metadataParser.ipynb

{
 "cells": [
  {
   "cell_type": "code",
   "execution_count": 71,
   "id": "isolated-moment",
   "metadata": {},
   "outputs": [],
   "source": [
    "import pandas as pd\n",
    "pd.options.display.float_format = '{:.0f}'.format\n",
    "tokenId = '_metadata.json-2022-09-21T06-18-25'"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 72,
   "id": "fifteen-prophet",
   "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>name</th>\n",
       "      <th>serial</th>\n",
       "      <th>figure</th>\n",
       "      <th>shoes</th>\n",
       "      <th>topping</th>\n",
       "      <th>hat</th>\n",
       "      <th>eyes</th>\n",
       "      <th>lefthand</th>\n",
       "      <th>righthand</th>\n",
       "      <th>feels</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>Hotdog Hustle Generation 2</td>\n",
       "      <td>1</td>\n",
       "      <td>Hotdog</td>\n",
       "      <td>BlackAdidas</td>\n",
       "      <td>Mustard</td>\n",
       "      <td>Raccoon</td>\n",
       "      <td>BlackRaybanSunglasses</td>\n",
       "      <td>BinxWiener</td>\n",
       "      <td>PeaceSign</td>\n",
       "      <td>Happy</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>Hotdog Hustle Generation 2</td>\n",
       "      <td>2</td>\n",
       "      <td>Hotdog</td>\n",
       "      <td>PurpleAdidas</td>\n",
       "      <td>BlueFannyPack444WithMustard</td>\n",
       "      <td>Raccoon</td>\n",
       "      <td>MintCateyeSunglasses</td>\n",
       "      <td>FingersWithFingers</td>\n",
       "      <td>FingersWithFingers</td>\n",
       "      <td>Happy</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>Hotdog Hustle Generation 2</td>\n",
       "      <td>3</td>\n",
       "      <td>Hotdog</td>\n",
       "      <td>PurpleMonsterSlippers</td>\n",
       "      <td>PinkFannyPackHDH</td>\n",
       "      <td>GoldTiara</td>\n",
       "      <td>Laughing</td>\n",
       "      <td>YellowFlowers</td>\n",
       "      <td>HulkHand</td>\n",
       "      <td>Happy</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>Hotdog Hustle Generation 2</td>\n",
       "      <td>4</td>\n",
       "      <td>Hotdog</td>\n",
       "      <td>BlackAdidas</td>\n",
       "      <td>RadFannyPackHDHWithMustard</td>\n",
       "      <td>GoldTiara</td>\n",
       "      <td>Laughing</td>\n",
       "      <td>FingersWithFingers</td>\n",
       "      <td>BinxWiener</td>\n",
       "      <td>Happy</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>Hotdog Hustle Generation 2</td>\n",
       "      <td>5</td>\n",
       "      <td>MutantDog</td>\n",
       "      <td>RadAdidas</td>\n",
       "      <td>RadFannyPack444</td>\n",
       "      <td>HiTrucker</td>\n",
       "      <td>Laughing</td>\n",
       "      <td>GreenMonster</td>\n",
       "      <td>PeaceSign</td>\n",
       "      <td>Happy</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "                         name  serial     figure                  shoes  \\\n",
       "0  Hotdog Hustle Generation 2       1     Hotdog            BlackAdidas   \n",
       "1  Hotdog Hustle Generation 2       2     Hotdog           PurpleAdidas   \n",
       "2  Hotdog Hustle Generation 2       3     Hotdog  PurpleMonsterSlippers   \n",
       "3  Hotdog Hustle Generation 2       4     Hotdog            BlackAdidas   \n",
       "4  Hotdog Hustle Generation 2       5  MutantDog              RadAdidas   \n",
       "\n",
       "                       topping        hat                   eyes  \\\n",
       "0                      Mustard    Raccoon  BlackRaybanSunglasses   \n",
       "1  BlueFannyPack444WithMustard    Raccoon   MintCateyeSunglasses   \n",
       "2             PinkFannyPackHDH  GoldTiara               Laughing   \n",
       "3   RadFannyPackHDHWithMustard  GoldTiara               Laughing   \n",
       "4              RadFannyPack444  HiTrucker               Laughing   \n",
       "\n",
