06-Seaborn Exercises.ipynb

{
 "cells": [
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "___\n",
    "\n",
    "<a href='http://www.pieriandata.com'> <img src='../Pierian_Data_Logo.png' /></a>\n",
    "___\n",
    "# Seaborn Exercises\n",
    "\n",
    "Time to practice your new seaborn skills! Try to recreate the plots below (don't worry about color schemes, just the plot itself."
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## The Data\n",
    "\n",
    "We will be working with a famous titanic data set for these exercises. Later on in the Machine Learning section of the course, we will revisit this data, and use it to predict survival rates of passengers. For now, we'll just focus on the visualization of the data with seaborn:"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 1,
   "metadata": {},
   "outputs": [],
   "source": [
    "import seaborn as sns\n",
    "import matplotlib.pyplot as plt\n",
    "%matplotlib inline"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 27,
   "metadata": {
    "collapsed": true
   },
   "outputs": [],
   "source": [
    "sns.set_style('whitegrid')"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 2,
   "metadata": {},
   "outputs": [],
   "source": [
    "titanic = sns.load_dataset('titanic')"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 3,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": "<div>\n<style scoped>\n    .dataframe tbody tr th:only-of-type {\n        vertical-align: middle;\n    }\n\n    .dataframe tbody tr th {\n        vertical-align: top;\n    }\n\n    .dataframe thead th {\n        text-align: right;\n    }\n</style>\n<table border=\"1\" class=\"dataframe\">\n  <thead>\n    <tr style=\"text-align: right;\">\n      <th></th>\n      <th>survived</th>\n      <th>pclass</th>\n      <th>sex</th>\n      <th>age</th>\n      <th>sibsp</th>\n      <th>parch</th>\n      <th>fare</th>\n      <th>embarked</th>\n      <th>class</th>\n      <th>who</th>\n      <th>adult_male</th>\n      <th>deck</th>\n      <th>embark_town</th>\n      <th>alive</th>\n      <th>alone</th>\n    </tr>\n  </thead>\n  <tbody>\n    <tr>\n      <td>0</td>\n      <td>0</td>\n      <td>3</td>\n      <td>male</td>\n      <td>22.0</td>\n      <td>1</td>\n      <td>0</td>\n      <td>7.2500</td>\n      <td>S</td>\n      <td>Third</td>\n      <td>man</td>\n      <td>True</td>\n      <td>NaN</td>\n      <td>Southampton</td>\n      <td>no</td>\n      <td>False</td>\n    </tr>\n    <tr>\n      <td>1</td>\n      <td>1</td>\n      <td>1</td>\n      <td>female</td>\n      <td>38.0</td>\n      <td>1</td>\n      <td>0</td>\n      <td>71.2833</td>\n      <td>C</td>\n      <td>First</td>\n      <td>woman</td>\n      <td>False</td>\n      <td>C</td>\n      <td>Cherbourg</td>\n      <td>yes</td>\n      <td>False</td>\n    </tr>\n    <tr>\n      <td>2</td>\n      <td>1</td>\n      <td>3</td>\n      <td>female</td>\n      <td>26.0</td>\n      <td>0</td>\n      <td>0</td>\n      <td>7.9250</td>\n      <td>S</td>\n      <td>Third</td>\n      <td>woman</td>\n      <td>False</td>\n      <td>NaN</td>\n      <td>Southampton</td>\n      <td>yes</td>\n      <td>True</td>\n    </tr>\n    <tr>\n      <td>3</td>\n      <td>1</td>\n      <td>1</td>\n      <td>female</td>\n      <td>35.0</td>\n      <td>1</td>\n      <td>0</td>\n      <td>53.1000</td>\n      <td>S</td>\n      <td>First</td>\n      <td>woman</td>\n      <td>False</td>\n      <td>C</td>\n      <td>Southampton</td>\n      <td>yes</td>\n      <td>False</td>\n    </tr>\n    <tr>\n      <td>4</td>\n      <td>0</td>\n      <td>3</td>\n      <td>male</td>\n      <td>35.0</td>\n      <td>0</td>\n      <td>0</td>\n      <td>8.0500</td>\n      <td>S</td>\n      <td>Third</td>\n      <td>man</td>\n      <td>True</td>\n      <td>NaN</td>\n      <td>Southampton</td>\n      <td>no</td>\n      <td>True</td>\n    </tr>\n  </tbody>\n</table>\n</div>",
