Shakespeares.ipynb

{
 "cells": [
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "# Data Analyzing and  Classfication for Shakespeare_data.csv"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "# Part 1: Data analyzing by Pandas"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 1,
   "metadata": {},
   "outputs": [],
   "source": [
    "import pandas as pd\n",
    "import networkx as nx\n",
    "import numpy as np\n",
    "import seaborn as sns\n",
    "import matplotlib.pyplot as plt"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 2,
   "metadata": {},
   "outputs": [],
   "source": [
    "data = pd.read_csv('Shakespeare_data.csv')"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 3,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "<class 'pandas.core.frame.DataFrame'>\n",
      "RangeIndex: 111396 entries, 0 to 111395\n",
      "Data columns (total 6 columns):\n",
      "Dataline            111396 non-null int64\n",
      "Play                111396 non-null object\n",
      "PlayerLinenumber    111393 non-null float64\n",
      "ActSceneLine        105153 non-null object\n",
      "Player              111389 non-null object\n",
      "PlayerLine          111396 non-null object\n",
      "dtypes: float64(1), int64(1), object(4)\n",
      "memory usage: 5.1+ MB\n"
     ]
    }
   ],
   "source": [
    "data.info()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 4,
   "metadata": {},
   "outputs": [
    {
     "data": {
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       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>Dataline</th>\n",
       "      <th>Play</th>\n",
       "      <th>PlayerLinenumber</th>\n",
       "      <th>ActSceneLine</th>\n",
       "      <th>Player</th>\n",
       "      <th>PlayerLine</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>1</td>\n",
       "      <td>Henry IV</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>Unknown</td>\n",
       "      <td>ACT I</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>2</td>\n",
       "      <td>Henry IV</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>Unknown</td>\n",
       "      <td>SCENE I. London. The palace.</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>3</td>\n",
       "      <td>Henry IV</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>Unknown</td>\n",
       "      <td>Enter KING HENRY, LORD JOHN OF LANCASTER, the ...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>4</td>\n",
       "      <td>Henry IV</td>\n",
       "      <td>1.0</td>\n",
       "      <td>1.1.1</td>\n",
       "      <td>KING HENRY IV</td>\n",
       "      <td>So shaken as we are, so wan with care,</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>5</td>\n",
       "      <td>Henry IV</td>\n",
       "      <td>1.0</td>\n",
       "      <td>1.1.2</td>\n",
       "      <td>KING HENRY IV</td>\n",
       "      <td>Find we a time for frighted peace to pant,</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>5</th>\n",
       "      <td>6</td>\n",
       "      <td>Henry IV</td>\n",
       "      <td>1.0</td>\n",
       "      <td>1.1.3</td>\n",
       "      <td>KING HENRY IV</td>\n",
       "      <td>And breathe short-winded accents of new broils</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>6</th>\n",
       "      <td>7</td>\n",
       "      <td>Henry IV</td>\n",
       "      <td>1.0</td>\n",
       "      <td>1.1.4</td>\n",
       "      <td>KING HENRY IV</td>\n",
       "      <td>To be commenced in strands afar remote.</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>7</th>\n",
       "      <td>8</td>\n",
       "      <td>Henry IV</td>\n",
       "      <td>1.0</td>\n",
       "      <td>1.1.5</td>\n",
       "      <td>KING HENRY IV</td>\n",
       "      <td>No more the thirsty entrance of this soil</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>8</th>\n",
       "      <td>9</td>\n",
       "      <td>Henry IV</td>\n",
       "      <td>1.0</td>\n",
       "      <td>1.1.6</td>\n",
       "      <td>KING HENRY IV</td>\n",
       "      <td>Shall daub her lips with her own children's bl...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>9</th>\n",
       "      <td>10</td>\n",
       "      <td>Henry IV</td>\n",
       "      <td>1.0</td>\n",
       "      <td>1.1.7</td>\n",
       "      <td>KING HENRY IV</td>\n",
       "      <td>Nor more shall trenching war channel her fields,</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "   Dataline      Play  PlayerLinenumber ActSceneLine         Player  \\\n",
       "0         1  Henry IV               NaN          NaN        Unknown   \n",
       "1         2  Henry IV               NaN          NaN        Unknown   \n",
       "2         3  Henry IV               NaN          NaN        Unknown   \n",
       "3         4  Henry IV               1.0        1.1.1  KING HENRY IV   \n",
       "4         5  Henry IV               1.0        1.1.2  KING HENRY IV   \n",
       "5         6  Henry IV               1.0        1.1.3  KING HENRY IV   \n",
       "6         7  Henry IV               1.0        1.1.4  KING HENRY IV   \n",
       "7         8  Henry IV               1.0        1.1.5  KING HENRY IV   \n",
       "8         9  Henry IV               1.0        1.1.6  KING HENRY IV   \n",
       "9        10  Henry IV               1.0        1.1.7  KING HENRY IV   \n",
       "\n",
       "                                          PlayerLine  \n",
       "0                                              ACT I  \n",
       "1                       SCENE I. London. The palace.  \n",
       "2  Enter KING HENRY, LORD JOHN OF LANCASTER, the ...  \n",
       "3             So shaken as we are, so wan with care,  \n",
       "4         Find we a time for frighted peace to pant,  \n",
       "5     And breathe short-winded accents of new broils  \n",
       "6            To be commenced in strands afar remote.  \n",
       "7          No more the thirsty entrance of this soil  \n",
       "8  Shall daub her lips with her own children's bl...  \n",
       "9   Nor more shall trenching war channel her fields,  "
      ]
     },
     "execution_count": 4,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "data['Player'].replace(np.nan, 'Unknown', inplace = True)\n",
    "data.head(10)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## List the name of play"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 6,
   "metadata": {},
   "outputs": [
    {
     "data": {
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       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>Play</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>Henry IV</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>Henry VI Part 1</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>Henry VI Part 2</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>Henry VI Part 3</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>Alls well that ends well</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>5</th>\n",
       "      <td>As you like it</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>6</th>\n",
       "      <td>Antony and Cleopatra</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>7</th>\n",
       "      <td>A Comedy of Errors</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>8</th>\n",
       "      <td>Coriolanus</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>9</th>\n",
       "      <td>Cymbeline</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>10</th>\n",
       "      <td>Hamlet</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>11</th>\n",
       "      <td>Henry V</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>12</th>\n",
       "      <td>Henry VIII</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>13</th>\n",
       "      <td>King John</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>14</th>\n",
       "      <td>Julius Caesar</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>15</th>\n",
       "      <td>King Lear</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>16</th>\n",
       "      <td>Loves Labours Lost</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>17</th>\n",
       "      <td>macbeth</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>18</th>\n",
       "      <td>Measure for measure</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>19</th>\n",
       "      <td>Merchant of Venice</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>20</th>\n",
       "      <td>Merry Wives of Windsor</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>21</th>\n",
       "      <td>A Midsummer nights dream</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>22</th>\n",
       "      <td>Much Ado about nothing</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>23</th>\n",
       "      <td>Othello</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>24</th>\n",
       "      <td>Pericles</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>25</th>\n",
       "      <td>Richard II</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>26</th>\n",
       "      <td>Richard III</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>27</th>\n",
