "Total number of values in the column us  150\n",
      "Number of unique values are 22\n",
      "petal_width is of  float type \n"
     ]
    },
    {
     "data": {
      "image/png": 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      "text/plain": [
       "<matplotlib.figure.Figure at 0x117674290>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      " ITs discrete so you may not want to display this \n",
      "***************************\n",
      "species is discrete\n",
      "Its unique occurance is\n",
      "setosa        50\n",
      "versicolor    50\n",
      "virginica     50\n",
      "Name: species, dtype: int64\n",
      "species is of String type\n",
      "***************************\n",
      " Primary Key analysis \n",
      "sepal_length\n",
      "35 150\n",
      "sepal_width\n",
      "23 150\n",
      "petal_length\n",
      "43 150\n",
      "petal_width\n",
      "22 150\n",
      "species\n",
      "3 150\n",
      "[]\n",
      " \n",
      " \n",
      " \n",
      " \n",
      "Final outliers\n",
      "[ 1.  1.  1.  1.  1.  1.  1.  1. -1.  1.  1.  1.  1. -1.  1. -1.  1.  1.\n",
      "  1.  1.  1.  1.  1.  1.  1.  1.  1.  1.  1.  1.  1.  1. -1. -1.  1.  1.\n",
      "  1.  1. -1.  1.  1. -1.  1.  1.  1.  1.  1.  1.  1.  1.  1.  1.  1.  1.\n",
      "  1.  1.  1.  1.  1.  1. -1.  1.  1.  1.  1.  1.  1.  1.  1.  1.  1.  1.\n",
      "  1.  1.  1.  1.  1.  1.  1.  1.  1.  1.  1.  1.  1.  1.  1.  1.  1.  1.\n",
      "  1.  1.  1.  1.  1.  1.  1.  1.  1.  1.  1.  1.  1.  1.  1.  1. -1.  1.\n",
      "  1. -1.  1.  1.  1.  1.  1.  1.  1. -1. -1. -1.  1.  1. -1.  1.  1.  1.\n",
      "  1.  1.  1.  1.  1. -1.  1.  1.  1. -1.  1.  1.  1.  1.  1.  1.  1.  1.\n",
      "  1.  1.  1.  1.  1.  1.]\n",
      "9 is an outlier \n",
      "14 is an outlier \n",
      "16 is an outlier \n",
      "33 is an outlier \n",
      "34 is an outlier \n",
      "39 is an outlier \n",
      "42 is an outlier \n",
      "61 is an outlier \n",
      "107 is an outlier \n",
      "110 is an outlier \n",
      "118 is an outlier \n",
      "119 is an outlier \n",
      "120 is an outlier \n",
      "123 is an outlier \n",
      "132 is an outlier \n",
      "136 is an outlier \n",
      "16\n",
      " \n",
      " \n",
      " \n",
      " \n"
     ]
    }
   ],
   "source": [
    "com.result(a)"
   ]
  }
 ],
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