Untitled.ipynb

{
 "cells": [
  {
   "cell_type": "code",
   "execution_count": 2,
   "metadata": {},
   "outputs": [],
   "source": [
    "import numpy as np\n",
    "import pandas as pd\n",
    "import torch\n",
    "\n",
    "data_raw = pd.read_csv('../data/titanic/raw/train.csv')"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 3,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
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       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>PassengerId</th>\n",
       "      <th>Survived</th>\n",
       "      <th>Pclass</th>\n",
       "      <th>Name</th>\n",
       "      <th>Sex</th>\n",
       "      <th>Age</th>\n",
       "      <th>SibSp</th>\n",
       "      <th>Parch</th>\n",
       "      <th>Ticket</th>\n",
       "      <th>Fare</th>\n",
       "      <th>Cabin</th>\n",
       "      <th>Embarked</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>3</td>\n",
       "      <td>Braund, Mr. Owen Harris</td>\n",
       "      <td>male</td>\n",
       "      <td>22.0</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>A/5 21171</td>\n",
       "      <td>7.2500</td>\n",
       "      <td>NaN</td>\n",
       "      <td>S</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>2</td>\n",
       "      <td>1</td>\n",
       "      <td>1</td>\n",
       "      <td>Cumings, Mrs. John Bradley (Florence Briggs Th...</td>\n",
       "      <td>female</td>\n",
       "      <td>38.0</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>PC 17599</td>\n",
       "      <td>71.2833</td>\n",
       "      <td>C85</td>\n",
       "      <td>C</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>3</td>\n",
       "      <td>1</td>\n",
       "      <td>3</td>\n",
       "      <td>Heikkinen, Miss. Laina</td>\n",
       "      <td>female</td>\n",
       "      <td>26.0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>STON/O2. 3101282</td>\n",
       "      <td>7.9250</td>\n",
       "      <td>NaN</td>\n",
       "      <td>S</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>4</td>\n",
       "      <td>1</td>\n",
       "      <td>1</td>\n",
       "      <td>Futrelle, Mrs. Jacques Heath (Lily May Peel)</td>\n",
       "      <td>female</td>\n",
       "      <td>35.0</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>113803</td>\n",
       "      <td>53.1000</td>\n",
       "      <td>C123</td>\n",
       "      <td>S</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>5</td>\n",
       "      <td>0</td>\n",
       "      <td>3</td>\n",
       "      <td>Allen, Mr. William Henry</td>\n",
       "      <td>male</td>\n",
       "      <td>35.0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>373450</td>\n",
       "      <td>8.0500</td>\n",
       "      <td>NaN</td>\n",
       "      <td>S</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "   PassengerId  Survived  Pclass  \\\n",
       "0            1         0       3   \n",
       "1            2         1       1   \n",
       "2            3         1       3   \n",
       "3            4         1       1   \n",
       "4            5         0       3   \n",
       "\n",
       "                                                Name     Sex   Age  SibSp  \\\n",
       "0                            Braund, Mr. Owen Harris    male  22.0      1   \n",
       "1  Cumings, Mrs. John Bradley (Florence Briggs Th...  female  38.0      1   \n",
       "2                             Heikkinen, Miss. Laina  female  26.0      0   \n",
       "3       Futrelle, Mrs. Jacques Heath (Lily May Peel)  female  35.0      1   \n",
       "4                           Allen, Mr. William Henry    male  35.0      0   \n",
       "\n",
       "   Parch            Ticket     Fare Cabin Embarked  \n",
       "0      0         A/5 21171   7.2500   NaN        S  \n",
       "1      0          PC 17599  71.2833   C85        C  \n",
       "2      0  STON/O2. 3101282   7.9250   NaN        S  \n",
       "3      0            113803  53.1000  C123        S  \n",
       "4      0            373450   8.0500   NaN        S  "
      ]
     },
     "execution_count": 3,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "data_raw.head()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 7,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
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       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>PassengerId</th>\n",
       "      <th>Pclass</th>\n",
       "      <th>Sex</th>\n",
       "      <th>Ticket</th>\n",
       "      <th>Cabin</th>\n",
       "      <th>Embarked</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>1</td>\n",
       "      <td>3</td>\n",
       "      <td>male</td>\n",
       "      <td>A/5 21171</td>\n",
       "      <td>NaN</td>\n",
       "      <td>S</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>2</td>\n",
       "      <td>1</td>\n",
       "      <td>female</td>\n",
       "      <td>PC 17599</td>\n",
       "      <td>C85</td>\n",
       "      <td>C</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>3</td>\n",
       "      <td>3</td>\n",
       "      <td>female</td>\n",
       "      <td>STON/O2. 3101282</td>\n",
       "      <td>NaN</td>\n",
       "      <td>S</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>4</td>\n",
       "      <td>1</td>\n",
       "      <td>female</td>\n",
       "      <td>113803</td>\n",
       "      <td>C123</td>\n",
       "      <td>S</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>5</td>\n",
       "      <td>3</td>\n",
       "      <td>male</td>\n",
       "      <td>373450</td>\n",
