ShaxFinalProject.ipynb

{
 "cells": [
  {
   "cell_type": "code",
   "execution_count": 1,
   "id": "e55cce50",
   "metadata": {},
   "outputs": [],
   "source": [
    "import pandas as pd\n",
    "\n",
    "# Import data\n",
    "plays_df = pd.read_csv(\"Shakespeare_data.csv\")\n",
    "\n",
    "# Do some preliminary reorganization of data\n",
    "plays_df[['Act','Scene','Line']] = plays_df['ActSceneLine'].str.split('.',expand= True).astype(float)\n",
    "plays_df = plays_df.drop('ActSceneLine',axis=1)\n",
    "plays_df.loc[(plays_df.Player == 'Shepard'),'Player']='Shepherd'\n",
    "\n",
    "# Get data from A Winters Tale act 4 scene 4\n",
    "wintersTale_df = plays_df[109775:110737]\n",
    "\n",
    "# Get spoken lines\n",
    "WintersTale_df = plays_df[plays_df['Play'] == 'A Winters Tale']\n",
    "WintersTale4_4_df = WintersTale_df[WintersTale_df['Act'] == 4.0]\n",
    "lines_df = WintersTale4_4_df[WintersTale4_4_df['Scene'] == 4.0]\n",
    "\n",
    "# Get entrances from stage directions\n",
    "entrances_df = wintersTale_df[wintersTale_df['PlayerLine'].str.contains('Enter') | wintersTale_df['PlayerLine'].str.contains('Re-enter')]\n",
    "\n",
    "# Get exits from stage directions\n",
    "exits_df = wintersTale_df[wintersTale_df['PlayerLine'].str.contains('Exit') | wintersTale_df['PlayerLine'].str.contains('Exeunt')]"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 2,
   "id": "90c9bfe2",
   "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>Play</th>\n",
       "      <th>PlayerLinenumber</th>\n",
       "      <th>Player</th>\n",
       "      <th>PlayerLine</th>\n",
       "      <th>Act</th>\n",
       "      <th>Scene</th>\n",
       "      <th>Line</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>109775</th>\n",
       "      <td>109776</td>\n",
       "      <td>A Winters Tale</td>\n",
       "      <td>35.0</td>\n",
       "      <td>AUTOLYCUS</td>\n",
       "      <td>Enter FLORIZEL and PERDITA</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>109839</th>\n",
       "      <td>109840</td>\n",
       "      <td>A Winters Tale</td>\n",
       "      <td>9.0</td>\n",
       "      <td>FLORIZEL</td>\n",
       "      <td>Enter Shepherd, Clown, MOPSA, DORCAS, and othe...</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>109989</th>\n",
       "      <td>109990</td>\n",
       "      <td>A Winters Tale</td>\n",
       "      <td>37.0</td>\n",
       "      <td>Shepherd</td>\n",
       "      <td>Enter Servant</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>110026</th>\n",
       "      <td>110027</td>\n",
       "      <td>A Winters Tale</td>\n",
       "      <td>47.0</td>\n",
       "      <td>PERDITA</td>\n",
       "      <td>Enter AUTOLYCUS, singing</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>110135</th>\n",
       "      <td>110136</td>\n",
       "      <td>A Winters Tale</td>\n",
       "      <td>92.0</td>\n",
       "      <td>AUTOLYCUS</td>\n",
       "      <td>Re-enter Servant</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>110473</th>\n",
       "      <td>110474</td>\n",
       "      <td>A Winters Tale</td>\n",
       "      <td>163.0</td>\n",
       "      <td>CAMILLO</td>\n",
       "      <td>Re-enter AUTOLYCUS</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>110578</th>\n",
       "      <td>110579</td>\n",
       "      <td>A Winters Tale</td>\n",
       "      <td>189.0</td>\n",
       "      <td>AUTOLYCUS</td>\n",
       "      <td>Re-enter Clown and Shepherd</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "        Dataline            Play  PlayerLinenumber     Player  \\\n",
       "109775    109776  A Winters Tale              35.0  AUTOLYCUS   \n",
       "109839    109840  A Winters Tale               9.0   FLORIZEL   \n",
       "109989    109990  A Winters Tale              37.0   Shepherd   \n",
       "110026    110027  A Winters Tale              47.0    PERDITA   \n",
       "110135    110136  A Winters Tale              92.0  AUTOLYCUS   \n",
       "110473    110474  A Winters Tale             163.0    CAMILLO   \n",
       "110578    110579  A Winters Tale             189.0  AUTOLYCUS   \n",
       "\n",
       "                                               PlayerLine  Act  Scene  Line  \n",
       "109775                         Enter FLORIZEL and PERDITA  NaN    NaN   NaN  \n",
       "109839  Enter Shepherd, Clown, MOPSA, DORCAS, and othe...  NaN    NaN   NaN  \n",
       "109989                                      Enter Servant  NaN    NaN   NaN  \n",
       "110026                           Enter AUTOLYCUS, singing  NaN    NaN   NaN  \n",
       "110135                                   Re-enter Servant  NaN    NaN   NaN  \n",
       "110473                                 Re-enter AUTOLYCUS  NaN    NaN   NaN  \n",
       "110578                        Re-enter Clown and Shepherd  NaN    NaN   NaN  "
      ]
     },
     "execution_count": 2,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "entrances_df"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 3,
   "id": "1674a936",
   "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>Play</th>\n",
       "      <th>PlayerLinenumber</th>\n",
       "      <th>Player</th>\n",
       "      <th>PlayerLine</th>\n",
       "      <th>Act</th>\n",
       "      <th>Scene</th>\n",
       "      <th>Line</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>109776</th>\n",
       "      <td>109777</td>\n",
       "      <td>A Winters Tale</td>\n",
       "      <td>1.0</td>\n",
       "      <td>FLORIZEL</td>\n",
       "      <td>These your unusual weeds to each part of you</td>\n",
       "      <td>4.0</td>\n",
       "      <td>4.0</td>\n",
       "      <td>1.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>109777</th>\n",
       "      <td>109778</td>\n",
       "      <td>A Winters Tale</td>\n",
       "      <td>1.0</td>\n",
       "      <td>FLORIZEL</td>\n",
       "      <td>Do give a life: no shepherdess, but Flora</td>\n",
       "      <td>4.0</td>\n",
       "      <td>4.0</td>\n",
       "      <td>2.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>109778</th>\n",
       "      <td>109779</td>\n",
       "      <td>A Winters Tale</td>\n",
       "      <td>1.0</td>\n",
       "      <td>FLORIZEL</td>\n",
       "      <td>Peering in April's front. This your sheep-shea...</td>\n",
       "      <td>4.0</td>\n",
       "      <td>4.0</td>\n",
       "      <td>3.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>109779</th>\n",
       "      <td>109780</td>\n",
       "      <td>A Winters Tale</td>\n",
       "      <td>1.0</td>\n",
       "      <td>FLORIZEL</td>\n",
       "      <td>Is as a meeting of the petty gods,</td>\n",
       "      <td>4.0</td>\n",
       "      <td>4.0</td>\n",
       "      <td>4.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>109780</th>\n",
       "      <td>109781</td>\n",
       "      <td>A Winters Tale</td>\n",
       "      <td>1.0</td>\n",
       "      <td>FLORIZEL</td>\n",
       "      <td>And you the queen on't.</td>\n",
       "      <td>4.0</td>\n",
       "      <td>4.0</td>\n",
       "      <td>5.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>...</th>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>110731</th>\n",
       "      <td>110732</td>\n",
       "      <td>A Winters Tale</td>\n",
       "      <td>240.0</td>\n",
       "      <td>AUTOLYCUS</td>\n",
       "      <td>complaint they have to the king concerns him</td>\n",
       "      <td>4.0</td>\n",
       "      <td>4.0</td>\n",
       "      <td>925.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>110732</th>\n",
       "      <td>110733</td>\n",
       "      <td>A Winters Tale</td>\n",
       "      <td>240.0</td>\n",
       "      <td>AUTOLYCUS</td>\n",
       "      <td>nothing, let him call me rogue for being so far</td>\n",
       "      <td>4.0</td>\n",
       "      <td>4.0</td>\n",
       "      <td>926.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>110733</th>\n",
       "      <td>110734</td>\n",
       "      <td>A Winters Tale</td>\n",
       "      <td>240.0</td>\n",
       "      <td>AUTOLYCUS</td>\n",
       "      <td>officious, for I am proof against that title and</td>\n",
       "      <td>4.0</td>\n",
       "      <td>4.0</td>\n",
       "      <td>927.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>110734</th>\n",
       "      <td>110735</td>\n",
       "      <td>A Winters Tale</td>\n",
       "      <td>240.0</td>\n",
       "      <td>AUTOLYCUS</td>\n",
       "      <td>what shame else belongs to't. To him will I pr...</td>\n",
       "      <td>4.0</td>\n",
       "      <td>4.0</td>\n",
       "      <td>928.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>110735</th>\n",
       "      <td>110736</td>\n",
       "      <td>A Winters Tale</td>\n",
       "      <td>240.0</td>\n",
       "      <td>AUTOLYCUS</td>\n",
       "      <td>them: there may be matter in it.</td>\n",
       "      <td>4.0</td>\n",
       "      <td>4.0</td>\n",
       "      <td>929.0</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "<p>929 rows × 8 columns</p>\n",
       "</div>"
      ],
      "text/plain": [
       "        Dataline            Play  PlayerLinenumber     Player  \\\n",
       "109776    109777  A Winters Tale               1.0   FLORIZEL   \n",
       "109777    109778  A Winters Tale               1.0   FLORIZEL   \n",
       "109778    109779  A Winters Tale               1.0   FLORIZEL   \n",
       "109779    109780  A Winters Tale               1.0   FLORIZEL   \n",
       "109780    109781  A Winters Tale               1.0   FLORIZEL   \n",
       "...          ...             ...               ...        ...   \n",
       "110731    110732  A Winters Tale             240.0  AUTOLYCUS   \n",
       "110732    110733  A Winters Tale             240.0  AUTOLYCUS   \n",
       "110733    110734  A Winters Tale             240.0  AUTOLYCUS   \n",
       "110734    110735  A Winters Tale             240.0  AUTOLYCUS   \n",
       "110735    110736  A Winters Tale             240.0  AUTOLYCUS   \n",
       "\n",
       "                                               PlayerLine  Act  Scene   Line  \n",
       "109776       These your unusual weeds to each part of you  4.0    4.0    1.0  \n",
       "109777          Do give a life: no shepherdess, but Flora  4.0    4.0    2.0  \n",
       "109778  Peering in April's front. This your sheep-shea...  4.0    4.0    3.0  \n",
       "109779                 Is as a meeting of the petty gods,  4.0    4.0    4.0  \n",
       "109780                            And you the queen on't.  4.0    4.0    5.0  \n",
       "...                                                   ...  ...    ...    ...  \n",
       "110731       complaint they have to the king concerns him  4.0    4.0  925.0  \n",
       "110732    nothing, let him call me rogue for being so far  4.0    4.0  926.0  \n",
       "110733   officious, for I am proof against that title and  4.0    4.0  927.0  \n",
       "110734  what shame else belongs to't. To him will I pr...  4.0    4.0  928.0  \n",
       "110735                   them: there may be matter in it.  4.0    4.0  929.0  \n",
       "\n",
       "[929 rows x 8 columns]"
      ]
     },
     "execution_count": 3,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "lines_df"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 4,
   "id": "4614c8f5",
   "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>Play</th>\n",
       "      <th>PlayerLinenumber</th>\n",
       "      <th>Player</th>\n",
       "      <th>PlayerLine</th>\n",
       "      <th>Act</th>\n",
       "      <th>Scene</th>\n",
       "      <th>Line</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>110022</th>\n",
       "      <td>110023</td>\n",
       "      <td>A Winters Tale</td>\n",
       "      <td>45.0</td>\n",
       "      <td>PERDITA</td>\n",
       "      <td>Exit Servant</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>110122</th>\n",
       "      <td>110123</td>\n",
       "      <td>A Winters Tale</td>\n",
       "      <td>91.0</td>\n",
       "      <td>Clown</td>\n",
