PythonPandasCookbook5.2.ipynb

{
 "metadata": {
  "name": "",
  "signature": "sha256:16ea39dbbfec7cc126731cbbcf97711a408db153a6dba74672b0f03f22e769f3"
 },
 "nbformat": 3,
 "nbformat_minor": 0,
 "worksheets": [
  {
   "cells": [
    {
     "cell_type": "markdown",
     "metadata": {},
     "source": [
      "# Python for Data Analysis Lightning Tutorials\n",
      "## Pandas Cookbook Series\n",
      "\n",
      "**Python for Data Analysis Lightning Tutorials** is a series of tutorials in Data Analysis, Statistics, and Graphics using Python. The **Pandas Cookbook** series of tutorials provides recipes for common tasks and moves on to more advanced topics in statistics and time series analysis. \n",
      "\n",
      "<i>Created by Alfred Essa</i>, June 29th, 2014 \n",
      "\n",
      "Note: IPython Notebook and Data files can be found at my Github Site: http://github/alfredessa\n"
     ]
    },
    {
     "cell_type": "heading",
     "level": 2,
     "metadata": {},
     "source": [
      "5.2 Descriptive Statistics and Data Visualizations"
     ]
    },
    {
     "cell_type": "heading",
     "level": 3,
     "metadata": {},
     "source": [
      "Seaborn Visualization Library by Michael Waskom"
     ]
    },
    {
     "cell_type": "code",
     "collapsed": false,
     "input": [
      "from IPython.display import HTML\n",
      "HTML('<iframe src=http://stanford.edu/~mwaskom/software/seaborn/index.html width=700 height=350></iframe>')"
     ],
     "language": "python",
     "metadata": {},
     "outputs": [
      {
       "html": [
        "<iframe src=http://stanford.edu/~mwaskom/software/seaborn/index.html width=700 height=350></iframe>"
       ],
       "metadata": {},
       "output_type": "pyout",
       "prompt_number": 11,
       "text": [
        "<IPython.core.display.HTML at 0x10b83a650>"
       ]
      }
     ],
     "prompt_number": 11
    },
    {
     "cell_type": "heading",
     "level": 3,
     "metadata": {},
     "source": [
      "Preliminaries"
     ]
    },
    {
     "cell_type": "code",
     "collapsed": false,
     "input": [
      "import numpy as np\n",
      "import pandas as pd\n",
      "import matplotlib.pyplot as plt\n",
      "import seaborn as sns\n"
     ],
     "language": "python",
     "metadata": {},
     "outputs": [],
     "prompt_number": 12
    },
    {
     "cell_type": "code",
     "collapsed": false,
     "input": [
      "#seaborn settings\n",
      "sns.set_palette(\"deep\", desat=.6)\n",
      "sns.set_context(rc={\"figure.figsize\": (8,4)})"
     ],
     "language": "python",
     "metadata": {},
     "outputs": [],
     "prompt_number": 13
    },
    {
     "cell_type": "code",
     "collapsed": false,
     "input": [],
     "language": "python",
     "metadata": {},
     "outputs": []
    },
    {
     "cell_type": "heading",
     "level": 3,
     "metadata": {},
     "source": [
      "Load Data Sets"
     ]
    },
    {
     "cell_type": "code",
     "collapsed": false,
     "input": [
      "titanic = pd.read_csv('data/titanic.csv')"
     ],
     "language": "python",
     "metadata": {},
     "outputs": [],
     "prompt_number": 14
    },
    {
     "cell_type": "code",
     "collapsed": false,
     "input": [
      "server = pd.read_csv('data/serverdata.csv')"
     ],
     "language": "python",
     "metadata": {},
     "outputs": [],
     "prompt_number": 15
    },
    {
     "cell_type": "code",
     "collapsed": false,
     "input": [
      "mlb = pd.read_csv('data/mlb.csv')"
     ],
     "language": "python",
     "metadata": {},
     "outputs": [],
     "prompt_number": 16
    },
    {
     "cell_type": "code",
     "collapsed": false,
     "input": [
      "titanic.head()"
     ],
     "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>PassengerId</th>\n",
        "      <th>Survived</th>\n",
        "      <th>Pclass</th>\n",
        "      <th>Name</th>\n",
        "      <th>Sex</th>\n",
        "      <th>Age</th>\n",
        "      <th>SibSp</th>\n",
        "      <th>Parch</th>\n",
        "      <th>Ticket</th>\n",
        "      <th>Fare</th>\n",
        "      <th>Cabin</th>\n",
        "      <th>Embarked</th>\n",
        "    </tr>\n",
        "  </thead>\n",
        "  <tbody>\n",
        "    <tr>\n",
        "      <th>0</th>\n",
        "      <td> 1</td>\n",
        "      <td> 0</td>\n",
        "      <td> 3</td>\n",
        "      <td>                           Braund, Mr. Owen Harris</td>\n",
        "      <td>   male</td>\n",
        "      <td> 22</td>\n",
        "      <td> 1</td>\n",
        "      <td> 0</td>\n",
        "      <td>        A/5 21171</td>\n",
        "      <td>  7.2500</td>\n",
        "      <td>  NaN</td>\n",
        "      <td> S</td>\n",
        "    </tr>\n",
        "    <tr>\n",
        "      <th>1</th>\n",
        "      <td> 2</td>\n",
        "      <td> 1</td>\n",
        "      <td> 1</td>\n",
        "      <td> Cumings, Mrs. John Bradley (Florence Briggs Th...</td>\n",
        "      <td> female</td>\n",
        "      <td> 38</td>\n",
        "      <td> 1</td>\n",
        "      <td> 0</td>\n",
        "      <td>         PC 17599</td>\n",
        "      <td> 71.2833</td>\n",
        "      <td>  C85</td>\n",
        "      <td> C</td>\n",
        "    </tr>\n",
        "    <tr>\n",
        "      <th>2</th>\n",
        "      <td> 3</td>\n",
        "      <td> 1</td>\n",
        "      <td> 3</td>\n",
        "      <td>                            Heikkinen, Miss. Laina</td>\n",
        "      <td> female</td>\n",
        "      <td> 26</td>\n",
        "      <td> 0</td>\n",
        "      <td> 0</td>\n",
        "      <td> STON/O2. 3101282</td>\n",
        "      <td>  7.9250</td>\n",
        "      <td>  NaN</td>\n",
        "      <td> S</td>\n",
        "    </tr>\n",
        "    <tr>\n",
        "      <th>3</th>\n",
        "      <td> 4</td>\n",
        "      <td> 1</td>\n",
        "      <td> 1</td>\n",
        "      <td>      Futrelle, Mrs. Jacques Heath (Lily May Peel)</td>\n",
        "      <td> female</td>\n",
        "      <td> 35</td>\n",
        "      <td> 1</td>\n",
        "      <td> 0</td>\n",
        "      <td>           113803</td>\n",
        "      <td> 53.1000</td>\n",
        "      <td> C123</td>\n",
        "      <td> S</td>\n",
        "    </tr>\n",
        "    <tr>\n",
        "      <th>4</th>\n",
        "      <td> 5</td>\n",
        "      <td> 0</td>\n",
        "      <td> 3</td>\n",
        "      <td>                          Allen, Mr. William Henry</td>\n",
        "      <td>   male</td>\n",