       "      <td>NaN</td>\n",
       "      <td>S</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
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      ],
      "text/plain": [
       "   PassengerId  Pclass     Sex            Ticket Cabin Embarked\n",
       "0            1       3    male         A/5 21171   NaN        S\n",
       "1            2       1  female          PC 17599   C85        C\n",
       "2            3       3  female  STON/O2. 3101282   NaN        S\n",
       "3            4       1  female            113803  C123        S\n",
       "4            5       3    male            373450   NaN        S"
      ]
     },
     "execution_count": 7,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "cat_cols = ['PassengerId', 'Pclass', 'Sex', 'Ticket', 'Cabin', 'Embarked']\n",
    "data_raw[cat_cols].head()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 11,
   "metadata": {},
   "outputs": [],
   "source": [
    "data_cat_col_str = data_raw[cat_cols].applymap(str)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 75,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
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     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
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      "(3, 891)\n",
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      "(3, 891)\n"
     ]
    },
    {
     "ename": "IndexError",
     "evalue": "index 3 is out of bounds for axis 0 with size 3",
     "traceback": [
      "\u001b[0;31m---------------------------------------------------------------------------\u001b[0m",
      "\u001b[0;31mIndexError\u001b[0m                                Traceback (most recent call last)",
      "\u001b[0;32m<ipython-input-75-63099e7ef469>\u001b[0m in \u001b[0;36m<module>\u001b[0;34m()\u001b[0m\n\u001b[1;32m     10\u001b[0m         \u001b[0midx\u001b[0m \u001b[0;34m=\u001b[0m \u001b[0mindex_dict\u001b[0m\u001b[0;34m[\u001b[0m\u001b[0mcolumn\u001b[0m\u001b[0;34m]\u001b[0m\u001b[0;34m[\u001b[0m\u001b[0mx\u001b[0m\u001b[0;34m]\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m     11\u001b[0m         \u001b[0mprint\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0mtemp_data\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0mshape\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0;32m---> 12\u001b[0;31m         \u001b[0mtemp_data\u001b[0m\u001b[0;34m[\u001b[0m\u001b[0mi\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0midx\u001b[0m\u001b[0;34m]\u001b[0m \u001b[0;34m=\u001b[0m \u001b[0;36m1\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0m\u001b[1;32m     13\u001b[0m \u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m     14\u001b[0m     \u001b[0mone_hot_data\u001b[0m\u001b[0;34m[\u001b[0m\u001b[0mcolumn\u001b[0m\u001b[0;34m]\u001b[0m \u001b[0;34m=\u001b[0m \u001b[0mtemp_data\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n",
      "\u001b[0;31mIndexError\u001b[0m: index 3 is out of bounds for axis 0 with size 3"
     ],
     "output_type": "error"
    }
   ],
   "source": [
    "from collections import Counter\n",
    "\n",
    "index_dict = {column: {pair[0]: i for i, pair in enumerate(Counter(data_cat_col_str[column].tolist()).most_common())} for column in data_cat_col_str.columns}\n",
    "\n",
    "one_hot_data = {}\n",
    "\n",
    "for column in data_cat_col_str.columns:\n",
    "    temp_data = np.zeros((len(index_dict[column]), len(data_cat_col_str)))\n",
    "    for i, x in data_cat_col_str[column].iteritems():\n",
    "        idx = index_dict[column][x]\n",
    "        print(temp_data.shape)\n",
    "        temp_data[i, idx] = 1\n",
    "        \n",
    "    one_hot_data[column] = temp_data"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 73,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "{'Cabin': array([[ 1.,  1.,  1., ...,  1.,  1.,  1.],\n",
       "        [ 1.,  1.,  1., ...,  1.,  1.,  1.],\n",
       "        [ 1.,  1.,  1., ...,  1.,  1.,  1.],\n",
       "        ..., \n",
       "        [ 1.,  1.,  1., ...,  1.,  1.,  1.],\n",
       "        [ 1.,  1.,  1., ...,  1.,  1.,  1.],\n",
       "        [ 1.,  1.,  1., ...,  1.,  1.,  1.]]),\n",
       " 'Embarked': array([[ 1.,  1.,  1., ...,  1.,  1.,  1.],\n",
       "        [ 1.,  1.,  1., ...,  1.,  1.,  1.],\n",
       "        [ 1.,  1.,  1., ...,  1.,  1.,  1.],\n",
       "        [ 1.,  1.,  1., ...,  1.,  1.,  1.]]),\n",
       " 'PassengerId': array([[ 1.,  1.,  1., ...,  1.,  1.,  1.],\n",
       "        [ 1.,  1.,  1., ...,  1.,  1.,  1.],\n",
       "        [ 1.,  1.,  1., ...,  1.,  1.,  1.],\n",
       "        ..., \n",
       "        [ 1.,  1.,  1., ...,  1.,  1.,  1.],\n",
       "        [ 1.,  1.,  1., ...,  1.,  1.,  1.],\n",
       "        [ 1.,  1.,  1., ...,  1.,  1.,  1.]]),\n",
       " 'Pclass': array([[ 1.,  1.,  1., ...,  1.,  1.,  1.],\n",
       "        [ 1.,  1.,  1., ...,  1.,  1.,  1.],\n",
       "        [ 1.,  1.,  1., ...,  1.,  1.,  1.]]),\n",
       " 'Sex': array([[ 1.,  1.,  1., ...,  1.,  1.,  1.],\n",
       "        [ 1.,  1.,  1., ...,  1.,  1.,  1.]]),\n",
       " 'Ticket': array([[ 1.,  1.,  1., ...,  1.,  1.,  1.],\n",
       "        [ 1.,  1.,  1., ...,  1.,  1.,  1.],\n",
       "        [ 1.,  1.,  1., ...,  1.,  1.,  1.],\n",
       "        ..., \n",
       "        [ 1.,  1.,  1., ...,  1.,  1.,  1.],\n",
       "        [ 1.,  1.,  1., ...,  1.,  1.,  1.],\n",
       "        [ 1.,  1.,  1., ...,  1.,  1.,  1.]])}"
      ]
     },