       "      <td>Exit with DORCAS and MOPSA</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>110134</th>\n",
       "      <td>110135</td>\n",
       "      <td>A Winters Tale</td>\n",
       "      <td>92.0</td>\n",
       "      <td>AUTOLYCUS</td>\n",
       "      <td>Exit</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>110154</th>\n",
       "      <td>110155</td>\n",
       "      <td>A Winters Tale</td>\n",
       "      <td>98.0</td>\n",
       "      <td>Servant</td>\n",
       "      <td>Exit</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>110282</th>\n",
       "      <td>110283</td>\n",
       "      <td>A Winters Tale</td>\n",
       "      <td>128.0</td>\n",
       "      <td>POLIXENES</td>\n",
       "      <td>Exit</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>110308</th>\n",
       "      <td>110309</td>\n",
       "      <td>A Winters Tale</td>\n",
       "      <td>131.0</td>\n",
       "      <td>Shepherd</td>\n",
       "      <td>Exit</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>110563</th>\n",
       "      <td>110564</td>\n",
       "      <td>A Winters Tale</td>\n",
       "      <td>188.0</td>\n",
       "      <td>CAMILLO</td>\n",
       "      <td>Exeunt FLORIZEL, PERDITA, and CAMILLO</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>110723</th>\n",
       "      <td>110724</td>\n",
       "      <td>A Winters Tale</td>\n",
       "      <td>239.0</td>\n",
       "      <td>Shepherd</td>\n",
       "      <td>Exeunt Shepherd and Clown</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>110736</th>\n",
       "      <td>110737</td>\n",
       "      <td>A Winters Tale</td>\n",
       "      <td>240.0</td>\n",
       "      <td>AUTOLYCUS</td>\n",
       "      <td>Exit</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "        Dataline            Play  PlayerLinenumber     Player  \\\n",
       "110022    110023  A Winters Tale              45.0    PERDITA   \n",
       "110122    110123  A Winters Tale              91.0      Clown   \n",
       "110134    110135  A Winters Tale              92.0  AUTOLYCUS   \n",
       "110154    110155  A Winters Tale              98.0    Servant   \n",
       "110282    110283  A Winters Tale             128.0  POLIXENES   \n",
       "110308    110309  A Winters Tale             131.0   Shepherd   \n",
       "110563    110564  A Winters Tale             188.0    CAMILLO   \n",
       "110723    110724  A Winters Tale             239.0   Shepherd   \n",
       "110736    110737  A Winters Tale             240.0  AUTOLYCUS   \n",
       "\n",
       "                                   PlayerLine  Act  Scene  Line  \n",
       "110022                           Exit Servant  NaN    NaN   NaN  \n",
       "110122             Exit with DORCAS and MOPSA  NaN    NaN   NaN  \n",
       "110134                                   Exit  NaN    NaN   NaN  \n",
       "110154                                   Exit  NaN    NaN   NaN  \n",
       "110282                                   Exit  NaN    NaN   NaN  \n",
       "110308                                   Exit  NaN    NaN   NaN  \n",
       "110563  Exeunt FLORIZEL, PERDITA, and CAMILLO  NaN    NaN   NaN  \n",
       "110723              Exeunt Shepherd and Clown  NaN    NaN   NaN  \n",
       "110736                                   Exit  NaN    NaN   NaN  "
      ]
     },
     "execution_count": 4,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "exits_df"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 5,
   "id": "9b8c3b32",
   "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>Count</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>AUTOLYCUS</td>\n",
       "      <td>189</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>CAMILLO</td>\n",
       "      <td>131</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>Clown</td>\n",
       "      <td>74</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>DORCAS</td>\n",
       "      <td>12</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>FLORIZEL</td>\n",
       "      <td>168</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>5</th>\n",
       "      <td>MOPSA</td>\n",
       "      <td>20</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>6</th>\n",
       "      <td>PERDITA</td>\n",
       "      <td>121</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>7</th>\n",
       "      <td>POLIXENES</td>\n",
       "      <td>95</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>8</th>\n",
       "      <td>Servant</td>\n",
       "      <td>35</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>9</th>\n",
       "      <td>Shepherd</td>\n",
       "      <td>84</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "      Player  Count\n",
       "0  AUTOLYCUS    189\n",
       "1    CAMILLO    131\n",
       "2      Clown     74\n",
       "3     DORCAS     12\n",
       "4   FLORIZEL    168\n",
       "5      MOPSA     20\n",
       "6    PERDITA    121\n",
       "7  POLIXENES     95\n",
       "8    Servant     35\n",
       "9   Shepherd     84"
      ]
     },
     "execution_count": 5,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "# Get list of characters in scene and count their total number of lines\n",
    "characters_df = lines_df.groupby(['Player']).size().reset_index()\n",
    "characters_df.rename(columns = {0: 'Count'}, inplace = True)\n",
    "characters_df"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 6,
   "id": "01205ccd",
   "metadata": {},
   "outputs": [],
   "source": [
    "# Get coappearances of characters\n",
    "inlist = entrances_df.index.values.tolist()\n",
    "outlist = exits_df.index.values.tolist()\n",
    "inoutlist = inlist\n",
    "for out in outlist:\n",
    "    inoutlist.append(out)\n",
    "inoutlist.sort()\n",
    "\n",
    "co_ap = []\n",
    "for change in range(len(inoutlist)-1):\n",
    "    co_ap.append(plays_df[inoutlist[change]+1:inoutlist[change+1]])"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 7,
   "id": "f0e563dc",
   "metadata": {},
   "outputs": [],
   "source": [
    "# Count number of lines each character speaks in each coappearance\n",
    "num_lines = []\n",
    "for coappearance in co_ap:\n",
    "    tmp_df = coappearance.groupby(['Player']).size().reset_index()\n",
    "    tmp_df.rename(columns = {0: 'Count'}, inplace = True)\n",
    "    num_lines.append(tmp_df)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 8,
   "id": "36578523",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "{'AUTOLYCUS': {'CAMILLO': 37,\n",
       "  'Clown': 121,\n",
       "  'DORCAS': 44,\n",
       "  'FLORIZEL': 37,\n",
       "  'MOPSA': 44,\n",
       "  'PERDITA': 37,\n",
       "  'POLIXENES': 0,\n",
       "  'Servant': 0,\n",
       "  'Shepherd': 77},\n",
       " 'CAMILLO': {'AUTOLYCUS': 40,\n",
       "  'Clown': 5,\n",
       "  'DORCAS': 5,\n",
       "  'FLORIZEL': 133,\n",
       "  'MOPSA': 5,\n",
       "  'PERDITA': 135,\n",
       "  'POLIXENES': 6,\n",
       "  'Servant': 1,\n",
       "  'Shepherd': 8},\n",
       " 'Clown': {'AUTOLYCUS': 62,\n",
       "  'CAMILLO': 4,\n",
       "  'DORCAS': 26,\n",
       "  'FLORIZEL': 4,\n",
       "  'MOPSA': 26,\n",
       "  'PERDITA': 13,\n",
       "  'POLIXENES': 11,\n",
       "  'Servant': 7,\n",
       "  'Shepherd': 44},\n",
       " 'DORCAS': {'AUTOLYCUS': 10,\n",
       "  'CAMILLO': 2,\n",
       "  'Clown': 12,\n",
       "  'FLORIZEL': 2,\n",
       "  'MOPSA': 12,\n",
       "  'PERDITA': 2,\n",
       "  'POLIXENES': 2,\n",
       "  'Servant': 0,\n",
       "  'Shepherd': 2},\n",
       " 'FLORIZEL': {'AUTOLYCUS': 8,\n",
       "  'CAMILLO': 134,\n",
       "  'Clown': 18,\n",
       "  'DORCAS': 18,\n",
       "  'MOPSA': 18,\n",
       "  'PERDITA': 169,\n",
       "  'POLIXENES': 57,\n",
       "  'Servant': 39,\n",
       "  'Shepherd': 57},\n",
       " 'MOPSA': {'AUTOLYCUS': 19,\n",
       "  'CAMILLO': 1,\n",
       "  'Clown': 20,\n",
       "  'DORCAS': 20,\n",
       "  'FLORIZEL': 1,\n",
       "  'PERDITA': 1,\n",
       "  'POLIXENES': 1,\n",
       "  'Servant': 0,\n",
       "  'Shepherd': 1},\n",
       " 'PERDITA': {'AUTOLYCUS': 4,\n",
       "  'CAMILLO': 92,\n",
       "  'Clown': 68,\n",
       "  'DORCAS': 66,\n",
       "  'FLORIZEL': 110,\n",
       "  'MOPSA': 66,\n",
       "  'POLIXENES': 71,\n",
       "  'Servant': 5,\n",
       "  'Shepherd': 80},\n",
       " 'POLIXENES': {'AUTOLYCUS': 0,\n",
       "  'CAMILLO': 95,\n",
       "  'Clown': 25,\n",
       "  'DORCAS': 24,\n",
       "  'FLORIZEL': 95,\n",
       "  'MOPSA': 24,\n",
       "  'PERDITA': 96,\n",
       "  'Servant': 74,\n",
       "  'Shepherd': 97},\n",
       " 'Servant': {'AUTOLYCUS': 0,\n",
       "  'CAMILLO': 1,\n",
       "  'Clown': 23,\n",
       "  'DORCAS': 0,\n",
       "  'FLORIZEL': 1,\n",
       "  'MOPSA': 0,\n",
       "  'PERDITA': 24,\n",
       "  'POLIXENES': 36,\n",
       "  'Shepherd': 13},\n",
       " 'Shepherd': {'AUTOLYCUS': 27,\n",
       "  'CAMILLO': 53,\n",
       "  'Clown': 56,\n",
       "  'DORCAS': 29,\n",
       "  'FLORIZEL': 40,\n",
       "  'MOPSA': 29,\n",
       "  'PERDITA': 53,\n",
       "  'POLIXENES': 44,\n",
       "  'Servant': 15}}"
      ]
     },
     "execution_count": 8,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "# Count the number of lines each character speaks in the presence of each other character\n",
    "interactions_count = {}\n",
    "for character in characters_df['Player']:\n",
    "    companions = {}\n",
    "    for companion in characters_df['Player']:\n",
    "        if companion != character:\n",
    "            companions[companion] = 0\n",
    "    interactions_count[character] = companions\n",
    "\n",
    "for interaction in num_lines:\n",
    "    for character in interaction['Player']:\n",
    "        for companion in interaction['Player']:\n",
    "            if character != companion:\n",
    "                interactions_count[character][companion] += interaction.loc[interaction['Player'] == character, 'Count'].values[0]\n",
    "                #interactions_count[character][companion] += interaction.loc[interaction['Player'] == companion, 'Count'].values[0]\n",
    "        \n",
    "interactions_count"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "42856758",
   "metadata": {},
   "source": [
    "## Graph the network"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 9,
   "id": "0fad6b5c",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "        <script type=\"text/javascript\">\n",
       "        window.PlotlyConfig = {MathJaxConfig: 'local'};\n",
       "        if (window.MathJax) {MathJax.Hub.Config({SVG: {font: \"STIX-Web\"}});}\n",
       "        if (typeof require !== 'undefined') {\n",
       "        require.undef(\"plotly\");\n",
       "        requirejs.config({\n",
       "            paths: {\n",
       "                'plotly': ['https://cdn.plot.ly/plotly-latest.min']\n",
       "            }\n",
       "        });\n",
       "        require(['plotly'], function(Plotly) {\n",
       "            window._Plotly = Plotly;\n",
       "        });\n",
       "        }\n",
       "        </script>\n",
       "        "
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "import math\n",
    "import numpy as np\n",
    "import plotly.offline as py\n",
    "import plotly.graph_objects as go\n",
    "import networkx as nx\n",
    "import re\n",
    "import matplotlib.pyplot as plt\n",
    "\n",
    "py.init_notebook_mode(connected=True)\n",
    "A_Winters_Tale = nx.Graph()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 10,
   "id": "efa8ae8b",
   "metadata": {},
   "outputs": [],
   "source": [
    "# Add node for each character\n",
    "for char in characters_df['Player']:\n",
    "    A_Winters_Tale.add_node(char, size = 6*(characters_df.loc[characters_df['Player'] == char, 'Count'].values[0]))\n",
    "#    A_Winters_Tale.add_node(char, size = 6*(characters_df.loc[characters_df['Player'] == char, 'Count'].values[0])/100)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 11,