       "      <td>Romeo and Juliet</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>28</th>\n",
       "      <td>Taming of the Shrew</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>29</th>\n",
       "      <td>The Tempest</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>30</th>\n",
       "      <td>Timon of Athens</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>31</th>\n",
       "      <td>Titus Andronicus</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>32</th>\n",
       "      <td>Troilus and Cressida</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>33</th>\n",
       "      <td>Twelfth Night</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>34</th>\n",
       "      <td>Two Gentlemen of Verona</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>35</th>\n",
       "      <td>A Winters Tale</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "                        Play\n",
       "0                   Henry IV\n",
       "1            Henry VI Part 1\n",
       "2            Henry VI Part 2\n",
       "3            Henry VI Part 3\n",
       "4   Alls well that ends well\n",
       "5             As you like it\n",
       "6       Antony and Cleopatra\n",
       "7         A Comedy of Errors\n",
       "8                 Coriolanus\n",
       "9                  Cymbeline\n",
       "10                    Hamlet\n",
       "11                   Henry V\n",
       "12                Henry VIII\n",
       "13                 King John\n",
       "14             Julius Caesar\n",
       "15                 King Lear\n",
       "16        Loves Labours Lost\n",
       "17                   macbeth\n",
       "18       Measure for measure\n",
       "19        Merchant of Venice\n",
       "20    Merry Wives of Windsor\n",
       "21  A Midsummer nights dream\n",
       "22    Much Ado about nothing\n",
       "23                   Othello\n",
       "24                  Pericles\n",
       "25                Richard II\n",
       "26               Richard III\n",
       "27          Romeo and Juliet\n",
       "28       Taming of the Shrew\n",
       "29               The Tempest\n",
       "30           Timon of Athens\n",
       "31          Titus Andronicus\n",
       "32      Troilus and Cressida\n",
       "33             Twelfth Night\n",
       "34   Two Gentlemen of Verona\n",
       "35            A Winters Tale"
      ]
     },
     "execution_count": 6,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "pd.DataFrame(data['Play'].unique().tolist(), columns=['Play'])"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## Count the players in each play"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 8,
   "metadata": {},
   "outputs": [],
   "source": [
    "numberPlayers = data.groupby(['Play'])['Player'].nunique().sort_values(ascending= True).to_frame()\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 9,
   "metadata": {},
   "outputs": [
    {
     "data": {
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       "      <th></th>\n",
       "      <th>Player</th>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Play</th>\n",
       "      <th></th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>Two Gentlemen of Verona</th>\n",
       "      <td>18</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Twelfth Night</th>\n",
       "      <td>19</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>The Tempest</th>\n",
       "      <td>20</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>A Comedy of Errors</th>\n",
       "      <td>21</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Loves Labours Lost</th>\n",
       "      <td>21</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Much Ado about nothing</th>\n",
       "      <td>24</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Merchant of Venice</th>\n",
       "      <td>24</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Merry Wives of Windsor</th>\n",
       "      <td>25</td>\n",
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       "      <th>Alls well that ends well</th>\n",
       "      <td>26</td>\n",
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       "    <tr>\n",
       "      <th>Measure for measure</th>\n",
       "      <td>26</td>\n",
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       "    <tr>\n",
       "      <th>King Lear</th>\n",
       "      <td>27</td>\n",
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       "    <tr>\n",
       "      <th>Titus Andronicus</th>\n",
       "      <td>28</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>As you like it</th>\n",
       "      <td>28</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Othello</th>\n",
       "      <td>29</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Troilus and Cressida</th>\n",
       "      <td>29</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>King John</th>\n",
       "      <td>29</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>A Midsummer nights dream</th>\n",
       "      <td>31</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Hamlet</th>\n",
       "      <td>35</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>A Winters Tale</th>\n",
       "      <td>36</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Henry IV</th>\n",
       "      <td>36</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Romeo and Juliet</th>\n",
       "      <td>37</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Richard II</th>\n",
       "      <td>37</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Taming of the Shrew</th>\n",
       "      <td>38</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>macbeth</th>\n",
       "      <td>42</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Cymbeline</th>\n",
       "      <td>42</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Henry VI Part 3</th>\n",
       "      <td>46</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Henry VIII</th>\n",
       "      <td>47</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Henry V</th>\n",
       "      <td>47</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Pericles</th>\n",
       "      <td>48</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Julius Caesar</th>\n",
       "      <td>51</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Henry VI Part 1</th>\n",
       "      <td>53</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Antony and Cleopatra</th>\n",
       "      <td>55</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Timon of Athens</th>\n",
       "      <td>55</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Coriolanus</th>\n",
       "      <td>62</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Henry VI Part 2</th>\n",
       "      <td>65</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Richard III</th>\n",
       "      <td>71</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "                          Player\n",
       "Play                            \n",
       "Two Gentlemen of Verona       18\n",
       "Twelfth Night                 19\n",
       "The Tempest                   20\n",
       "A Comedy of Errors            21\n",
       "Loves Labours Lost            21\n",
       "Much Ado about nothing        24\n",
       "Merchant of Venice            24\n",
       "Merry Wives of Windsor        25\n",
       "Alls well that ends well      26\n",
       "Measure for measure           26\n",
       "King Lear                     27\n",
       "Titus Andronicus              28\n",
       "As you like it                28\n",
       "Othello                       29\n",
       "Troilus and Cressida          29\n",
       "King John                     29\n",
       "A Midsummer nights dream      31\n",
       "Hamlet                        35\n",
       "A Winters Tale                36\n",
       "Henry IV                      36\n",
       "Romeo and Juliet              37\n",
       "Richard II                    37\n",
       "Taming of the Shrew           38\n",
       "macbeth                       42\n",
       "Cymbeline                     42\n",
       "Henry VI Part 3               46\n",
       "Henry VIII                    47\n",
       "Henry V                       47\n",
       "Pericles                      48\n",
       "Julius Caesar                 51\n",
       "Henry VI Part 1               53\n",
       "Antony and Cleopatra          55\n",
       "Timon of Athens               55\n",
       "Coriolanus                    62\n",
       "Henry VI Part 2               65\n",
       "Richard III                   71"
      ]
     },
     "execution_count": 9,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    " numberPlayers"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 10,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 720x720 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "numberPlayers['Play'] = numberPlayers.index.tolist()\n",
    "numberPlayers.columns = ['Num Players','Play']\n",
    "numberPlayers.index= np.arange(0,len(numberPlayers))\n",
    "numberPlayers\n",
    "\n",
    "plt.figure(figsize=(10,10))\n",