     "execution_count": 73,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "one_hot_data"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 71,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "{'Cabin': {'A10': 109,\n",
       "  'A14': 96,\n",
       "  'A16': 107,\n",
       "  'A19': 74,\n",
       "  'A20': 112,\n",
       "  'A23': 116,\n",
       "  'A24': 144,\n",
       "  'A26': 118,\n",
       "  'A31': 67,\n",
       "  'A32': 64,\n",
       "  'A34': 89,\n",
       "  'A36': 137,\n",
       "  'A5': 55,\n",
       "  'A6': 51,\n",
       "  'A7': 62,\n",
       "  'B101': 127,\n",
       "  'B102': 138,\n",
       "  'B18': 30,\n",
       "  'B19': 61,\n",
       "  'B20': 42,\n",
       "  'B22': 37,\n",
       "  'B28': 12,\n",
       "  'B3': 134,\n",
       "  'B30': 53,\n",
       "  'B35': 32,\n",
       "  'B37': 97,\n",
       "  'B38': 103,\n",
       "  'B39': 104,\n",
       "  'B4': 65,\n",
       "  'B41': 111,\n",
       "  'B42': 146,\n",
       "  'B49': 27,\n",
       "  'B5': 41,\n",
       "  'B50': 117,\n",
       "  'B51 B53 B55': 40,\n",
       "  'B57 B59 B63 B66': 29,\n",
       "  'B58 B60': 16,\n",
       "  'B69': 139,\n",
       "  'B71': 121,\n",
       "  'B73': 101,\n",
       "  'B77': 24,\n",
       "  'B78': 52,\n",
       "  'B79': 99,\n",
       "  'B80': 66,\n",
       "  'B82 B84': 136,\n",
       "  'B86': 60,\n",
       "  'B94': 70,\n",
       "  'B96 B98': 3,\n",
       "  'C101': 108,\n",
       "  'C103': 49,\n",
       "  'C104': 90,\n",
       "  'C106': 75,\n",
       "  'C110': 57,\n",
       "  'C111': 91,\n",
       "  'C118': 72,\n",
       "  'C123': 9,\n",
       "  'C124': 31,\n",
       "  'C125': 26,\n",
       "  'C126': 39,\n",
       "  'C128': 84,\n",
       "  'C148': 147,\n",
       "  'C2': 17,\n",
       "  'C22 C26': 8,\n",
       "  'C23 C25 C27': 2,\n",
       "  'C30': 98,\n",
       "  'C32': 80,\n",
       "  'C45': 126,\n",
       "  'C46': 129,\n",
       "  'C47': 141,\n",
       "  'C49': 63,\n",
       "  'C50': 145,\n",
       "  'C52': 11,\n",
       "  'C54': 77,\n",
       "  'C62 C64': 124,\n",
       "  'C65': 28,\n",
       "  'C68': 38,\n",
       "  'C7': 78,\n",
       "  'C70': 106,\n",
       "  'C78': 22,\n",
       "  'C82': 87,\n",
       "  'C83': 13,\n",
       "  'C85': 47,\n",
       "  'C86': 105,\n",
       "  'C87': 69,\n",
       "  'C90': 125,\n",
       "  'C91': 81,\n",
       "  'C92': 34,\n",
       "  'C93': 21,\n",
       "  'C95': 102,\n",
       "  'C99': 71,\n",
       "  'D': 7,\n",
       "  'D10 D12': 56,\n",
       "  'D11': 131,\n",
       "  'D15': 68,\n",
       "  'D17': 46,\n",
       "  'D19': 113,\n",
       "  'D20': 35,\n",
       "  'D21': 93,\n",
       "  'D26': 15,\n",
       "  'D28': 142,\n",
       "  'D30': 130,\n",
       "  'D33': 10,\n",
       "  'D35': 23,\n",
       "  'D36': 20,\n",
       "  'D37': 85,\n",
       "  'D45': 128,\n",
       "  'D46': 100,\n",
       "  'D47': 59,\n",
       "  'D48': 119,\n",
       "  'D49': 122,\n",
       "  'D50': 114,\n",
       "  'D56': 50,\n",
       "  'D6': 135,\n",
       "  'D7': 73,\n",
       "  'D9': 115,\n",
       "  'E10': 88,\n",
       "  'E101': 5,\n",
       "  'E12': 94,\n",
       "  'E121': 45,\n",
       "  'E17': 143,\n",
       "  'E24': 43,\n",
       "  'E25': 36,\n",
       "  'E31': 54,\n",
       "  'E33': 18,\n",
       "  'E34': 79,\n",
       "  'E36': 76,\n",
       "  'E38': 92,\n",
       "  'E40': 82,\n",
       "  'E44': 33,\n",
       "  'E46': 48,\n",
       "  'E49': 140,\n",
       "  'E50': 86,\n",
       "  'E58': 120,\n",
       "  'E63': 95,\n",
       "  'E67': 25,\n",
       "  'E68': 110,\n",
       "  'E77': 132,\n",
       "  'E8': 44,\n",
       "  'F E69': 58,\n",
       "  'F G63': 123,\n",
       "  'F G73': 14,\n",
       "  'F2': 6,\n",
       "  'F33': 4,\n",
       "  'F38': 133,\n",
       "  'F4': 19,\n",
       "  'G6': 1,\n",
       "  'T': 83,\n",
       "  'nan': 0},\n",
       " 'Embarked': {'C': 1, 'Q': 2, 'S': 0, 'nan': 3},\n",
       " 'PassengerId': {'1': 0,\n",
       "  '10': 9,\n",
       "  '100': 99,\n",
       "  '101': 100,\n",
       "  '102': 101,\n",
       "  '103': 102,\n",
       "  '104': 103,\n",
       "  '105': 104,\n",
       "  '106': 105,\n",
       "  '107': 106,\n",
       "  '108': 107,\n",
       "  '109': 108,\n",
       "  '11': 10,\n",
       "  '110': 109,\n",
       "  '111': 110,\n",
       "  '112': 111,\n",
       "  '113': 112,\n",
       "  '114': 113,\n",
       "  '115': 114,\n",
       "  '116': 115,\n",
       "  '117': 116,\n",
       "  '118': 117,\n",
       "  '119': 118,\n",
       "  '12': 11,\n",
       "  '120': 119,\n",
       "  '121': 120,\n",
       "  '122': 121,\n",
       "  '123': 122,\n",
       "  '124': 123,\n",
       "  '125': 124,\n",
       "  '126': 125,\n",
       "  '127': 126,\n",
       "  '128': 127,\n",
       "  '129': 128,\n",
       "  '13': 12,\n",
       "  '130': 129,\n",
       "  '131': 130,\n",
       "  '132': 131,\n",
       "  '133': 132,\n",
       "  '134': 133,\n",
       "  '135': 134,\n",
       "  '136': 135,\n",
       "  '137': 136,\n",
       "  '138': 137,\n",
       "  '139': 138,\n",
       "  '14': 13,\n",
       "  '140': 139,\n",
       "  '141': 140,\n",
       "  '142': 141,\n",
       "  '143': 142,\n",
       "  '144': 143,\n",
       "  '145': 144,\n",
       "  '146': 145,\n",
       "  '147': 146,\n",
       "  '148': 147,\n",
       "  '149': 148,\n",
       "  '15': 14,\n",
       "  '150': 149,\n",
       "  '151': 150,\n",
       "  '152': 151,\n",
       "  '153': 152,\n",
       "  '154': 153,\n",
       "  '155': 154,\n",
       "  '156': 155,\n",
       "  '157': 156,\n",