   "id": "a27adbdc",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "NodeView(('AUTOLYCUS', 'CAMILLO', 'Clown', 'DORCAS', 'FLORIZEL', 'MOPSA', 'PERDITA', 'POLIXENES', 'Servant', 'Shepherd'))"
      ]
     },
     "execution_count": 11,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "A_Winters_Tale.nodes"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 12,
   "id": "c95978e7",
   "metadata": {},
   "outputs": [],
   "source": [
    "# For each co-appearance between two characters, add an edge\n",
    "for char in interactions_count.keys():\n",
    "    for co_char in interactions_count[char].keys():\n",
    "        \n",
    "        # Only add edge if the count is positive\n",
    "        if interactions_count[char][co_char] > 0:\n",
    "            A_Winters_Tale.add_edge(char, co_char, weight = (5*(interactions_count[char][co_char]) / 100))\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 13,
   "id": "054e3bfe",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "[('CAMILLO', 1.0),\n",
       " ('Clown', 1.0),\n",
       " ('FLORIZEL', 1.0),\n",
       " ('PERDITA', 1.0),\n",
       " ('Shepherd', 1.0),\n",
       " ('DORCAS', 0.8888888888888888),\n",
       " ('MOPSA', 0.8888888888888888),\n",
       " ('POLIXENES', 0.8888888888888888),\n",
       " ('AUTOLYCUS', 0.7777777777777777),\n",
       " ('Servant', 0.6666666666666666)]"
      ]
     },
     "execution_count": 13,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "sorted(nx.degree_centrality(A_Winters_Tale).items(), key=lambda x: -x[1])[:]"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 14,
   "id": "67e5348b",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": "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\n",
      "text/plain": [
       "<Figure size 1008x576 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "plt.figure(figsize=(14,8))  # make the figure size a little larger\n",
    "plt.axis('off')  # remove the axis, which isn't meaningful in this case\n",
    "plt.title(\"The Winter's Tale Social Network\", fontsize=20)\n",
    "\n",
    "# The 'k' argument determines how spaced out the nodes will be from\n",
    "# one another on the graph.\n",
    "pos = nx.spring_layout(A_Winters_Tale, k=0.5)\n",
    "\n",
    "node_size = [data['size'] for __, data in A_Winters_Tale.nodes(data=True)]\n",
    "\n",
    "\n",
    "nx.draw_networkx(\n",
    "    A_Winters_Tale,\n",
    "    pos=pos,\n",
    "#    node_size = node_size,\n",
    "    edge_color='gray',  # change edge color\n",
    "    alpha=0.3,  # make nodes more transparent to make labels clearer\n",
    "    font_size=14,\n",
    "    with_labels=True,\n",
    "    font_color=\"k\"\n",
    ")"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 15,
   "id": "c52f2ec8",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "EdgeView([('AUTOLYCUS', 'CAMILLO'), ('AUTOLYCUS', 'Clown'), ('AUTOLYCUS', 'DORCAS'), ('AUTOLYCUS', 'FLORIZEL'), ('AUTOLYCUS', 'MOPSA'), ('AUTOLYCUS', 'PERDITA'), ('AUTOLYCUS', 'Shepherd'), ('CAMILLO', 'Clown'), ('CAMILLO', 'DORCAS'), ('CAMILLO', 'FLORIZEL'), ('CAMILLO', 'MOPSA'), ('CAMILLO', 'PERDITA'), ('CAMILLO', 'POLIXENES'), ('CAMILLO', 'Servant'), ('CAMILLO', 'Shepherd'), ('Clown', 'DORCAS'), ('Clown', 'FLORIZEL'), ('Clown', 'MOPSA'), ('Clown', 'PERDITA'), ('Clown', 'POLIXENES'), ('Clown', 'Servant'), ('Clown', 'Shepherd'), ('DORCAS', 'FLORIZEL'), ('DORCAS', 'MOPSA'), ('DORCAS', 'PERDITA'), ('DORCAS', 'POLIXENES'), ('DORCAS', 'Shepherd'), ('FLORIZEL', 'MOPSA'), ('FLORIZEL', 'PERDITA'), ('FLORIZEL', 'POLIXENES'), ('FLORIZEL', 'Servant'), ('FLORIZEL', 'Shepherd'), ('MOPSA', 'PERDITA'), ('MOPSA', 'POLIXENES'), ('MOPSA', 'Shepherd'), ('PERDITA', 'POLIXENES'), ('PERDITA', 'Servant'), ('PERDITA', 'Shepherd'), ('POLIXENES', 'Servant'), ('POLIXENES', 'Shepherd'), ('Servant', 'Shepherd')])"
      ]
     },
     "execution_count": 15,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "A_Winters_Tale.edges()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 16,
   "id": "4c64392c",
   "metadata": {},
   "outputs": [],
   "source": [
    "pos_ = nx.spring_layout(A_Winters_Tale)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 17,
   "id": "3daf15e1",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "{'AUTOLYCUS': array([-0.50843995, -0.66548516]),\n",
       " 'CAMILLO': array([ 0.53187462, -0.29662197]),\n",
       " 'Clown': array([-0.45202839, -0.09549786]),\n",
       " 'DORCAS': array([-0.62332353,  0.29583196]),\n",
       " 'FLORIZEL': array([0.57441477, 0.24693788]),\n",
       " 'MOPSA': array([-0.02772152, -0.73543212]),\n",
       " 'PERDITA': array([ 0.06053984, -0.08626445]),\n",
       " 'POLIXENES': array([0.34969218, 0.09377655]),\n",
       " 'Servant': array([0.1814824, 1.       ]),\n",
       " 'Shepherd': array([-0.08649041,  0.24275518])}"
      ]
     },
     "execution_count": 17,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "pos_"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 18,
   "id": "38fe2b61",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "{'weight': 2.0}"
      ]
     },
     "execution_count": 18,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "A_Winters_Tale.edges()[('AUTOLYCUS','CAMILLO')]"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 19,
   "id": "47a0ee10",
   "metadata": {},
   "outputs": [],
   "source": [
    "def make_edge(x, y, text, width):\n",
    "    \n",
    "    '''Creates a scatter trace for the edge between x's and y's with given width\n",
    "\n",
    "    Parameters\n",
    "    ----------\n",
    "    x    : a tuple of the endpoints' x-coordinates in the form, tuple([x0, x1, None])\n",
    "    \n",
    "    y    : a tuple of the endpoints' y-coordinates in the form, tuple([y0, y1, None])\n",
    "    \n",
    "    width: the width of the line\n",
    "\n",
    "    Returns\n",
    "    -------\n",
    "    An edge trace that goes between x0 and x1 with specified width.\n",
    "    '''\n",
    "    return  go.Scatter(x         = x,\n",
    "                       y         = y,\n",
    "                       line      = dict(width = width,\n",
    "                                   color = 'cornflowerblue'),\n",
    "                       hoverinfo = 'text',\n",
    "                       text      = ([text]),\n",
    "                       mode      = 'lines')"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 20,
   "id": "ce4c0b65",
   "metadata": {},
   "outputs": [],
   "source": [
    "# For each edge, make an edge_trace, append to list\n",
    "edge_trace = []\n",
    "for edge in A_Winters_Tale.edges():\n",
    "    \n",
    "    if A_Winters_Tale.edges()[edge]['weight'] > 0:\n",
    "        char_1 = edge[0]\n",
    "        char_2 = edge[1]\n",
    "\n",
    "        x0, y0 = pos_[char_1]\n",
    "        x1, y1 = pos_[char_2]\n",
    "\n",
    "        text   = char_1 + '--' + char_2 + ': ' + str(A_Winters_Tale.edges()[edge]['weight'])\n",
    "        \n",
    "        trace  = make_edge([x0, x1, None], [y0, y1, None], text,\n",
    "                           0.3*A_Winters_Tale.edges()[edge]['weight']**1.75)\n",
    "\n",
    "        edge_trace.append(trace)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 21,
   "id": "6c927029",
   "metadata": {},
   "outputs": [],
   "source": [
    "# Make a node trace\n",
    "node_trace = go.Scatter(x         = [],\n",
    "                        y         = [],\n",
    "                        text      = [],\n",
    "                        textposition = \"top center\",\n",
    "                        textfont_size = 10,\n",
    "                        mode      = 'markers+text',\n",
    "                        hoverinfo = 'none',\n",
    "                        marker    = dict(color = [],\n",
    "                                         size  = [],\n",
    "                                         line  = None))\n",
    "# For each node in midsummer, get the position and size and add to the node_trace\n",
    "for node in A_Winters_Tale.nodes():\n",
    "    x, y = pos_[node]\n",
    "    node_trace['x'] += tuple([x])\n",
    "    node_trace['y'] += tuple([y])\n",
    "    node_trace['marker']['color'] += tuple(['cornflowerblue'])\n",
    "    node_trace['marker']['size'] += tuple([5*A_Winters_Tale.nodes()[node]['size']])\n",
    "    node_trace['text'] += tuple(['<b>' + node + '</b>'])"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 22,
   "id": "ebd4f025",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "application/vnd.plotly.v1+json": {
       "config": {
        "plotlyServerURL": "https://plot.ly"
       },
       "data": [
        {
         "hoverinfo": "text",
         "line": {
          "color": "cornflowerblue",
          "width": 1.0090756983044573
         },
         "mode": "lines",
         "text": [
          "AUTOLYCUS--CAMILLO: 2.0"
         ],
         "type": "scatter",
         "x": [
          -0.508439948169892,
          0.5318746193957582,
          null
         ],
         "y": [
          -0.6654851612295354,
          -0.2966219686325922,
          null
         ]
        },
        {
         "hoverinfo": "text",
         "line": {
          "color": "cornflowerblue",
          "width": 2.172722285551274
         },
         "mode": "lines",
         "text": [
          "AUTOLYCUS--Clown: 3.1"
         ],
         "type": "scatter",
         "x": [
          -0.508439948169892,
          -0.4520283925048223,
          null
         ],
         "y": [
          -0.6654851612295354,
          -0.09549786119821281,
          null
         ]
        },
        {
         "hoverinfo": "text",
         "line": {
          "color": "cornflowerblue",
          "width": 0.08919053362520407
         },
         "mode": "lines",
         "text": [
          "AUTOLYCUS--DORCAS: 0.5"
         ],
         "type": "scatter",
         "x": [
          -0.508439948169892,
          -0.6233235273262008,
          null
         ],
         "y": [
          -0.6654851612295354,
          0.2958319626602499,
          null
         ]
        },
        {
         "hoverinfo": "text",
         "line": {
          "color": "cornflowerblue",
          "width": 0.06035680462478091
         },
         "mode": "lines",
         "text": [
          "AUTOLYCUS--FLORIZEL: 0.4"
         ],
         "type": "scatter",
         "x": [
          -0.508439948169892,
          0.5744147658947862,
          null
         ],
         "y": [
          -0.6654851612295354,
          0.24693788131499958,
          null
         ]
        },
        {
         "hoverinfo": "text",
         "line": {
          "color": "cornflowerblue",
          "width": 0.27424427106582416
         },
         "mode": "lines",
         "text": [
          "AUTOLYCUS--MOPSA: 0.95"
         ],
         "type": "scatter",
         "x": [
          -0.508439948169892,
          -0.027721520777830827,
          null
         ],
         "y": [
          -0.6654851612295354,
          -0.7354321235314945,
          null
         ]
        },
        {
         "hoverinfo": "text",
         "line": {
          "color": "cornflowerblue",
          "width": 0.01794418537465465
         },
         "mode": "lines",
         "text": [
          "AUTOLYCUS--PERDITA: 0.2"
         ],
         "type": "scatter",
         "x": [
          -0.508439948169892,
          0.06053983664920965,
          null
         ],
         "y": [
          -0.6654851612295354,
          -0.08626445416797977,
          null
         ]
        },
        {
         "hoverinfo": "text",
         "line": {
          "color": "cornflowerblue",
          "width": 0.5072304878568292
         },
         "mode": "lines",
         "text": [
          "AUTOLYCUS--Shepherd: 1.35"
         ],
         "type": "scatter",
         "x": [
          -0.508439948169892,
          -0.08649041288833349,
          null
         ],
         "y": [
          -0.6654851612295354,
          0.24275517874137242,
          null
         ]
        },
        {
         "hoverinfo": "text",
         "line": {
          "color": "cornflowerblue",
          "width": 0.01794418537465465
         },
         "mode": "lines",
         "text": [
          "CAMILLO--Clown: 0.2"
         ],
         "type": "scatter",