        "      <td> 35</td>\n",
        "      <td> 0</td>\n",
        "      <td> 0</td>\n",
        "      <td>           373450</td>\n",
        "      <td>  8.0500</td>\n",
        "      <td>  NaN</td>\n",
        "      <td> S</td>\n",
        "    </tr>\n",
        "  </tbody>\n",
        "</table>\n",
        "<p>5 rows \u00d7 12 columns</p>\n",
        "</div>"
       ],
       "metadata": {},
       "output_type": "pyout",
       "prompt_number": 17,
       "text": [
        "   PassengerId  Survived  Pclass  \\\n",
        "0            1         0       3   \n",
        "1            2         1       1   \n",
        "2            3         1       3   \n",
        "3            4         1       1   \n",
        "4            5         0       3   \n",
        "\n",
        "                                                Name     Sex  Age  SibSp  \\\n",
        "0                            Braund, Mr. Owen Harris    male   22      1   \n",
        "1  Cumings, Mrs. John Bradley (Florence Briggs Th...  female   38      1   \n",
        "2                             Heikkinen, Miss. Laina  female   26      0   \n",
        "3       Futrelle, Mrs. Jacques Heath (Lily May Peel)  female   35      1   \n",
        "4                           Allen, Mr. William Henry    male   35      0   \n",
        "\n",
        "   Parch            Ticket     Fare Cabin Embarked  \n",
        "0      0         A/5 21171   7.2500   NaN        S  \n",
        "1      0          PC 17599  71.2833   C85        C  \n",
        "2      0  STON/O2. 3101282   7.9250   NaN        S  \n",
        "3      0            113803  53.1000  C123        S  \n",
        "4      0            373450   8.0500   NaN        S  \n",
        "\n",
        "[5 rows x 12 columns]"
       ]
      }
     ],
     "prompt_number": 17
    },
    {
     "cell_type": "code",
     "collapsed": false,
     "input": [
      "server.head()"
     ],
     "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>Time</th>\n",
        "    </tr>\n",
        "  </thead>\n",
        "  <tbody>\n",
        "    <tr>\n",
        "      <th>0</th>\n",
        "      <td>  452.42</td>\n",
        "    </tr>\n",
        "    <tr>\n",
        "      <th>1</th>\n",
        "      <td>  318.58</td>\n",
        "    </tr>\n",
        "    <tr>\n",
        "      <th>2</th>\n",
        "      <td>  144.82</td>\n",
        "    </tr>\n",
        "    <tr>\n",
        "      <th>3</th>\n",
        "      <td>  129.13</td>\n",
        "    </tr>\n",
        "    <tr>\n",
        "      <th>4</th>\n",
        "      <td> 1216.45</td>\n",
        "    </tr>\n",
        "  </tbody>\n",
        "</table>\n",
        "<p>5 rows \u00d7 1 columns</p>\n",
        "</div>"
       ],
       "metadata": {},
       "output_type": "pyout",
       "prompt_number": 18,
       "text": [
        "      Time\n",
        "0   452.42\n",
        "1   318.58\n",
        "2   144.82\n",
        "3   129.13\n",
        "4  1216.45\n",
        "\n",
        "[5 rows x 1 columns]"
       ]
      }
     ],
     "prompt_number": 18
    },
    {
     "cell_type": "code",
     "collapsed": false,
     "input": [
      "mlb.head()"
     ],
     "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>Year</th>\n",
        "      <th>Player</th>\n",
        "      <th>Salary</th>\n",
        "      <th>Position</th>\n",
        "      <th>Team</th>\n",
        "    </tr>\n",
        "  </thead>\n",
        "  <tbody>\n",
        "    <tr>\n",
        "      <th>0</th>\n",
        "      <td> 1988</td>\n",
        "      <td>       Mike Witt</td>\n",
        "      <td> 1400000</td>\n",
        "      <td>           Pitcher</td>\n",
        "      <td> Los Angeles Angels</td>\n",
        "    </tr>\n",
        "    <tr>\n",
        "      <th>1</th>\n",
        "      <td> 1988</td>\n",
        "      <td> George Hendrick</td>\n",
        "      <td>  989333</td>\n",
        "      <td>        Outfielder</td>\n",
        "      <td> Los Angeles Angels</td>\n",
        "    </tr>\n",
        "    <tr>\n",
        "      <th>2</th>\n",
        "      <td> 1988</td>\n",
        "      <td>     Chili Davis</td>\n",
        "      <td>  950000</td>\n",
        "      <td>        Outfielder</td>\n",
        "      <td> Los Angeles Angels</td>\n",
        "    </tr>\n",
        "    <tr>\n",
        "      <th>3</th>\n",
        "      <td> 1988</td>\n",
        "      <td>   Brian Downing</td>\n",
        "      <td>  900000</td>\n",
        "      <td> Designated Hitter</td>\n",
        "      <td> Los Angeles Angels</td>\n",
        "    </tr>\n",
        "    <tr>\n",
        "      <th>4</th>\n",
        "      <td> 1988</td>\n",
        "      <td>       Bob Boone</td>\n",
        "      <td>  883000</td>\n",
        "      <td>           Catcher</td>\n",
        "      <td> Los Angeles Angels</td>\n",
        "    </tr>\n",
        "  </tbody>\n",
        "</table>\n",
        "<p>5 rows \u00d7 5 columns</p>\n",
        "</div>"
       ],
       "metadata": {},
       "output_type": "pyout",
       "prompt_number": 19,
       "text": [
        "   Year           Player   Salary           Position                Team\n",
        "0  1988        Mike Witt  1400000            Pitcher  Los Angeles Angels\n",
        "1  1988  George Hendrick   989333         Outfielder  Los Angeles Angels\n",
        "2  1988      Chili Davis   950000         Outfielder  Los Angeles Angels\n",
        "3  1988    Brian Downing   900000  Designated Hitter  Los Angeles Angels\n",
        "4  1988        Bob Boone   883000            Catcher  Los Angeles Angels\n",
        "\n",
        "[5 rows x 5 columns]"
       ]
      }
     ],
     "prompt_number": 19
    },
    {
     "cell_type": "heading",
     "level": 3,
     "metadata": {},
     "source": [
      "1: Histograms"
     ]
    },
    {
     "cell_type": "code",
     "collapsed": false,
     "input": [
      "plt.hist(titanic.Age.dropna(),bins=25)"
     ],
     "language": "python",
     "metadata": {},
     "outputs": [
      {
       "metadata": {},
       "output_type": "pyout",
       "prompt_number": 22,
       "text": [
        "(array([ 30.,  17.,  15.,   9.,  29.,  64.,  67.,  70.,  83.,  62.,  51.,\n",
        "         40.,  35.,  27.,  35.,  23.,  15.,   9.,  11.,  11.,   4.,   2.,\n",
        "          3.,   1.,   1.]),\n",
        " array([  0.42  ,   3.6032,   6.7864,   9.9696,  13.1528,  16.336 ,\n",
        "         19.5192,  22.7024,  25.8856,  29.0688,  32.252 ,  35.4352,\n",