       "  '158': 157,\n",
       "  '159': 158,\n",
       "  '16': 15,\n",
       "  '160': 159,\n",
       "  '161': 160,\n",
       "  '162': 161,\n",
       "  '163': 162,\n",
       "  '164': 163,\n",
       "  '165': 164,\n",
       "  '166': 165,\n",
       "  '167': 166,\n",
       "  '168': 167,\n",
       "  '169': 168,\n",
       "  '17': 16,\n",
       "  '170': 169,\n",
       "  '171': 170,\n",
       "  '172': 171,\n",
       "  '173': 172,\n",
       "  '174': 173,\n",
       "  '175': 174,\n",
       "  '176': 175,\n",
       "  '177': 176,\n",
       "  '178': 177,\n",
       "  '179': 178,\n",
       "  '18': 17,\n",
       "  '180': 179,\n",
       "  '181': 180,\n",
       "  '182': 181,\n",
       "  '183': 182,\n",
       "  '184': 183,\n",
       "  '185': 184,\n",
       "  '186': 185,\n",
       "  '187': 186,\n",
       "  '188': 187,\n",
       "  '189': 188,\n",
       "  '19': 18,\n",
       "  '190': 189,\n",
       "  '191': 190,\n",
       "  '192': 191,\n",
       "  '193': 192,\n",
       "  '194': 193,\n",
       "  '195': 194,\n",
       "  '196': 195,\n",
       "  '197': 196,\n",
       "  '198': 197,\n",
       "  '199': 198,\n",
       "  '2': 1,\n",
       "  '20': 19,\n",
       "  '200': 199,\n",
       "  '201': 200,\n",
       "  '202': 201,\n",
       "  '203': 202,\n",
       "  '204': 203,\n",
       "  '205': 204,\n",
       "  '206': 205,\n",
       "  '207': 206,\n",
       "  '208': 207,\n",
       "  '209': 208,\n",
       "  '21': 20,\n",
       "  '210': 209,\n",
       "  '211': 210,\n",
       "  '212': 211,\n",
       "  '213': 212,\n",
       "  '214': 213,\n",
       "  '215': 214,\n",
       "  '216': 215,\n",
       "  '217': 216,\n",
       "  '218': 217,\n",
       "  '219': 218,\n",
       "  '22': 21,\n",
       "  '220': 219,\n",
       "  '221': 220,\n",
       "  '222': 221,\n",
       "  '223': 222,\n",
       "  '224': 223,\n",
       "  '225': 224,\n",
       "  '226': 225,\n",
       "  '227': 226,\n",
       "  '228': 227,\n",
       "  '229': 228,\n",
       "  '23': 22,\n",
       "  '230': 229,\n",
       "  '231': 230,\n",
       "  '232': 231,\n",
       "  '233': 232,\n",
       "  '234': 233,\n",
       "  '235': 234,\n",
       "  '236': 235,\n",
       "  '237': 236,\n",
       "  '238': 237,\n",
       "  '239': 238,\n",
       "  '24': 23,\n",
       "  '240': 239,\n",
       "  '241': 240,\n",
       "  '242': 241,\n",
       "  '243': 242,\n",
       "  '244': 243,\n",
       "  '245': 244,\n",
       "  '246': 245,\n",
       "  '247': 246,\n",
       "  '248': 247,\n",
       "  '249': 248,\n",
       "  '25': 24,\n",
       "  '250': 249,\n",
       "  '251': 250,\n",
       "  '252': 251,\n",
       "  '253': 252,\n",
       "  '254': 253,\n",
       "  '255': 254,\n",
       "  '256': 255,\n",
       "  '257': 256,\n",
       "  '258': 257,\n",
       "  '259': 258,\n",
       "  '26': 25,\n",
       "  '260': 259,\n",
       "  '261': 260,\n",
       "  '262': 261,\n",
       "  '263': 262,\n",
       "  '264': 263,\n",
       "  '265': 264,\n",
       "  '266': 265,\n",
       "  '267': 266,\n",
       "  '268': 267,\n",
       "  '269': 268,\n",
       "  '27': 26,\n",
       "  '270': 269,\n",
       "  '271': 270,\n",
       "  '272': 271,\n",
       "  '273': 272,\n",
       "  '274': 273,\n",
       "  '275': 274,\n",
       "  '276': 275,\n",
       "  '277': 276,\n",
       "  '278': 277,\n",
       "  '279': 278,\n",
       "  '28': 27,\n",
       "  '280': 279,\n",
       "  '281': 280,\n",
       "  '282': 281,\n",
       "  '283': 282,\n",
       "  '284': 283,\n",
       "  '285': 284,\n",
       "  '286': 285,\n",
       "  '287': 286,\n",
       "  '288': 287,\n",
       "  '289': 288,\n",
       "  '29': 28,\n",
       "  '290': 289,\n",
       "  '291': 290,\n",
       "  '292': 291,\n",
       "  '293': 292,\n",
       "  '294': 293,\n",
       "  '295': 294,\n",
       "  '296': 295,\n",
       "  '297': 296,\n",
       "  '298': 297,\n",
       "  '299': 298,\n",
       "  '3': 2,\n",
       "  '30': 29,\n",
       "  '300': 299,\n",
       "  '301': 300,\n",
       "  '302': 301,\n",
       "  '303': 302,\n",
       "  '304': 303,\n",
       "  '305': 304,\n",
       "  '306': 305,\n",
       "  '307': 306,\n",
       "  '308': 307,\n",
       "  '309': 308,\n",
       "  '31': 30,\n",
       "  '310': 309,\n",
       "  '311': 310,\n",
       "  '312': 311,\n",
       "  '313': 312,\n",
       "  '314': 313,\n",
       "  '315': 314,\n",
       "  '316': 315,\n",
       "  '317': 316,\n",
       "  '318': 317,\n",
       "  '319': 318,\n",
       "  '32': 31,\n",
       "  '320': 319,\n",
       "  '321': 320,\n",
       "  '322': 321,\n",
       "  '323': 322,\n",
       "  '324': 323,\n",
       "  '325': 324,\n",
       "  '326': 325,\n",
       "  '327': 326,\n",
       "  '328': 327,\n",
       "  '329': 328,\n",
       "  '33': 32,\n",
       "  '330': 329,\n",
       "  '331': 330,\n",
       "  '332': 331,\n",
       "  '333': 332,\n",
       "  '334': 333,\n",
       "  '335': 334,\n",
       "  '336': 335,\n",
       "  '337': 336,\n",
       "  '338': 337,\n",
       "  '339': 338,\n",
       "  '34': 33,\n",
       "  '340': 339,\n",
       "  '341': 340,\n",
       "  '342': 341,\n",
       "  '343': 342,\n",
       "  '344': 343,\n",
       "  '345': 344,\n",
       "  '346': 345,\n",
       "  '347': 346,\n",
       "  '348': 347,\n",
       "  '349': 348,\n",
       "  '35': 34,\n",
       "  '350': 349,\n",
       "  '351': 350,\n",
       "  '352': 351,\n",
       "  '353': 352,\n",
       "  '354': 353,\n",