       "             lefthand           righthand  feels  \n",
       "0          BinxWiener           PeaceSign  Happy  \n",
       "1  FingersWithFingers  FingersWithFingers  Happy  \n",
       "2       YellowFlowers            HulkHand  Happy  \n",
       "3  FingersWithFingers          BinxWiener  Happy  \n",
       "4        GreenMonster           PeaceSign  Happy  "
      ]
     },
     "execution_count": 72,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "metadata_df = pd.read_table(tokenId+'.tsv')\n",
    "metadata_df.head()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 73,
   "id": "steady-ceremony",
   "metadata": {
    "scrolled": false
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "<class 'pandas.core.frame.DataFrame'>\n",
      "RangeIndex: 2222 entries, 0 to 2221\n",
      "Data columns (total 10 columns):\n",
      " #   Column     Non-Null Count  Dtype \n",
      "---  ------     --------------  ----- \n",
      " 0   name       2222 non-null   object\n",
      " 1   serial     2222 non-null   int64 \n",
      " 2   figure     2222 non-null   object\n",
      " 3   shoes      2222 non-null   object\n",
      " 4   topping    2222 non-null   object\n",
      " 5   hat        2222 non-null   object\n",
      " 6   eyes       2222 non-null   object\n",
      " 7   lefthand   2222 non-null   object\n",
      " 8   righthand  2222 non-null   object\n",
      " 9   feels      2222 non-null   object\n",
      "dtypes: int64(1), object(9)\n",
      "memory usage: 173.7+ KB\n"
     ]
    },
    {
     "data": {
      "text/plain": [
       "['name',\n",
       " 'serial',\n",
       " 'figure',\n",
       " 'shoes',\n",
       " 'topping',\n",
       " 'hat',\n",
       " 'eyes',\n",
       " 'lefthand',\n",
       " 'righthand',\n",
       " 'feels']"
      ]
     },
     "execution_count": 73,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "metadata_df.info()\n",
    "metadata_df.columns.values.tolist()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 74,
   "id": "sophisticated-internship",
   "metadata": {},
   "outputs": [],
   "source": [
    "column_list = [\n",
    " 'figure',\n",
    " 'shoes',\n",
    " 'topping',\n",
    " 'hat',\n",
    " 'eyes',\n",
    " 'lefthand',\n",
    " 'righthand',\n",
    " 'feels'\n",
    "]"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 75,
   "id": "stopped-beaver",
   "metadata": {
    "scrolled": false
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "             percentage  count\n",
      "MutantDog         0.86%     19\n",
      "GoldenDog         1.58%     35\n",
      "Hotdog           97.57%   2168\n",
      "Column_Total    100.00%   2222\n",
      "                      percentage  count\n",
      "BlueMonsterSlippers        3.60%     80\n",
      "RadAdidas                  4.01%     89\n",
      "PurpleMonsterSlippers      4.46%     99\n",
      "NeonLowVans                4.77%    106\n",
      "NeonHighVans               5.58%    124\n",
      "BlackAdidas                6.62%    147\n",
      "LeopardLowVans             8.01%    178\n",
      "PinkHighVans               9.32%    207\n",
      "PurpleAdidas               9.68%    215\n",
      "PinkLowVans                9.77%    217\n",
      "GreenAdidas               10.44%    232\n",
      "BlueHighVans              11.66%    259\n",
      "BlueLowVans               12.11%    269\n",
      "Column_Total             100.00%   2222\n",
      "                            percentage  count\n",
      "RadFannyPack444WithMustard       1.67%     37\n",
      "RadFannyPack444                  2.48%     55\n",
      "PinkSundress                     2.66%     59\n",
      "PinkFannyPack444                 2.93%     65\n",
      "GreenMonsterPack                 3.56%     79\n",
      "None                             3.69%     82\n",
      "MintSundress                     3.96%     88\n",
      "GreenMonsterPackWithMustard      4.23%     94\n",