        "         38.6184,  41.8016,  44.9848,  48.168 ,  51.3512,  54.5344,\n",
        "         57.7176,  60.9008,  64.084 ,  67.2672,  70.4504,  73.6336,\n",
        "         76.8168,  80.    ]),\n",
        " <a list of 25 Patch objects>)"
       ]
      },
      {
       "metadata": {},
       "output_type": "display_data",
       "png": "iVBORw0KGgoAAAANSUhEUgAAAeMAAAECCAYAAADNb78fAAAABHNCSVQICAgIfAhkiAAAAAlwSFlz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\n",
       "text": [
        "<matplotlib.figure.Figure at 0x10b9a9410>"
       ]
      }
     ],
     "prompt_number": 22
    },
    {
     "cell_type": "code",
     "collapsed": false,
     "input": [
      "plt.hist(server.Time, 25, color=sns.desaturate(\"indianred\",1))"
     ],
     "language": "python",
     "metadata": {},
     "outputs": [
      {
       "metadata": {},
       "output_type": "pyout",
       "prompt_number": 23,
       "text": [
        "(array([  53.,  125.,  133.,   97.,   93.,   83.,   65.,   48.,   40.,\n",
        "          36.,   27.,   23.,   25.,   27.,   13.,   19.,   14.,    9.,\n",
        "          11.,    7.,    9.,   11.,   12.,   10.,   10.]),\n",
        " array([   44.5   ,   162.1316,   279.7632,   397.3948,   515.0264,\n",
        "          632.658 ,   750.2896,   867.9212,   985.5528,  1103.1844,\n",
        "         1220.816 ,  1338.4476,  1456.0792,  1573.7108,  1691.3424,\n",
        "         1808.974 ,  1926.6056,  2044.2372,  2161.8688,  2279.5004,\n",
        "         2397.132 ,  2514.7636,  2632.3952,  2750.0268,  2867.6584,  2985.29  ]),\n",
        " <a list of 25 Patch objects>)"
       ]
      },
      {
       "metadata": {},
       "output_type": "display_data",
       "png": "iVBORw0KGgoAAAANSUhEUgAAAe0AAAECCAYAAADTpo+sAAAABHNCSVQICAgIfAhkiAAAAAlwSFlz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\n",
       "text": [
        "<matplotlib.figure.Figure at 0x107e7dad0>"
       ]
      }
     ],
     "prompt_number": 23
    },
    {
     "cell_type": "code",
     "collapsed": false,
     "input": [
      "plt.hist(mlb.Salary.dropna(), 25)"
     ],
     "language": "python",
     "metadata": {},
     "outputs": [
      {
       "metadata": {},
       "output_type": "pyout",
       "prompt_number": 24,
       "text": [
        "(array([  1.29580000e+04,   2.21800000e+03,   1.57700000e+03,\n",
        "          8.15000000e+02,   5.56000000e+02,   3.67000000e+02,\n",
        "          2.97000000e+02,   2.01000000e+02,   1.02000000e+02,\n",
        "          1.78000000e+02,   8.10000000e+01,   6.80000000e+01,\n",
        "          4.30000000e+01,   1.70000000e+01,   2.70000000e+01,\n",
        "          1.10000000e+01,   1.10000000e+01,   7.00000000e+00,\n",
        "          3.00000000e+00,   2.00000000e+00,   0.00000000e+00,\n",
        "          1.00000000e+00,   0.00000000e+00,   0.00000000e+00,\n",
        "          3.00000000e+00]),\n",
        " array([    62500.,   1380000.,   2697500.,   4015000.,   5332500.,\n",
        "          6650000.,   7967500.,   9285000.,  10602500.,  11920000.,\n",
        "         13237500.,  14555000.,  15872500.,  17190000.,  18507500.,\n",
        "         19825000.,  21142500.,  22460000.,  23777500.,  25095000.,\n",
        "         26412500.,  27730000.,  29047500.,  30365000.,  31682500.,\n",
        "         33000000.]),\n",
        " <a list of 25 Patch objects>)"
       ]
      },
      {
       "metadata": {},
       "output_type": "display_data",
       "png": "iVBORw0KGgoAAAANSUhEUgAAAfQAAAEOCAYAAAB/3+X1AAAABHNCSVQICAgIfAhkiAAAAAlwSFlz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\n",
       "text": [
        "<matplotlib.figure.Figure at 0x10bee4710>"
       ]
      }
     ],
     "prompt_number": 24
    },
    {
     "cell_type": "code",
     "collapsed": false,
     "input": [],
     "language": "python",
     "metadata": {},
     "outputs": []
    },
    {
     "cell_type": "heading",
     "level": 3,
     "metadata": {},
     "source": [
      "2: Boxplot"
     ]
    },
    {
     "cell_type": "code",
     "collapsed": false,
     "input": [
      "sns.boxplot(titanic.Age.dropna())"
     ],
     "language": "python",
     "metadata": {},
     "outputs": [
      {
       "metadata": {},
       "output_type": "pyout",
       "prompt_number": 26,
       "text": [
        "<matplotlib.axes.AxesSubplot at 0x10bb200d0>"
       ]
      },
      {
       "metadata": {},
       "output_type": "display_data",
       "png": "iVBORw0KGgoAAAANSUhEUgAAAd4AAAECCAYAAABQYraXAAAABHNCSVQICAgIfAhkiAAAAAlwSFlz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\nSZIk1cT/ARVk/T0mQk72AAAAAElFTkSuQmCC\n",
       "text": [
        "<matplotlib.figure.Figure at 0x10c0cce90>"
       ]
      }
     ],
     "prompt_number": 26
    },
    {
     "cell_type": "code",
     "collapsed": false,
     "input": [
      "sns.boxplot(titanic.Age, titanic.Sex, vert=False)"
     ],
     "language": "python",
     "metadata": {},
     "outputs": [
      {
       "metadata": {},
       "output_type": "pyout",
       "prompt_number": 27,
       "text": [
        "<matplotlib.axes.AxesSubplot at 0x10bf5b790>"
       ]
      },
      {
       "metadata": {},
       "output_type": "display_data",
       "png": "iVBORw0KGgoAAAANSUhEUgAAAgUAAAEMCAYAAABUe8VYAAAABHNCSVQICAgIfAhkiAAAAAlwSFlz\nAAALEgAACxIB0t1+/AAAEV9JREFUeJzt3X2QXXV9x/F3zGV5yCSbGILPqIx+rRZtFXyIwWWjQbTW\nUTtVR6k2qK3SDnUEyzRqpXQ6xoK2I61PI1LAB5zqWG1Ha0AQU7bxgfpsIV8xI1sfGEOS3fDoErL9\n4/xW1kyy7Gb33LP33PdrJpNz7t179vude/ecz/7Ob88BSZIkSZIkSZIkSZIkSZIkSZIkSZKkB7Sk\n6QK66d57903u2XNX02XUZtWqY2hrf23uDeyv19lf72pzbwDHHbdiTsf5B9VVyGLU6SxtuoRatbm/\nNvcG9tfr7K93tbm3w9FXoUCSJB2aoUCSJAGGAkmSVBgKJEkSYCiQJEmFoUCSJAGGAkmSVBgKJEkS\nAJ2mC5C64brrvsy2bSNNl3FIAwMdJib2Lfh2x8fHABgcXLng256LuvpbLNre32mnPY+TTz6l6TLU\nBYYC9YVt20bYvuNmeHCzB8eu212Fglsn23vAUs12jzHw1Y6hoE8YCtQ/HrySzunPbbqKrtq35VqA\nvutbC2fqM6T+4JwCSZIEGAokSVJhKJAkSYChQJIkFYYCSZIEGAokSVJhKJAkSYChQJIkFYYCSZIE\nGAokSVJhKJAkSYChQJIkFYYCSZIEGAokSVJhKJAkSYChQJIkFYYCSZIEGAokSVJhKJAkSUAfhoKR\nka2MjGxtugxJkmp1OMe6Tg11LGpbt34FgHXrhhquRJKk+kwd7+ai70YKJEnSwRkKJEkSYCiQJEmF\noUCSJAGGAkmSVBgKJEkSYCiQJEmFoUCSJAGGAkmSVBgKJEkSYCiQJEmFoUCSJAGGAkmSVBgKJEkS\nYCiQJEmFoUCSJAGGAkmSVPRcKIiIjRGxuek6JElqm54LBcBk0wVIktRGnSa/eURsBF4MHAU8DHgf\n8BLgROCtwPHAy4BlwG1lecm0158NvIoqKHwqM/+pi+VLktQqjYaCYllmviAiXgm8JTOfFRHDwFuA\nG4ANmTkZEV8Cnk4ZKYiIJwGvANZRjXhcFRFbMjNn+mZ7944zNjbG5s0X1NhSMwYGOkxM7Gu6jFrM\nt7fR0VvgiKULWJHUJ+6+hx07drRynwnt3m+Ojt4y59c0HQomge+U5XHgxrI8BgwA9wJXRsQdwCOB\nI6a99reBRwPXlvWVwOOAGUOBJEk6uKZDARx6jsCRwEvLyMExVKMGS6Y9vx34YWa+ECAizgG+90Df\nbMWKQVasGGTTpvPnWfbis2bNcnbuvL3pMmox3942b