       "  '355': 354,\n",
       "  '356': 355,\n",
       "  '357': 356,\n",
       "  '358': 357,\n",
       "  '359': 358,\n",
       "  '36': 35,\n",
       "  '360': 359,\n",
       "  '361': 360,\n",
       "  '362': 361,\n",
       "  '363': 362,\n",
       "  '364': 363,\n",
       "  '365': 364,\n",
       "  '366': 365,\n",
       "  '367': 366,\n",
       "  '368': 367,\n",
       "  '369': 368,\n",
       "  '37': 36,\n",
       "  '370': 369,\n",
       "  '371': 370,\n",
       "  '372': 371,\n",
       "  '373': 372,\n",
       "  '374': 373,\n",
       "  '375': 374,\n",
       "  '376': 375,\n",
       "  '377': 376,\n",
       "  '378': 377,\n",
       "  '379': 378,\n",
       "  '38': 37,\n",
       "  '380': 379,\n",
       "  '381': 380,\n",
       "  '382': 381,\n",
       "  '383': 382,\n",
       "  '384': 383,\n",
       "  '385': 384,\n",
       "  '386': 385,\n",
       "  '387': 386,\n",
       "  '388': 387,\n",
       "  '389': 388,\n",
       "  '39': 38,\n",
       "  '390': 389,\n",
       "  '391': 390,\n",
       "  '392': 391,\n",
       "  '393': 392,\n",
       "  '394': 393,\n",
       "  '395': 394,\n",
       "  '396': 395,\n",
       "  '397': 396,\n",
       "  '398': 397,\n",
       "  '399': 398,\n",
       "  '4': 3,\n",
       "  '40': 39,\n",
       "  '400': 399,\n",
       "  '401': 400,\n",
       "  '402': 401,\n",
       "  '403': 402,\n",
       "  '404': 403,\n",
       "  '405': 404,\n",
       "  '406': 405,\n",
       "  '407': 406,\n",
       "  '408': 407,\n",
       "  '409': 408,\n",
       "  '41': 40,\n",
       "  '410': 409,\n",
       "  '411': 410,\n",
       "  '412': 411,\n",
       "  '413': 412,\n",
       "  '414': 413,\n",
       "  '415': 414,\n",
       "  '416': 415,\n",
       "  '417': 416,\n",
       "  '418': 417,\n",
       "  '419': 418,\n",
       "  '42': 41,\n",
       "  '420': 419,\n",
       "  '421': 420,\n",
       "  '422': 421,\n",
       "  '423': 422,\n",
       "  '424': 423,\n",
       "  '425': 424,\n",
       "  '426': 425,\n",
       "  '427': 426,\n",
       "  '428': 427,\n",
       "  '429': 428,\n",
       "  '43': 42,\n",
       "  '430': 429,\n",
       "  '431': 430,\n",
       "  '432': 431,\n",
       "  '433': 432,\n",
       "  '434': 433,\n",
       "  '435': 434,\n",
       "  '436': 435,\n",
       "  '437': 436,\n",
       "  '438': 437,\n",
       "  '439': 438,\n",
       "  '44': 43,\n",
       "  '440': 439,\n",
       "  '441': 440,\n",
       "  '442': 441,\n",
       "  '443': 442,\n",
       "  '444': 443,\n",
       "  '445': 444,\n",
       "  '446': 445,\n",
       "  '447': 446,\n",
       "  '448': 447,\n",
       "  '449': 448,\n",
       "  '45': 44,\n",
       "  '450': 449,\n",
       "  '451': 450,\n",
       "  '452': 451,\n",
       "  '453': 452,\n",
       "  '454': 453,\n",
       "  '455': 454,\n",
       "  '456': 455,\n",
       "  '457': 456,\n",
       "  '458': 457,\n",
       "  '459': 458,\n",
       "  '46': 45,\n",
       "  '460': 459,\n",
       "  '461': 460,\n",
       "  '462': 461,\n",
       "  '463': 462,\n",
       "  '464': 463,\n",
       "  '465': 464,\n",
       "  '466': 465,\n",
       "  '467': 466,\n",
       "  '468': 467,\n",
       "  '469': 468,\n",
       "  '47': 46,\n",
       "  '470': 469,\n",
       "  '471': 470,\n",
       "  '472': 471,\n",
       "  '473': 472,\n",
       "  '474': 473,\n",
       "  '475': 474,\n",
       "  '476': 475,\n",
       "  '477': 476,\n",
       "  '478': 477,\n",
       "  '479': 478,\n",
       "  '48': 47,\n",
       "  '480': 479,\n",
       "  '481': 480,\n",
       "  '482': 481,\n",
       "  '483': 482,\n",
       "  '484': 483,\n",
       "  '485': 484,\n",
       "  '486': 485,\n",
       "  '487': 486,\n",
       "  '488': 487,\n",
       "  '489': 488,\n",
       "  '49': 48,\n",
       "  '490': 489,\n",
       "  '491': 490,\n",
       "  '492': 491,\n",
       "  '493': 492,\n",
       "  '494': 493,\n",
       "  '495': 494,\n",
       "  '496': 495,\n",
       "  '497': 496,\n",
       "  '498': 497,\n",
       "  '499': 498,\n",
       "  '5': 4,\n",
       "  '50': 49,\n",
       "  '500': 499,\n",
       "  '501': 500,\n",
       "  '502': 501,\n",
       "  '503': 502,\n",
       "  '504': 503,\n",
       "  '505': 504,\n",
       "  '506': 505,\n",
       "  '507': 506,\n",
       "  '508': 507,\n",
       "  '509': 508,\n",
       "  '51': 50,\n",
       "  '510': 509,\n",
       "  '511': 510,\n",
       "  '512': 511,\n",
       "  '513': 512,\n",
       "  '514': 513,\n",
       "  '515': 514,\n",
       "  '516': 515,\n",
       "  '517': 516,\n",
       "  '518': 517,\n",
       "  '519': 518,\n",
       "  '52': 51,\n",
       "  '520': 519,\n",
       "  '521': 520,\n",
       "  '522': 521,\n",
       "  '523': 522,\n",
       "  '524': 523,\n",
       "  '525': 524,\n",
       "  '526': 525,\n",
       "  '527': 526,\n",
       "  '528': 527,\n",
       "  '529': 528,\n",
       "  '53': 52,\n",
       "  '530': 529,\n",
       "  '531': 530,\n",
       "  '532': 531,\n",
       "  '533': 532,\n",
       "  '534': 533,\n",
       "  '535': 534,\n",
       "  '536': 535,\n",
       "  '537': 536,\n",
       "  '538': 537,\n",
       "  '539': 538,\n",
       "  '54': 53,\n",
       "  '540': 539,\n",
       "  '541': 540,\n",
       "  '542': 541,\n",
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       "  '546': 545,\n",
       "  '547': 546,\n",
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       "  '549': 548,\n",
       "  '55': 54,\n",
       "  '550': 549,\n",
       "  '551': 550,\n",