      "BlueMonsterPackWithMustard       4.86%    108\n",
      "BlueMonsterPack                  5.54%    123\n",
      "BlueFannyPack444                 5.94%    132\n",
      "BlueFannyPack444WithMustard      6.39%    142\n",
      "RadSundress                      6.44%    143\n",
      "BlueFannyPackHDH                 6.93%    154\n",
      "BlueFannyPackHDHWithMustard      7.29%    162\n",
      "RadFannyPackHDHWithMustard       7.34%    163\n",
      "PinkFannyPackHDH                 7.74%    172\n",
      "RadFannyPackHDH                  8.10%    180\n",
      "Mustard                          8.28%    184\n",
      "Column_Total                   100.00%   2222\n",
      "                    percentage  count\n",
      "Raccoon                  4.55%    101\n",
      "RainbowTrucker           5.63%    125\n",
      "RedMonster               6.30%    140\n",
      "RadTrucker               6.30%    140\n",
      "YellowMonster            6.35%    141\n",
      "SilverTiara              6.44%    143\n",
      "GoofyUnicornTrucker      7.88%    175\n",
      "UnicornTrucker           7.97%    177\n",
      "HiTrucker                8.37%    186\n",
      "HotdogTrucker            9.09%    202\n",
      "GoldTiara               10.13%    225\n",
      "Bunny                   10.49%    233\n",
      "Flowers                 10.53%    234\n",
      "Column_Total           100.00%   2222\n",
      "                       percentage  count\n",
      "RainbowStarSunglasses       3.92%     87\n",
      "WhiteRaybanSunglasses       4.19%     93\n",
      "PurpleCateyeSunglasses      5.54%    123\n",
      "BlueFlowerSunglasses        6.17%    137\n",
      "RedStarSunglasses           6.75%    150\n",
      "MintCateyeSunglasses        8.46%    188\n",
      "PinkFlowerSunglasses        9.59%    213\n",
      "HbarSunglasses             10.08%    224\n",
      "BlackRaybanSunglasses      10.40%    231\n",
      "Laughing                   34.92%    776\n",
      "Column_Total              100.00%   2222\n",
      "                   percentage  count\n",
      "YellowPepeTroll         2.16%     48\n",
      "RadPepeTroll            3.06%     68\n",
      "OrangeMonster           3.24%     72\n",
      "GreenMonster            3.83%     85\n",
      "Lifteeg                 5.27%    117\n",
      "BinxWiener              5.63%    125\n",
      "OrangePepeTroll         6.03%    134\n",
      "RedFlowers              6.12%    136\n",
      "FingersWithFingers      7.83%    174\n",
      "YellowFlowers           8.51%    189\n",
      "Soaker                  8.73%    194\n",
      "GreenTRex               9.09%    202\n",
      "PeaceSign               9.14%    203\n",
      "HulkHand               10.08%    224\n",
      "Empty                  11.30%    251\n",
      "Column_Total          100.00%   2222\n",
      "                   percentage  count\n",
      "RedTRex                 0.50%     11\n",
      "PurpleFlowers           1.22%     27\n",
      "PurplePepeTroll         1.94%     43\n",
      "RadPepeTroll            3.60%     80\n",
      "GreenMonster            3.83%     85\n",
      "OrangeMonster           4.59%    102\n",
      "RedPepeTroll            5.36%    119\n",
      "WhiteFlowers            6.30%    140\n",
      "BinxWiener              6.80%    151\n",
      "Toobetch                7.61%    169\n",
      "FingersWithFingers      8.46%    188\n",
      "PeaceSign               8.64%    192\n",
      "Soaker                  9.59%    213\n",
      "HulkHand               10.40%    231\n",
      "Bubbles                10.44%    232\n",
      "Empty                  10.76%    239\n",
      "Column_Total          100.00%   2222\n",
      "             percentage  count\n",
      "Everything        0.54%     12\n",
      "Perfect           0.86%     19\n",
      "RainbowPuke       4.14%     92\n",
      "Happy            94.46%   2099\n",