76A7WO3LWBFUp84+ihOOO6hnHvu25uupBZt\n3m8ezujOYgoFkwcs3wvcERFbqeYTfAt4+NTzmfm9iLgmIq6nmpPwNeDn3StbkqR2aTQUZObl05a3\nAFvK8neB02fx+vcA76mtQEmS+kgv/kmiJEmqgaFAkiQBhgJJklQYCiRJEmAokCRJhaFAkiQBhgJJ\nklQYCiRJEmAokCRJhaFAkiQBhgJJklQYCiRJEmAokCRJhaFAkiQBhgJJklQYCiRJEmAokCRJhaFA\nkiQBhgJJklT0XSgYGlrP0ND6psuQJKlWh3Os69RQx6K2bt1Q0yVIklS7wzne9d1IgSRJOjhDgSRJ\nAgwFkiSpMBRIkiTAUCBJkgpDgSRJAgwFkiSpMBRIkiTAUCBJkgpDgSRJAgwFkiSpMBRIkiTAUCBJ\nkgpDgSRJAgwFkiSpMBRIkiTAUCBJkgpDgSRJAgwFkiSp6DRdgNQ1u8fYt+Xapqvort1jAP3XtxbO\n7jE47qFNV6EuMRSoL6xdu67pEmY0MNBhYmLfgm93fEn1Iz44uHLBtz0XdfW3WLS6v5XHcuqppzZd\nhbrEUKC+MDy8geHhDU2XcUhr1ixn587bmy6jNvbX29ren+7nnAJJkgQYCiRJUvGAoSAi3nTA+jER\n8f76SpIkSU2YzZyCl0XEi4HXAU8ALgG21FqVJEnqugccKcjM04EvAtuBK4EzMvPsuguTJEndNZvT\nB88FzqYKBNuBt0fEI+ouTJIkdddsJhp+FDgrM88CngdcDXyz1qokSVLXzWZOwVMy83aAzJwE3h8R\nX6y3LEmS1G2zCQWrI+KzwGOBIeATVJMOJUlSi8zm9MGHgfcAtwO3UoWCy+ssSpIkdd9sQsGxmbkF\nIDP3Z+YlwGC9ZUmSpG6bTSi4KyIeObUSEacA99RXkiRJasJs5hScA3wBOCEivgs8GHh5rVVJkqSu\nm3GkoFzJcDfwdOBCYBfwMeCG+kuTJEnddMhQEBFvBc4HjgJ+C9gEfBI4mmrioSRJapGZRgpeC5ya\nmT8EXg18vkwyPAd4QTeKkyRJ3TNTKNifmXeW5fWUmyCVCxhN1l2YJEnqrpkmGu6LiFXAMuCplFAQ\nEccD93ahNkmS1EUzjRS8G/g28HXgksz8RUS8HLgW5xRIktQ6hxwpyMzPRMQ2qosXfbc8fBfwhsy8\nrhvFSTO57rovs23bSNNlzNv4+BidzlKWLVvedCm1GRjoMDGxr+ky5mTt2nUMD29ougypq2a8TkFm\n/gz42bT1L9RekTRL27aNMPrjmzl+cFXTpczL+PgeAJYNTjRcSX16rbPR8p4YCtRvZnPxImnROn5w\nFeedclrTZczLhddfDdDzfbTJ1Hsi9ZvZXOZYkiT1AUOBJEkCDAWSJKkwFEiSJMBQIEmSCkOBJEkC\nDAWSJKkwFEiSJMBQIEmSCkOBJEkCDAWSJKkwFEiSJMBQIEmSCkOBJEkCDAWSJKkwFEiSJMBQIEmS\nCkOBJEkCDAWSJKkwFEiSJKCPQ8HIyFZGRrY2XYYktZr72t7SabqApmzd+hUA1q0bargSSWov97W9\npW9HCiRJ0m8yFEiSJMBQIEmSCkOBJEkCDAWSJKkwFEiSJMBQIEmSCkOBJEkCDAWSJKkwFEiSJMBQ\nIEmSCkOBJEkCDAWSJKkwFEiSJMBQIEmSCkOBJEkCDAWSJKno1LXhiFgKfBk4AnhRZo4v0HZvzcyH\nLsS2JEnS/WoLBcAjgOWZefICb3dygbcnSZKoNxR8CHh8RFwKLAdWl8f/IjN/EBE3AyNAANcAg8Az\ngO2Z+dqIOBF4L7AUOBY4KzO3TW08Ip4MvA9YAuwCXpeZe2vsR5KkVqszFJwFfAr4JfCNzPxQRDwe\nuBR4DvBoYBi4FdgNPCMzz46IHRExCDwJOLcEiFcBZwLbpm3/I8DGzLwpIl4PnAe8Y7bF7d07ztjY\nGJs3XzDvRheLgYEOExP7mi6jFgfrbXT0FgaXLm2oIrXZ+K/uZnz0llnvH9r8swfz62909BZWrly5\nwBWpLnWGgiXl/ycDz42IV5b1VeX/XZn5U4CIuDMzbyqPjwNHAj8H/joi7qYaaThwTsITgQ9GBFTz\nFrKWLiRJ6hN1hoIpNwIfz8wrI+IRwKvK4zPNDVhCdWrgjDIS8DfAYw74mpuA12TmTyNiiPtPT8zK\nihWDrFgxyKZN58/lZYvamjXL2bnz9qbLqMXBetu8+QK4bVdDFanNBo88msFjV896/9Dmnz2YX39t\nGo3tB3WHgkngXcBHI+JPgRXA+dOeY4bljwOfjoj/A24AHnbA82cBH4uITnnsdQtfviRJ/aO2UJCZ\nPwGeXVZfdpDnH36I5aeVxX8s/w76usz8FrB+4SqWJKm/efEiSZIEGAokSVJhKJAkSYChQJIkFYYC\nSZIEGAokSVJhKJAkSYChQJIkFYYCSZIEGAokSVJhKJAkSYChQJIkFYYCSZIEGAokSVJhKJAkSYCh\nQJIkFYYCSZIEGAokSVLRabqApgwNrW+6BElqPfe1vaVvQ8G6dUNNlyBJree+trd4+kCSJAGGAkmS\nVBgKJEkSYCiQJEmFoUCSJAGGAkmSVBgKJEkSYCiQJEmFoUCSJAGGAkmSVBgKJEkSYCiQJEmFoUCS\nJAGGAkmSVBgKJEkSYCiQJEmFoUCSJAGGAkmSVBgKJEkSYCiQJElFp+kCpPkYHd/Dhddf3XQZ8zI6\nvgeg5/tok9HxPRx/7Oqmy5C6zlCgnrV27bqmS1gQg0cspdNZCsuWN11KbQYGOkxM7Gu6jFk7/tjV\nrfl8SXNhKFDPGh7ewPDwhqbLWBBr1ixn587bmy6jNm3vT2oL5xRIkiTAUCBJkgpDgSRJAgwFkiSp\nMBRIkiTAUCBJkgpDgSRJAgwFkiSpMBRIkiRJkiRJkiRJkiRJkiRJkiRJkiRJkqTZWtJ0Ad0QEQ8C\nPgA8BfgV8IbM/HGzVc1fRDwTeHdmro+IxwGXAfuBHwB/npmTTdZ3uCLiCOBS4NHAkcDfATfSnv6W\nAh8BApgE3kT1ubyMFvQ3JSKOA/4HeB5VX5fRkv4i4lvAeFndAWymXf1tAl4MHAH8MzBCC/qLiD8G\nNpbVo4HfAU4B3keP9wa/PtZdQrVv2Q/8CXAfc3jv+uXiRS8FBjLz2cBfAe9tuJ55i4jzqA4sR5aH\n/gF4W2YOUYW9lzRV2wI4A9hZenkB8H6q96wt/f0+sD8zTwHeAbyLdvU3Few+DNxJ1U9rPp8RcRRA\nZq4v/15Pu/obBtaW/eUwcAIt+Xxm5uVT7xtwA3A28E5a0FvxfGBZ2bf8LYexb+mXULAO+BJAZn4d\nOLnZchbEzcAfcP9oz9Myc2tZ/k9gQyNVLYxPU/2gQvUZvZcW9ZeZnwfeWFYfA+wBTmpLf8VFwAeB\nX5T11rx/VL9dHhMRWyLimoh4Fu3q7/nA9yPic8B/AP9Oyz6fEXEy8KTMvIR29XY3MBgRS4BBYII5\n9tcvoWAFsHfa+n1lmKVnZeZngX3THpp+KugOqg9ET8rMOzPzjohYThUQ3sFvflZ7uj+AzLwvIi6j\nGrb8BC16/yJiI9VIz1XloSW0qD+q0Y+LMvN0qlM/nzjg+V7vbw1wEvCHVP19kna9fwBvAy4oy23q\nbQQ4CriJaqTuYubYX08fGOdgL7B82vqDMnN/U8XUZHo/y4GxpgpZCBHxKOBa4IrMvJKW9QeQmRuB\nJ1CdAzxq2lO93t+ZwGkR8RXgd4HLqQ40U3q9v6QEgcz8EbALeMi053u9v9uAqzJzX2YmcA+/eSDp\n6f4iYiUQmfnV8lCb9i3nASOZ+QSqn70rqOaFTHnA/volFIwAvwdQhvq+12w5tfh2RJxall8IbJ3p\nixeziHgIcBVwXmZeVh5uU3+vKRO5oBruuw+4oS39ZeapmTlcztt+B3gt8KW29EcVet4LEBEPp9rR\nXtWi/q6nmssz1d8xwDUt6m8IuGbaemv2LcAy7h8V3wN0mGN/nfpqW1T+jeo3l5GyfmaTxSywqVmk\n5wIfiYgB4H+BzzRX0ry9jeo3k3dGxNTcgjcDF7ekv88Al0XEV6lS/Juphvva8v4daJJ2fT4/CvxL\nREztXM+kGi1oRX+Z+YWIGIqIb1D94vhnwE9oSX9UM/On//VZmz6bF1F9Nv+Lat+yieovgNrSnyRJ\nkiRJkiRJkiRJkiRJkiRJkiRJWhyWNl2ApHaIiBNXr1596+rVq7+/a9euG5uuR9Lc9csVDSXV70yq\nC6O8qelCJB2eJQ/8JZI0s4joAD8FngP8N/DMzNxRbsN7MdXNu74GPDEz10fE44APAKuBu4CzM/M7\njRQv6dccKZC0EF4E/KTcIOhzwBtLULgCeHVmPo3qNq5Tl+W+nOreFidR3Ub6Uw3ULOkAhgJJC+FM\n7j+w/yuwEXgq8MvM/EF5/FJgSUQsA55OdY32b1PdcXBZRKzqbsmSDtQvN0SSVJOIOI7qLqQnRcSb\nqU5LrqS6I9v0XzymTlcuBe7OzKdO28ajMnNPl0qWdAiOFEiarz8Crs7MR2XmYzPzMcC7qG6/uzIi\nTixf92pgf2buBX4UEWcARMQG4Lruly3pQI4USJqvjVS3aJ3ug8BfAqcDV0TEfmA7cE95/gzgQxFx\nHvAr4BXdKVWSJHVdRCyJiL+PiGPK+jkRcVHTdUk6NE8fSKpFZk4Cu4FvlgmFp1CdVpAkSZIkSZIk\nSZIkSZIkSZIkSZIkSZLUu/4fQCV4JJ0UvSMAAAAASUVORK5CYII=\n",
       "text": [
        "<matplotlib.figure.Figure at 0x10bf49790>"
       ]
      }
     ],
     "prompt_number": 27
    },
    {
     "cell_type": "code",
     "collapsed": false,
     "input": [
      "sns.boxplot(server.Time)"
     ],
     "language": "python",
     "metadata": {},
     "outputs": [
      {
       "metadata": {},
       "output_type": "pyout",
       "prompt_number": 28,
       "text": [
        "<matplotlib.axes.AxesSubplot at 0x10c31df10>"
       ]
      },
      {
       "metadata": {},
       "output_type": "display_data",
       "png": "iVBORw0KGgoAAAANSUhEUgAAAekAAAECCAYAAADaTS/WAAAABHNCSVQICAgIfAhkiAAAAAlwSFlz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\nrkJggg==\n",
       "text": [
        "<matplotlib.figure.Figure at 0x10c0e4710>"
       ]
      }
     ],
     "prompt_number": 28
    },
    {
     "cell_type": "code",
     "collapsed": false,
     "input": [
      "sns.boxplot(mlb.Salary)"
     ],
     "language": "python",
     "metadata": {},
     "outputs": [
      {
       "metadata": {},
       "output_type": "pyout",
       "prompt_number": 29,
       "text": [
        "<matplotlib.axes.AxesSubplot at 0x10c32fc10>"
       ]
      },
      {
       "metadata": {},
       "output_type": "display_data",
       "png": "iVBORw0KGgoAAAANSUhEUgAAAeEAAAEHCAYAAACZV/6RAAAABHNCSVQICAgIfAhkiAAAAAlwSFlz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\nkAAAAABJRU5ErkJggg==\n",
       "text": [
        "<matplotlib.figure.Figure at 0x10c323490>"
       ]
      }
     ],
     "prompt_number": 29
    },
    {
     "cell_type": "heading",
     "level": 3,
     "metadata": {},
     "source": [
      "3: Kernel Density Estimate Plot"
     ]
    },
    {
     "cell_type": "code",