      "text/plain": "   survived  pclass     sex   age  sibsp  parch     fare embarked  class  \\\n0         0       3    male  22.0      1      0   7.2500        S  Third   \n1         1       1  female  38.0      1      0  71.2833        C  First   \n2         1       3  female  26.0      0      0   7.9250        S  Third   \n3         1       1  female  35.0      1      0  53.1000        S  First   \n4         0       3    male  35.0      0      0   8.0500        S  Third   \n\n     who  adult_male deck  embark_town alive  alone  \n0    man        True  NaN  Southampton    no  False  \n1  woman       False    C    Cherbourg   yes  False  \n2  woman       False  NaN  Southampton   yes   True  \n3  woman       False    C  Southampton   yes  False  \n4    man        True  NaN  Southampton    no   True  "
     },
     "execution_count": 3,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "titanic.head()"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "# Exercises\n",
    "\n",
    "** Recreate the plots below using the titanic dataframe. There are very few hints since most of the plots can be done with just one or two lines of code and a hint would basically give away the solution. Keep careful attention to the x and y labels for hints.**\n",
    "\n",
    "** *Note! In order to not lose the plot image, make sure you don't code in the cell that is directly above the plot, there is an extra cell above that one which won't overwrite that plot!* **"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 5,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": "<seaborn.axisgrid.JointGrid at 0x7f659f2335d0>"
     },
     "execution_count": 5,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "image/png": 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      "text/plain": "<Figure size 432x432 with 3 Axes>"
     },
     "metadata": {
      "needs_background": "dark"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "# CODE HERE\n",
    "# REPLICATE EXERCISE PLOT IMAGE BELOW\n",
    "# BE CAREFUL NOT TO OVERWRITE CELL BELOW\n",
    "# THAT WOULD REMOVE THE EXERCISE PLOT IMAGE!\n",
    "sns.jointplot(data=titanic, y=\"age\", x=\"fare\", kind=\"scatter\")"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 41,
   "metadata": {
    "collapsed": false
   },
   "outputs": [
    {
     "data": {
      "text/plain": [
       "<seaborn.axisgrid.JointGrid at 0x11d0389e8>"
      ]
     },
     "execution_count": 41,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
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K4njHJIhgC3K5WJeI9Dm5CX+n5MLEJIhgC3K5WJeIkgkTk0IivcsJtiCXi3WJKJlwjEkh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\nIiIiofx/wXPk8jWAjFAAAAAASUVORK5CYII=\n",
      "text/plain": [
       "<matplotlib.figure.Figure at 0x11d038cf8>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": []
  },
  {
   "cell_type": "code",
   "execution_count": 8,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": "<matplotlib.axes._subplots.AxesSubplot at 0x7f659d14a990>"
     },
     "execution_count": 8,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
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      "text/plain": "<Figure size 432x288 with 1 Axes>"
     },
     "metadata": {
      "needs_background": "dark"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "# CODE HERE\n",
    "# REPLICATE EXERCISE PLOT IMAGE BELOW\n",
    "# BE CAREFUL NOT TO OVERWRITE CELL BELOW\n",
    "# THAT WOULD REMOVE THE EXERCISE PLOT IMAGE!\n",
    "sns.distplot(titanic[\"fare\"], kde=False, color=\"red\")"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 44,
   "metadata": {
    "collapsed": false
   },
   "outputs": [
    {
     "data": {
      "text/plain": [
       "<matplotlib.axes._subplots.AxesSubplot at 0x11fc5ca90>"