      "Column_Total    100.00%   2222\n"
     ]
    }
   ],
   "source": [
    "\n",
    "for column_name in column_list:\n",
    "    df_norm = metadata_df[column_name].value_counts(ascending=True, normalize=True, dropna=False)\n",
    "    df_count = metadata_df[column_name].value_counts(ascending=True, dropna=False)\n",
    "    df_stat_table = pd.concat([df_norm, df_count], axis=1, join='inner')\n",
    "    df_stat_table.set_axis([\"percentage\", \"count\"], axis=1, inplace = True)\n",
    "    df_stat_table.loc['Column_Total'] = df_stat_table.sum(numeric_only=True, axis=0)\n",
    "    df_stat_table['percentage'] = pd.Series([\"{0:.2f}%\".format(val * 100) for val in df_stat_table['percentage']], index = df_stat_table.index)\n",
    "    print(df_stat_table)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 76,
   "id": "temporal-negotiation",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "'\\n\\nfigure:\\n             percentage  count\\nMutantDog         0.86%     19\\nGoldenDog         1.58%     35\\nHotdog           97.57%   2168\\nColumn_Total    100.00%   2222\\n\\nshoes:\\n                      percentage  count\\nBlueMonsterSlippers        3.60%     80\\nRadAdidas                  4.01%     89\\nPurpleMonsterSlippers      4.46%     99\\nNeonLowVans                4.77%    106\\nNeonHighVans               5.58%    124\\nBlackAdidas                6.62%    147\\nLeopardLowVans             8.01%    178\\nPinkHighVans               9.32%    207\\nPurpleAdidas               9.68%    215\\nPinkLowVans                9.77%    217\\nGreenAdidas               10.44%    232\\nBlueHighVans              11.66%    259\\nBlueLowVans               12.11%    269\\nColumn_Total             100.00%   2222\\n\\ntopping:\\n                            percentage  count\\nRadFannyPack444WithMustard       1.67%     37\\nRadFannyPack444                  2.48%     55\\nPinkSundress                     2.66%     59\\nPinkFannyPack444                 2.93%     65\\nGreenMonsterPack                 3.56%     79\\nNone                             3.69%     82\\nMintSundress                     3.96%     88\\nGreenMonsterPackWithMustard      4.23%     94\\nBlueMonsterPackWithMustard       4.86%    108\\nBlueMonsterPack                  5.54%    123\\nBlueFannyPack444                 5.94%    132\\nBlueFannyPack444WithMustard      6.39%    142\\nRadSundress                      6.44%    143\\nBlueFannyPackHDH                 6.93%    154\\nBlueFannyPackHDHWithMustard      7.29%    162\\nRadFannyPackHDHWithMustard       7.34%    163\\nPinkFannyPackHDH                 7.74%    172\\nRadFannyPackHDH                  8.10%    180\\nMustard                          8.28%    184\\nColumn_Total                   100.00%   2222\\n\\nhat:\\n                    percentage  count\\nRaccoon                  4.55%    101\\nRainbowTrucker           5.63%    125\\nRedMonster               6.30%    140\\nRadTrucker               6.30%    140\\nYellowMonster            6.35%    141\\nSilverTiara              6.44%    143\\nGoofyUnicornTrucker      7.88%    175\\nUnicornTrucker           7.97%    177\\nHiTrucker                8.37%    186\\nHotdogTrucker            9.09%    202\\nGoldTiara               10.13%    225\\nBunny                   10.49%    233\\nFlowers                 10.53%    234\\nColumn_Total           100.00%   2222\\n\\neyes:\\n                       percentage  count\\nRainbowStarSunglasses       3.92%     87\\nWhiteRaybanSunglasses       4.19%     93\\nPurpleCateyeSunglasses      5.54%    123\\nBlueFlowerSunglasses        6.17%    137\\nRedStarSunglasses           6.75%    150\\nMintCateyeSunglasses        8.46%    188\\nPinkFlowerSunglasses        9.59%    213\\nHbarSunglasses             10.08%    224\\nBlackRaybanSunglasses      10.40%    231\\nLaughing                   34.92%    776\\nColumn_Total              100.00%   2222\\n\\nlefthand:\\n                   percentage  count\\nYellowPepeTroll         