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       "  '553': 552,\n",
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       "  '555': 554,\n",
       "  '556': 555,\n",
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       "  '56': 55,\n",
       "  '560': 559,\n",
       "  '561': 560,\n",
       "  '562': 561,\n",
       "  '563': 562,\n",
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       "  '566': 565,\n",
       "  '567': 566,\n",
       "  '568': 567,\n",
       "  '569': 568,\n",
       "  '57': 56,\n",
       "  '570': 569,\n",
       "  '571': 570,\n",
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       "  '576': 575,\n",
       "  '577': 576,\n",
       "  '578': 577,\n",
       "  '579': 578,\n",
       "  '58': 57,\n",
       "  '580': 579,\n",
       "  '581': 580,\n",
       "  '582': 581,\n",
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       "  '584': 583,\n",
       "  '585': 584,\n",
       "  '586': 585,\n",
       "  '587': 586,\n",
       "  '588': 587,\n",
       "  '589': 588,\n",
       "  '59': 58,\n",
       "  '590': 589,\n",
       "  '591': 590,\n",
       "  '592': 591,\n",
       "  '593': 592,\n",
       "  '594': 593,\n",
       "  '595': 594,\n",
       "  '596': 595,\n",
       "  '597': 596,\n",
       "  '598': 597,\n",
       "  '599': 598,\n",
       "  '6': 5,\n",
       "  '60': 59,\n",
       "  '600': 599,\n",
       "  '601': 600,\n",
       "  '602': 601,\n",
       "  '603': 602,\n",
       "  '604': 603,\n",
       "  '605': 604,\n",
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       "  '614': 613,\n",
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       "  '335097': 594,\n",
       "  '335677': 154,\n",
       "  '33638': 402,\n",
       "  '336439': 302,\n",
       "  '3411': 496,\n",
       "  '341826': 374,\n",
       "  '34218': 574,\n",
       "  '342826': 552,\n",
       "  '343095': 383,\n",
       "  '343120': 201,\n",
       "  '343275': 188,\n",
       "  '343276': 189,\n",
       "  '345364': 328,\n",
       "  '345572': 477,\n",
       "  '345763': 145,\n",
       "  '345764': 47,\n",
       "  '345765': 669,\n",
       "  '345767': 182,\n",
       "  '345769': 398,\n",
       "  '345770': 257,\n",
       "  '345773': 37,\n",
       "  '345774': 308,\n",
       "  '345777': 666,\n",
       "  '345778': 304,\n",
       "  '345779': 183,\n",
       "  '345780': 596,\n",
       "  '345781': 607,\n",
       "  '345783': 345,\n",
       "  '3460': 425,\n",
       "  '347054': 76,\n",
       "  '347060': 654,\n",
       "  '347061': 212,\n",
       "  '347062': 576,\n",
       "  '347063': 628,\n",
       "  '347064': 378,\n",
       "  '347067': 279,\n",
       "  '347068': 235,\n",
       "  '347069': 361,\n",
       "  '347071': 289,\n",
       "  '347073': 301,\n",
       "  '347074': 603,\n",
       "  '347076': 399,\n",
       "  '347077': 9,\n",
       "  '347078': 611,\n",
       "  '347080': 108,\n",
       "  '347081': 220,\n",
       "  '347082': 0,\n",
       "  '347083': 298,\n",
       "  '347085': 474,\n",
       "  '347087': 630,\n",
       "  '347088': 5,\n",
       "  '347089': 627,\n",
       "  '3474': 632,\n",
       "  '347464': 303,\n",
       "  '347466': 190,\n",
       "  '347468': 643,\n",
       "  '347470': 323,\n",
       "  '347742': 19,\n",
       "  '347743': 524,\n",
       "  '348121': 564,\n",
       "  '348123': 179,\n",
       "  '348124': 573,\n",
       "  '349201': 587,\n",
       "  '349203': 621,\n",
       "  '349204': 597,\n",
       "  '349205': 483,\n",
       "  '349206': 309,\n",
       "  '349207': 200,\n",
       "  '349208': 180,\n",
       "  '349209': 450,\n",
       "  '349210': 542,\n",
       "  '349212': 671,\n",
       "  '349213': 653,\n",
       "  '349214': 506,\n",
       "  '349215': 197,\n",
       "  '349216': 152,\n",
       "  '349217': 672,\n",
       "  '349218': 588,\n",
       "  '349219': 326,\n",
       "  '349221': 534,\n",
       "  '349222': 380,\n",
       "  '349223': 538,\n",
       "  '349224': 521,\n",
       "  '349225': 331,\n",
       "  '349227': 363,\n",
       "  '349228': 556,\n",
       "  '349231': 530,\n",
       "  '349233': 314,\n",
       "  '349234': 274,\n",
       "  '349236': 313,\n",
       "  '349237': 50,\n",
       "  '349239': 307,\n",
       "  '349240': 408,\n",
       "  '349241': 213,\n",
       "  '349242': 454,\n",
       "  '349243': 322,\n",
       "  '349244': 624,\n",
       "  '349245': 196,\n",
       "  '349246': 511,\n",
       "  '349247': 248,\n",
       "  '349248': 667,\n",
       "  '349249': 203,\n",
       "  '349251': 479,\n",
       "  '349252': 455,\n",
       "  '349253': 159,\n",
       "  '349254': 387,\n",
       "  '349256': 558,\n",
       "  '349257': 673,\n",
       "  '349909': 8,\n",
       "  '349910': 510,\n",
       "  '349912': 551,\n",
       "  '350025': 567,\n",
       "  '350026': 659,\n",
       "  '350029': 518,\n",
       "  '350034': 367,\n",
       "  '350035': 439,\n",
       "  '350036': 557,\n",
       "  '350042': 598,\n",
       "  '350043': 223,\n",
       "  '350046': 251,\n",
       "  '350047': 608,\n",
       "  '350048': 577,\n",
       "  '350050': 529,\n",
       "  '350052': 369,\n",
       "  '350060': 426,\n",
       "  '350404': 241,\n",
       "  '350406': 142,\n",
       "  '350407': 370,\n",
       "  '350417': 485,\n",
       "  '35273': 26,\n",
       "  '35281': 60,\n",
       "  '35851': 230,\n",
       "  '35852': 563,\n",
       "  '358585': 121,\n",
       "  '36209': 420,\n",
       "  '362316': 290,\n",
       "  '363291': 25,\n",
       "  '363294': 600,\n",