         "x": [
          0.5318746193957582,
          -0.4520283925048223,
          null
         ],
         "y": [
          -0.2966219686325922,
          -0.09549786119821281,
          null
         ]
        },
        {
         "hoverinfo": "text",
         "line": {
          "color": "cornflowerblue",
          "width": 0.005334838230116768
         },
         "mode": "lines",
         "text": [
          "CAMILLO--DORCAS: 0.1"
         ],
         "type": "scatter",
         "x": [
          0.5318746193957582,
          -0.6233235273262008,
          null
         ],
         "y": [
          -0.2966219686325922,
          0.2958319626602499,
          null
         ]
        },
        {
         "hoverinfo": "text",
         "line": {
          "color": "cornflowerblue",
          "width": 8.370514623234188
         },
         "mode": "lines",
         "text": [
          "CAMILLO--FLORIZEL: 6.7"
         ],
         "type": "scatter",
         "x": [
          0.5318746193957582,
          0.5744147658947862,
          null
         ],
         "y": [
          -0.2966219686325922,
          0.24693788131499958,
          null
         ]
        },
        {
         "hoverinfo": "text",
         "line": {
          "color": "cornflowerblue",
          "width": 0.0015860568951608462
         },
         "mode": "lines",
         "text": [
          "CAMILLO--MOPSA: 0.05"
         ],
         "type": "scatter",
         "x": [
          0.5318746193957582,
          -0.027721520777830827,
          null
         ],
         "y": [
          -0.2966219686325922,
          -0.7354321235314945,
          null
         ]
        },
        {
         "hoverinfo": "text",
         "line": {
          "color": "cornflowerblue",
          "width": 4.334584365205041
         },
         "mode": "lines",
         "text": [
          "CAMILLO--PERDITA: 4.6"
         ],
         "type": "scatter",
         "x": [
          0.5318746193957582,
          0.06053983664920965,
          null
         ],
         "y": [
          -0.2966219686325922,
          -0.08626445416797977,
          null
         ]
        },
        {
         "hoverinfo": "text",
         "line": {
          "color": "cornflowerblue",
          "width": 4.584954936764896
         },
         "mode": "lines",
         "text": [
          "CAMILLO--POLIXENES: 4.75"
         ],
         "type": "scatter",
         "x": [
          0.5318746193957582,
          0.34969217610037684,
          null
         ],
         "y": [
          -0.2966219686325922,
          0.09377654604319183,
          null
         ]
        },
        {
         "hoverinfo": "text",
         "line": {
          "color": "cornflowerblue",
          "width": 0.0015860568951608462
         },
         "mode": "lines",
         "text": [
          "CAMILLO--Servant: 0.05"
         ],
         "type": "scatter",
         "x": [
          0.5318746193957582,
          0.18148240362694995,
          null
         ],
         "y": [
          -0.2966219686325922,
          1,
          null
         ]
        },
        {
         "hoverinfo": "text",
         "line": {
          "color": "cornflowerblue",
          "width": 1.65120704959167
         },
         "mode": "lines",
         "text": [
          "CAMILLO--Shepherd: 2.65"
         ],
         "type": "scatter",
         "x": [
          0.5318746193957582,
          -0.08649041288833349,
          null
         ],
         "y": [
          -0.2966219686325922,
          0.24275517874137242,
          null
         ]
        },
        {
         "hoverinfo": "text",
         "line": {
          "color": "cornflowerblue",
          "width": 0.12271169157848992
         },
         "mode": "lines",
         "text": [
          "Clown--DORCAS: 0.6"
         ],
         "type": "scatter",
         "x": [
          -0.4520283925048223,
          -0.6233235273262008,
          null
         ],
         "y": [
          -0.09549786119821281,
          0.2958319626602499,
          null
         ]
        },
        {
         "hoverinfo": "text",
         "line": {
          "color": "cornflowerblue",
          "width": 0.24948569334752285
         },
         "mode": "lines",
         "text": [
          "Clown--FLORIZEL: 0.9"
         ],
         "type": "scatter",
         "x": [
          -0.4520283925048223,
          0.5744147658947862,
          null
         ],
         "y": [
          -0.09549786119821281,
          0.24693788131499958,
          null
         ]
        },
        {
         "hoverinfo": "text",
         "line": {
          "color": "cornflowerblue",
          "width": 0.3
         },
         "mode": "lines",
         "text": [
          "Clown--MOPSA: 1.0"
         ],
         "type": "scatter",
         "x": [
          -0.4520283925048223,
          -0.027721520777830827,
          null
         ],
         "y": [
          -0.09549786119821281,
          -0.7354321235314945,
          null
         ]
        },
        {
         "hoverinfo": "text",
         "line": {
          "color": "cornflowerblue",
          "width": 2.5539321753503774
         },
         "mode": "lines",
         "text": [
          "Clown--PERDITA: 3.4"
         ],
         "type": "scatter",
         "x": [
          -0.4520283925048223,
          0.06053983664920965,
          null
         ],
         "y": [
          -0.09549786119821281,
          -0.08626445416797977,
          null
         ]
        },
        {
         "hoverinfo": "text",
         "line": {
          "color": "cornflowerblue",
          "width": 0.44331637922023864
         },
         "mode": "lines",
         "text": [
          "Clown--POLIXENES: 1.25"
         ],
         "type": "scatter",
         "x": [
          -0.4520283925048223,
          0.34969217610037684,
          null
         ],
         "y": [
          -0.09549786119821281,
          0.09377654604319183,
          null
         ]
        },
        {
         "hoverinfo": "text",
         "line": {
          "color": "cornflowerblue",
          "width": 0.38312674978270883
         },
         "mode": "lines",
         "text": [
          "Clown--Servant: 1.15"
         ],
         "type": "scatter",
         "x": [
          -0.4520283925048223,
          0.18148240362694995,
          null
         ],
         "y": [
          -0.09549786119821281,
          1,
          null
         ]
        },
        {
         "hoverinfo": "text",
         "line": {
          "color": "cornflowerblue",
          "width": 1.8182257732321594
         },
         "mode": "lines",
         "text": [
          "Clown--Shepherd: 2.8"
         ],
         "type": "scatter",
         "x": [
          -0.4520283925048223,
          -0.08649041288833349,
          null
         ],
         "y": [
          -0.09549786119821281,
          0.24275517874137242,
          null
         ]
        },
        {
         "hoverinfo": "text",
         "line": {
          "color": "cornflowerblue",
          "width": 0.24948569334752285
         },
         "mode": "lines",
         "text": [
          "DORCAS--FLORIZEL: 0.9"
         ],
         "type": "scatter",
         "x": [
          -0.6233235273262008,
          0.5744147658947862,
          null
         ],
         "y": [
          0.2958319626602499,
          0.24693788131499958,
          null
         ]
        },
        {
         "hoverinfo": "text",
         "line": {
          "color": "cornflowerblue",
          "width": 0.3
         },
         "mode": "lines",
         "text": [
          "DORCAS--MOPSA: 1.0"
         ],
         "type": "scatter",
         "x": [
          -0.6233235273262008,
          -0.027721520777830827,
          null
         ],
         "y": [
          0.2958319626602499,
          -0.7354321235314945,
          null
         ]
        },
        {
         "hoverinfo": "text",
         "line": {
          "color": "cornflowerblue",
          "width": 2.423933213160149
         },
         "mode": "lines",
         "text": [
          "DORCAS--PERDITA: 3.3"
         ],
         "type": "scatter",
         "x": [
          -0.6233235273262008,
          0.06053983664920965,
          null
         ],
         "y": [
          0.2958319626602499,
          -0.08626445416797977,
          null
         ]
        },
        {
         "hoverinfo": "text",
         "line": {
          "color": "cornflowerblue",
          "width": 0.41275128623228646
         },
         "mode": "lines",
         "text": [
          "DORCAS--POLIXENES: 1.2"
         ],
         "type": "scatter",
         "x": [
          -0.6233235273262008,
          0.34969217610037684,
          null
         ],
         "y": [
          0.2958319626602499,
          0.09377654604319183,
          null
         ]
        },
        {
         "hoverinfo": "text",
         "line": {
          "color": "cornflowerblue",
          "width": 0.5747980136142921
         },
         "mode": "lines",
         "text": [
          "DORCAS--Shepherd: 1.45"
         ],
         "type": "scatter",
         "x": [
          -0.6233235273262008,
          -0.08649041288833349,
          null
         ],
         "y": [
          0.2958319626602499,
          0.24275517874137242,
          null
         ]
        },
        {
         "hoverinfo": "text",
         "line": {
          "color": "cornflowerblue",
          "width": 0.0015860568951608462
         },
         "mode": "lines",
         "text": [
          "FLORIZEL--MOPSA: 0.05"
         ],
         "type": "scatter",
         "x": [
          0.5744147658947862,
          -0.027721520777830827,
          null
         ],
         "y": [
          0.24693788131499958,
          -0.7354321235314945,
          null
         ]
        },
        {
         "hoverinfo": "text",
         "line": {
          "color": "cornflowerblue",
          "width": 5.9259224169599145
         },
         "mode": "lines",
         "text": [
          "FLORIZEL--PERDITA: 5.5"
         ],
         "type": "scatter",
         "x": [
          0.5744147658947862,
          0.06053983664920965,
          null
         ],
         "y": [
          0.24693788131499958,
          -0.08626445416797977,
          null
         ]
        },
        {
         "hoverinfo": "text",
         "line": {
          "color": "cornflowerblue",
          "width": 4.584954936764896
         },
         "mode": "lines",
         "text": [
          "FLORIZEL--POLIXENES: 4.75"
         ],
         "type": "scatter",
         "x": [
          0.5744147658947862,
          0.34969217610037684,
          null
         ],
         "y": [
          0.24693788131499958,
          0.09377654604319183,
          null
         ]
        },
        {
         "hoverinfo": "text",
         "line": {
          "color": "cornflowerblue",
          "width": 0.0015860568951608462
         },
         "mode": "lines",
         "text": [
          "FLORIZEL--Servant: 0.05"
         ],
         "type": "scatter",
         "x": [
          0.5744147658947862,
          0.18148240362694995,
          null
         ],
         "y": [
          0.24693788131499958,
          1,
          null
         ]
        },
        {
         "hoverinfo": "text",
         "line": {
          "color": "cornflowerblue",
          "width": 1.0090756983044573
         },
         "mode": "lines",
         "text": [
          "FLORIZEL--Shepherd: 2.0"
         ],
         "type": "scatter",
         "x": [
          0.5744147658947862,
          -0.08649041288833349,
          null
         ],
         "y": [
          0.24693788131499958,
          0.24275517874137242,
          null
         ]
        },
        {
         "hoverinfo": "text",
         "line": {
          "color": "cornflowerblue",
          "width": 2.423933213160149
         },
         "mode": "lines",
         "text": [
          "MOPSA--PERDITA: 3.3"
         ],
         "type": "scatter",
         "x": [
          -0.027721520777830827,
          0.06053983664920965,
          null
         ],
         "y": [
          -0.7354321235314945,
          -0.08626445416797977,