    "ax = sns.barplot(x='Num Players',y='Play',data=numberPlayers)\n",
    "ax.set(xlabel='Number of Players', ylabel='Play Name')\n",
    "plt.show()\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 11,
   "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>Dataline</th>\n",
       "      <th>PlayerLinenumber</th>\n",
       "      <th>ActSceneLine</th>\n",
       "      <th>Player</th>\n",
       "      <th>PlayerLine</th>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Play</th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>A Comedy of Errors</th>\n",
       "      <td>2055</td>\n",
       "      <td>2055</td>\n",
       "      <td>1967</td>\n",
       "      <td>2055</td>\n",
       "      <td>2055</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>A Midsummer nights dream</th>\n",
       "      <td>2300</td>\n",
       "      <td>2300</td>\n",
       "      <td>2162</td>\n",
       "      <td>2300</td>\n",
       "      <td>2300</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>A Winters Tale</th>\n",
       "      <td>3489</td>\n",
       "      <td>3489</td>\n",
       "      <td>3364</td>\n",
       "      <td>3489</td>\n",
       "      <td>3489</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Alls well that ends well</th>\n",
       "      <td>3083</td>\n",
       "      <td>3083</td>\n",
       "      <td>2925</td>\n",
       "      <td>3083</td>\n",
       "      <td>3083</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Antony and Cleopatra</th>\n",
       "      <td>3862</td>\n",
       "      <td>3862</td>\n",
       "      <td>3565</td>\n",
       "      <td>3862</td>\n",
       "      <td>3862</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>As you like it</th>\n",
       "      <td>2822</td>\n",
       "      <td>2822</td>\n",
       "      <td>2677</td>\n",
       "      <td>2822</td>\n",
       "      <td>2822</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Coriolanus</th>\n",
       "      <td>3992</td>\n",
       "      <td>3992</td>\n",
       "      <td>3768</td>\n",
       "      <td>3992</td>\n",
       "      <td>3992</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Cymbeline</th>\n",
       "      <td>3958</td>\n",
       "      <td>3958</td>\n",
       "      <td>3757</td>\n",
       "      <td>3958</td>\n",
       "      <td>3958</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Hamlet</th>\n",
       "      <td>4244</td>\n",
       "      <td>4244</td>\n",
       "      <td>4020</td>\n",
       "      <td>4244</td>\n",
       "      <td>4244</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Henry IV</th>\n",
       "      <td>3205</td>\n",
       "      <td>3202</td>\n",
       "      <td>3044</td>\n",
       "      <td>3205</td>\n",
       "      <td>3205</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Henry V</th>\n",
       "      <td>3395</td>\n",
       "      <td>3395</td>\n",
       "      <td>3233</td>\n",
       "      <td>3395</td>\n",
       "      <td>3395</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Henry VI Part 1</th>\n",
       "      <td>2983</td>\n",
       "      <td>2983</td>\n",
       "      <td>2777</td>\n",
       "      <td>2983</td>\n",
       "      <td>2983</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Henry VI Part 2</th>\n",
       "      <td>3334</td>\n",
       "      <td>3334</td>\n",
       "      <td>3130</td>\n",
       "      <td>3334</td>\n",
       "      <td>3334</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Henry VI Part 3</th>\n",
       "      <td>3138</td>\n",
       "      <td>3138</td>\n",
       "      <td>2939</td>\n",
       "      <td>3138</td>\n",
       "      <td>3138</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Henry VIII</th>\n",
       "      <td>3419</td>\n",
       "      <td>3419</td>\n",
       "      <td>3279</td>\n",
       "      <td>3419</td>\n",
       "      <td>3419</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Julius Caesar</th>\n",
       "      <td>2771</td>\n",
       "      <td>2771</td>\n",
       "      <td>2597</td>\n",
       "      <td>2771</td>\n",
       "      <td>2771</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>King John</th>\n",
       "      <td>2766</td>\n",
       "      <td>2766</td>\n",
       "      <td>2649</td>\n",
       "      <td>2766</td>\n",
       "      <td>2766</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>King Lear</th>\n",
       "      <td>3766</td>\n",
       "      <td>3766</td>\n",
       "      <td>3500</td>\n",
       "      <td>3766</td>\n",
       "      <td>3766</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Loves Labours Lost</th>\n",
       "      <td>2986</td>\n",
       "      <td>2986</td>\n",
       "      <td>2878</td>\n",
       "      <td>2986</td>\n",
       "      <td>2986</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Measure for measure</th>\n",
       "      <td>2998</td>\n",
       "      <td>2998</td>\n",
       "      <td>2840</td>\n",
       "      <td>2998</td>\n",
       "      <td>2998</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Merchant of Venice</th>\n",
       "      <td>2802</td>\n",
       "      <td>2802</td>\n",
       "      <td>2665</td>\n",
       "      <td>2802</td>\n",
       "      <td>2802</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Merry Wives of Windsor</th>\n",
       "      <td>2831</td>\n",
       "      <td>2831</td>\n",
       "      <td>2614</td>\n",
       "      <td>2831</td>\n",
       "      <td>2831</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Much Ado about nothing</th>\n",
       "      <td>2704</td>\n",
       "      <td>2704</td>\n",
       "      <td>2584</td>\n",
       "      <td>2704</td>\n",
       "      <td>2704</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Othello</th>\n",
       "      <td>3762</td>\n",
       "      <td>3762</td>\n",
       "      <td>3563</td>\n",
       "      <td>3762</td>\n",
       "      <td>3762</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Pericles</th>\n",
       "      <td>2641</td>\n",
       "      <td>2641</td>\n",
       "      <td>2472</td>\n",
       "      <td>2641</td>\n",
       "      <td>2641</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Richard II</th>\n",
       "      <td>2937</td>\n",
       "      <td>2937</td>\n",
       "      <td>2800</td>\n",
       "      <td>2937</td>\n",
       "      <td>2937</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Richard III</th>\n",
       "      <td>3941</td>\n",
       "      <td>3941</td>\n",
       "      <td>3705</td>\n",
       "      <td>3941</td>\n",
       "      <td>3941</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Romeo and Juliet</th>\n",
       "      <td>3313</td>\n",
       "      <td>3313</td>\n",
       "      <td>3096</td>\n",
       "      <td>3313</td>\n",
       "      <td>3313</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Taming of the Shrew</th>\n",
       "      <td>2806</td>\n",
       "      <td>2806</td>\n",
       "      <td>2637</td>\n",
       "      <td>2806</td>\n",
       "      <td>2806</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>The Tempest</th>\n",
       "      <td>2403</td>\n",
       "      <td>2403</td>\n",
       "      <td>2289</td>\n",
       "      <td>2403</td>\n",
       "      <td>2403</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Timon of Athens</th>\n",
       "      <td>2662</td>\n",
       "      <td>2662</td>\n",
       "      <td>2500</td>\n",
       "      <td>2662</td>\n",
       "      <td>2662</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Titus Andronicus</th>\n",
       "      <td>2726</td>\n",
       "      <td>2726</td>\n",
       "      <td>2559</td>\n",
       "      <td>2726</td>\n",
       "      <td>2726</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Troilus and Cressida</th>\n",
       "      <td>3711</td>\n",
       "      <td>3711</td>\n",
       "      <td>3491</td>\n",
       "      <td>3711</td>\n",
       "      <td>3711</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Twelfth Night</th>\n",
       "      <td>2648</td>\n",
       "      <td>2648</td>\n",
       "      <td>2483</td>\n",
       "      <td>2648</td>\n",
       "      <td>2648</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Two Gentlemen of Verona</th>\n",
       "      <td>2357</td>\n",
       "      <td>2357</td>\n",
       "      <td>2234</td>\n",
       "      <td>2357</td>\n",
       "      <td>2357</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>macbeth</th>\n",
       "      <td>2586</td>\n",
       "      <td>2586</td>\n",
       "      <td>2390</td>\n",
       "      <td>2586</td>\n",
       "      <td>2586</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "                          Dataline  PlayerLinenumber  ActSceneLine  Player  \\\n",
       "Play                                                                         \n",
       "A Comedy of Errors            2055              2055          1967    2055   \n",
       "A Midsummer nights dream      2300              2300          2162    2300   \n",