      ]
     },
     "execution_count": 44,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
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MJZ8lPrQFwOylNPqWZenxxx/X0NCQsrKy9KMf/Ui33nprKn/FgpLoyp6WlLJLPo9duaJR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\nAAAAAElFTkSuQmCC\n",
      "text/plain": [
       "<matplotlib.figure.Figure at 0x11ff50668>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": []
  },
  {
   "cell_type": "code",
   "execution_count": 9,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": "<matplotlib.axes._subplots.AxesSubplot at 0x7f65a0242650>"
     },
     "execution_count": 9,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
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      "text/plain": "<Figure size 432x288 with 1 Axes>"
     },
     "metadata": {
      "needs_background": "dark"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "# CODE HERE\n",
    "# REPLICATE EXERCISE PLOT IMAGE BELOW\n",
    "# BE CAREFUL NOT TO OVERWRITE CELL BELOW\n",
    "# THAT WOULD REMOVE THE EXERCISE PLOT IMAGE!\n",
    "sns.boxplot(data=titanic, x=\"class\", y=\"age\", palette=\"rainbow\")"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 45,
   "metadata": {
    "collapsed": false
   },
   "outputs": [
    {
     "data": {
      "text/plain": [
       "<matplotlib.axes._subplots.AxesSubplot at 0x11f23da90>"
      ]
     },
     "execution_count": 45,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
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cXAyVSoWCggIolUrExMSgqKhIZAlE5CN9IsOwMXuYv8sIWm+Xnei2toQG/759+6BQKPDn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\nMv8P9qlbLeIn4+kAAAAASUVORK5CYII=\n",
      "text/plain": [
       "<matplotlib.figure.Figure at 0x12139aa90>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": []
  },
  {
   "cell_type": "code",
   "execution_count": 14,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": "<matplotlib.axes._subplots.AxesSubplot at 0x7f659cf6b410>"
     },
     "execution_count": 14,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "image/png": 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      "text/plain": "<Figure size 432x288 with 1 Axes>"
     },
     "metadata": {
      "needs_background": "dark"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "# CODE HERE\n",
    "# REPLICATE EXERCISE PLOT IMAGE BELOW\n",
    "# BE CAREFUL NOT TO OVERWRITE CELL BELOW\n",
    "# THAT WOULD REMOVE THE EXERCISE PLOT IMAGE!\n",
    "sns.swarmplot(data=titanic, x=\"class\", y=\"age\", palette=\"rainbow\")"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 46,
   "metadata": {
    "collapsed": false
   },
   "outputs": [
    {
     "data": {
      "text/plain": [
       "<matplotlib.axes._subplots.AxesSubplot at 0x11f215320>"
      ]
     },
     "execution_count": 46,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "image/png": 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nUy6LMzL5j7YDeKIhSjLcXJNTiqpp/Ka/mbimkmt18mDVBtDh5OQAFsWUauM8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\n+esDLZhlhS0FlanirUK7iyd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v5Lste1JPFPXZxdxSXMd3W/akXEkPVW3k9rI17+etX3L0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\n6Kk1bwetsQAAAABJRU5ErkJggg==\n",
      "text/plain": [
       "<matplotlib.figure.Figure at 0x11f2395f8>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": []
  },
  {
   "cell_type": "code",
   "execution_count": 17,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": "<matplotlib.axes._subplots.AxesSubplot at 0x7f659ccd93d0>"
     },
     "execution_count": 17,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
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      "text/plain": "<Figure size 432x288 with 1 Axes>"
     },
     "metadata": {