          null
         ]
        },
        {
         "hoverinfo": "text",
         "line": {
          "color": "cornflowerblue",
          "width": 0.41275128623228646
         },
         "mode": "lines",
         "text": [
          "MOPSA--POLIXENES: 1.2"
         ],
         "type": "scatter",
         "x": [
          -0.027721520777830827,
          0.34969217610037684,
          null
         ],
         "y": [
          -0.7354321235314945,
          0.09377654604319183,
          null
         ]
        },
        {
         "hoverinfo": "text",
         "line": {
          "color": "cornflowerblue",
          "width": 0.5747980136142921
         },
         "mode": "lines",
         "text": [
          "MOPSA--Shepherd: 1.45"
         ],
         "type": "scatter",
         "x": [
          -0.027721520777830827,
          -0.08649041288833349,
          null
         ],
         "y": [
          -0.7354321235314945,
          0.24275517874137242,
          null
         ]
        },
        {
         "hoverinfo": "text",
         "line": {
          "color": "cornflowerblue",
          "width": 4.66974773501311
         },
         "mode": "lines",
         "text": [
          "PERDITA--POLIXENES: 4.8"
         ],
         "type": "scatter",
         "x": [
          0.06053983664920965,
          0.34969217610037684,
          null
         ],
         "y": [
          -0.08626445416797977,
          0.09377654604319183,
          null
         ]
        },
        {
         "hoverinfo": "text",
         "line": {
          "color": "cornflowerblue",
          "width": 0.41275128623228646
         },
         "mode": "lines",
         "text": [
          "PERDITA--Servant: 1.2"
         ],
         "type": "scatter",
         "x": [
          0.06053983664920965,
          0.18148240362694995,
          null
         ],
         "y": [
          -0.08626445416797977,
          1,
          null
         ]
        },
        {
         "hoverinfo": "text",
         "line": {
          "color": "cornflowerblue",
          "width": 1.65120704959167
         },
         "mode": "lines",
         "text": [
          "PERDITA--Shepherd: 2.65"
         ],
         "type": "scatter",
         "x": [
          0.06053983664920965,
          -0.08649041288833349,
          null
         ],
         "y": [
          -0.08626445416797977,
          0.24275517874137242,
          null
         ]
        },
        {
         "hoverinfo": "text",
         "line": {
          "color": "cornflowerblue",
          "width": 0.8391665007720779
         },
         "mode": "lines",
         "text": [
          "POLIXENES--Servant: 1.8"
         ],
         "type": "scatter",
         "x": [
          0.34969217610037684,
          0.18148240362694995,
          null
         ],
         "y": [
          0.09377654604319183,
          1,
          null
         ]
        },
        {
         "hoverinfo": "text",
         "line": {
          "color": "cornflowerblue",
          "width": 1.1922324718068633
         },
         "mode": "lines",
         "text": [
          "POLIXENES--Shepherd: 2.2"
         ],
         "type": "scatter",
         "x": [
          0.34969217610037684,
          -0.08649041288833349,
          null
         ],
         "y": [
          0.09377654604319183,
          0.24275517874137242,
          null
         ]
        },
        {
         "hoverinfo": "text",
         "line": {
          "color": "cornflowerblue",
          "width": 0.18133367599522268
         },
         "mode": "lines",
         "text": [
          "Servant--Shepherd: 0.75"
         ],
         "type": "scatter",
         "x": [
          0.18148240362694995,
          -0.08649041288833349,
          null
         ],
         "y": [
          1,
          0.24275517874137242,
          null
         ]
        },
        {
         "hoverinfo": "none",
         "marker": {
          "color": [
           "cornflowerblue",
           "cornflowerblue",
           "cornflowerblue",
           "cornflowerblue",
           "cornflowerblue",
           "cornflowerblue",
           "cornflowerblue",
           "cornflowerblue",
           "cornflowerblue",
           "cornflowerblue"
          ],
          "size": [
           5670,
           3930,
           2220,
           360,
           5040,
           600,
           3630,
           2850,
           1050,
           2520
          ]
         },
         "mode": "markers+text",
         "text": [
          "<b>AUTOLYCUS</b>",
          "<b>CAMILLO</b>",
          "<b>Clown</b>",
          "<b>DORCAS</b>",
          "<b>FLORIZEL</b>",
          "<b>MOPSA</b>",
          "<b>PERDITA</b>",
          "<b>POLIXENES</b>",
          "<b>Servant</b>",
          "<b>Shepherd</b>"
         ],
         "textfont": {
          "size": 10
         },
         "textposition": "top center",
         "type": "scatter",
         "x": [
          -0.508439948169892,
          0.5318746193957582,
          -0.4520283925048223,
          -0.6233235273262008,
          0.5744147658947862,
          -0.027721520777830827,
          0.06053983664920965,
          0.34969217610037684,
          0.18148240362694995,
          -0.08649041288833349
         ],
         "y": [
          -0.6654851612295354,
          -0.2966219686325922,
          -0.09549786119821281,
          0.2958319626602499,
          0.24693788131499958,
          -0.7354321235314945,
          -0.08626445416797977,
          0.09377654604319183,
          1,
          0.24275517874137242
         ]
        }
       ],
       "layout": {
        "paper_bgcolor": "rgba(0,0,0,0)",
        "plot_bgcolor": "rgba(0,0,0,0)",
        "showlegend": false,
        "template": {
         "data": {
          "bar": [
           {
            "error_x": {
             "color": "#2a3f5f"
            },
            "error_y": {
             "color": "#2a3f5f"
            },
            "marker": {
             "line": {
              "color": "#E5ECF6",
              "width": 0.5
             }
            },
            "type": "bar"
           }
          ],
          "barpolar": [
           {
            "marker": {
             "line": {
              "color": "#E5ECF6",
              "width": 0.5
             }
            },
            "type": "barpolar"
           }
          ],
          "carpet": [
           {
            "aaxis": {
             "endlinecolor": "#2a3f5f",
             "gridcolor": "white",
             "linecolor": "white",
             "minorgridcolor": "white",
             "startlinecolor": "#2a3f5f"
            },
            "baxis": {
             "endlinecolor": "#2a3f5f",
             "gridcolor": "white",
             "linecolor": "white",
             "minorgridcolor": "white",
             "startlinecolor": "#2a3f5f"
            },
            "type": "carpet"
           }
          ],
          "choropleth": [
           {
            "colorbar": {
             "outlinewidth": 0,
             "ticks": ""
            },
            "type": "choropleth"
           }
          ],
          "contour": [
           {
            "colorbar": {
             "outlinewidth": 0,
             "ticks": ""
            },
            "colorscale": [
             [
              0,
              "#0d0887"
             ],
             [
              0.1111111111111111,
              "#46039f"
             ],
             [
              0.2222222222222222,
              "#7201a8"
             ],
             [
              0.3333333333333333,
              "#9c179e"
             ],
             [
              0.4444444444444444,
              "#bd3786"
             ],
             [
              0.5555555555555556,
              "#d8576b"
             ],
             [
              0.6666666666666666,
              "#ed7953"
             ],
             [
              0.7777777777777778,
              "#fb9f3a"
             ],
             [
              0.8888888888888888,
              "#fdca26"
             ],
             [
              1,
              "#f0f921"
             ]
            ],
            "type": "contour"
           }
          ],
          "contourcarpet": [
           {
            "colorbar": {
             "outlinewidth": 0,
             "ticks": ""
            },
            "type": "contourcarpet"
           }
          ],
          "heatmap": [
           {
            "colorbar": {
             "outlinewidth": 0,
             "ticks": ""
            },
            "colorscale": [
             [
              0,
              "#0d0887"
             ],
             [
              0.1111111111111111,
              "#46039f"
             ],
             [
              0.2222222222222222,
              "#7201a8"
             ],
             [
              0.3333333333333333,
              "#9c179e"
             ],
             [
              0.4444444444444444,
              "#bd3786"
             ],
             [
              0.5555555555555556,
              "#d8576b"
             ],
             [
              0.6666666666666666,
              "#ed7953"
             ],
             [
              0.7777777777777778,
              "#fb9f3a"
             ],
             [
              0.8888888888888888,
              "#fdca26"
             ],
             [
              1,
              "#f0f921"
             ]
            ],
            "type": "heatmap"
           }
          ],
          "heatmapgl": [
           {
            "colorbar": {
             "outlinewidth": 0,
             "ticks": ""
            },
            "colorscale": [
             [
              0,
              "#0d0887"
             ],
             [
              0.1111111111111111,
              "#46039f"
             ],
             [
              0.2222222222222222,
              "#7201a8"
             ],
             [
              0.3333333333333333,
              "#9c179e"
             ],
             [
              0.4444444444444444,
              "#bd3786"
             ],
             [
              0.5555555555555556,
              "#d8576b"
             ],
             [
              0.6666666666666666,
              "#ed7953"
             ],
             [
              0.7777777777777778,
              "#fb9f3a"
             ],
             [
              0.8888888888888888,
              "#fdca26"
             ],
             [
              1,
              "#f0f921"
             ]
            ],
            "type": "heatmapgl"
           }
          ],
          "histogram": [
           {
            "marker": {
             "colorbar": {
              "outlinewidth": 0,
              "ticks": ""
             }
            },
            "type": "histogram"
           }
          ],
          "histogram2d": [
           {
            "colorbar": {
             "outlinewidth": 0,
             "ticks": ""
            },
            "colorscale": [
             [
              0,
              "#0d0887"
             ],
             [
              0.1111111111111111,
              "#46039f"
             ],
             [
              0.2222222222222222,
              "#7201a8"
             ],
             [
              0.3333333333333333,
              "#9c179e"
             ],
             [
              0.4444444444444444,
              "#bd3786"
             ],
             [
              0.5555555555555556,
              "#d8576b"
             ],
             [
              0.6666666666666666,
              "#ed7953"
             ],
             [
              0.7777777777777778,
              "#fb9f3a"
             ],
             [
              0.8888888888888888,
              "#fdca26"
             ],
             [
              1,
              "#f0f921"
             ]
            ],
            "type": "histogram2d"
           }
          ],
          "histogram2dcontour": [
           {
            "colorbar": {
             "outlinewidth": 0,
             "ticks": ""
            },
            "colorscale": [
             [
              0,
              "#0d0887"
             ],
             [
              0.1111111111111111,