2.16%     48\\nRadPepeTroll            3.06%     68\\nOrangeMonster           3.24%     72\\nGreenMonster            3.83%     85\\nLifteeg                 5.27%    117\\nBinxWiener              5.63%    125\\nOrangePepeTroll         6.03%    134\\nRedFlowers              6.12%    136\\nFingersWithFingers      7.83%    174\\nYellowFlowers           8.51%    189\\nSoaker                  8.73%    194\\nGreenTRex               9.09%    202\\nPeaceSign               9.14%    203\\nHulkHand               10.08%    224\\nEmpty                  11.30%    251\\nColumn_Total          100.00%   2222\\n\\nrighthand:\\n                   percentage  count\\nRedTRex                 0.50%     11\\nPurpleFlowers           1.22%     27\\nPurplePepeTroll         1.94%     43\\nRadPepeTroll            3.60%     80\\nGreenMonster            3.83%     85\\nOrangeMonster           4.59%    102\\nRedPepeTroll            5.36%    119\\nWhiteFlowers            6.30%    140\\nBinxWiener              6.80%    151\\nToobetch                7.61%    169\\nFingersWithFingers      8.46%    188\\nPeaceSign               8.64%    192\\nSoaker                  9.59%    213\\nHulkHand               10.40%    231\\nBubbles                10.44%    232\\nEmpty                  10.76%    239\\nColumn_Total          100.00%   2222\\n\\nfeels:\\n             percentage  count\\nEverything        0.54%     12\\nPerfect           0.86%     19\\nRainbowPuke       4.14%     92\\nHappy            94.46%   2099\\nColumn_Total    100.00%   2222'"
      ]
     },
     "execution_count": 76,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "#produce the stats tables\n",
    "output_str = \"\"\n",
    "for column_name in column_list:\n",
    "    df_norm = metadata_df[column_name].value_counts(ascending=True, normalize=True, dropna=False)\n",
    "    df_count = metadata_df[column_name].value_counts(ascending=True, dropna=False)\n",
    "    df_stat_table = pd.concat([df_norm, df_count], axis=1, join='inner')\n",
    "    df_stat_table.set_axis([\"percentage\", \"count\"], axis=1, inplace = True)\n",
    "    df_stat_table.loc['Column_Total'] = df_stat_table.sum(numeric_only=True, axis=0)\n",
    "    df_stat_table['percentage'] = pd.Series([\"{0:.2f}%\".format(val * 100) for val in df_stat_table['percentage']], index = df_stat_table.index)\n",
    "    output_str = output_str + \"\\n\\n\" + column_name + \":\\n\" + df_stat_table.to_string()\n",
    "\n",
    "output_str\n",
    "#with open(\"0.0.848553_stats.txt\", \"w\") as a_file:\n",
    "#   a_file.write(output_str)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 77,
   "id": "gothic-gospel",
   "metadata": {},
   "outputs": [],
   "source": [
    "#process the data for % and points then sort and rank\n",
    "column_pts_lst = []\n",
    "\n",
    "for column_name in column_list:\n",
    "    metadata_df[column_name +'_perc'] = metadata_df[column_name].map(metadata_df[column_name].value_counts(normalize=True, dropna=False))\n",
    "    metadata_df[column_name +'_pts'] = 1/metadata_df[column_name +'_perc']\n",
    "    column_pts_lst.append(column_name +'_pts')\n",
    "\n",
    "#column_pts_lst.append('total')\n",
    "metadata_df['total_pts'] = metadata_df[column_pts_lst].sum(axis=1)\n",
    "\n",
    "sorted_metadata_df = metadata_df.sort_values(by=['total_pts','serial'], ascending=(False,True)).reset_index()\n",
    "sorted_metadata_df['rank'] = sorted_metadata_df.index + 1\n",
    "sorted_metadata_df.drop('index', axis=1, inplace=True)\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 78,
   "id": "guided-syntax",
   "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>name</th>\n",
       "      <th>serial</th>\n",
       "      <th>figure</th>\n",
       "      <th>shoes</th>\n",
       "      <th>topping</th>\n",
       "      <th>hat</th>\n",
       "      <th>eyes</th>\n",
       "      <th>lefthand</th>\n",
       "      <th>righthand</th>\n",