       "A Winters Tale                3489              3489          3364    3489   \n",
       "Alls well that ends well      3083              3083          2925    3083   \n",
       "Antony and Cleopatra          3862              3862          3565    3862   \n",
       "As you like it                2822              2822          2677    2822   \n",
       "Coriolanus                    3992              3992          3768    3992   \n",
       "Cymbeline                     3958              3958          3757    3958   \n",
       "Hamlet                        4244              4244          4020    4244   \n",
       "Henry IV                      3205              3202          3044    3205   \n",
       "Henry V                       3395              3395          3233    3395   \n",
       "Henry VI Part 1               2983              2983          2777    2983   \n",
       "Henry VI Part 2               3334              3334          3130    3334   \n",
       "Henry VI Part 3               3138              3138          2939    3138   \n",
       "Henry VIII                    3419              3419          3279    3419   \n",
       "Julius Caesar                 2771              2771          2597    2771   \n",
       "King John                     2766              2766          2649    2766   \n",
       "King Lear                     3766              3766          3500    3766   \n",
       "Loves Labours Lost            2986              2986          2878    2986   \n",
       "Measure for measure           2998              2998          2840    2998   \n",
       "Merchant of Venice            2802              2802          2665    2802   \n",
       "Merry Wives of Windsor        2831              2831          2614    2831   \n",
       "Much Ado about nothing        2704              2704          2584    2704   \n",
       "Othello                       3762              3762          3563    3762   \n",
       "Pericles                      2641              2641          2472    2641   \n",
       "Richard II                    2937              2937          2800    2937   \n",
       "Richard III                   3941              3941          3705    3941   \n",
       "Romeo and Juliet              3313              3313          3096    3313   \n",
       "Taming of the Shrew           2806              2806          2637    2806   \n",
       "The Tempest                   2403              2403          2289    2403   \n",
       "Timon of Athens               2662              2662          2500    2662   \n",
       "Titus Andronicus              2726              2726          2559    2726   \n",
       "Troilus and Cressida          3711              3711          3491    3711   \n",
       "Twelfth Night                 2648              2648          2483    2648   \n",
       "Two Gentlemen of Verona       2357              2357          2234    2357   \n",
       "macbeth                       2586              2586          2390    2586   \n",
       "\n",
       "                          PlayerLine  \n",
       "Play                                  \n",
       "A Comedy of Errors              2055  \n",
       "A Midsummer nights dream        2300  \n",
       "A Winters Tale                  3489  \n",
       "Alls well that ends well        3083  \n",
       "Antony and Cleopatra            3862  \n",
       "As you like it                  2822  \n",
       "Coriolanus                      3992  \n",
       "Cymbeline                       3958  \n",
       "Hamlet                          4244  \n",
       "Henry IV                        3205  \n",
       "Henry V                         3395  \n",
       "Henry VI Part 1                 2983  \n",
       "Henry VI Part 2                 3334  \n",
       "Henry VI Part 3                 3138  \n",
       "Henry VIII                      3419  \n",
       "Julius Caesar                   2771  \n",
       "King John                       2766  \n",
       "King Lear                       3766  \n",
       "Loves Labours Lost              2986  \n",
       "Measure for measure             2998  \n",
       "Merchant of Venice              2802  \n",
       "Merry Wives of Windsor          2831  \n",
       "Much Ado about nothing          2704  \n",
       "Othello                         3762  \n",
       "Pericles                        2641  \n",
       "Richard II                      2937  \n",
       "Richard III                     3941  \n",
       "Romeo and Juliet                3313  \n",
       "Taming of the Shrew             2806  \n",
       "The Tempest                     2403  \n",
       "Timon of Athens                 2662  \n",
       "Titus Andronicus                2726  \n",
       "Troilus and Cressida            3711  \n",
       "Twelfth Night                   2648  \n",
       "Two Gentlemen of Verona         2357  \n",
       "macbeth                         2586  "
      ]
     },
     "execution_count": 11,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "data.groupby('Play').count()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 12,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<style scoped>\n",
       "    .dataframe tbody tr th:only-of-type {\n",
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       "\n",
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       "        vertical-align: top;\n",
       "    }\n",
       "\n",
       "    .dataframe thead th {\n",
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       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>Lines</th>\n",
       "      <th>Play</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>4244</td>\n",
       "      <td>Hamlet</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>3992</td>\n",
       "      <td>Coriolanus</td>\n",
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       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>3958</td>\n",
       "      <td>Cymbeline</td>\n",
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       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>3941</td>\n",
       "      <td>Richard III</td>\n",
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       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>3862</td>\n",
       "      <td>Antony and Cleopatra</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>5</th>\n",
       "      <td>3766</td>\n",
       "      <td>King Lear</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>6</th>\n",
       "      <td>3762</td>\n",
       "      <td>Othello</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>7</th>\n",
       "      <td>3711</td>\n",
       "      <td>Troilus and Cressida</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>8</th>\n",
       "      <td>3489</td>\n",
       "      <td>A Winters Tale</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>9</th>\n",
       "      <td>3419</td>\n",
       "      <td>Henry VIII</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>10</th>\n",
       "      <td>3395</td>\n",
       "      <td>Henry V</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>11</th>\n",
       "      <td>3334</td>\n",
       "      <td>Henry VI Part 2</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>12</th>\n",
       "      <td>3313</td>\n",
       "      <td>Romeo and Juliet</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>13</th>\n",
       "      <td>3205</td>\n",
       "      <td>Henry IV</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>14</th>\n",
       "      <td>3138</td>\n",
       "      <td>Henry VI Part 3</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>15</th>\n",
       "      <td>3083</td>\n",
       "      <td>Alls well that ends well</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>16</th>\n",
       "      <td>2998</td>\n",
       "      <td>Measure for measure</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>17</th>\n",
       "      <td>2986</td>\n",
       "      <td>Loves Labours Lost</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>18</th>\n",
       "      <td>2983</td>\n",
       "      <td>Henry VI Part 1</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>19</th>\n",
       "      <td>2937</td>\n",
       "      <td>Richard II</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>20</th>\n",
       "      <td>2831</td>\n",
       "      <td>Merry Wives of Windsor</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>21</th>\n",
       "      <td>2822</td>\n",
       "      <td>As you like it</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>22</th>\n",
       "      <td>2806</td>\n",
       "      <td>Taming of the Shrew</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>23</th>\n",
       "      <td>2802</td>\n",
       "      <td>Merchant of Venice</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>24</th>\n",
       "      <td>2771</td>\n",
       "      <td>Julius Caesar</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>25</th>\n",
       "      <td>2766</td>\n",
       "      <td>King John</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>26</th>\n",
       "      <td>2726</td>\n",