              "#46039f"
             ],
             [
              0.2222222222222222,
              "#7201a8"
             ],
             [
              0.3333333333333333,
              "#9c179e"
             ],
             [
              0.4444444444444444,
              "#bd3786"
             ],
             [
              0.5555555555555556,
              "#d8576b"
             ],
             [
              0.6666666666666666,
              "#ed7953"
             ],
             [
              0.7777777777777778,
              "#fb9f3a"
             ],
             [
              0.8888888888888888,
              "#fdca26"
             ],
             [
              1,
              "#f0f921"
             ]
            ],
            "type": "histogram2dcontour"
           }
          ],
          "mesh3d": [
           {
            "colorbar": {
             "outlinewidth": 0,
             "ticks": ""
            },
            "type": "mesh3d"
           }
          ],
          "parcoords": [
           {
            "line": {
             "colorbar": {
              "outlinewidth": 0,
              "ticks": ""
             }
            },
            "type": "parcoords"
           }
          ],
          "pie": [
           {
            "automargin": true,
            "type": "pie"
           }
          ],
          "scatter": [
           {
            "marker": {
             "colorbar": {
              "outlinewidth": 0,
              "ticks": ""
             }
            },
            "type": "scatter"
           }
          ],
          "scatter3d": [
           {
            "line": {
             "colorbar": {
              "outlinewidth": 0,
              "ticks": ""
             }
            },
            "marker": {
             "colorbar": {
              "outlinewidth": 0,
              "ticks": ""
             }
            },
            "type": "scatter3d"
           }
          ],
          "scattercarpet": [
           {
            "marker": {
             "colorbar": {
              "outlinewidth": 0,
              "ticks": ""
             }
            },
            "type": "scattercarpet"
           }
          ],
          "scattergeo": [
           {
            "marker": {
             "colorbar": {
              "outlinewidth": 0,
              "ticks": ""
             }
            },
            "type": "scattergeo"
           }
          ],
          "scattergl": [
           {
            "marker": {
             "colorbar": {
              "outlinewidth": 0,
              "ticks": ""
             }
            },
            "type": "scattergl"
           }
          ],
          "scattermapbox": [
           {
            "marker": {
             "colorbar": {
              "outlinewidth": 0,
              "ticks": ""
             }
            },
            "type": "scattermapbox"
           }
          ],
          "scatterpolar": [
           {
            "marker": {
             "colorbar": {
              "outlinewidth": 0,
              "ticks": ""
             }
            },
            "type": "scatterpolar"
           }
          ],
          "scatterpolargl": [
           {
            "marker": {
             "colorbar": {
              "outlinewidth": 0,
              "ticks": ""
             }
            },
            "type": "scatterpolargl"
           }
          ],
          "scatterternary": [
           {
            "marker": {
             "colorbar": {
              "outlinewidth": 0,
              "ticks": ""
             }
            },
            "type": "scatterternary"
           }
          ],
          "surface": [
           {
            "colorbar": {
             "outlinewidth": 0,
             "ticks": ""
            },
            "colorscale": [
             [
              0,
              "#0d0887"
             ],
             [
              0.1111111111111111,
              "#46039f"
             ],
             [
              0.2222222222222222,
              "#7201a8"
             ],
             [
              0.3333333333333333,
              "#9c179e"
             ],
             [
              0.4444444444444444,
              "#bd3786"
             ],
             [
              0.5555555555555556,
              "#d8576b"
             ],
             [
              0.6666666666666666,
              "#ed7953"
             ],
             [
              0.7777777777777778,
              "#fb9f3a"
             ],
             [
              0.8888888888888888,
              "#fdca26"
             ],
             [
              1,
              "#f0f921"
             ]
            ],
            "type": "surface"
           }
          ],
          "table": [
           {
            "cells": {
             "fill": {
              "color": "#EBF0F8"
             },
             "line": {
              "color": "white"
             }
            },
            "header": {
             "fill": {
              "color": "#C8D4E3"
             },
             "line": {
              "color": "white"
             }
            },
            "type": "table"
           }
          ]
         },
         "layout": {
          "annotationdefaults": {
           "arrowcolor": "#2a3f5f",
           "arrowhead": 0,
           "arrowwidth": 1
          },
          "autotypenumbers": "strict",
          "coloraxis": {
           "colorbar": {
            "outlinewidth": 0,
            "ticks": ""
           }
          },
          "colorscale": {
           "diverging": [
            [
             0,
             "#8e0152"
            ],
            [
             0.1,
             "#c51b7d"
            ],
            [
             0.2,
             "#de77ae"
            ],
            [
             0.3,
             "#f1b6da"
            ],
            [
             0.4,
             "#fde0ef"
            ],
            [
             0.5,
             "#f7f7f7"
            ],
            [
             0.6,
             "#e6f5d0"
            ],
            [
             0.7,
             "#b8e186"
            ],
            [
             0.8,
             "#7fbc41"
            ],
            [
             0.9,
             "#4d9221"
            ],
            [
             1,
             "#276419"
            ]
           ],
           "sequential": [
            [
             0,
             "#0d0887"
            ],
            [
             0.1111111111111111,
             "#46039f"
            ],
            [
             0.2222222222222222,
             "#7201a8"
            ],
            [
             0.3333333333333333,
             "#9c179e"
            ],
            [
             0.4444444444444444,
             "#bd3786"
            ],
            [
             0.5555555555555556,
             "#d8576b"
            ],
            [
             0.6666666666666666,
             "#ed7953"
            ],
            [
             0.7777777777777778,
             "#fb9f3a"
            ],
            [
             0.8888888888888888,
             "#fdca26"
            ],
            [
             1,
             "#f0f921"
            ]
           ],
           "sequentialminus": [
            [
             0,
             "#0d0887"
            ],
            [
             0.1111111111111111,
             "#46039f"
            ],
            [
             0.2222222222222222,
             "#7201a8"
            ],
            [
             0.3333333333333333,
             "#9c179e"
            ],
            [
             0.4444444444444444,
             "#bd3786"
            ],
            [
             0.5555555555555556,
             "#d8576b"
            ],
            [
             0.6666666666666666,
             "#ed7953"
            ],
            [
             0.7777777777777778,
             "#fb9f3a"
            ],
            [
             0.8888888888888888,
             "#fdca26"
            ],
            [
             1,
             "#f0f921"
            ]
           ]
          },
          "colorway": [
           "#636efa",
           "#EF553B",
           "#00cc96",
           "#ab63fa",
           "#FFA15A",
           "#19d3f3",
           "#FF6692",
           "#B6E880",
           "#FF97FF",
           "#FECB52"
          ],
          "font": {
           "color": "#2a3f5f"
          },
          "geo": {
           "bgcolor": "white",
           "lakecolor": "white",
           "landcolor": "#E5ECF6",
           "showlakes": true,
           "showland": true,
           "subunitcolor": "white"
          },
          "hoverlabel": {
           "align": "left"
          },
          "hovermode": "closest",
          "mapbox": {
           "style": "light"
          },
          "paper_bgcolor": "white",
          "plot_bgcolor": "#E5ECF6",
          "polar": {
           "angularaxis": {
            "gridcolor": "white",
            "linecolor": "white",
            "ticks": ""
           },
           "bgcolor": "#E5ECF6",
           "radialaxis": {
            "gridcolor": "white",
            "linecolor": "white",
            "ticks": ""
           }
          },
          "scene": {
           "xaxis": {
            "backgroundcolor": "#E5ECF6",
            "gridcolor": "white",
            "gridwidth": 2,
            "linecolor": "white",
            "showbackground": true,
            "ticks": "",
            "zerolinecolor": "white"
           },
           "yaxis": {
            "backgroundcolor": "#E5ECF6",
            "gridcolor": "white",
            "gridwidth": 2,
            "linecolor": "white",
            "showbackground": true,
            "ticks": "",
            "zerolinecolor": "white"
           },
           "zaxis": {
            "backgroundcolor": "#E5ECF6",
            "gridcolor": "white",
            "gridwidth": 2,
            "linecolor": "white",
            "showbackground": true,
            "ticks": "",
            "zerolinecolor": "white"
           }
          },
          "shapedefaults": {
           "line": {
            "color": "#2a3f5f"
           }
          },
          "ternary": {
           "aaxis": {
            "gridcolor": "white",
            "linecolor": "white",
            "ticks": ""
           },
           "baxis": {
            "gridcolor": "white",
            "linecolor": "white",
            "ticks": ""
           },
           "bgcolor": "#E5ECF6",
           "caxis": {
            "gridcolor": "white",
            "linecolor": "white",
            "ticks": ""
           }
          },
          "title": {
           "x": 0.05
          },
          "xaxis": {
           "automargin": true,
           "gridcolor": "white",
           "linecolor": "white",
           "ticks": "",
           "title": {
            "standoff": 15
           },
           "zerolinecolor": "white",
           "zerolinewidth": 2
          },
          "yaxis": {
           "automargin": true,
           "gridcolor": "white",
           "linecolor": "white",
           "ticks": "",
           "title": {
            "standoff": 15
           },
           "zerolinecolor": "white",
           "zerolinewidth": 2
          }
         }
        },
        "xaxis": {
         "showticklabels": false
        },
        "yaxis": {
         "showticklabels": false
        }
       }
      },
      "text/html": [