     "collapsed": false,
     "input": [
      "sns.kdeplot(titanic.Age.dropna(), shade=True)"
     ],
     "language": "python",
     "metadata": {},
     "outputs": [
      {
       "metadata": {},
       "output_type": "pyout",
       "prompt_number": 31,
       "text": [
        "<matplotlib.axes.AxesSubplot at 0x105c28510>"
       ]
      },
      {
       "metadata": {},
       "output_type": "display_data",
       "png": "iVBORw0KGgoAAAANSUhEUgAAAfMAAAECCAYAAADqwT73AAAABHNCSVQICAgIfAhkiAAAAAlwSFlz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\niIiIiIiIiIiIjLT/H2DueuDzmC2PAAAAAElFTkSuQmCC\n",
       "text": [
        "<matplotlib.figure.Figure at 0x105c2d490>"
       ]
      }
     ],
     "prompt_number": 31
    },
    {
     "cell_type": "code",
     "collapsed": false,
     "input": [
      " sns.kdeplot(server.Time.dropna(), shade=True)"
     ],
     "language": "python",
     "metadata": {},
     "outputs": [
      {
       "metadata": {},
       "output_type": "pyout",
       "prompt_number": 32,
       "text": [
        "<matplotlib.axes.AxesSubplot at 0x105c41d10>"
       ]
      },
      {
       "metadata": {},
       "output_type": "display_data",
       "png": "iVBORw0KGgoAAAANSUhEUgAAAfwAAAECCAYAAAAbymV6AAAABHNCSVQICAgIfAhkiAAAAAlwSFlz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\niIiIiIiIiIiIiIiIiIiIiIiIOOf/B5oB4k01nWDfAAAAAElFTkSuQmCC\n",
       "text": [
        "<matplotlib.figure.Figure at 0x10b8ae250>"
       ]
      }
     ],
     "prompt_number": 32
    },
    {
     "cell_type": "code",
     "collapsed": false,
     "input": [
      "sns.kdeplot(mlb.Salary.dropna(), shade=True)"
     ],
     "language": "python",
     "metadata": {},
     "outputs": [
      {
       "metadata": {},
       "output_type": "pyout",
       "prompt_number": 33,
       "text": [
        "<matplotlib.axes.AxesSubplot at 0x10ce96c90>"
       ]
      },
      {
       "metadata": {},
       "output_type": "display_data",
       "png": "iVBORw0KGgoAAAANSUhEUgAAAd8AAAETCAYAAAB3KgyXAAAABHNCSVQICAgIfAhkiAAAAAlwSFlz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\nERERERERaSn/Hwlv75gSiL7wAAAAAElFTkSuQmCC\n",
       "text": [
        "<matplotlib.figure.Figure at 0x10ce99ad0>"
       ]
      }
     ],
     "prompt_number": 33
    },
    {
     "cell_type": "code",
     "collapsed": false,
     "input": [
      "sns.distplot(titanic.Age.dropna())"
     ],
     "language": "python",
     "metadata": {},
     "outputs": [
      {
       "metadata": {},
       "output_type": "pyout",
       "prompt_number": 34,
       "text": [
        "<matplotlib.axes.AxesSubplot at 0x10ced2590>"
       ]
      },
      {
       "metadata": {},
       "output_type": "display_data",
       "png": "iVBORw0KGgoAAAANSUhEUgAAAfMAAAERCAYAAABvg07CAAAABHNCSVQICAgIfAhkiAAAAAlwSFlz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\nTFmxkMQAAAAASUVORK5CYII=\n",
       "text": [
        "<matplotlib.figure.Figure at 0x10ce8cf10>"
       ]
      }
     ],
     "prompt_number": 34
    },
    {
     "cell_type": "code",
     "collapsed": false,
     "input": [
      " sns.distplot(server.Time.dropna())"
     ],
     "language": "python",
     "metadata": {},
     "outputs": [
      {
       "metadata": {},
       "output_type": "pyout",
       "prompt_number": 35,
       "text": [
        "<matplotlib.axes.AxesSubplot at 0x10cee4f50>"
       ]
      },
      {
       "metadata": {},
       "output_type": "display_data",
       "png": "iVBORw0KGgoAAAANSUhEUgAAAfwAAAERCAYAAACeiBVPAAAABHNCSVQICAgIfAhkiAAAAAlwSFlz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\n",
       "text": [
        "<matplotlib.figure.Figure at 0x105bdf410>"
       ]
      }
     ],
     "prompt_number": 35
    },
    {
     "cell_type": "code",
     "collapsed": false,
     "input": [
      " sns.distplot(mlb.Salary.dropna())"
     ],
     "language": "python",
     "metadata": {},
     "outputs": [
      {
       "metadata": {},
       "output_type": "pyout",
       "prompt_number": 36,
       "text": [
        "<matplotlib.axes.AxesSubplot at 0x10d0b9450>"
       ]
      },
      {
       "metadata": {},
       "output_type": "display_data",
       "png": "iVBORw0KGgoAAAANSUhEUgAAAgkAAAERCAYAAADxDzSTAAAABHNCSVQICAgIfAhkiAAAAAlwSFlz\nAAALEgAACxIB0t1+/AAAIABJREFUeJzt3XuYXNV55/tvXbqrqq8SqAXmZpvLa2NsTDAELIgUx2AG\nMhqTmTMXnOPDYANjzPg5CWQmHB2YOASGONgah+eJcSIgwODxZOCMJxMzQs4QjISwQbZBWObyIiQL\nDAK1bt3V3dXVddnnj72rKbWqurpbQlLt/n2eR09X7XXZa9WGrrfXWnsvEBERERERERERERERERER\nERERERERERERERERETniJKZLNLMk8C3gTKAIXO3ur9WlLwduAcrAfe5+T7MyZnYqcD9QBTYB17t7\nYGbXANdGddzm7o+aWQ54CBgA8sCV7r4zOmcK+BtglbuvqWtLF/A08If1x0VERGRuki3SLwc63X0J\ncBPwjVqCmXUAK4GLgWXAtWa2OCqTaVBmJbDC3ZcSBiefNbNjga8AS4BLgDvMrBO4DtgY5X0QuDk6\n5ynAWuAcIJjS1r8gDECmHhcREZE5aBUkXAA8BuDuzxB+OdecDmx29yF3LwFPAUujMqsblDnb3ddG\nr1cDFwHnAuvdveTuw8BmwhGIyfNGPy+KXncDXwSeoG4UxMz+IDr/xhn3XERERKbVKkjoA4br3lei\n6YRa2lBdWh7ob1Imxb5TG/V5W9VRO4a7v+DuL0fHAwAz+zRwqrvfG51j2ikUERERmZlWQcIw0Fuf\n392r0euhKWm9wN4mZSqEUwE1fU3yNqqjdqyZLwAfNbMnCKcs/szMzmzRLxEREWkh3SJ9PbAceNjM\nzgdeqEt7GTjNzBYCo4RTDXcS/oXfqMxzZrbM3Z8ELgUeB54FbjezDJAlnMLYFJ33MmBDlHct+0sA\nuPvv1g6Y2V8D33X3Fxrkn1StVoNEQgMOIiIyPyTm+KXXKkj4HnCxma2P3l9lZlcAPe6+ysxuANYQ\njkjc6+7bzWy/MtHPG4FV0cLEF4FHorsb7gLWRXWscPeimd0NPGBm6wjvkPhcg7bNeYFiIpFgcDA/\n1+JHvIGBXvWvTcW5b6D+tTv1b/6Zl39OB0EQxPk/hLj/hx7n/sW5b6D+tTv1r30tXtw3p+/7VmsS\nREREZJ5SkCAiIiINKUgQERGRhhQkiIiISEMKEkRERKQhBQkiIiLSkIIEERERaUhBgoiIiDSkIEFE\nREQaUpAgIiIiDSlIEBERkYYUJIiIiEhDChJERESkIQUJIiIi0pCCBBEREWlIQYKIiIg0pCBBRERE\nGkof7gbIwfezjZvYum0nJ7xvESd/4P2HuzkiItKmNJIQQ6VSlc7uBYwXi4e7KSIi0sYUJIiIiEhD\nChJERESkIQUJIiIi0pCCBBEREWlIQYKIiIg0NO0tkGaWBL4FnAkUgavd/bW69OXALUAZuM/d72lW\nxsxOBe4HqsAm4Hp3D8zsGuDaqI7b3P1RM8sBDwEDQB640t13RudMAX8DrHL3NdGxO4ELov78lbvf\nc+AfjYiIyPzWaiThcqDT3ZcANwHfqCWYWQewErgYWAZca2aLozKZBmVWAivcfSmQAD5rZscCXwGW\nAJcAd5hZJ3AdsDHK+yBwc3TOU4C1wDlAEB37FHBydL4LgT80s/65fyQiIiICrYOEC4DHANz9GcIv\n55rTgc3uPuTuJeApYGlUZnWDMme7+9ro9WrgIuBcYL27l9x9GNhMOAIxed7o50XR627gi8AThIEG\nwNPRsZoUUGrZcxEREZlWqycu9gHDde8rZpZ092qUNlSXlgf6m5RJ8e6X+tS8reqoHcPdXwAws8kC\n7l4EitHIxgPAX7r7WIt+iYiISAutgoRhoLfufS1AgPDLvT6tF9jbpEzFzKp1x/qa5G1UR+1YU2a2\nEHgYeMLdv9aiTwAMDPS2ztSmtmyD3p4sC7uD2PYzrv2CePcN1L92p/7NL62ChPXAcuBhMzsfeKEu\n7WXgtOgLepRwquFOwrUCjco8Z2bL3P1J4FLgceBZ4HYzywBZwimMTdF5LwM2RHnX0kS0yPFx4E53\n/+5MOz44mJ9p1raUHxknUarEsp8DA72x7BfEu2+g/rU79W/+aRUkfA+42MzWR++vMrMrgB53X2Vm\nNwBrCNc23Ovu281svzLRzxuBVdHCxBeBR6K7G+4C1kV1rHD3opndDTxgZusI75D4XIO2BdHPLwEf\nJFw4eW3tnO7+yxl/CiIiIrKfROss8RMEQRDnaHHLtq3sGKrSl6nwkQ9Z6wJtJs7Rfpz7Bupfu1P/\n2tfixX1z+r7Xw5RERESkIQUJIiIi0pCCBBEREWlIQYKIiIg0pCBBREREGlKQICIiIg0pSBAREZGG\nFCSIiIhIQwoSREREpCEFCSIiItKQggQRERFpSEGCiIiINKQgQURERBpSkCAiIiINKUgQERGRhhQk\niIiISEMKEkRERKQhBQkiIiLSkIIEERERaUhBgoiIiDSkIEFEREQaUpAgIiIiDSlIEBERkYYUJIiI\niEhD6ekSzSwJfAs4EygCV7v7a3Xpy4FbgDJwn7vf06yMmZ0K3A9UgU3A9e4emNk1wLVRHbe5+6Nm\nlgMeAgaAPHClu++MzpkC/gZY5e5romN/BFwW1fF77r7hwD8aERGR+a3VSMLlQKe7LwFuAr5RSzCz\nDmAlcDGwDLjWzBZHZTINyqwEVrj7UiABfNbMjgW+AiwBLgHuMLNO4DpgY5T3QeDm6JynAGuBc4Ag\nOnY2sNTdzwP+FfAXc/84REREpKZVkHAB8BiAuz9D+OVcczqw2d2H3L0EPAUsjcqsblDmbHdfG71e\nDVwEnAusd/eSuw8DmwlHICbPG/28KHrdDXwReKKuHRcCa6LzvQGkzezoGfVeREREmmoVJPQBw3Xv\nK9F0Qi1tqC4tD/Q3KZMiHD1olLdVHbVjuPsL7v7ylDb2TjnfZP75LAgCRkZGGB4eIgiCw90cERFp\nQ9OuSSD88u2te59092r0emhKWi+wt0mZiplV6471NcnbqI7asZm2sVV+AAYGeltlaVtbtkEyUea1\nN95hrBTwmaW/Rn9/3+Fu1kEV5+sX576B+tfu1L/5pVWQsB5YDjxsZucDL9SlvQycZmYLgVHCqYY7\nCdcKNCrznJktc/cngUuBx4FngdvNLANkCacwNkXnvQzYEOVdy/5qIxPrgT8zs68DJxIGJbtbdXxw\nMN8qS1sbGRknIE2lmmLnzjwTE/G5kWVgoDe21y/OfQP1r92pf/NPqyDhe8DFZrY+en+VmV0B9Lj7\nKjO7gXA9QBK41923m9l+ZaKfNwKrooWJLwKPRHc33AWsi+pY4e5FM7sbeMDM1hHeIfG5Bm0LANz9\nZ1G+H0V1fHnWn4KIiIjsJ9E6S/wEQRDEOVrcsm0rW98c4p0dgxyzeIBzP/pB+vris0wjztF+nPsG\n6l+7U//a1+LFfXP6vo/PGLSIiIgcVAoSREREpCEFCSIiItKQggQRERFpqNXdDdLmgiAgnw+fNdXb\n20ciMS/XqoqIyBxoJCHmCmOj/Pj5V1m74ReTwYKIiMhMaCRhHsjlushks4e7GSIi0mY0kiAiIiIN\nKUgQERGRhhQkiIiISEMKEkRERKQhBQkiIiLSkIIEERERaUhBgoiIiDSkIEFEREQaUpAgIiIiDSlI\nEBERkYYUJIiIiEhDChJERESkIQUJIiIi0pCCBBEREWlIQYKIiIg0pCBBREREGlKQICIiIg2lp0s0\nsyTwLeBMoAhc7e6v1aUvB24BysB97n5PszJmdipwP1AFNgHXu3tgZtcA10Z13Obuj5pZDngIGADy\nwJXuvtPMzge+GeX9gbvfGrXjNuAiIABudPenD8JnIyIiMq+1Gkm4HOh09yXATcA3aglm1gGsBC4G\nlgHXmtniqEymQZmVwAp3XwokgM+a2bHAV4AlwCXAHWbWCVwHbIzyPgjcHNXxbeAKd78QOM/MzjKz\nDwOfdvfzgc8Dd8394xAREZGaVkHCBcBjAO7+DHBOXdrpwGZ3H3L3EvAUsDQqs7pBmbPdfW30ejXh\nX/7nAuvdveTuw8BmwhGIyfNGPy8ys17CgGVrdHxNVEcR6DKzDNAPTMzuIxAREZFGWgUJfcBw3ftK\nNJ1QSxuqS8sTfkk3KpMiHD1olLdVHc3qzQP9UdDwc+Bl4O+Br7fok4iIiMzAtGsSCL+Ue+veJ929\nGr0empLWC+xtUqZiZtW6Y31N8jaqo1m9fcBeM/sc4VqEk6NjT5nZM+7+5nQdGxjonS65rW3ZBj09\nWYbzHXR3Z0mlUmRzWRYt6qW/Px79jvP1i3PfQP1rd+rf/NIqSFgPLAcejhYNvlCX9jJwmpktBEYJ\npxruJPzCblTmOTNb5u5PApcCjwPPArdHUwVZwimMTdF5LwM2RHnXunvezCbM7GRgK/AZ4KvAWcBI\ntAhyhGj6oVXHBwfzrbK0tZGRcQqFEunkOKlUmnIlwc6deSYm2v+GloGB3thevzj3DdS/dqf+zT+t\ngoTvAReb2fro/VVmdgXQ4+6rzOwGwrUBSeBed99uZvuViX7eCKyKFia+CDwSfbHfBayL6ljh7kUz\nuxt4wMzWEX7pfy6q40vAd4AUsMbdN5jZ88AFZvZ0VMdD7v7qgXwoIiIisu86gXkjCIIgztHilm1b\n2frmEO/sGKS3O0cqlSaTzXLuRz9IX1//4W7eAYtztB/nvoH61+7Uv/a1eHHfnL7v23/sWRqqVgPK\nlWrrjCIiIk0oSIipV7YN8vLrw1SqChRERGRuFCTE1GhhgnI1YLRQPtxNERGRNqUgIaYq0VTD6Hjp\nMLdERETalYKEmCpXFSSIiMiBUZAQU9VqAKDpBhERmTMFCTFVP90QBMFhbo2IiLQjBQkxVYlGEirV\ngPGJymFujYiItCMFCTEUBMHkSAKEdzqIiIjMloKEGKpWA+onGEa0eFFEROZAQUIM1Z60mMukABjR\nSIKIiMyBgoQYKpXDICHbkSKdSjBa0EiCiIjMnoKEGCpXwoWKyQR0ZzsoFMvax0FERGZNQUIM1UYS\nEskE3dkOAEbGioezSSIi0oYUJMRQbdQglUjQnQuDhLyCBBERmSUFCTFUjkYSkknozqYByI8qSBAR\nkdlRkBBDpck1CQm6JqcbdIeDiIjMjoKEGHp3JCFBKpmgK5MmP1bU45lFRGRWFCTEUG3hYjKRAKAr\n20G5UmVMD1USEZFZUJAQQ7WFi8no6qZT4YvihIIEERGZOQUJMVSeMpJQCxLGJ7RttIiIzJyChBia\nXLiY3DdIKCpIEBGRWVCQEEPvjiSE798dSdB0g4iIzJyChBh6d01CbSQh/KmRBBERmY30dIlmlgS+\nBZwJFIGr3f21uvTlwC1AGbjP3e9pVsbMTgXuB6rAJuB6dw/M7Brg2qiO29z9UTPLAQ8BA0AeuNLd\nd5rZ+cA3o7w/cPdbo3b8a+BLhEHPf3f3Pz3wj6Z9Tb27YXIkoaggQUREZq7VSMLlQKe7LwFuAr5R\nSzCzDmAlcDGwDLjWzBZHZTINyqwEVrj7UiABfNbMjgW+AiwBLgHuMLNO4DpgY5T3QeDmqI5vA1e4\n+4XAeWZ2lpmdQhggLAPOB3rMbNrgJ+7KU9YkpGprEkoKEkREZOZaBQkXAI8BuPszwDl1aacDm919\nyN1LwFPA0qjM6gZlznb3tdHr1cBFwLnAencvufswsJlwBGLyvNHPi8yslzBg2RodXxPV8WngJ4TB\nxA+Bde4+r78NS83WJBS1JkFERGauVZDQBwzXva9E0wm1tKG6tDzQ36RMinD0oFHeVnU0q7d2fBFh\ncPIF4J8Bd5lZf4t+xVq5XCWRSJBI6O4GERGZu1bD8sNAb937pLtXo9dDU9J6gb1NylTMrFp3rK9J\n3kZ1NKu3VscI8EN3HwVGzewl4DTC0YWmBgZ6p0tua+VKlXQqSS7XQXd3llz0NOYq8el3XPrRSJz7\nBupfu1P/5pdWQcJ6YDnwcLRo8IW6tJeB08xsITBK+Nf8nUDQpMxzZrbM3Z8ELgUeB54FbjezDJAl\nnMLYFJ33MmBDlHetu+fNbMLMTga2Ap8BvgoUgOujOtLARwinLaY1OJhvlaVtlSpVUskEhUKJdHKc\nZDIFQH6kEIt+Dwz0xqIfjcS5b6D+tTv1b/5pFSR8D7jYzNZH768ysyuAHndfZWY3EK4NSAL3uvt2\nM9uvTPTzRmBVtDDxReCR6O6Gu4B1UR0r3L1oZncDD5jZOsI7JD4X1fEl4DtACljj7hsAzOxewsAi\nAdzq7nvn/pG0v3K5MrloESCRSJBKJfXERRERmZVE6yzxEwRBEOdoccU3HyGX7eCUY7vo7c6RSqX5\n8S/eIpvpYMW1yw938w5YnKP9OPcN1L92p/61r8WL++b0fa+HKcVMEASUK1VSyX0vbTqV1BMXRURk\nVhQkxEy5HD4jIZXcN2hMp5MUJyoEQXA4miUiIm1IQULMTJSiICE1dSQhRRAETOiBSiIiMkMKEmJm\nohwGAVNHEjrS4aUu6IFKIiIyQwoSYqY2UrD/SIKeuigiIrOjICFmJqcbpi5cTIfPSlCQICIiM6Ug\nIWYmRxKmLlxMabpBRERmR0FCzDRbuFhbkzBenDjkbRIRkfakICFmSi1GEjTdICIiM6UgIWYmys1v\ngQRNN4iIyMwpSIiZd9ckNJtuUJAgIiIzoyAhZlovXNSaBBERmRkFCTHT9DkJugVSRERmSUFCzLz7\nnIQpT1zUwkUREZklBQkxU2oykpBMJkgmEgoSRERkxhQkxMzk3Q1TFi4mEgkynWltFy0iIjOmICFm\nmi1cBMhm0roFUkREZkxBQsw0W7gIkOns0HSDiIjMmIKEmCk1WbgIkO1MM1EqU6lUD3WzRESkDSlI\niJmJUpl0KkkisX+QkOlMA2hdgoiIzIiChJiZKFUmH5w0VbazA9BtkCIiMjMKEmJmolQmnW58WWsj\nCVq8KCIiM6EgIWYmSuXJBydNla1NN+jRzCIiMgMKEmKmVK60HEnQdIOIiMxEerpEM0sC3wLOBIrA\n1e7+Wl36cuAWoAzc5+73NCtjZqcC9wNVYBNwvbsHZnYNcG1Ux23u/qiZ5YCHgAEgD1zp7jvN7Hzg\nm1HeH7j7rXVt6QKeBv7Q3dcc6AfTjqpBEAYJ0bbQU2Uz4ZoETTeIiMhMtBpJuBzodPclwE3AN2oJ\nZtYBrAQuBpYB15rZ4qhMpkGZlcAKd18KJIDPmtmxwFeAJcAlwB1m1glcB2yM8j4I3BzV8W3gCne/\nEDjPzM6qa+tfEAYgwew/hnioPZK56UhCh0YSRERk5loFCRcAjwG4+zPAOXVppwOb3X3I3UvAU8DS\nqMzqBmXOdve10evVwEXAucB6dy+5+zCwmXAEYvK80c+LzKyXMGDZGh1fE9WBmf1BdP6Ns+t+vNQ2\nd2q6JiFTW7ioNQkiItJaqyChDxiue1+JphNqaUN1aXmgv0mZFOHoQaO8repoVm8e6DezTwOnuvu9\n0Tn2f0DAPFEqtxhJ0C2QIiIyC9OuSSD8Uu6te59099rj+oampPUCe5uUqZhZ/WP++prkbVRHs3pr\nx78AvN/MngA+DPyamW139xem69jAQO90yW2pWAm//DvSKXp6sgznO+juzpJKpcjmsrzvmP4wY6L9\n+9/u7Z9OnPsG6l+7U//ml1ZBwnpgOfBwtGiw/ov3ZeA0M1sIjBJONdxJuCagUZnnzGyZuz8JXAo8\nDjwL3G5mGSBLOIWxKTrvZcCGKO9ad8+b2YSZnQxsJVzD8FV3r18n8dfAd1sFCACDg/lWWdrOOzvC\ngZZ0KsnIyDiFQol0cpxUKk25kmBstAjA3qGxtu7/wEBvW7d/OnHuG6h/7U79m39aBQnfAy42s/XR\n+6vM7Aqgx91XmdkNhGsDksC97r7dzPYrE/28EVgVLUx8EXgkurvhLmBdVMcKdy+a2d3AA2a2jvAO\nic9FdXwJ+A6QAta4+4YD7H+s1DZ3avbERT2WWUREZmPaIMHdA8I7DfY5XJf+feD7MyiDu78K/GaD\n4/cA90w5VgD+RYO8zwCfnKa9VzVLmw8mFy42WZOQSibp7EhTGFeQICIirelhSjEyOZKQbvycBAif\nlaCRBBERmQkFCTFSajHdAJDLdFAY1y2QIiLSmoKEGGk13QDhTpDjEyWCYN4+c0pERGZIQUKMtFq4\nCJDNdlCtho9vFhERmY6ChBiZKLceSejOZQDIj44fkjaJiEj7UpAQIzMZSVjY1wXAnuGxQ9ImERFp\nXwoSYmQmdzcs7OsGYO/w6CFpk4iItC8FCTFSarHBE7wbJOxWkCAiIi0oSIiRiRZbRQMc1R8GCZpu\nEBGRVhQkxEhxIgwSOqaZbujvzZEA9gxpJEFERKanICFGxooTdKRT0y5cTKdS9PXk2KPpBhERaUFB\nQowUxifoyna2zLewr5uhfIFKtdoyr4iIzF8KEmJkbHyC3EyChP4uqkHA8EjhELRKRETalYKEmKhU\nq4wXS9OOJARBwPDwEF2ZcPPP3VqXICIi05h2q2hpH+PR9s/NgoQgCNi+/S02/2ovO3aPALrDQURE\npqeRhJgYi3Z2bDbdUBgbZd2GTSSTSfp6otsgNZIgIiLTUJAQE7UgYbrphmxnuG9DLtMBoDscRERk\nWgoSYmImQUJNNlqToOkGERGZjoKEmCjUphtyrYOEVDJJT1dGIwkiIjItBQkxMTZeBGY2kgCwoCfH\n3vwYVT0rQUREmlCQEBOzmW4A6O/NUq0GDI+Mv5fNEhGRNqYgISYKsw0SenKAFi+KiEhzChJiotUt\nkFP194ZBgraMFhGRZhQkxMRspxsW1EYS9KwEERFpYtonLppZEvgWcCZQBK5299fq0pcDtwBl4D53\nv6dZGTM7FbgfqAKbgOvdPTCza4Brozpuc/dHzSwHPAQMAHngSnffaWbnA9+M8v7A3W+N2nEncEHU\nn79y93sOwmfTVgrjE6SSSTo7ZvYQzQW9tekG3QYpIiKNtRpJuBzodPclwE3AN2oJZtYBrAQuBpYB\n15rZ4qhMpkGZlcAKd18KJIDPmtmxwFeAJcAlwB1m1glcB2yM8j4I3BzV8W3gCne/EDjPzM4ys08B\nJ0fnuxD4QzPrn/tH0p5qmzslEomWeYMgIBmEIw9akyAiIs20ChIuAB4DcPdngHPq0k4HNrv7kLuX\ngKeApVGZ1Q3KnO3ua6PXq4GLgHOB9e5ecvdhYDPhCMTkeaOfF5lZL2HAsjU6viaq42ngi3XtSgGl\nmXU/PsYKM9smGsJHNP9k0xY60kl27c2/xy0TEZF21SpI6AOG695XoumEWtpQXVoe6G9SJkU4etAo\nb6s6mtWbB/rdvejue6ORjQeAv3T3eTWGXg0CCi12gJwql+uiK9vJ0Mg4lYqelSAiIvtrNYE9DPTW\nvU+6e+0bZWhKWi+wt0mZipnVfxP1NcnbqI5m9dbqwMwWAg8DT7j711r0CYCBgd7WmdrEWKFIEAQs\n6O9iYKCXLdugpyfLcL6D7u4sqVSKSiVNsZihuztDpZImlUrRlU0zNDLO8FgeO/mEw92NWYnT9Zsq\nzn0D9a/dqX/zS6sgYT2wHHg4WjT4Ql3ay8Bp0Rf0KOFUw51A0KTMc2a2zN2fBC4FHgeeBW43swyQ\nJZzC2BSd9zJgQ5R3rbvnzWzCzE4GtgKfAb4aLXJ8HLjT3b87044PDsZnmH3X3nDr51QyOdmvkZFx\nCoUS6eQ4qVSaSqVMYbTIaFeRSqVMKpWmO5MC4GebtrGwt32WcQwM9Mbq+tWLc99A/Wt36t/802q6\n4XvAuJmtJ1yA+PtmdoWZXROtQ7iBcG3A08C97r69UZmorhuBPzazpwmDk0fc/R3gLmAd4Rf9Cncv\nAncDZ5jZOuBq4I+jOr4EfAd4BviZu2+Ijn2QcOHkE9G/DxzYx9JeZnv7Y83C3nBXyC2/2nXQ2yQi\nIu1v2pEEdw8I7zTY53Bd+veB78+gDO7+KvCbDY7fA9wz5VgB+BcN8j4DfHLKsf8E/Kfp+hF3s33a\nYk22M022I8m27bspVyqkU6n3onkiItKm9DClGJjt0xbr9Xd3MFGq8Pr23Qe7WSIi0uYUJMTAXKcb\nAPq6OgDwX759UNskIiLtT0FCDMx1ugHCICGZTChIEBGR/ShIiIEDmW5IJROceMwC3nxnD6NjxYPd\nNBERaWMKEmLgQEYSAE4+YREB8Orr7xzEVomISLtTkBADB7ImAeDk448GtC5BRET2pSAhBsbGJ0gk\nEmQyHXMqf+yiPrqynby67R2CIDjIrRMRkXalICEGCuMT5DIdJGewA+RUQRAwMpLn5BOOZmikwMZX\n3miYZ3h4SAGEiMg8oyAhBsbGJ+jKzW2qYbwwxo+ff5VcR0A6leRv/+E5Rgv7LmDM54dZ8+Sz5PPD\nTWoREZE4UpDQ5oIgYGx8glxmbkEChDtCHrWgj2WfOJXRQpFHn9y4X55sNncgzRQRkTakIKHNlcoV\nKpXqnBct1jvvY+/nuMUL+MkvfqlFjCIioiCh3Y0V5v6MhHpBEDA6OsKys04E4L899iwbX3mDSqXa\noqSIiMRVq62i5Qh3oLc/1hTGRvnx83uoVCuccHSOX+0q8J3v/4iergx24lEM5cd4aevbnPi+gPcN\n9JOIFkkGQUA+P0xvb9+0x0REpP0oSGhzBytIgHBtQqVS5rijEyz/rU/w05de56cvvsHPXtkOwGtv\nhWsV3reoj3PPOInzPm4UCqOsefJZLln26/T19QPvLnSsPyYiIu1HQUKbm3za4hzvbmjm6AXdfOaT\np9Pb1cmOnXsYK4xzygdOZNtbu3ll2w7+55ObePxZ5zfOPoXOTHa/8lroKCLS/hQktLmx8fB2xQNd\nk1CvNl0AkE4lWdCTIZcO+PWPvp9f/+j7WfsT5/V39vLW4DCPrX+JXGeKgUVvcdZHcgdlRENERI4M\nChLa3MGcbqipPTuhUq3Q0927X3ou28GH3j/A5Z/6OE899xo/ffEN/scTP+d/PPFzjl3Uz3GLehnO\nj/Lmjr1ksl0Ux8cmH8TU19e/zzqF+oBEaxhERI4sChLa3IFu7tRMbX1CTf2Xee19UClywZknEJTH\nSXVk2LEUFZReAAAPnElEQVRnjDd3DPH2ziEANr/5DMlkgv7uTnpzKbo7qvyzy5bts04hnx9m7YZf\nALD03DO0hkFE5AiiIKHNHcg20bMxdXShUilP3g0xMTZGV08vJy3u4opLP8GO3SOs3fASC/r7eOPt\nPby9K8+efFjPf33sp1xw9oc4flEXyWSSIAjI5bpm1IZaoLJoUc972FMREalRkNDm3ovphmamji7U\n3hfHxsjluujMZBgbHaEnA8cszPGJM46Hjx3Pc/42b769m7d3j7D5jZ1sfmMnHekkfV2dnHrSIkrl\ngKP7WwcKtbsmfnfRp9EjPkRE3nsKEtpYqVxhyxuDdGU7j4gFg/XPWiiOjfHj50uTIw/HLerm6J4U\nH//oh/jZS7/i55vfYtfwOLs2/QqAjnSSPfki5338VN63aAHj46PA/usUZnrXhNY6iIgcOAUJbewF\nf4Ox8Ql+89wPkUweGX9ZTx1dmLquoasTLvz4CSxakKM4Uaavu5ONr77N9p15fvLi6/zkxdcByHam\n6Mp2cOKxR3PUgl7SyYAkFfbki+zYlae/J/zib/bgppmudZhtMKHgQ0TmEwUJbexHz28mAZz/8VMO\nd1NmZOq6hkw2ywePW0ixVOWERTkG94ySL1QIgoDdw0V2D4+ze/jN/erZ9FdrWLSghw9/cDHvP6aH\nVza/zj/61Hn7BQIzWesw24WTWmgpIvPJtEGCmSWBbwFnAkXgand/rS59OXALUAbuc/d7mpUxs1OB\n+4EqsAm43t0DM7sGuDaq4zZ3f9TMcsBDwACQB650951mdj7wzSjvD9z91qgdfwRcFh3/PXffcBA+\nmyPar97Zzevbd3P6ye/jqP72Wcg3dXShJplIcNzAAiqVMm+//RYf/thJJFJpTlzcx1ixxOY3dpMf\nHWN8fIKBgaPZ9OpbPPXcFp4CUskEg6PPcsKxR08uhiwWi7w1uJdKpcprv9rJ4qP6OeHYRfR2pVm0\noJujFi6cHAWY6cLJ+j7M1ExHHmr5OjurBEFCIxQickRoNZJwOdDp7kvM7DzgG9ExzKwDWAmcA4wB\n683sfwIXApkGZVYCK9x9rZndDXzWzH4MfAX4BJADnjKzvweuAza6+61m9i+Bm4HfA74N/I67bzWz\nR83sLMIVbEvd/TwzOxH4/4BfP0ifzxHrR8+Hsdonzzr1MLdk7sIvxvx+x7OdGQDKE+O8smWYSrXC\ngu5eerPdjBeS/OPfOp1PnnEc6194ne2DQ+RHi2zbvodt2/c0PtEu2PzGbti4dfLQgt4cA0f1USgU\n2T08SrlS5acvvUl/bxeZjhTduU6OWtBLKhGQTqfo6e4mlUyyZ2iIX761m0o1oL+3m4+cNv0DpGY6\n8lDL19Od4eyPnHrQRyi0n4aIzEWrIOEC4DEAd3/GzM6pSzsd2OzuQwBm9hSwFPgksLpBmbPdfW30\nejXwGaACrHf3ElAys82EIxAXAF+L8j4G3GJmvYQBS+03/RrgIsLRih9E53vDzNJmdrS775rlZ9E2\nxgpFnnv5dY5e0IN94NjD3Zw5K4yNsm7Lqxx//ElN80wdeRgvjPHkMy8ynB/jqJ5e+nMLGS8UOOfM\n09ibL/Dy1neAgJOO6WPXSIVSsUAylWZkbJy3d+yiI9tDYaLCeLHEq9veIZGAjnSKVDLJSKHIzr2j\nM27/5jd2kfjBcyxa2E1/T47uXIaF/T37rA8pFotsHxwD4Onnt7BgQR/Zzg6K4wUSiQTZbI6x4gS7\ndg+x7Z0RerrLZDLbOe6YMl25TnKZDjo70owX9l3IOZu1EUEQsGNwJ2vW/pQl53yUvt4+UqkkiUR4\nDZLJJP19faTTKRLA2NgIiURiVms0FHyIxFOrIKEPGK57XzGzpLtXo7ShurQ80N+kTApINMnbqo5m\n9eaBk4FxYFeDOmIbJGz4xS8plyuc//FTSLb5L+baqMFs5HJdlErB5Pvxwhg/+8UWKtUK/T3hMxxe\n9Nc4/viTSHSkSKVSpHsyMJHh6IGjqFTKTExMMFEukx/aywknHE9nJsPpH1hEpVLl56/tYHg4zzuD\nO+lbcDSVcpmJcplUKs3xi3oYKYbn7kwneXNwmLcGhxnc0zq42PLm7hn17xeb397vWCIRPiI7l+kg\nkUhSLJWYmCiTSibp68mSy3QSEFCtBlSqVarVgIAElUqVkbFxytGW35u2PT2jNgCkUglymU56ujL0\n5DrJdnbQ2ZGipzucbilXqowVCrz59iCnnHQc3d1dJKMApjhRpLMzA9Hr8IGbAV1dGcpTZptq00M1\nnZ0ZkskE5XKJ7q5ceP1SSdKpJKlkklKpSCqZpKenh450mJZIJKJ/vPsa9jkWBOHnMzKSJ5frphoE\n4bEgoFqtMjI6CkFANtcFJCAIGCuEAV5XrotkKkkykSCZTLz7MxmeOxmdp1gpsWfP2H7Xru5dg1f7\nvknU3tSORdu4A3R395JMNv5/vtF5mv16SOx7wsZtalBBOpNkeKQwXZaGNc3k11Ri/7MfkICgdaYp\nMiPhHxSHS7PPoNaXVCpJLnNo72RrFSQMA/XP5a0FCBB+uden9QJ7m5SpmFm17lhfk7yN6mhWb62O\niSZ1xNaOXcPkMh2ce8YHGqYH1Qqjw7spjhdIpyCVTFGpVhifKFIojFGpVg7Ksfeq3pmcqzBe2OdY\nV/SfQK1c/etm9aaS4S/2QmGMkdE8T2x/k2qlTHdPH6lkhe4M9OcSVKpJUskclWqF13+5mWOPO5FK\ntUJhpMiCzjLZRdC/4CiKpTKFQpFqtcLY6Cg9vX1UqxVyuW4q1Qp7du0i09VLuVKhszNLNagyMjxE\nT08PqUSV7u5uEskEu/eOUixVKBYnSHVkwi/4RIpKtcpYoUhXLkN3toN0MkGlGjBaKLJrKPxiSiTC\nX88JIJvpIJ1OMbCwh1wmxZ69QyQTSapBFUhQDQJSqTRBEFAqlTj6qAVUqwHDIwUqlQoTEyUmJiZ4\np1Dk7Ra/bwd//suD8t+2iDSXAK68/EI+cspxh+ycrYKE9cBy4OFo0eALdWkvA6eZ2UJglHCq4U4g\naFLmOTNb5u5PApcCjwPPArebWQbIEk5hbIrOexmwIcq71t3zZjZhZicDWwmnK75KOGXxZ2b2deBE\nwqBk2j/ZEjEZF7371sPdAhEROZT++mut8xxMrYKE7wEXm9n66P1VZnYF0OPuq8zsBsK1AUngXnff\nbmb7lYl+3gisMrNO4EXgkejuhruAdVEdK9y9GC1sfMDM1hGuOfhcVMeXgO8AKWBN7S6GKN+Pojq+\nPPePQ0REREREREREREREREREREREREREREREDrlY3ArYSrO9IKbk+XPCJz3mCW/jvNzdh6fWdaSY\ny74ah6WhczSD/v0+8EVgMDr0b9zdD3lDD0D02PI/dfdPTTne1teuZpr+xeHadQD3Ae8HMoT7zvxd\nXXrbXsMZ9K2tr1/0cL9VgBH+rv+Su/+iLr1trx3MqH+zun7zZRfIZntB1Dsb+EyrZywcQWa9r4a7\n7zhsrZ29pv2LnA183t2fOyytO0Bm9u+B/xMYmXI8Dteuaf8ibX3tIr8LDLr756NnxTwP/B3E4ho2\n7Vuk3a/fPwaq7n6hmS0Dbidevzub9i8yq+uXbJ0lFib3oIh+XlSfGP3VehrhcxyeMrOrOPLts68G\n4X/UNZP7akT7YtT21Wgn0/UPwk3BVpjZOjO76VA37iDYDPxT9h/Ni8O1g+b9g/a/dgAPA/8hep0k\n/Kuzpt2v4XR9gza/fu7+t8C/id5+AKjfGa7dr12r/sEsr1/sggQz+6KZ/bz+H+FeDlP3gqjXBdxF\nGEH/I+DLZvaxQ9bouWm4r0ZdWqM9MdrJdP0D+C7h/wi/BVxoZr99KBt3oNz9v7P/L1+Ix7Wbrn/Q\n5tcOwN1H3X0k2njuYeD/rUtu62vYom8Qj+tXMbP7CX/v/5e6pLa+djXT9A9mef1iFyS4+73u/rH6\nf+y7z0SjvR3GgLvcfdzdR4B/AD5+6Fo9J7PdV6PJPspHrOn6B/Dn7r47ivYfBX7tkLbuvROHa9dK\nLK5dtDX9PwAPuvt/rUtq+2s4Td8gJtfP3f814bz9qmjdGsTg2tU06R/M8vrNlzUJ++0FMSX9Q8B3\nzexswkc+XwjcfygbOAdz2VejnTTtn5n1Ay+Y2UcIA7zfAu49LK08+OJw7ZqKy7Uzs2MIt6j/srs/\nMSW5ra/