       "      <td>Titus Andronicus</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>27</th>\n",
       "      <td>2704</td>\n",
       "      <td>Much Ado about nothing</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>28</th>\n",
       "      <td>2662</td>\n",
       "      <td>Timon of Athens</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>29</th>\n",
       "      <td>2648</td>\n",
       "      <td>Twelfth Night</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>30</th>\n",
       "      <td>2641</td>\n",
       "      <td>Pericles</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>31</th>\n",
       "      <td>2586</td>\n",
       "      <td>macbeth</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>32</th>\n",
       "      <td>2403</td>\n",
       "      <td>The Tempest</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>33</th>\n",
       "      <td>2357</td>\n",
       "      <td>Two Gentlemen of Verona</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>34</th>\n",
       "      <td>2300</td>\n",
       "      <td>A Midsummer nights dream</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>35</th>\n",
       "      <td>2055</td>\n",
       "      <td>A Comedy of Errors</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "    Lines                      Play\n",
       "0    4244                    Hamlet\n",
       "1    3992                Coriolanus\n",
       "2    3958                 Cymbeline\n",
       "3    3941               Richard III\n",
       "4    3862      Antony and Cleopatra\n",
       "5    3766                 King Lear\n",
       "6    3762                   Othello\n",
       "7    3711      Troilus and Cressida\n",
       "8    3489            A Winters Tale\n",
       "9    3419                Henry VIII\n",
       "10   3395                   Henry V\n",
       "11   3334           Henry VI Part 2\n",
       "12   3313          Romeo and Juliet\n",
       "13   3205                  Henry IV\n",
       "14   3138           Henry VI Part 3\n",
       "15   3083  Alls well that ends well\n",
       "16   2998       Measure for measure\n",
       "17   2986        Loves Labours Lost\n",
       "18   2983           Henry VI Part 1\n",
       "19   2937                Richard II\n",
       "20   2831    Merry Wives of Windsor\n",
       "21   2822            As you like it\n",
       "22   2806       Taming of the Shrew\n",
       "23   2802        Merchant of Venice\n",
       "24   2771             Julius Caesar\n",
       "25   2766                 King John\n",
       "26   2726          Titus Andronicus\n",
       "27   2704    Much Ado about nothing\n",
       "28   2662           Timon of Athens\n",
       "29   2648             Twelfth Night\n",
       "30   2641                  Pericles\n",
       "31   2586                   macbeth\n",
       "32   2403               The Tempest\n",
       "33   2357   Two Gentlemen of Verona\n",
       "34   2300  A Midsummer nights dream\n",
       "35   2055        A Comedy of Errors"
      ]
     },
     "execution_count": 12,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "play_data = data.groupby('Play').count().sort_values(by='PlayerLine',ascending=False)['PlayerLine']\n",
    "play_data = play_data.to_frame()\n",
    "play_data['Play'] = play_data.index.tolist()\n",
    "play_data.index = np.arange(0,len(play_data)) #changing the index from plays to numbers\n",
    "play_data.columns =['Lines','Play']\n",
    "play_data"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 13,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "Play                      Player            \n",
       "A Comedy of Errors        ADRIANA               284\n",
       "                          AEGEON                150\n",
       "                          AEMELIA                75\n",
       "                          ANGELO                 99\n",
       "                          ANTIPHOLUS              6\n",
       "                          BALTHAZAR              31\n",
       "                          Courtezan              43\n",
       "                          DROMIO OF EPHESUS     191\n",
       "                          DROMIO OF SYRACUSE    323\n",
       "                          DUKE SOLINUS           97\n",
       "                          First Merchant         19\n",
       "                          Gaoler                  1\n",
       "                          LUCE                   11\n",
       "                          LUCIANA               118\n",
       "                          OCTAVIUS CAESAR         3\n",
       "                          OF EPHESUS            221\n",
       "                          OF SYRACUSE           292\n",
       "                          Officer                17\n",
       "                          PINCH                  17\n",
       "                          Second Merchant        41\n",
       "                          Servant                16\n",
       "A Midsummer nights dream  ALL                     2\n",
       "                          BOTTOM                220\n",
       "                          COBWEB                  4\n",
       "                          DEMETRIUS             144\n",
       "                          EGEUS                  42\n",
       "                          FLUTE                  26\n",
       "                          FORD                    3\n",
       "                          Fairy                  33\n",
       "                          HELENA                237\n",
       "                                               ... \n",
       "macbeth                   First Murderer         35\n",
       "                          First Witch            68\n",
       "                          Gentlewoman            27\n",
       "                          HECATE                 43\n",
       "                          LADY MACBETH          279\n",
       "                          LADY MACDUFF           43\n",
       "                          LENNOX                 79\n",
       "                          Lord                   25\n",
       "                          Lords                   4\n",
       "                          MACBETH               783\n",
       "                          MACDUFF               193\n",
       "                          MALCOLM               222\n",
       "                          MENTEITH               12\n",
       "                          Messenger              24\n",
       "                          Old Man                15\n",
       "                          Porter                 53\n",
       "                          ROSS                  137\n",
       "                          SEYTON                  6\n",
       "                          SIWARD                 37\n",
       "                          Second Apparition       5\n",
       "                          Second Murderer        16\n",
       "                          Second Witch           29\n",
       "                          Sergeant               35\n",
       "                          Servant                 6\n",
       "                          Soldiers                1\n",
       "                          Son                    24\n",
       "                          Third Apparition        6\n",
       "                          Third Murderer          8\n",
       "                          Third Witch            27\n",
       "                          YOUNG SIWARD            8\n",
       "Name: PlayerLine, Length: 1328, dtype: int64"
      ]
     },
     "execution_count": 13,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "data.groupby(['Play','Player']).count()['PlayerLine']"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 14,
   "metadata": {},
   "outputs": [
    {
     "data": {
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       "  <thead>\n",
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       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th rowspan=\"21\" valign=\"top\">A Comedy of Errors</th>\n",
       "      <th>ADRIANA</th>\n",
       "      <td>284</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>AEGEON</th>\n",
       "      <td>150</td>\n",
       "    </tr>\n",
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       "      <th>AEMELIA</th>\n",
       "      <td>75</td>\n",
       "    </tr>\n",
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       "      <th>ANGELO</th>\n",
       "      <td>99</td>\n",
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       "      <th>ANTIPHOLUS</th>\n",
       "      <td>6</td>\n",
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       "      <th>BALTHAZAR</th>\n",
       "      <td>31</td>\n",
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       "    <tr>\n",
       "      <th>Courtezan</th>\n",
       "      <td>43</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>DROMIO OF EPHESUS</th>\n",
       "      <td>191</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>DROMIO OF SYRACUSE</th>\n",
       "      <td>323</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>DUKE SOLINUS</th>\n",