       "<div>                            <div id=\"3e5b6ba4-952f-4efe-9913-f7122056c766\" class=\"plotly-graph-div\" style=\"height:525px; width:100%;\"></div>            <script type=\"text/javascript\">                require([\"plotly\"], function(Plotly) {                    window.PLOTLYENV=window.PLOTLYENV || {};                                    if (document.getElementById(\"3e5b6ba4-952f-4efe-9913-f7122056c766\")) {                    Plotly.newPlot(                        \"3e5b6ba4-952f-4efe-9913-f7122056c766\",                        [{\"hoverinfo\": \"text\", \"line\": {\"color\": \"cornflowerblue\", \"width\": 1.0090756983044573}, \"mode\": \"lines\", \"text\": [\"AUTOLYCUS--CAMILLO: 2.0\"], \"type\": \"scatter\", \"x\": [-0.508439948169892, 0.5318746193957582, null], \"y\": [-0.6654851612295354, -0.2966219686325922, null]}, {\"hoverinfo\": \"text\", \"line\": {\"color\": \"cornflowerblue\", \"width\": 2.172722285551274}, \"mode\": \"lines\", \"text\": [\"AUTOLYCUS--Clown: 3.1\"], \"type\": \"scatter\", \"x\": [-0.508439948169892, -0.4520283925048223, null], \"y\": [-0.6654851612295354, -0.09549786119821281, null]}, {\"hoverinfo\": \"text\", \"line\": {\"color\": \"cornflowerblue\", \"width\": 0.08919053362520407}, \"mode\": \"lines\", \"text\": [\"AUTOLYCUS--DORCAS: 0.5\"], \"type\": \"scatter\", \"x\": [-0.508439948169892, -0.6233235273262008, null], \"y\": [-0.6654851612295354, 0.2958319626602499, null]}, {\"hoverinfo\": \"text\", \"line\": {\"color\": \"cornflowerblue\", \"width\": 0.06035680462478091}, \"mode\": \"lines\", \"text\": [\"AUTOLYCUS--FLORIZEL: 0.4\"], \"type\": \"scatter\", \"x\": [-0.508439948169892, 0.5744147658947862, null], \"y\": [-0.6654851612295354, 0.24693788131499958, null]}, {\"hoverinfo\": \"text\", \"line\": {\"color\": \"cornflowerblue\", \"width\": 0.27424427106582416}, \"mode\": \"lines\", \"text\": [\"AUTOLYCUS--MOPSA: 0.95\"], \"type\": \"scatter\", \"x\": [-0.508439948169892, -0.027721520777830827, null], \"y\": [-0.6654851612295354, -0.7354321235314945, null]}, {\"hoverinfo\": \"text\", \"line\": {\"color\": \"cornflowerblue\", \"width\": 0.01794418537465465}, \"mode\": \"lines\", \"text\": [\"AUTOLYCUS--PERDITA: 0.2\"], \"type\": \"scatter\", \"x\": [-0.508439948169892, 0.06053983664920965, null], \"y\": [-0.6654851612295354, -0.08626445416797977, null]}, {\"hoverinfo\": \"text\", \"line\": {\"color\": \"cornflowerblue\", \"width\": 0.5072304878568292}, \"mode\": \"lines\", \"text\": [\"AUTOLYCUS--Shepherd: 1.35\"], \"type\": \"scatter\", \"x\": [-0.508439948169892, -0.08649041288833349, null], \"y\": [-0.6654851612295354, 0.24275517874137242, null]}, {\"hoverinfo\": \"text\", \"line\": {\"color\": \"cornflowerblue\", \"width\": 0.01794418537465465}, \"mode\": \"lines\", \"text\": [\"CAMILLO--Clown: 0.2\"], \"type\": \"scatter\", \"x\": [0.5318746193957582, -0.4520283925048223, null], \"y\": [-0.2966219686325922, -0.09549786119821281, null]}, {\"hoverinfo\": \"text\", \"line\": {\"color\": \"cornflowerblue\", \"width\": 0.005334838230116768}, \"mode\": \"lines\", \"text\": [\"CAMILLO--DORCAS: 0.1\"], \"type\": \"scatter\", \"x\": [0.5318746193957582, -0.6233235273262008, null], \"y\": [-0.2966219686325922, 0.2958319626602499, null]}, {\"hoverinfo\": \"text\", \"line\": {\"color\": \"cornflowerblue\", \"width\": 8.370514623234188}, \"mode\": \"lines\", \"text\": [\"CAMILLO--FLORIZEL: 6.7\"], \"type\": \"scatter\", \"x\": [0.5318746193957582, 0.5744147658947862, null], \"y\": [-0.2966219686325922, 0.24693788131499958, null]}, {\"hoverinfo\": \"text\", \"line\": {\"color\": \"cornflowerblue\", \"width\": 0.0015860568951608462}, \"mode\": \"lines\", \"text\": [\"CAMILLO--MOPSA: 0.05\"], \"type\": \"scatter\", \"x\": [0.5318746193957582, -0.027721520777830827, null], \"y\": [-0.2966219686325922, -0.7354321235314945, null]}, {\"hoverinfo\": \"text\", \"line\": {\"color\": \"cornflowerblue\", \"width\": 4.334584365205041}, \"mode\": \"lines\", \"text\": [\"CAMILLO--PERDITA: 4.6\"], \"type\": \"scatter\", \"x\": [0.5318746193957582, 0.06053983664920965, null], \"y\": [-0.2966219686325922, -0.08626445416797977, null]}, {\"hoverinfo\": \"text\", \"line\": {\"color\": \"cornflowerblue\", \"width\": 4.584954936764896}, \"mode\": \"lines\", \"text\": [\"CAMILLO--POLIXENES: 4.75\"], \"type\": \"scatter\", \"x\": [0.5318746193957582, 0.34969217610037684, null], \"y\": [-0.2966219686325922, 0.09377654604319183, null]}, {\"hoverinfo\": \"text\", \"line\": {\"color\": \"cornflowerblue\", \"width\": 0.0015860568951608462}, \"mode\": \"lines\", \"text\": [\"CAMILLO--Servant: 0.05\"], \"type\": \"scatter\", \"x\": [0.5318746193957582, 0.18148240362694995, null], \"y\": [-0.2966219686325922, 1.0, null]}, {\"hoverinfo\": \"text\", \"line\": {\"color\": \"cornflowerblue\", \"width\": 1.65120704959167}, \"mode\": \"lines\", \"text\": [\"CAMILLO--Shepherd: 2.65\"], \"type\": \"scatter\", \"x\": [0.5318746193957582, -0.08649041288833349, null], \"y\": [-0.2966219686325922, 0.24275517874137242, null]}, {\"hoverinfo\": \"text\", \"line\": {\"color\": \"cornflowerblue\", \"width\": 0.12271169157848992}, \"mode\": \"lines\", \"text\": [\"Clown--DORCAS: 0.6\"], \"type\": \"scatter\", \"x\": [-0.4520283925048223, -0.6233235273262008, null], \"y\": [-0.09549786119821281, 0.2958319626602499, null]}, {\"hoverinfo\": \"text\", \"line\": {\"color\": \"cornflowerblue\", \"width\": 0.24948569334752285}, \"mode\": \"lines\", \"text\": [\"Clown--FLORIZEL: 0.9\"], \"type\": \"scatter\", \"x\": [-0.4520283925048223, 0.5744147658947862, null], \"y\": [-0.09549786119821281, 0.24693788131499958, null]}, {\"hoverinfo\": \"text\", \"line\": {\"color\": \"cornflowerblue\", \"width\": 0.3}, \"mode\": \"lines\", \"text\": [\"Clown--MOPSA: 1.0\"], \"type\": \"scatter\", \"x\": [-0.4520283925048223, -0.027721520777830827, null], \"y\": [-0.09549786119821281, -0.7354321235314945, null]}, {\"hoverinfo\": \"text\", \"line\": {\"color\": \"cornflowerblue\", \"width\": 2.5539321753503774}, \"mode\": \"lines\", \"text\": [\"Clown--PERDITA: 3.4\"], \"type\": \"scatter\", \"x\": [-0.4520283925048223, 0.06053983664920965, null], \"y\": [-0.09549786119821281, -0.08626445416797977, null]}, {\"hoverinfo\": \"text\", \"line\": {\"color\": \"cornflowerblue\", \"width\": 0.44331637922023864}, \"mode\": \"lines\", \"text\": [\"Clown--POLIXENES: 1.25\"], \"type\": \"scatter\", \"x\": [-0.4520283925048223, 0.34969217610037684, null], \"y\": [-0.09549786119821281, 0.09377654604319183, null]}, {\"hoverinfo\": \"text\", \"line\": {\"color\": \"cornflowerblue\", \"width\": 0.38312674978270883}, \"mode\": \"lines\", \"text\": [\"Clown--Servant: 1.15\"], \"type\": \"scatter\", \"x\": [-0.4520283925048223, 0.18148240362694995, null], \"y\": [-0.09549786119821281, 1.0, null]}, {\"hoverinfo\": \"text\", \"line\": {\"color\": \"cornflowerblue\", \"width\": 1.8182257732321594}, \"mode\": \"lines\", \"text\": [\"Clown--Shepherd: 2.8\"], \"type\": \"scatter\", \"x\": [-0.4520283925048223, -0.08649041288833349, null], \"y\": [-0.09549786119821281, 0.24275517874137242, null]}, {\"hoverinfo\": \"text\", \"line\": {\"color\": \"cornflowerblue\", \"width\": 0.24948569334752285}, \"mode\": \"lines\", \"text\": [\"DORCAS--FLORIZEL: 0.9\"], \"type\": \"scatter\", \"x\": [-0.6233235273262008, 0.5744147658947862, null], \"y\": [0.2958319626602499, 0.24693788131499958, null]}, {\"hoverinfo\": \"text\", \"line\": {\"color\": \"cornflowerblue\", \"width\": 0.3}, \"mode\": \"lines\", \"text\": [\"DORCAS--MOPSA: 1.0\"], \"type\": \"scatter\", \"x\": [-0.6233235273262008, -0.027721520777830827, null], \"y\": [0.2958319626602499, -0.7354321235314945, null]}, {\"hoverinfo\": \"text\", \"line\": {\"color\": \"cornflowerblue\", \"width\": 2.423933213160149}, \"mode\": \"lines\", \"text\": [\"DORCAS--PERDITA: 3.3\"], \"type\": \"scatter\", \"x\": [-0.6233235273262008, 0.06053983664920965, null], \"y\": [0.2958319626602499, -0.08626445416797977, null]}, {\"hoverinfo\": \"text\", \"line\": {\"color\": \"cornflowerblue\", \"width\": 0.41275128623228646}, \"mode\": \"lines\", \"text\": [\"DORCAS--POLIXENES: 1.2\"], \"type\": \"scatter\", \"x\": [-0.6233235273262008, 0.34969217610037684, null], \"y\": [0.2958319626602499, 0.09377654604319183, null]}, {\"hoverinfo\": \"text\", \"line\": {\"color\": \"cornflowerblue\", \"width\": 0.5747980136142921}, \"mode\": \"lines\", \"text\": [\"DORCAS--Shepherd: 1.45\"], \"type\": \"scatter\", \"x\": [-0.6233235273262008, -0.08649041288833349, null], \"y\": [0.2958319626602499, 0.24275517874137242, null]}, {\"hoverinfo\": \"text\", \"line\": {\"color\": \"cornflowerblue\", \"width\": 0.0015860568951608462}, \"mode\": \"lines\", \"text\": [\"FLORIZEL--MOPSA: 0.05\"], \"type\": \"scatter\", \"x\": [0.5744147658947862, -0.027721520777830827, null], \"y\": [0.24693788131499958, -0.7354321235314945, null]}, {\"hoverinfo\": \"text\", \"line\": {\"color\": \"cornflowerblue\", \"width\": 5.9259224169599145}, \"mode\": \"lines\", \"text\": [\"FLORIZEL--PERDITA: 5.5\"], \"type\": \"scatter\", \"x\": [0.5744147658947862, 0.06053983664920965, null], \"y\": [0.24693788131499958, -0.08626445416797977, null]}, {\"hoverinfo\": \"text\", \"line\": {\"color\": \"cornflowerblue\", \"width\": 4.584954936764896}, \"mode\": \"lines\", \"text\": [\"FLORIZEL--POLIXENES: 4.75\"], \"type\": \"scatter\", \"x\": [0.5744147658947862, 0.34969217610037684, null], \"y\": [0.24693788131499958, 0.09377654604319183, null]}, {\"hoverinfo\": \"text\", \"line\": {\"color\": \"cornflowerblue\", \"width\": 0.0015860568951608462}, \"mode\": \"lines\", \"text\": [\"FLORIZEL--Servant: 0.05\"], \"type\": \"scatter\", \"x\": [0.5744147658947862, 0.18148240362694995, null], \"y\": [0.24693788131499958, 1.0, null]}, {\"hoverinfo\": \"text\", \"line\": {\"color\": \"cornflowerblue\", \"width\": 1.0090756983044573}, \"mode\": \"lines\", \"text\": [\"FLORIZEL--Shepherd: 2.0\"], \"type\": \"scatter\", \"x\": [0.5744147658947862, -0.08649041288833349, null], \"y\": [0.24693788131499958, 0.24275517874137242, null]}, {\"hoverinfo\": \"text\", \"line\": {\"color\": \"cornflowerblue\", \"width\": 2.423933213160149}, \"mode\": \"lines\", \"text\": [\"MOPSA--PERDITA: 3.3\"], \"type\": \"scatter\", \"x\": [-0.027721520777830827, 0.06053983664920965, null], \"y\": [-0.7354321235314945, -0.08626445416797977, null]}, {\"hoverinfo\": \"text\", \"line\": {\"color\": \"cornflowerblue\", \"width\": 0.41275128623228646}, \"mode\": \"lines\", \"text\": [\"MOPSA--POLIXENES: 1.2\"], \"type\": \"scatter\", \"x\": [-0.027721520777830827, 0.34969217610037684, null], \"y\": [-0.7354321235314945, 0.09377654604319183, null]}, {\"hoverinfo\": \"text\", \"line\": {\"color\": \"cornflowerblue\", \"width\": 0.5747980136142921}, \"mode\": \"lines\", \"text\": [\"MOPSA--Shepherd: 1.45\"], \"type\": \"scatter\", \"x\": [-0.027721520777830827, -0.08649041288833349, null], \"y\": [-0.7354321235314945, 0.24275517874137242, null]}, {\"hoverinfo\": \"text\", \"line\": {\"color\": \"cornflowerblue\", \"width\": 4.66974773501311}, \"mode\": \"lines\", \"text\": [\"PERDITA--POLIXENES: 4.8\"], \"type\": \"scatter\", \"x\": [0.06053983664920965, 0.34969217610037684, null], \"y\": [-0.08626445416797977, 0.09377654604319183, null]}, {\"hoverinfo\": \"text\", \"line\": {\"color\": \"cornflowerblue\", \"width\": 0.41275128623228646}, \"mode\": \"lines\", \"text\": [\"PERDITA--Servant: 1.2\"], \"type\": \"scatter\", \"x\": [0.06053983664920965, 0.18148240362694995, null], \"y\": [-0.08626445416797977, 1.0, null]}, {\"hoverinfo\": \"text\", \"line\": {\"color\": \"cornflowerblue\", \"width\": 1.65120704959167}, \"mode\": \"lines\", \"text\": [\"PERDITA--Shepherd: 2.65\"], \"type\": \"scatter\", \"x\": [0.06053983664920965, -0.08649041288833349, null], \"y\": [-0.08626445416797977, 0.24275517874137242, null]}, {\"hoverinfo\": \"text\", \"line\": {\"color\": \"cornflowerblue\", \"width\": 0.8391665007720779}, \"mode\": \"lines\", \"text\": [\"POLIXENES--Servant: 1.8\"], \"type\": \"scatter\", \"x\": [0.34969217610037684, 0.18148240362694995, null], \"y\": [0.09377654604319183, 1.0, null]}, {\"hoverinfo\": \"text\", \"line\": {\"color\": \"cornflowerblue\", \"width\": 1.1922324718068633}, \"mode\": \"lines\", \"text\": [\"POLIXENES--Shepherd: 2.2\"], \"type\": \"scatter\", \"x\": [0.34969217610037684, -0.08649041288833349, null], \"y\": [0.09377654604319183, 0.24275517874137242, null]}, {\"hoverinfo\": \"text\", \"line\": {\"color\": \"cornflowerblue\", \"width\": 0.18133367599522268}, \"mode\": \"lines\", \"text\": [\"Servant--Shepherd: 0.75\"], \"type\": \"scatter\", \"x\": [0.18148240362694995, -0.08649041288833349, null], \"y\": [1.0, 0.24275517874137242, null]}, {\"hoverinfo\": \"none\", \"marker\": {\"color\": [\"cornflowerblue\", \"cornflowerblue\", \"cornflowerblue\", \"cornflowerblue\", \"cornflowerblue\", \"cornflowerblue\", \"cornflowerblue\", \"cornflowerblue\", \"cornflowerblue\", \"cornflowerblue\"], \"size\": [5670, 3930, 2220, 360, 5040, 600, 3630, 2850, 1050, 