       "  '363592': 562,\n",
       "  '364498': 467,\n",
       "  '364499': 634,\n",
       "  '364500': 192,\n",
       "  '364506': 414,\n",
       "  '364511': 508,\n",
       "  '364512': 515,\n",
       "  '364516': 55,\n",
       "  '364846': 441,\n",
       "  '364848': 503,\n",
       "  '364849': 75,\n",
       "  '364850': 605,\n",
       "  '364851': 392,\n",
       "  '365222': 221,\n",
       "  '365226': 537,\n",
       "  '36568': 575,\n",
       "  '367226': 93,\n",
       "  '367228': 641,\n",
       "  '367229': 267,\n",
       "  '367230': 80,\n",
       "  '367231': 261,\n",
       "  '367232': 458,\n",
       "  '367655': 365,\n",
       "  '368323': 640,\n",
       "  '36864': 566,\n",
       "  '36865': 613,\n",
       "  '36866': 581,\n",
       "  '368703': 253,\n",
       "  '36928': 99,\n",
       "  '36947': 114,\n",
       "  '36963': 519,\n",
       "  '36967': 451,\n",
       "  '36973': 52,\n",
       "  '370129': 86,\n",
       "  '370365': 74,\n",
       "  '370369': 207,\n",
       "  '370370': 255,\n",
       "  '370371': 162,\n",
       "  '370372': 210,\n",
       "  '370373': 311,\n",
       "  '370375': 300,\n",
       "  '370376': 680,\n",
       "  '370377': 514,\n",
       "  '371060': 412,\n",
       "  '371110': 23,\n",
       "  '371362': 233,\n",
       "  '372622': 478,\n",
       "  '373450': 137,\n",
       "  '374746': 181,\n",
       "  '374887': 617,\n",
       "  '374910': 193,\n",
       "  '376564': 110,\n",
       "  '376566': 590,\n",
       "  '382649': 296,\n",
       "  '382651': 446,\n",
       "  '382652': 6,\n",
       "  '383121': 612,\n",
       "  '384461': 294,\n",
       "  '386525': 339,\n",
       "  '392091': 656,\n",
       "  '392092': 647,\n",
       "  '392096': 130,\n",
       "  '394140': 381,\n",
       "  '4133': 12,\n",
       "  '4134': 430,\n",
       "  '4135': 443,\n",
       "  '4136': 205,\n",
       "  '4137': 375,\n",
       "  '4138': 553,\n",
       "  '4579': 254,\n",
       "  '54636': 124,\n",
       "  '5727': 541,\n",
       "  '65303': 405,\n",
       "  '65304': 433,\n",
       "  '65306': 401,\n",
       "  '6563': 555,\n",
       "  '693': 469,\n",
       "  '695': 668,\n",
       "  '7267': 341,\n",
       "  '7534': 66,\n",
       "  '7540': 198,\n",
       "  '7545': 572,\n",
       "  '7546': 158,\n",
       "  '7552': 674,\n",
       "  '7553': 424,\n",
       "  '7598': 332,\n",
       "  '8471': 606,\n",
       "  '8475': 535,\n",
       "  '9234': 318,\n",
       "  'A./5. 2152': 157,\n",
       "  'A./5. 3235': 500,\n",
       "  'A.5. 11206': 226,\n",
       "  'A.5. 18509': 432,\n",
       "  'A/4 45380': 437,\n",
       "  'A/4 48871': 120,\n",
       "  'A/4. 20589': 490,\n",
       "  'A/4. 34244': 390,\n",
       "  'A/4. 39886': 165,\n",
       "  'A/5 21171': 134,\n",
       "  'A/5 21172': 325,\n",
       "  'A/5 21173': 277,\n",
       "  'A/5 21174': 265,\n",
       "  'A/5 2466': 320,\n",
       "  'A/5 2817': 407,\n",
       "  'A/5 3536': 546,\n",
       "  'A/5 3540': 260,\n",
       "  'A/5 3594': 429,\n",
       "  'A/5 3902': 502,\n",
       "  'A/5. 10482': 305,\n",
       "  'A/5. 13032': 388,\n",
       "  'A/5. 2151': 141,\n",
       "  'A/5. 3336': 85,\n",
       "  'A/5. 3337': 215,\n",
       "  'A/5. 851': 227,\n",
       "  'A/S 2816': 417,\n",
       "  'A4. 54510': 208,\n",
       "  'C 17369': 211,\n",
       "  'C 4001': 445,\n",
       "  'C 7075': 637,\n",
       "  'C 7076': 351,\n",
       "  'C 7077': 358,\n",
       "  'C.A. 17248': 297,\n",
       "  'C.A. 18723': 397,\n",
       "  'C.A. 2315': 57,\n",
       "  'C.A. 24579': 155,\n",
       "  'C.A. 24580': 548,\n",
       "  'C.A. 2673': 90,\n",
       "  'C.A. 29178': 217,\n",
       "  'C.A. 29395': 173,\n",
       "  'C.A. 29566': 281,\n",
       "  'C.A. 31026': 169,\n",
       "  'C.A. 31921': 27,\n",
       "  'C.A. 33111': 177,\n",
       "  'C.A. 33112': 70,\n",
       "  'C.A. 33595': 234,\n",
       "  'C.A. 34260': 452,\n",
       "  'C.A. 34651': 22,\n",
       "  'C.A. 37671': 103,\n",
       "  'C.A. 5547': 652,\n",
       "  'C.A. 6212': 438,\n",
       "  'C.A./SOTON 34068': 675,\n",
       "  'CA 2144': 4,\n",
       "  'CA. 2314': 533,\n",
       "  'CA. 2343': 2,\n",
       "  'F.C. 12750': 547,\n",
       "  'F.C.C. 13528': 264,\n",
       "  'F.C.C. 13529': 35,\n",
       "  'F.C.C. 13531': 411,\n",
       "  'Fa 265302': 228,\n",
       "  'LINE': 13,\n",
       "  'P/PP 3381': 95,\n",
       "  'PC 17318': 237,\n",
       "  'PC 17473': 448,\n",
       "  'PC 17474': 488,\n",
       "  'PC 17475': 565,\n",
       "  'PC 17476': 569,\n",
       "  'PC 17477': 105,\n",
       "  'PC 17482': 570,\n",
       "  'PC 17483': 460,\n",
       "  'PC 17485': 96,\n",
       "  'PC 17558': 64,\n",
       "  'PC 17569': 44,\n",
       "  'PC 17572': 21,\n",
       "  'PC 17582': 31,\n",
       "  'PC 17585': 293,\n",
       "  'PC 17590': 665,\n",
       "  'PC 17592': 655,\n",
       "  'PC 17593': 67,\n",
       "  'PC 17595': 242,\n",
       "  'PC 17596': 299,\n",
       "  'PC 17597': 229,\n",
       "  'PC 17599': 135,\n",
       "  'PC 17600': 620,\n",
       "  'PC 17601': 153,\n",
       "  'PC 17603': 449,\n",
       "  'PC 17604': 45,\n",
       "  'PC 17605': 172,\n",
       "  'PC 17608': 98,\n",
       "  'PC 17609': 436,\n",
       "  'PC 17610': 252,\n",
       "  'PC 17611': 102,\n",
       "  'PC 17612': 315,\n",
       "  'PC 17754': 194,\n",
       "  'PC 17755': 29,\n",
       "  'PC 17756': 645,\n",
       "  'PC 17757': 16,\n",
       "  'PC 17758': 94,\n",
       "  'PC 17759': 195,\n",
       "  'PC 17760': 32,\n",