       "      <td>97</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>First Merchant</th>\n",
       "      <td>19</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Gaoler</th>\n",
       "      <td>1</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>LUCE</th>\n",
       "      <td>11</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>LUCIANA</th>\n",
       "      <td>118</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>OCTAVIUS CAESAR</th>\n",
       "      <td>3</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>OF EPHESUS</th>\n",
       "      <td>221</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>OF SYRACUSE</th>\n",
       "      <td>292</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Officer</th>\n",
       "      <td>17</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>PINCH</th>\n",
       "      <td>17</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Second Merchant</th>\n",
       "      <td>41</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Servant</th>\n",
       "      <td>16</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th rowspan=\"9\" valign=\"top\">A Midsummer nights dream</th>\n",
       "      <th>ALL</th>\n",
       "      <td>2</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>BOTTOM</th>\n",
       "      <td>220</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>COBWEB</th>\n",
       "      <td>4</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>DEMETRIUS</th>\n",
       "      <td>144</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>EGEUS</th>\n",
       "      <td>42</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>FLUTE</th>\n",
       "      <td>26</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>FORD</th>\n",
       "      <td>3</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Fairy</th>\n",
       "      <td>33</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>HELENA</th>\n",
       "      <td>237</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>...</th>\n",
       "      <th>...</th>\n",
       "      <td>...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th rowspan=\"30\" valign=\"top\">macbeth</th>\n",
       "      <th>First Murderer</th>\n",
       "      <td>35</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>First Witch</th>\n",
       "      <td>68</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Gentlewoman</th>\n",
       "      <td>27</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>HECATE</th>\n",
       "      <td>43</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>LADY MACBETH</th>\n",
       "      <td>279</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>LADY MACDUFF</th>\n",
       "      <td>43</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>LENNOX</th>\n",
       "      <td>79</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Lord</th>\n",
       "      <td>25</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Lords</th>\n",
       "      <td>4</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>MACBETH</th>\n",
       "      <td>783</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>MACDUFF</th>\n",
       "      <td>193</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>MALCOLM</th>\n",
       "      <td>222</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>MENTEITH</th>\n",
       "      <td>12</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Messenger</th>\n",
       "      <td>24</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Old Man</th>\n",
       "      <td>15</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Porter</th>\n",
       "      <td>53</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>ROSS</th>\n",
       "      <td>137</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>SEYTON</th>\n",
       "      <td>6</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>SIWARD</th>\n",
       "      <td>37</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Second Apparition</th>\n",
       "      <td>5</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Second Murderer</th>\n",
       "      <td>16</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Second Witch</th>\n",
       "      <td>29</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Sergeant</th>\n",
       "      <td>35</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Servant</th>\n",
       "      <td>6</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Soldiers</th>\n",
       "      <td>1</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Son</th>\n",
       "      <td>24</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Third Apparition</th>\n",
       "      <td>6</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Third Murderer</th>\n",
       "      <td>8</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Third Witch</th>\n",
       "      <td>27</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>YOUNG SIWARD</th>\n",
       "      <td>8</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "<p>1328 rows × 1 columns</p>\n",
       "</div>"
      ],
      "text/plain": [
       "                                             PlayerLine\n",
       "Play                     Player                        \n",
       "A Comedy of Errors       ADRIANA                    284\n",
       "                         AEGEON                     150\n",
       "                         AEMELIA                     75\n",
       "                         ANGELO                      99\n",
       "                         ANTIPHOLUS                   6\n",
       "                         BALTHAZAR                   31\n",
       "                         Courtezan                   43\n",
       "                         DROMIO OF EPHESUS          191\n",
       "                         DROMIO OF SYRACUSE         323\n",
       "                         DUKE SOLINUS                97\n",
       "                         First Merchant              19\n",
       "                         Gaoler                       1\n",
       "                         LUCE                        11\n",
       "                         LUCIANA                    118\n",
       "                         OCTAVIUS CAESAR              3\n",
       "                         OF EPHESUS                 221\n",
       "                         OF SYRACUSE                292\n",
       "                         Officer                     17\n",
       "                         PINCH                       17\n",
       "                         Second Merchant             41\n",
       "                         Servant                     16\n",
       "A Midsummer nights dream ALL                          2\n",
       "                         BOTTOM                     220\n",
       "                         COBWEB                       4\n",
       "                         DEMETRIUS                  144\n",
       "                         EGEUS                       42\n",
       "                         FLUTE                       26\n",
       "                         FORD                         3\n",
       "                         Fairy                       33\n",
       "                         HELENA                     237\n",
       "...                                                 ...\n",
       "macbeth                  First Murderer              35\n",
       "                         First Witch                 68\n",
       "                         Gentlewoman                 27\n",
       "                         HECATE                      43\n",
       "                         LADY MACBETH               279\n",
       "                         LADY MACDUFF                43\n",
       "                         LENNOX                      79\n",
       "                         Lord                        25\n",
       "                         Lords                        4\n",
       "                         MACBETH                    783\n",
       "                         MACDUFF                    193\n",
       "                         MALCOLM                    222\n",
       "                         MENTEITH                    12\n",
       "                         Messenger                   24\n",
       "                         Old Man                     15\n",
       "                         Porter                      53\n",
       "                         ROSS                       137\n",
       "                         SEYTON                       6\n",
       "                         SIWARD                      37\n",
       "                         Second Apparition            5\n",
       "                         Second Murderer             16\n",
       "                         Second Witch                29\n",
       "                         Sergeant                    35\n",
       "                         Servant                      6\n",
       "                         Soldiers                     1\n",
       "                         Son                         24\n",
       "                         Third Apparition             6\n",