2520]}, \"mode\": \"markers+text\", \"text\": [\"<b>AUTOLYCUS</b>\", \"<b>CAMILLO</b>\", \"<b>Clown</b>\", \"<b>DORCAS</b>\", \"<b>FLORIZEL</b>\", \"<b>MOPSA</b>\", \"<b>PERDITA</b>\", \"<b>POLIXENES</b>\", \"<b>Servant</b>\", \"<b>Shepherd</b>\"], \"textfont\": {\"size\": 10}, \"textposition\": \"top center\", \"type\": \"scatter\", \"x\": [-0.508439948169892, 0.5318746193957582, -0.4520283925048223, -0.6233235273262008, 0.5744147658947862, -0.027721520777830827, 0.06053983664920965, 0.34969217610037684, 0.18148240362694995, -0.08649041288833349], \"y\": [-0.6654851612295354, -0.2966219686325922, -0.09549786119821281, 0.2958319626602499, 0.24693788131499958, -0.7354321235314945, -0.08626445416797977, 0.09377654604319183, 1.0, 0.24275517874137242]}],                        {\"paper_bgcolor\": \"rgba(0,0,0,0)\", \"plot_bgcolor\": \"rgba(0,0,0,0)\", \"showlegend\": false, \"template\": {\"data\": {\"bar\": [{\"error_x\": {\"color\": \"#2a3f5f\"}, \"error_y\": {\"color\": \"#2a3f5f\"}, \"marker\": {\"line\": {\"color\": \"#E5ECF6\", \"width\": 0.5}}, \"type\": \"bar\"}], \"barpolar\": [{\"marker\": {\"line\": {\"color\": \"#E5ECF6\", \"width\": 0.5}}, \"type\": \"barpolar\"}], \"carpet\": [{\"aaxis\": {\"endlinecolor\": \"#2a3f5f\", \"gridcolor\": \"white\", \"linecolor\": \"white\", \"minorgridcolor\": \"white\", \"startlinecolor\": \"#2a3f5f\"}, \"baxis\": {\"endlinecolor\": \"#2a3f5f\", \"gridcolor\": \"white\", \"linecolor\": \"white\", \"minorgridcolor\": \"white\", \"startlinecolor\": \"#2a3f5f\"}, \"type\": \"carpet\"}], \"choropleth\": [{\"colorbar\": {\"outlinewidth\": 0, \"ticks\": \"\"}, \"type\": \"choropleth\"}], \"contour\": [{\"colorbar\": {\"outlinewidth\": 0, \"ticks\": \"\"}, \"colorscale\": [[0.0, \"#0d0887\"], [0.1111111111111111, \"#46039f\"], [0.2222222222222222, \"#7201a8\"], [0.3333333333333333, \"#9c179e\"], [0.4444444444444444, \"#bd3786\"], [0.5555555555555556, \"#d8576b\"], [0.6666666666666666, \"#ed7953\"], [0.7777777777777778, \"#fb9f3a\"], [0.8888888888888888, \"#fdca26\"], [1.0, \"#f0f921\"]], \"type\": \"contour\"}], \"contourcarpet\": [{\"colorbar\": {\"outlinewidth\": 0, \"ticks\": \"\"}, \"type\": \"contourcarpet\"}], \"heatmap\": [{\"colorbar\": {\"outlinewidth\": 0, \"ticks\": \"\"}, \"colorscale\": [[0.0, \"#0d0887\"], [0.1111111111111111, \"#46039f\"], [0.2222222222222222, \"#7201a8\"], [0.3333333333333333, \"#9c179e\"], [0.4444444444444444, \"#bd3786\"], [0.5555555555555556, \"#d8576b\"], [0.6666666666666666, \"#ed7953\"], [0.7777777777777778, \"#fb9f3a\"], [0.8888888888888888, \"#fdca26\"], [1.0, \"#f0f921\"]], \"type\": \"heatmap\"}], \"heatmapgl\": [{\"colorbar\": {\"outlinewidth\": 0, \"ticks\": \"\"}, \"colorscale\": [[0.0, \"#0d0887\"], [0.1111111111111111, \"#46039f\"], [0.2222222222222222, \"#7201a8\"], [0.3333333333333333, \"#9c179e\"], [0.4444444444444444, \"#bd3786\"], [0.5555555555555556, \"#d8576b\"], [0.6666666666666666, \"#ed7953\"], [0.7777777777777778, \"#fb9f3a\"], [0.8888888888888888, \"#fdca26\"], [1.0, \"#f0f921\"]], \"type\": \"heatmapgl\"}], \"histogram\": [{\"marker\": {\"colorbar\": {\"outlinewidth\": 0, \"ticks\": \"\"}}, \"type\": \"histogram\"}], \"histogram2d\": [{\"colorbar\": {\"outlinewidth\": 0, \"ticks\": \"\"}, \"colorscale\": [[0.0, \"#0d0887\"], [0.1111111111111111, \"#46039f\"], [0.2222222222222222, \"#7201a8\"], [0.3333333333333333, \"#9c179e\"], [0.4444444444444444, \"#bd3786\"], [0.5555555555555556, \"#d8576b\"], [0.6666666666666666, \"#ed7953\"], [0.7777777777777778, \"#fb9f3a\"], [0.8888888888888888, \"#fdca26\"], [1.0, \"#f0f921\"]], \"type\": \"histogram2d\"}], \"histogram2dcontour\": [{\"colorbar\": {\"outlinewidth\": 0, \"ticks\": \"\"}, \"colorscale\": [[0.0, \"#0d0887\"], [0.1111111111111111, \"#46039f\"], [0.2222222222222222, \"#7201a8\"], [0.3333333333333333, \"#9c179e\"], [0.4444444444444444, \"#bd3786\"], [0.5555555555555556, \"#d8576b\"], [0.6666666666666666, \"#ed7953\"], [0.7777777777777778, \"#fb9f3a\"], [0.8888888888888888, \"#fdca26\"], [1.0, \"#f0f921\"]], \"type\": \"histogram2dcontour\"}], \"mesh3d\": [{\"colorbar\": {\"outlinewidth\": 0, \"ticks\": \"\"}, \"type\": \"mesh3d\"}], \"parcoords\": [{\"line\": {\"colorbar\": {\"outlinewidth\": 0, \"ticks\": \"\"}}, \"type\": \"parcoords\"}], \"pie\": [{\"automargin\": true, \"type\": \"pie\"}], \"scatter\": [{\"marker\": {\"colorbar\": {\"outlinewidth\": 0, \"ticks\": \"\"}}, \"type\": \"scatter\"}], \"scatter3d\": [{\"line\": {\"colorbar\": {\"outlinewidth\": 0, \"ticks\": \"\"}}, \"marker\": {\"colorbar\": {\"outlinewidth\": 0, \"ticks\": \"\"}}, \"type\": \"scatter3d\"}], \"scattercarpet\": [{\"marker\": {\"colorbar\": {\"outlinewidth\": 0, \"ticks\": \"\"}}, \"type\": \"scattercarpet\"}], \"scattergeo\": [{\"marker\": {\"colorbar\": {\"outlinewidth\": 0, \"ticks\": \"\"}}, \"type\": \"scattergeo\"}], \"scattergl\": [{\"marker\": {\"colorbar\": {\"outlinewidth\": 0, \"ticks\": \"\"}}, \"type\": \"scattergl\"}], \"scattermapbox\": [{\"marker\": {\"colorbar\": {\"outlinewidth\": 0, \"ticks\": \"\"}}, \"type\": \"scattermapbox\"}], \"scatterpolar\": [{\"marker\": {\"colorbar\": {\"outlinewidth\": 0, \"ticks\": \"\"}}, \"type\": \"scatterpolar\"}], \"scatterpolargl\": [{\"marker\": {\"colorbar\": {\"outlinewidth\": 0, \"ticks\": \"\"}}, \"type\": \"scatterpolargl\"}], \"scatterternary\": [{\"marker\": {\"colorbar\": {\"outlinewidth\": 0, \"ticks\": \"\"}}, \"type\": \"scatterternary\"}], \"surface\": [{\"colorbar\": {\"outlinewidth\": 0, \"ticks\": \"\"}, \"colorscale\": [[0.0, \"#0d0887\"], [0.1111111111111111, \"#46039f\"], [0.2222222222222222, \"#7201a8\"], [0.3333333333333333, \"#9c179e\"], [0.4444444444444444, \"#bd3786\"], [0.5555555555555556, \"#d8576b\"], [0.6666666666666666, \"#ed7953\"], [0.7777777777777778, \"#fb9f3a\"], [0.8888888888888888, \"#fdca26\"], [1.0, \"#f0f921\"]], \"type\": \"surface\"}], \"table\": [{\"cells\": {\"fill\": {\"color\": \"#EBF0F8\"}, \"line\": {\"color\": \"white\"}}, \"header\": {\"fill\": {\"color\": \"#C8D4E3\"}, \"line\": {\"color\": \"white\"}}, \"type\": \"table\"}]}, \"layout\": {\"annotationdefaults\": {\"arrowcolor\": \"#2a3f5f\", \"arrowhead\": 0, \"arrowwidth\": 1}, \"autotypenumbers\": \"strict\", \"coloraxis\": {\"colorbar\": {\"outlinewidth\": 0, \"ticks\": \"\"}}, \"colorscale\": {\"diverging\": [[0, \"#8e0152\"], [0.1, \"#c51b7d\"], [0.2, \"#de77ae\"], [0.3, \"#f1b6da\"], [0.4, \"#fde0ef\"], [0.5, \"#f7f7f7\"], [0.6, \"#e6f5d0\"], [0.7, \"#b8e186\"], [0.8, \"#7fbc41\"], [0.9, \"#4d9221\"], [1, \"#276419\"]], \"sequential\": [[0.0, \"#0d0887\"], [0.1111111111111111, \"#46039f\"], [0.2222222222222222, \"#7201a8\"], [0.3333333333333333, \"#9c179e\"], [0.4444444444444444, \"#bd3786\"], [0.5555555555555556, \"#d8576b\"], [0.6666666666666666, \"#ed7953\"], [0.7777777777777778, \"#fb9f3a\"], [0.8888888888888888, \"#fdca26\"], [1.0, \"#f0f921\"]], \"sequentialminus\": [[0.0, \"#0d0887\"], [0.1111111111111111, \"#46039f\"], [0.2222222222222222, \"#7201a8\"], [0.3333333333333333, \"#9c179e\"], [0.4444444444444444, \"#bd3786\"], [0.5555555555555556, \"#d8576b\"], [0.6666666666666666, \"#ed7953\"], [0.7777777777777778, \"#fb9f3a\"], [0.8888888888888888, \"#fdca26\"], [1.0, \"#f0f921\"]]}, \"colorway\": [\"#636efa\", \"#EF553B\", \"#00cc96\", \"#ab63fa\", \"#FFA15A\", \"#19d3f3\", \"#FF6692\", \"#B6E880\", \"#FF97FF\", \"#FECB52\"], \"font\": {\"color\": \"#2a3f5f\"}, \"geo\": {\"bgcolor\": \"white\", \"lakecolor\": \"white\", \"landcolor\": \"#E5ECF6\", \"showlakes\": true, \"showland\": true, \"subunitcolor\": \"white\"}, \"hoverlabel\": {\"align\": \"left\"}, \"hovermode\": \"closest\", \"mapbox\": {\"style\": \"light\"}, \"paper_bgcolor\": \"white\", \"plot_bgcolor\": \"#E5ECF6\", \"polar\": {\"angularaxis\": {\"gridcolor\": \"white\", \"linecolor\": \"white\", \"ticks\": \"\"}, \"bgcolor\": \"#E5ECF6\", \"radialaxis\": {\"gridcolor\": \"white\", \"linecolor\": \"white\", \"ticks\": \"\"}}, \"scene\": {\"xaxis\": {\"backgroundcolor\": \"#E5ECF6\", \"gridcolor\": \"white\", \"gridwidth\": 2, \"linecolor\": \"white\", \"showbackground\": true, \"ticks\": \"\", \"zerolinecolor\": \"white\"}, \"yaxis\": {\"backgroundcolor\": \"#E5ECF6\", \"gridcolor\": \"white\", \"gridwidth\": 2, \"linecolor\": \"white\", \"showbackground\": true, \"ticks\": \"\", \"zerolinecolor\": \"white\"}, \"zaxis\": {\"backgroundcolor\": \"#E5ECF6\", \"gridcolor\": \"white\", \"gridwidth\": 2, \"linecolor\": \"white\", \"showbackground\": true, \"ticks\": \"\", \"zerolinecolor\": \"white\"}}, \"shapedefaults\": {\"line\": {\"color\": \"#2a3f5f\"}}, \"ternary\": {\"aaxis\": {\"gridcolor\": \"white\", \"linecolor\": \"white\", \"ticks\": \"\"}, \"baxis\": {\"gridcolor\": \"white\", \"linecolor\": \"white\", \"ticks\": \"\"}, \"bgcolor\": \"#E5ECF6\", \"caxis\": {\"gridcolor\": \"white\", \"linecolor\": \"white\", \"ticks\": \"\"}}, \"title\": {\"x\": 0.05}, \"xaxis\": {\"automargin\": true, \"gridcolor\": \"white\", \"linecolor\": \"white\", \"ticks\": \"\", \"title\": {\"standoff\": 15}, \"zerolinecolor\": \"white\", \"zerolinewidth\": 2}, \"yaxis\": {\"automargin\": true, \"gridcolor\": \"white\", \"linecolor\": \"white\", \"ticks\": \"\", \"title\": {\"standoff\": 15}, \"zerolinecolor\": \"white\", \"zerolinewidth\": 2}}}, \"xaxis\": {\"showticklabels\": false}, \"yaxis\": {\"showticklabels\": false}},                        {\"responsive\": true}                    ).then(function(){\n",
       "                            \n",
       "var gd = document.getElementById('3e5b6ba4-952f-4efe-9913-f7122056c766');\n",
       "var x = new MutationObserver(function (mutations, observer) {{\n",
       "        var display = window.getComputedStyle(gd).display;\n",
       "        if (!display || display === 'none') {{\n",
       "            console.log([gd, 'removed!']);\n",
       "            Plotly.purge(gd);\n",
       "            observer.disconnect();\n",
       "        }}\n",
       "}});\n",
       "\n",
       "// Listen for the removal of the full notebook cells\n",
       "var notebookContainer = gd.closest('#notebook-container');\n",
       "if (notebookContainer) {{\n",
       "    x.observe(notebookContainer, {childList: true});\n",
       "}}\n",
       "\n",
       "// Listen for the clearing of the current output cell\n",
       "var outputEl = gd.closest('.output');\n",
       "if (outputEl) {{\n",
       "    x.observe(outputEl, {childList: true});\n",
       "}}\n",
       "\n",
       "                        })                };                });            </script>        </div>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
      "text/plain": [
       "'test.html'"
      ]
     },
     "execution_count": 22,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "layout = go.Layout(\n",
    "    paper_bgcolor='rgba(0,0,0,0)',\n",
    "    plot_bgcolor='rgba(0,0,0,0)'\n",
    ")\n",
    "\n",
    "\n",
    "fig = go.Figure(layout = layout)\n",
    "\n",
    "for trace in edge_trace:\n",
    "    fig.add_trace(trace)\n",
    "\n",
    "fig.add_trace(node_trace)\n",
    "\n",
    "fig.update_layout(showlegend = False)\n",
    "\n",
    "fig.update_xaxes(showticklabels = False)\n",
    "\n",
    "fig.update_yaxes(showticklabels = False)\n",
    "\n",
    "fig.show()\n",
    "#py.iplot(fig, filename='a_winters_tale4-4_network')\n",
    "py.plot(fig, filename='test.html')"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "2293769a",
   "metadata": {},
   "source": [
    "# Alternate Plotting Method"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 9,
   "id": "d7ce90d0",
   "metadata": {},
   "outputs": [],
   "source": [
    "import networkx as nx\n",
    "import matplotlib.pyplot as plt"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "id": "a659292f",
   "metadata": {},
   "outputs": [],
   "source": [
    "winters_tale_"
   ]
  }
 ],
 "metadata": {
  "kernelspec": {
   "display_name": "Python 3",
   "language": "python",
   "name": "python3"
  },
  "language_info": {
   "codemirror_mode": {
    "name": "ipython",
    "version": 3
   },
   "file_extension": ".py",
   "mimetype": "text/x-python",
   "name": "python",
   "nbconvert_exporter": "python",
   "pygments_lexer": "ipython3",
   "version": "3.9.2"
  }
 },
 "nbformat": 4,
 "nbformat_minor": 5
}