       "      <th>feels</th>\n",
       "      <th>...</th>\n",
       "      <th>eyes_perc</th>\n",
       "      <th>eyes_pts</th>\n",
       "      <th>lefthand_perc</th>\n",
       "      <th>lefthand_pts</th>\n",
       "      <th>righthand_perc</th>\n",
       "      <th>righthand_pts</th>\n",
       "      <th>feels_perc</th>\n",
       "      <th>feels_pts</th>\n",
       "      <th>total_pts</th>\n",
       "      <th>rank</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>Hotdog Hustle Generation 2</td>\n",
       "      <td>89</td>\n",
       "      <td>Hotdog</td>\n",
       "      <td>PurpleMonsterSlippers</td>\n",
       "      <td>BlueFannyPack444WithMustard</td>\n",
       "      <td>GoldTiara</td>\n",
       "      <td>BlackRaybanSunglasses</td>\n",
       "      <td>RadPepeTroll</td>\n",
       "      <td>RadPepeTroll</td>\n",
       "      <td>Everything</td>\n",
       "      <td>...</td>\n",
       "      <td>0</td>\n",
       "      <td>10</td>\n",
       "      <td>0</td>\n",
       "      <td>33</td>\n",
       "      <td>0</td>\n",
       "      <td>28</td>\n",
       "      <td>0</td>\n",
       "      <td>185</td>\n",
       "      <td>304</td>\n",
       "      <td>1</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>Hotdog Hustle Generation 2</td>\n",
       "      <td>1689</td>\n",
       "      <td>Hotdog</td>\n",
       "      <td>RadAdidas</td>\n",
       "      <td>GreenMonsterPack</td>\n",
       "      <td>HotdogTrucker</td>\n",
       "      <td>Laughing</td>\n",
       "      <td>GreenMonster</td>\n",
       "      <td>RedTRex</td>\n",
       "      <td>Happy</td>\n",
       "      <td>...</td>\n",
       "      <td>0</td>\n",
       "      <td>3</td>\n",
       "      <td>0</td>\n",
       "      <td>26</td>\n",
       "      <td>0</td>\n",
       "      <td>202</td>\n",
       "      <td>1</td>\n",
       "      <td>1</td>\n",
       "      <td>297</td>\n",
       "      <td>2</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>Hotdog Hustle Generation 2</td>\n",
       "      <td>1919</td>\n",
       "      <td>Hotdog</td>\n",
       "      <td>PurpleMonsterSlippers</td>\n",
       "      <td>MintSundress</td>\n",
       "      <td>RainbowTrucker</td>\n",
       "      <td>PurpleCateyeSunglasses</td>\n",
       "      <td>Soaker</td>\n",
       "      <td>WhiteFlowers</td>\n",
       "      <td>Everything</td>\n",
       "      <td>...</td>\n",
       "      <td>0</td>\n",
       "      <td>18</td>\n",
       "      <td>0</td>\n",
       "      <td>11</td>\n",
       "      <td>0</td>\n",
       "      <td>16</td>\n",
       "      <td>0</td>\n",
       "      <td>185</td>\n",
       "      <td>297</td>\n",
       "      <td>3</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>Hotdog Hustle Generation 2</td>\n",
       "      <td>2221</td>\n",
       "      <td>Hotdog</td>\n",
       "      <td>RadAdidas</td>\n",
       "      <td>BlueMonsterPackWithMustard</td>\n",
       "      <td>HiTrucker</td>\n",
       "      <td>RedStarSunglasses</td>\n",
       "      <td>BinxWiener</td>\n",
       "      <td>RedTRex</td>\n",
       "      <td>Happy</td>\n",
       "      <td>...</td>\n",
       "      <td>0</td>\n",
       "      <td>15</td>\n",
       "      <td>0</td>\n",
       "      <td>18</td>\n",
       "      <td>0</td>\n",
       "      <td>202</td>\n",
       "      <td>1</td>\n",
       "      <td>1</td>\n",
       "      <td>294</td>\n",
       "      <td>4</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>Hotdog Hustle Generation 2</td>\n",
       "      <td>1633</td>\n",
       "      <td>Hotdog</td>\n",
       "      <td>BlueMonsterSlippers</td>\n",
       "      <td>BlueFannyPack444WithMustard</td>\n",
       "      <td>RainbowTrucker</td>\n",
       "      <td>BlueFlowerSunglasses</td>\n",
       "      <td>RedFlowers</td>\n",
       "      <td>Empty</td>\n",
       "      <td>Everything</td>\n",
       "      <td>...</td>\n",