       "                         Third Murderer               8\n",
       "                         Third Witch                 27\n",
       "                         YOUNG SIWARD                 8\n",
       "\n",
       "[1328 rows x 1 columns]"
      ]
     },
     "execution_count": 14,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "lines_per_player= data.groupby(['Play','Player']).count()['PlayerLine']\n",
    "lines_per_player= lines_per_player.to_frame()\n",
    "lines_per_player"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "# Part 2: Classification "
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 7,
   "metadata": {},
   "outputs": [],
   "source": [
    "data=data.dropna()"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## Change the string object into int object"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 8,
   "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>Player</th>\n",
       "      <th>Play</th>\n",
       "      <th>PlayerLineNumber</th>\n",
       "      <th>Act</th>\n",
       "      <th>Scene</th>\n",
       "      <th>Line</th>\n",
       "      <th>WordPerLine</th>\n",
       "      <th>CharPerWord</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>77119</th>\n",
       "      <td>CERIMON</td>\n",
       "      <td>Pericles</td>\n",
       "      <td>26.0</td>\n",
       "      <td>3</td>\n",
       "      <td>2</td>\n",
       "      <td>73</td>\n",
       "      <td>9</td>\n",
       "      <td>4.333333</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>50012</th>\n",
       "      <td>Fool</td>\n",
       "      <td>King Lear</td>\n",
       "      <td>9.0</td>\n",
       "      <td>1</td>\n",
       "      <td>5</td>\n",
       "      <td>19</td>\n",
       "      <td>4</td>\n",
       "      <td>5.250000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>37509</th>\n",
       "      <td>KING HENRY V</td>\n",
       "      <td>Henry V</td>\n",
       "      <td>31.0</td>\n",
       "      <td>2</td>\n",
       "      <td>2</td>\n",
       "      <td>192</td>\n",
       "      <td>5</td>\n",
       "      <td>6.800000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>107779</th>\n",
       "      <td>SILVIA</td>\n",
       "      <td>Two Gentlemen of Verona</td>\n",
       "      <td>12.0</td>\n",
       "      <td>5</td>\n",
       "      <td>4</td>\n",
       "      <td>56</td>\n",
       "      <td>4</td>\n",
       "      <td>5.000000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>94148</th>\n",
       "      <td>VENTIDIUS</td>\n",
       "      <td>Timon of Athens</td>\n",
       "      <td>3.0</td>\n",
       "      <td>1</td>\n",
       "      <td>2</td>\n",
       "      <td>15</td>\n",
       "      <td>3</td>\n",
       "      <td>5.000000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>13739</th>\n",
       "      <td>KING</td>\n",
       "      <td>Alls well that ends well</td>\n",
       "      <td>63.0</td>\n",
       "      <td>2</td>\n",
       "      <td>3</td>\n",
       "      <td>182</td>\n",
       "      <td>7</td>\n",
       "      <td>5.142857</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>64184</th>\n",
       "      <td>SIR HUGH EVANS</td>\n",
       "      <td>Merry Wives of Windsor</td>\n",
       "      <td>8.0</td>\n",
       "      <td>1</td>\n",
       "      <td>1</td>\n",
       "      <td>17</td>\n",
       "      <td>10</td>\n",
       "      <td>5.000000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>93326</th>\n",
       "      <td>CALIBAN</td>\n",
       "      <td>The Tempest</td>\n",
       "      <td>45.0</td>\n",
       "      <td>4</td>\n",
       "      <td>1</td>\n",
       "      <td>215</td>\n",
       "      <td>10</td>\n",
       "      <td>5.100000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>87571</th>\n",
       "      <td>CAPULET</td>\n",
       "      <td>Romeo and Juliet</td>\n",
       "      <td>49.0</td>\n",
       "      <td>3</td>\n",
       "      <td>5</td>\n",
       "      <td>171</td>\n",
       "      <td>10</td>\n",
       "      <td>3.900000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>50480</th>\n",
       "      <td>Fool</td>\n",
       "      <td>King Lear</td>\n",
       "      <td>25.0</td>\n",
       "      <td>2</td>\n",
       "      <td>4</td>\n",
       "      <td>70</td>\n",
       "      <td>10</td>\n",
       "      <td>4.600000</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "                Player                      Play  PlayerLineNumber Act Scene  \\\n",
       "77119          CERIMON                  Pericles              26.0   3     2   \n",
       "50012             Fool                 King Lear               9.0   1     5   \n",
       "37509     KING HENRY V                   Henry V              31.0   2     2   \n",
       "107779          SILVIA   Two Gentlemen of Verona              12.0   5     4   \n",
       "94148        VENTIDIUS           Timon of Athens               3.0   1     2   \n",
       "13739             KING  Alls well that ends well              63.0   2     3   \n",
       "64184   SIR HUGH EVANS    Merry Wives of Windsor               8.0   1     1   \n",
       "93326          CALIBAN               The Tempest              45.0   4     1   \n",
       "87571          CAPULET          Romeo and Juliet              49.0   3     5   \n",
       "50480             Fool                 King Lear              25.0   2     4   \n",
       "\n",
       "       Line  WordPerLine  CharPerWord  \n",
       "77119    73            9     4.333333  \n",
       "50012    19            4     5.250000  \n",
       "37509   192            5     6.800000  \n",
       "107779   56            4     5.000000  \n",
       "94148    15            3     5.000000  \n",
       "13739   182            7     5.142857  \n",
       "64184    17           10     5.000000  \n",
       "93326   215           10     5.100000  \n",
       "87571   171           10     3.900000  \n",
       "50480    70           10     4.600000  "
      ]
     },
     "execution_count": 8,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "#get info from line\n",
    "a=data['ActSceneLine']\n",
    "aslSplit = a.str.split('.', expand=True)\n",
    "\n",
    "b=data['PlayerLine']\n",
    "charPerWord = b.str.len() #first hold total chars per line\n",
    "\n",
    "wordPerLine = b.str.split()\n",
    "wordPerLine = wordPerLine.str.len() #words per line\n",
    "\n",
    "charPerWord = charPerWord / wordPerLine #characters per word\n",
    "\n",
    "data_new = pd.DataFrame()\n",
    "data_new['Player'] = data['Player']\n",
    "data_new['Play'] = data['Play']\n",
    "data_new['PlayerLineNumber'] = data['PlayerLinenumber']\n",
    "data_new['Act'] = aslSplit[0]\n",
    "data_new['Scene'] = aslSplit[1]\n",
    "data_new['Line'] = aslSplit[2]\n",
    "data_new['WordPerLine'] = wordPerLine\n",
    "data_new['CharPerWord'] = charPerWord\n",
    "\n",
    "data_new.sample(10)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "# Encoding from string to number"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 9,
   "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>Player</th>\n",
       "      <th>Play</th>\n",
       "      <th>PlayerLineNumber</th>\n",
       "      <th>Act</th>\n",
       "      <th>Scene</th>\n",
       "      <th>Line</th>\n",
       "      <th>WordPerLine</th>\n",
       "      <th>CharPerWord</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>70361</th>\n",
       "      <td>83</td>\n",
       "      <td>22</td>\n",
       "      <td>79.0</td>\n",
       "      <td>2</td>\n",
       "      <td>3</td>\n",
       "      <td>237</td>\n",
       "      <td>7</td>\n",
       "      <td>5.428571</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>85715</th>\n",
       "      <td>600</td>\n",
       "      <td>27</td>\n",
       "      <td>11.0</td>\n",
       "      <td>1</td>\n",
       "      <td>3</td>\n",
       "      <td>51</td>\n",
       "      <td>11</td>\n",
       "      <td>5.272727</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>20326</th>\n",
       "      <td>550</td>\n",
       "      <td>4</td>\n",
       "      <td>1.0</td>\n",
       "      <td>3</td>\n",
       "      <td>4</td>\n",
       "      <td>8</td>\n",
       "      <td>8</td>\n",
       "      <td>5.500000</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "       Player  Play  PlayerLineNumber Act Scene Line  WordPerLine  CharPerWord\n",
       "70361      83    22              79.0   2     3  237            7     5.428571\n",
       "85715     600    27              11.0   1     3   51           11     5.272727\n",
       "20326     550     4               1.0   3     4    8            8     5.500000"
      ]
     },
     "execution_count": 9,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "# encoding from string to number\n",
    "from sklearn import preprocessing\n",
    "features = ['Player', 'Play']\n",
    "    \n",
    "for feature in features:\n",
    "    le = preprocessing.LabelEncoder()\n",
    "    le = le.fit(data_new[feature])\n",
    "    data_new[feature] = le.transform(data_new[feature])\n",
    "\n",