       "  'PC 17761': 117,\n",
       "  'PP 4348': 275,\n",
       "  'PP 9549': 42,\n",
       "  'S.C./A.4. 23567': 161,\n",
       "  'S.C./PARIS 2079': 133,\n",
       "  'S.O./P.P. 3': 131,\n",
       "  'S.O./P.P. 751': 532,\n",
       "  'S.O.C. 14879': 7,\n",
       "  'S.O.P. 1166': 225,\n",
       "  'S.P. 3464': 174,\n",
       "  'S.W./PP 752': 486,\n",
       "  'SC 1748': 366,\n",
       "  'SC/AH 29037': 504,\n",
       "  'SC/AH 3085': 395,\n",
       "  'SC/AH Basle 541': 423,\n",
       "  'SC/PARIS 2131': 244,\n",
       "  'SC/PARIS 2133': 218,\n",
       "  'SC/PARIS 2146': 470,\n",
       "  'SC/PARIS 2149': 664,\n",
       "  'SC/PARIS 2167': 349,\n",
       "  'SC/Paris 2123': 20,\n",
       "  'SC/Paris 2163': 312,\n",
       "  'SCO/W 1585': 285,\n",
       "  'SO/C 14885': 186,\n",
       "  'SOTON/O.Q. 3101305': 513,\n",
       "  'SOTON/O.Q. 3101306': 418,\n",
       "  'SOTON/O.Q. 3101307': 214,\n",
       "  'SOTON/O.Q. 3101310': 350,\n",
       "  'SOTON/O.Q. 3101311': 263,\n",
       "  'SOTON/O.Q. 3101312': 616,\n",
       "  'SOTON/O.Q. 392078': 393,\n",
       "  'SOTON/O.Q. 392087': 482,\n",
       "  'SOTON/O2 3101272': 601,\n",
       "  'SOTON/O2 3101287': 649,\n",
       "  'SOTON/OQ 3101316': 447,\n",
       "  'SOTON/OQ 3101317': 434,\n",
       "  'SOTON/OQ 392076': 676,\n",
       "  'SOTON/OQ 392082': 481,\n",
       "  'SOTON/OQ 392086': 187,\n",
       "  'SOTON/OQ 392089': 271,\n",
       "  'SOTON/OQ 392090': 231,\n",
       "  'STON/O 2. 3101269': 382,\n",
       "  'STON/O 2. 3101273': 501,\n",
       "  'STON/O 2. 3101274': 396,\n",
       "  'STON/O 2. 3101275': 287,\n",
       "  'STON/O 2. 3101280': 239,\n",
       "  'STON/O 2. 3101285': 543,\n",
       "  'STON/O 2. 3101286': 493,\n",
       "  'STON/O 2. 3101288': 591,\n",
       "  'STON/O 2. 3101289': 373,\n",
       "  'STON/O 2. 3101292': 528,\n",
       "  'STON/O 2. 3101293': 362,\n",
       "  'STON/O 2. 3101294': 206,\n",
       "  'STON/O2. 3101271': 583,\n",
       "  'STON/O2. 3101279': 69,\n",
       "  'STON/O2. 3101282': 136,\n",
       "  'STON/O2. 3101283': 268,\n",
       "  'STON/O2. 3101290': 636,\n",
       "  'SW/PP 751': 276,\n",
       "  'W./C. 14258': 459,\n",
       "  'W./C. 14263': 286,\n",
       "  'W./C. 6607': 132,\n",
       "  'W./C. 6608': 11,\n",
       "  'W./C. 6609': 282,\n",
       "  'W.E.P. 5734': 191,\n",
       "  'W/C 14208': 270,\n",
       "  'WE/P 5735': 118}}"
      ]
     },
     "execution_count": 71,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "index_dict"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 49,
   "metadata": {
    "scrolled": true
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "PassengerId 1\n",
      "Pclass 3\n",
      "Sex male\n",
      "Ticket A/5 21171\n",
      "Cabin nan\n",
      "Embarked S\n",
      "PassengerId 2\n",
      "Pclass 1\n",
      "Sex female\n",
      "Ticket PC 17599\n",
      "Cabin C85\n",
      "Embarked C\n",
      "PassengerId 3\n",
      "Pclass 3\n",
      "Sex female\n",
      "Ticket STON/O2. 3101282\n",
      "Cabin nan\n",
      "Embarked S\n",
      "PassengerId 4\n",
      "Pclass 1\n",
      "Sex female\n",
      "Ticket 113803\n",
      "Cabin C123\n",
      "Embarked S\n",
      "PassengerId 5\n",
      "Pclass 3\n",
      "Sex male\n",
      "Ticket 373450\n",
      "Cabin nan\n",
      "Embarked S\n",
      "PassengerId 6\n",
      "Pclass 3\n",
      "Sex male\n",
      "Ticket 330877\n",
      "Cabin nan\n",
      "Embarked Q\n",
      "PassengerId 7\n",
      "Pclass 1\n",
      "Sex male\n",
      "Ticket 17463\n",
      "Cabin E46\n",
      "Embarked S\n",
      "PassengerId 8\n",
      "Pclass 3\n",
      "Sex male\n",
      "Ticket 349909\n",
      "Cabin nan\n",
      "Embarked S\n",
      "PassengerId 9\n",
      "Pclass 3\n",
      "Sex female\n",
      "Ticket 347742\n",
      "Cabin nan\n",
      "Embarked S\n",
      "PassengerId 10\n",
      "Pclass 2\n",
      "Sex female\n",
      "Ticket 237736\n",
      "Cabin nan\n",
      "Embarked C\n"
     ]
    }
   ],
   "source": [
    "one_hot_data = []\n",
    "\n",
    "for i, row in list(data_cat_col_str.iterrows())[:10]:\n",
    "    temp_arr = np.zeros(len(all_values))\n",
    "\n",
    "    for j, x in row.iteritems():\n",
    "        idx = all_values.index(j + '_' + x)\n",
    "        temp_arr[idx] = 1\n",
    "    \n",
    "    one_hot_data.append(temp_arr)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 60,
   "metadata": {},
   "outputs": [],
   "source": [
    "one_hot_data = np.array(one_hot_data)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 67,
   "metadata": {},
   "outputs": [],
   "source": [
    "from collections import Counter\n",
    "\n",
    "test = {pair[0]: i for i, pair in enumerate(Counter(data_cat_col_str['Pclass'].tolist()).most_common())}"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 68,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "{'1': 1, '2': 2, '3': 0}"
      ]
     },
     "execution_count": 68,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "test"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {
    "collapsed": true
   },
   "outputs": [],
   "source": []
  }
 ],
 "metadata": {
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   "display_name": "Python [conda env:pytorch]",
   "language": "python",
   "name": "conda-env-pytorch-py"
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   "codemirror_mode": {
    "name": "ipython",
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   "name": "python",
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