matplotlib_scatterplot_from_pandas.ipynb

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 "worksheets": [
  {
   "cells": [
    {
     "cell_type": "markdown",
     "metadata": {},
     "source": [
      "# Making A Matplotlib Scatterplot From A Pandas Dataframe\n",
      "\n",
      "- **Author:** [Chris Albon](http://www.chrisalbon.com/), [@ChrisAlbon](https://twitter.com/chrisalbon)\n",
      "- **Date:** -\n",
      "- **Repo:** [Python 3 code snippets for data science](https://github.com/chrisalbon/code_py)\n",
      "- **Note:** Based on: [StackOverflow](http://stackoverflow.com/questions/14300137/making-matplotlib-scatter-plots-from-dataframes-in-pythons-pandas)."
     ]
    },
    {
     "cell_type": "markdown",
     "metadata": {},
     "source": [
      "### import modules"
     ]
    },
    {
     "cell_type": "code",
     "collapsed": false,
     "input": [
      "%matplotlib inline\n",
      "import pandas as pd\n",
      "import matplotlib.pyplot as plt\n",
      "import numpy as np"
     ],
     "language": "python",
     "metadata": {},
     "outputs": [],
     "prompt_number": 2
    },
    {
     "cell_type": "markdown",
     "metadata": {},
     "source": [
      "### Create dataframe"
     ]
    },
    {
     "cell_type": "code",
     "collapsed": false,
     "input": [
      "raw_data = {'first_name': ['Jason', 'Molly', 'Tina', 'Jake', 'Amy'], \n",
      "        'last_name': ['Miller', 'Jacobson', 'Ali', 'Milner', 'Cooze'], \n",
      "        'female': [0, 1, 1, 0, 1],\n",
      "        'age': [42, 52, 36, 24, 73], \n",
      "        'preTestScore': [4, 24, 31, 2, 3],\n",
      "        'postTestScore': [25, 94, 57, 62, 70]}\n",
      "df = pd.DataFrame(raw_data, columns = ['first_name', 'last_name', 'age', 'female', 'preTestScore', 'postTestScore'])\n",
      "df"
     ],
     "language": "python",
     "metadata": {},
     "outputs": [
      {
       "html": [
        "<div style=\"max-height:1000px;max-width:1500px;overflow:auto;\">\n",
        "<table border=\"1\" class=\"dataframe\">\n",
        "  <thead>\n",
        "    <tr style=\"text-align: right;\">\n",
        "      <th></th>\n",
        "      <th>first_name</th>\n",
        "      <th>last_name</th>\n",
        "      <th>age</th>\n",
        "      <th>female</th>\n",
        "      <th>preTestScore</th>\n",
        "      <th>postTestScore</th>\n",
        "    </tr>\n",
        "  </thead>\n",
        "  <tbody>\n",
        "    <tr>\n",
        "      <th>0</th>\n",
        "      <td> Jason</td>\n",
        "      <td>   Miller</td>\n",
        "      <td> 42</td>\n",
        "      <td> 0</td>\n",
        "      <td>  4</td>\n",
        "      <td> 25</td>\n",
        "    </tr>\n",
        "    <tr>\n",
        "      <th>1</th>\n",
        "      <td> Molly</td>\n",
        "      <td> Jacobson</td>\n",
        "      <td> 52</td>\n",
        "      <td> 1</td>\n",
        "      <td> 24</td>\n",
        "      <td> 94</td>\n",
        "    </tr>\n",
        "    <tr>\n",
        "      <th>2</th>\n",
        "      <td>  Tina</td>\n",
        "      <td>      Ali</td>\n",
        "      <td> 36</td>\n",
        "      <td> 1</td>\n",
        "      <td> 31</td>\n",
        "      <td> 57</td>\n",
        "    </tr>\n",
        "    <tr>\n",
        "      <th>3</th>\n",
        "      <td>  Jake</td>\n",
        "      <td>   Milner</td>\n",
        "      <td> 24</td>\n",
        "      <td> 0</td>\n",
        "      <td>  2</td>\n",
        "      <td> 62</td>\n",
        "    </tr>\n",
        "    <tr>\n",
        "      <th>4</th>\n",
        "      <td>   Amy</td>\n",
        "      <td>    Cooze</td>\n",
        "      <td> 73</td>\n",
        "      <td> 1</td>\n",
        "      <td>  3</td>\n",
        "      <td> 70</td>\n",
        "    </tr>\n",
        "  </tbody>\n",
        "</table>\n",
        "</div>"
       ],
       "metadata": {},
       "output_type": "pyout",
       "prompt_number": 3,
       "text": [
        "  first_name last_name  age  female  preTestScore  postTestScore\n",
        "0      Jason    Miller   42       0             4             25\n",
        "1      Molly  Jacobson   52       1            24             94\n",
        "2       Tina       Ali   36       1            31             57\n",
        "3       Jake    Milner   24       0             2             62\n",
        "4        Amy     Cooze   73       1             3             70"
       ]
      }
     ],
     "prompt_number": 3
    },
    {
     "cell_type": "markdown",
     "metadata": {},
     "source": [
      "### Scatterplot of preTestScore and postTestScore, with the size of each point determined by age"
     ]
    },
    {
     "cell_type": "code",
     "collapsed": false,
     "input": [
      "plt.scatter(df.preTestScore, df.postTestScore\n",
      ", s=df.age)"
     ],
     "language": "python",
     "metadata": {},
     "outputs": [
      {
       "metadata": {},
       "output_type": "pyout",
       "prompt_number": 4,
       "text": [
        "<matplotlib.collections.PathCollection at 0x10841df50>"
       ]
      },
      {
       "metadata": {},
       "output_type": "display_data",
       "png": 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       "text": [
        "<matplotlib.figure.Figure at 0x108380dd0>"
       ]
      }
     ],
     "prompt_number": 4
    },
    {
     "cell_type": "markdown",
     "metadata": {},
     "source": [
      "### Scatterplot of preTestScore and postTestScore with the size = 300 and the color determined by sex"
     ]
    },
    {
     "cell_type": "code",
     "collapsed": false,
     "input": [
      "plt.scatter(df.preTestScore, df.postTestScore, s=300, c='m')"
     ],
     "language": "python",
     "metadata": {},
     "outputs": [
      {
       "metadata": {},
       "output_type": "pyout",
       "prompt_number": 6,
       "text": [
        "<matplotlib.collections.PathCollection at 0x1086dcdd0>"
       ]
      },
      {
       "metadata": {},
       "output_type": "display_data",
       "png": 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       "text": [
        "<matplotlib.figure.Figure at 0x108496490>"
       ]
      }
     ],
     "prompt_number": 6
    },
    {
     "cell_type": "code",
     "collapsed": false,
     "input": [],
     "language": "python",
     "metadata": {},
     "outputs": []
    }
   ],
   "metadata": {}
  }
 ]
}