    "data_new.sample(3)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 10,
   "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>Player</th>\n",
       "      <th>Play</th>\n",
       "      <th>PlayerLineNumber</th>\n",
       "      <th>Act</th>\n",
       "      <th>Scene</th>\n",
       "      <th>Line</th>\n",
       "      <th>WordPerLine</th>\n",
       "      <th>CharPerWord</th>\n",
       "      <th>PrePlayer</th>\n",
       "      <th>NextPlayer</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>74737</th>\n",
       "      <td>428</td>\n",
       "      <td>23</td>\n",
       "      <td>144.0</td>\n",
       "      <td>4</td>\n",
       "      <td>1</td>\n",
       "      <td>299</td>\n",
       "      <td>10</td>\n",
       "      <td>4.600000</td>\n",
       "      <td>499.0</td>\n",
       "      <td>428.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>27499</th>\n",
       "      <td>298</td>\n",
       "      <td>6</td>\n",
       "      <td>13.0</td>\n",
       "      <td>4</td>\n",
       "      <td>6</td>\n",
       "      <td>27</td>\n",
       "      <td>8</td>\n",
       "      <td>6.125000</td>\n",
       "      <td>107.0</td>\n",
       "      <td>298.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>9822</th>\n",
       "      <td>700</td>\n",
       "      <td>13</td>\n",
       "      <td>7.0</td>\n",
       "      <td>1</td>\n",
       "      <td>2</td>\n",
       "      <td>9</td>\n",
       "      <td>8</td>\n",
       "      <td>5.625000</td>\n",
       "      <td>700.0</td>\n",
       "      <td>926.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>17009</th>\n",
       "      <td>170</td>\n",
       "      <td>5</td>\n",
       "      <td>20.0</td>\n",
       "      <td>3</td>\n",
       "      <td>2</td>\n",
       "      <td>65</td>\n",
       "      <td>10</td>\n",
       "      <td>4.500000</td>\n",
       "      <td>851.0</td>\n",
       "      <td>851.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>40235</th>\n",
       "      <td>595</td>\n",
       "      <td>14</td>\n",
       "      <td>26.0</td>\n",
       "      <td>1</td>\n",
       "      <td>1</td>\n",
       "      <td>129</td>\n",
       "      <td>8</td>\n",
       "      <td>5.250000</td>\n",
       "      <td>595.0</td>\n",
       "      <td>595.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>23165</th>\n",
       "      <td>224</td>\n",
       "      <td>0</td>\n",
       "      <td>26.0</td>\n",
       "      <td>3</td>\n",
       "      <td>1</td>\n",
       "      <td>73</td>\n",
       "      <td>11</td>\n",
       "      <td>4.727273</td>\n",
       "      <td>224.0</td>\n",
       "      <td>511.0</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "       Player  Play  PlayerLineNumber Act Scene Line  WordPerLine  \\\n",
       "74737     428    23             144.0   4     1  299           10   \n",
       "27499     298     6              13.0   4     6   27            8   \n",
       "9822      700    13               7.0   1     2    9            8   \n",
       "17009     170     5              20.0   3     2   65           10   \n",
       "40235     595    14              26.0   1     1  129            8   \n",
       "23165     224     0              26.0   3     1   73           11   \n",
       "\n",
       "       CharPerWord  PrePlayer  NextPlayer  \n",
       "74737     4.600000      499.0       428.0  \n",
       "27499     6.125000      107.0       298.0  \n",
       "9822      5.625000      700.0       926.0  \n",
       "17009     4.500000      851.0       851.0  \n",
       "40235     5.250000      595.0       595.0  \n",
       "23165     4.727273      224.0       511.0  "
      ]
     },
     "execution_count": 10,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "count = 0;\n",
    "preIndex = 0;\n",
    "thisIndex = 0;\n",
    "for i, row in data_new.iterrows():\n",
    "    if (count > 0):\n",
    "        if (count == 1):\n",
    "            data_new.loc[thisIndex, 'PrePlayer'] = data_new.loc[thisIndex, 'Player']\n",
    "            data_new.loc[thisIndex, 'NextPlayer'] = data_new.loc[i, 'Player']    \n",
    "        else:\n",
    "            data_new.loc[thisIndex, 'PrePlayer'] = data_new.loc[preIndex, 'Player']\n",
    "            data_new.loc[thisIndex, 'NextPlayer'] = data_new.loc[i, 'Player']   \n",
    "            if (i == 111394):\n",
    "                data_new.loc[i, 'PrePlayer'] = data_new.loc[thisIndex, 'Player']\n",
    "                data_new.loc[i, 'NextPlayer'] = data_new.loc[i, 'Player'] \n",
    "        \n",
    "    preIndex = thisIndex\n",
    "    thisIndex = i\n",
    "    count += 1\n",
    "data_new.sample(6)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "# Generate training and testing data"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 11,
   "metadata": {},
   "outputs": [],
   "source": [
    "from sklearn.model_selection import train_test_split\n",
    "\n",
    "data_x = data_new.drop(['Player'], axis=1)\n",
    "data_y = data_new['Player']\n",
    "\n",
    "perc_test = 0.10\n",
    "X_train, X_test, y_train, y_test = train_test_split(data_x, data_y, test_size=perc_test)\n",
    "\n",
    "#data_x\n",
    "#data_y\n",
    "#X_train\n",
    "#y_test"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "# Model 1: Decision Tree"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 12,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "DecisionTreeRegressor(criterion='mse', max_depth=None, max_features=None,\n",
       "                      max_leaf_nodes=None, min_impurity_decrease=0.0,\n",
       "                      min_impurity_split=None, min_samples_leaf=1,\n",
       "                      min_samples_split=2, min_weight_fraction_leaf=0.0,\n",
       "                      presort=False, random_state=None, splitter='best')"
      ]
     },
     "execution_count": 12,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "from sklearn.tree import DecisionTreeRegressor\n",
    "regressor1 = DecisionTreeRegressor()\n",
    "regressor1.fit(X_train, y_train)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 13,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "0.38352844303726996"
      ]
     },
     "execution_count": 13,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "regressor1.score(X_test, y_test)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "# Model 2: Random Forrest Regressor"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 21,
   "metadata": {},
   "outputs": [],
   "source": [
    "# Feature Scaling\n",
    "from sklearn.preprocessing import StandardScaler\n",
    "\n",
    "sc = StandardScaler()\n",
    "X_train = sc.fit_transform(X_train)\n",
    "X_test = sc.transform(X_test)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 22,
   "metadata": {},
   "outputs": [],
   "source": [
    "from sklearn.ensemble import RandomForestRegressor\n",
    "\n",
    "regressor = RandomForestRegressor(n_estimators=20, random_state=0)\n",
    "regressor.fit(X_train, y_train)\n",
    "y_pred = regressor.predict(X_test)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 23,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "0.6464352533394345"
      ]
     },
     "execution_count": 23,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "regressor.score(X_test, y_test)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "This can substantially increase the performance compared with Model 1"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "# Model 3: SVM"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 24,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "SVC(C=1.0, cache_size=200, class_weight=None, coef0=0.0,\n",
       "    decision_function_shape='ovr', degree=3, gamma='auto_deprecated',\n",
       "    kernel='linear', max_iter=-1, probability=False, random_state=None,\n",
       "    shrinking=True, tol=0.001, verbose=False)"
      ]
     },
     "execution_count": 24,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "from sklearn.svm import SVC\n",
    "svclassifier = SVC(kernel='linear')\n",
    "svclassifier.fit(X_train, y_train)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "linear SVM can not work for this case"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": [
    "y_pred=svclassifier.predict(X_test)\n",
    "svclassifier.score(X_test, y_test)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "# Model 4: Non-bayesian regressor"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 14,
   "metadata": {},
   "outputs": [],
   "source": [
    "\n",
    "from sklearn.naive_bayes import MultinomialNB\n",
    "\n",
    "# Run Training\n",
    "clf = MultinomialNB().fit(X_train, y_train)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 15,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "0.05182578927348802"
      ]
     },
     "execution_count": 15,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "predictions = clf.predict(X_test)\n",
    "clf.score(X_test, y_test)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "Bad performance by NB model"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": []
  }
 ],
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