      "needs_background": "dark"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "# CODE HERE\n",
    "# REPLICATE EXERCISE PLOT IMAGE BELOW\n",
    "# BE CAREFUL NOT TO OVERWRITE CELL BELOW\n",
    "# THAT WOULD REMOVE THE EXERCISE PLOT IMAGE!\n",
    "sns.countplot(data=titanic, x=\"sex\")"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 47,
   "metadata": {
    "collapsed": false
   },
   "outputs": [
    {
     "data": {
      "text/plain": [
       "<matplotlib.axes._subplots.AxesSubplot at 0x11f207ef0>"
      ]
     },
     "execution_count": 47,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "image/png": 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FoP3xQTu+hq7P49w81hPptAVh2bJlfPzxxzz00EMsXbqUSCTC3LlzWbhwIclkkoKCAsrL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\n/j9LPVtwvxCX4QAAAABJRU5ErkJggg==\n",
      "text/plain": [
       "<matplotlib.figure.Figure at 0x11d84cc18>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": []
  },
  {
   "cell_type": "code",
   "execution_count": 18,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": "<matplotlib.axes._subplots.AxesSubplot at 0x7f659672aad0>"
     },
     "execution_count": 18,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "# CODE HERE\n",
    "# REPLICATE EXERCISE PLOT IMAGE BELOW\n",
    "# BE CAREFUL NOT TO OVERWRITE CELL BELOW\n",
    "# THAT WOULD REMOVE THE EXERCISE PLOT IMAGE!\n",
    "sns.heatmap(data=titanic.corr()) "
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 48,
   "metadata": {
    "collapsed": false
   },
   "outputs": [
    {
     "data": {
      "text/plain": [
       "<matplotlib.text.Text at 0x11d72da58>"
      ]
     },
     "execution_count": 48,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "image/png": 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YY7hw4UKRYhARuRPyiuE0sDdNEkuXLqVx48ZER0eTmprK1q1bqVixIvv37yc0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\nISUJERFx6P8AZLY+O+sfZSgAAAAASUVORK5CYII=\n",
      "text/plain": [
       "<matplotlib.figure.Figure at 0x11d8229b0>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": []
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {
    "collapsed": true
   },
   "outputs": [],
   "source": [
    "# CODE HERE\n",
    "# REPLICATE EXERCISE PLOT IMAGE BELOW\n",
    "# BE CAREFUL NOT TO OVERWRITE CELL BELOW\n",
    "# THAT WOULD REMOVE THE EXERCISE PLOT IMAGE!"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 49,
   "metadata": {
    "collapsed": false
   },
   "outputs": [
    {
     "data": {
      "text/plain": [
       "<seaborn.axisgrid.FacetGrid at 0x11d81c240>"
      ]
     },
     "execution_count": 49,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "image/png": 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kqqqqAACZmZnYvHmzfX8AIhvi+HBcXM28F/jPf/6DN998E3369IGbmxsGDRoE\nlUqF7373u/jwww/h4eGBAQMGICgoCNHR0SgoKMC2bdtgNBoxePBgbNmyhSeBqdfi+HBcDKheqqqq\nCgUFBYiKigIALFu2DL/61a8QGhpq176I5IDjwzHwHFQvNWTIEJw5cwYzZ86EQqHAT37yEw4+ov/h\n+HAM3IMiIiJZ4iQJIiKSJQYUERHJEgOKiIhkiQFFRESyxIAiIiJZYkAREZEs/T9ZtOJ0ZIoq9gAA\nAABJRU5ErkJggg==\n",
      "text/plain": [
       "<matplotlib.figure.Figure at 0x11d6fcc50>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": []
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "# Great Job!\n",
    "\n",
    "### That is it for now! We'll see a lot more of seaborn practice problems in the machine learning section!"
   ]
  }
 ],
 "metadata": {
  "kernelspec": {
   "display_name": "Python 3",
   "language": "python",
   "name": "python3"
  },
  "language_info": {
   "codemirror_mode": {
    "name": "ipython",
    "version": 3
   },
   "file_extension": ".py",
   "mimetype": "text/x-python",
   "name": "python",
   "nbconvert_exporter": "python",
   "pygments_lexer": "ipython3",
   "version": "3.5.1"
  }
 },
 "nbformat": 4,
 "nbformat_minor": 0
}