hdH2Lw/Uzs88DJ7j7HUABqMLklpFtfe1g+v7N5frNlyCh4V4Q0SrPze7+d2b2IOH+DyXg\nfnd/6bC1dmZmva/G4WroHLXq303AE4TX83+7+2PNKjrC1f7njdO1q9eof3G4disIh6H/g5nV5u9X\nAd0xuIat+tbu1+8R4H4zexLoAP5v4HfMLC7//7XqX7tfPxERERERERERERERERERERERERGJq3mx\nd4OIiEgcNNsTpS79EqD2JMUE4S39Z7j7K3M5n4IEERGRNlC/J4q7L5lB/j8AFrj7zXM953x5ToKI\nHERm9n8Q/rWSJryf/EF3//o0+X8I/JG7P3lIGigST7U9Uf4zQLR9wJ8T/sG/C/hCbfdiMzsB+Dz7\n73szK7F7LLOIvLfM7Hjg68DF7n4W8EngX0Vb7DYT8O5T7URkDhrsibKK8MmYnwJWA/++Lu0GYGX0\n+OU500iCiMzWIsInuXUDe9x91Mz+L6BoZv+c8JdTLvp3tbuvqxWM9rr/NnAGcAzwCuFfRscS7vo5\nCIwDGeBP3P3vzSwBOPAb7v72IeqjSDs4HbjbzCD8f9Jhcmfj3wb+nwM9gUYSRGRW3H0j8LfAFjN7\nxsz+lPAPjq2Eu8v9djTC8DXg39UVTQBLgPFoPvVUwkDisijdgN9194uB+wjnXgF+IzytAgSRKV4G\nPh+NJKwA/i46/lHgZXcvHugJNJIgIrPm7l82sz8BLon+/Zhwq/XfAf6JmX0IWMa+Q6OBu68zs91m\ndj3wYeA0whEJgB3u/nr0+mHgP0a7113Jkb/hmsihVJu6uw74z2aWjo59ITpuwGsH40S6u0FEZiXa\nf77L3R+uO3Y1cAVwPPAgYdCwEPi37v4pM3sC+CrhxkF/DHyTcGfPf0c4zbAWeMLdP1hX5z3Auqic\nHejcqojMnqYbRGS2RoE7zOwkgGjNwBmEawkqwB3ADwmnEVJTyn4a+G/u/gDwDuFWvFPz1NwH3A78\nLwUIIoeHggQRmRV3/yFwK/B9M3sJeIlwVPJ3gI3R+ycJRwpOqisaEK7GvsLMNgB/Sbi24YM0uPvB\n3Z8GqsBfv4fdERERkXZjZh8zs58e7naIzGcaSRCRI46Z/T7hWoV/e7jbIiIiIiIiIiIiIiIiIiIi\nIiIiIiIiIiIiIiIiIiIiR5T/H5HbhEtWZC3UAAAAAElFTkSuQmCC\n",
       "text": [
        "<matplotlib.figure.Figure at 0x10d0f43d0>"
       ]
      }
     ],
     "prompt_number": 36
    },
    {
     "cell_type": "heading",
     "level": 3,
     "metadata": {},
     "source": [
      "4: Violin Plot"
     ]
    },
    {
     "cell_type": "code",
     "collapsed": false,
     "input": [
      "sns.violinplot(titanic.Age.dropna())"
     ],
     "language": "python",
     "metadata": {},
     "outputs": [
      {
       "metadata": {},
       "output_type": "pyout",
       "prompt_number": 37,
       "text": [
        "<matplotlib.axes.AxesSubplot at 0x10dcaae10>"
       ]
      },
      {
       "metadata": {},
       "output_type": "display_data",
       "png": "iVBORw0KGgoAAAANSUhEUgAAAeMAAAECCAYAAADNb78fAAAABHNCSVQICAgIfAhkiAAAAAlwSFlz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\nREREREREREREREREREREREREREQq5v8H9rClceZIbzkAAAAASUVORK5CYII=\n",
       "text": [
        "<matplotlib.figure.Figure at 0x10cee0a50>"
       ]
      }
     ],
     "prompt_number": 37
    },
    {
     "cell_type": "code",
     "collapsed": false,
     "input": [
      "sns.violinplot(titanic.Age.dropna(), titanic.Sex)"
     ],
     "language": "python",
     "metadata": {},
     "outputs": [
      {
       "metadata": {},
       "output_type": "pyout",
       "prompt_number": 38,
       "text": [
        "<matplotlib.axes.AxesSubplot at 0x10e18c310>"
       ]
      },
      {
       "metadata": {},
       "output_type": "display_data",
       "png": "iVBORw0KGgoAAAANSUhEUgAAAfIAAAERCAYAAACAQSX8AAAABHNCSVQICAgIfAhkiAAAAAlwSFlz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\nAElFTkSuQmCC\n",
       "text": [
        "<matplotlib.figure.Figure at 0x10dc19390>"
       ]
      }
     ],
     "prompt_number": 38
    },
    {
     "cell_type": "code",
     "collapsed": false,
     "input": [
      "sns.violinplot(mlb.Salary)"
     ],
     "language": "python",
     "metadata": {},
     "outputs": [
      {
       "metadata": {},
       "output_type": "pyout",
       "prompt_number": 39,
       "text": [
        "<matplotlib.axes.AxesSubplot at 0x10e19fa10>"
       ]
      },
      {
       "metadata": {},
       "output_type": "display_data",
       "png": "iVBORw0KGgoAAAANSUhEUgAAAeYAAAEHCAYAAAB7i+XoAAAABHNCSVQICAgIfAhkiAAAAAlwSFlz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\n",
       "text": [
        "<matplotlib.figure.Figure at 0x10d0b5090>"
       ]
      }
     ],
     "prompt_number": 39
    },
    {
     "cell_type": "heading",
     "level": 3,
     "metadata": {},
     "source": [
      "5: Cumulative Distribution Function\u00b6"
     ]
    },
    {
     "cell_type": "code",
     "collapsed": false,
     "input": [
      "sns.kdeplot(titanic.Age.dropna(), cumulative=True)"
     ],
     "language": "python",
     "metadata": {},
     "outputs": [
      {
       "metadata": {},
       "output_type": "pyout",
       "prompt_number": 41,
       "text": [
        "<matplotlib.axes.AxesSubplot at 0x10e968450>"
       ]
      },
      {
       "metadata": {},
       "output_type": "display_data",
       "png": "iVBORw0KGgoAAAANSUhEUgAAAegAAAECCAYAAAA1j0ToAAAABHNCSVQICAgIfAhkiAAAAAlwSFlz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\n",
       "text": [
        "<matplotlib.figure.Figure at 0x10e27f2d0>"
       ]
      }
     ],
     "prompt_number": 41
    },
    {
     "cell_type": "code",
     "collapsed": false,
     "input": [
      " sns.kdeplot(server.Time.dropna(), cumulative=True)"
     ],
     "language": "python",
     "metadata": {},
     "outputs": [
      {
       "metadata": {},
       "output_type": "pyout",
       "prompt_number": 42,
       "text": [
        "<matplotlib.axes.AxesSubplot at 0x10e989c90>"
       ]
      },
      {
       "metadata": {},
       "output_type": "display_data",
       "png": "iVBORw0KGgoAAAANSUhEUgAAAesAAAECCAYAAADeuP/rAAAABHNCSVQICAgIfAhkiAAAAAlwSFlz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\nrkJggg==\n",
       "text": [
        "<matplotlib.figure.Figure at 0x10e568b90>"
       ]
      }
     ],
     "prompt_number": 42
    },
    {
     "cell_type": "code",
     "collapsed": false,
     "input": [
      " sns.kdeplot(mlb.Salary.dropna(), cumulative=True)"
     ],
     "language": "python",
     "metadata": {},
     "outputs": [
      {
       "output_type": "stream",
       "stream": "stderr",
       "text": [
        "/Users/malpaso/anaconda/lib/python2.7/site-packages/scipy/integrate/quadpack.py:321: IntegrationWarning: The integral is probably divergent, or slowly convergent.\n",
        "  warnings.warn(msg, IntegrationWarning)\n"
       ]
      },
      {
       "metadata": {},
       "output_type": "pyout",
       "prompt_number": 43,
       "text": [
        "<matplotlib.axes.AxesSubplot at 0x10e9cb910>"
       ]
      },
      {
       "metadata": {},
       "output_type": "display_data",
       "png": "iVBORw0KGgoAAAANSUhEUgAAAecAAAEOCAYAAACzRt8eAAAABHNCSVQICAgIfAhkiAAAAAlwSFlz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\n8v8BA6RC2UKOSUYAAAAASUVORK5CYII=\n",
       "text": [
        "<matplotlib.figure.Figure at 0x10e9ef4d0>"
       ]
      }
     ],
     "prompt_number": 43
    },
    {
     "cell_type": "code",
     "collapsed": false,
     "input": [],
     "language": "python",
     "metadata": {},
     "outputs": []
    }
   ],
   "metadata": {}
  }
 ]
}