       "      <td>0</td>\n",
       "      <td>16</td>\n",
       "      <td>0</td>\n",
       "      <td>16</td>\n",
       "      <td>0</td>\n",
       "      <td>9</td>\n",
       "      <td>0</td>\n",
       "      <td>185</td>\n",
       "      <td>289</td>\n",
       "      <td>5</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "<p>5 rows × 28 columns</p>\n",
       "</div>"
      ],
      "text/plain": [
       "                         name  serial  figure                  shoes  \\\n",
       "0  Hotdog Hustle Generation 2      89  Hotdog  PurpleMonsterSlippers   \n",
       "1  Hotdog Hustle Generation 2    1689  Hotdog              RadAdidas   \n",
       "2  Hotdog Hustle Generation 2    1919  Hotdog  PurpleMonsterSlippers   \n",
       "3  Hotdog Hustle Generation 2    2221  Hotdog              RadAdidas   \n",
       "4  Hotdog Hustle Generation 2    1633  Hotdog    BlueMonsterSlippers   \n",
       "\n",
       "                       topping             hat                    eyes  \\\n",
       "0  BlueFannyPack444WithMustard       GoldTiara   BlackRaybanSunglasses   \n",
       "1             GreenMonsterPack   HotdogTrucker                Laughing   \n",
       "2                 MintSundress  RainbowTrucker  PurpleCateyeSunglasses   \n",
       "3   BlueMonsterPackWithMustard       HiTrucker       RedStarSunglasses   \n",
       "4  BlueFannyPack444WithMustard  RainbowTrucker    BlueFlowerSunglasses   \n",
       "\n",
       "       lefthand     righthand       feels  ...  eyes_perc  eyes_pts  \\\n",
       "0  RadPepeTroll  RadPepeTroll  Everything  ...          0        10   \n",
       "1  GreenMonster       RedTRex       Happy  ...          0         3   \n",
       "2        Soaker  WhiteFlowers  Everything  ...          0        18   \n",
       "3    BinxWiener       RedTRex       Happy  ...          0        15   \n",
       "4    RedFlowers         Empty  Everything  ...          0        16   \n",
       "\n",
       "   lefthand_perc  lefthand_pts  righthand_perc  righthand_pts  feels_perc  \\\n",
       "0              0            33               0             28           0   \n",
       "1              0            26               0            202           1   \n",
       "2              0            11               0             16           0   \n",
       "3              0            18               0            202           1   \n",
       "4              0            16               0              9           0   \n",
       "\n",
       "   feels_pts  total_pts  rank  \n",
       "0        185        304     1  \n",
       "1          1        297     2  \n",
       "2        185        297     3  \n",
       "3          1        294     4  \n",
       "4        185        289     5  \n",
       "\n",
       "[5 rows x 28 columns]"
      ]
     },
     "execution_count": 78,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "sorted_metadata_df.head(5)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 79,
   "id": "effective-instrumentation",
   "metadata": {},
   "outputs": [],
   "source": [
    "sorted_metadata_df.to_csv(tokenId+'_processed.tsv', index=False, sep = '\\t')\n",
    "sorted_metadata_df.to_csv(tokenId+'_processed.csv', index=False)\n",
    "\n",
    "with open(tokenId+'_stats.txt', \"w\") as a_file:\n",
    "   a_file.write(output_str)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "id": "hybrid-rally",
   "metadata": {},
   "outputs": [],
   "source": []
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "id": "heard-possibility",
   "metadata": {},
   "outputs": [],
   "source": []
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "id": "found-increase",
   "metadata": {},
   "outputs": [],
   "source": []
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "id": "ready-model",
   "metadata": {},
   "outputs": [],
   "source": []
  }
 ],
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