blabla/WOS/wos_extract/wos_aggr_concat.ipynb

{
 "cells": [
  {
   "cell_type": "code",
   "execution_count": 14,
   "metadata": {
    "collapsed": true
   },
   "outputs": [],
   "source": [
    "import pandas as pd\n",
    "import seaborn as sns\n",
    "import os\n",
    "import matplotlib.pyplot as plt"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 11,
   "outputs": [],
   "source": [
    "agg_df = pd.DataFrame()\n",
    "\n",
    "workdir_path = 'aggregated_yearly_from_wos'\n",
    "for root, dirs, files in os.walk(workdir_path):\n",
    "    for filename in files:\n",
    "        path=os.path.join(root, filename)\n",
    "        chunk = pd.read_csv(path, sep='\\t')[[\"Publication Years\",\"Record Count\"]]\n",
    "        chunk[\"name\"] = filename.replace(\".txt\",\"\")\n",
    "        agg_df = pd.concat([chunk,agg_df],ignore_index=True)"
   ],
   "metadata": {
    "collapsed": false,
    "pycharm": {
     "name": "#%%\n"
    }
   }
  },
  {
   "cell_type": "code",
   "execution_count": 12,
   "outputs": [
    {
     "data": {
      "text/plain": "array(['worldwide_kwds', 'eu_kwds', 'eu_all', 'eu+assoc_kwds',\n       'eu+assoc_all', 'ch_kwds', 'ch_all'], dtype=object)"
     },
     "execution_count": 12,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "agg_df[\"name\"].unique()"
   ],
   "metadata": {
    "collapsed": false,
    "pycharm": {
     "name": "#%%\n"
    }
   }
  },
  {
   "cell_type": "code",
   "execution_count": 13,
   "outputs": [
    {
     "data": {
      "text/plain": "    Publication Years  Record Count            name     region field\n0                2022        211014  worldwide_kwds  worldwide  kwds\n1                2021        197916  worldwide_kwds  worldwide  kwds\n2                2020        160472  worldwide_kwds  worldwide  kwds\n3                2019        142010  worldwide_kwds  worldwide  kwds\n4                2018        109746  worldwide_kwds  worldwide  kwds\n..                ...           ...             ...        ...   ...\n79               2015        393759          ch_all         ch   all\n80               2014        362784          ch_all         ch   all\n81               2013        329772          ch_all         ch   all\n82               2012        299804          ch_all         ch   all\n83               2011        263715          ch_all         ch   all\n\n[84 rows x 5 columns]",
      "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>Publication Years</th>\n      <th>Record Count</th>\n      <th>name</th>\n      <th>region</th>\n      <th>field</th>\n    </tr>\n  </thead>\n  <tbody>\n    <tr>\n      <th>0</th>\n      <td>2022</td>\n      <td>211014</td>\n      <td>worldwide_kwds</td>\n      <td>worldwide</td>\n      <td>kwds</td>\n    </tr>\n    <tr>\n      <th>1</th>\n      <td>2021</td>\n      <td>197916</td>\n      <td>worldwide_kwds</td>\n      <td>worldwide</td>\n      <td>kwds</td>\n    </tr>\n    <tr>\n      <th>2</th>\n      <td>2020</td>\n      <td>160472</td>\n      <td>worldwide_kwds</td>\n      <td>worldwide</td>\n      <td>kwds</td>\n    </tr>\n    <tr>\n      <th>3</th>\n      <td>2019</td>\n      <td>142010</td>\n      <td>worldwide_kwds</td>\n      <td>worldwide</td>\n      <td>kwds</td>\n    </tr>\n    <tr>\n      <th>4</th>\n      <td>2018</td>\n      <td>109746</td>\n      <td>worldwide_kwds</td>\n      <td>worldwide</td>\n      <td>kwds</td>\n    </tr>\n    <tr>\n      <th>...</th>\n      <td>...</td>\n      <td>...</td>\n      <td>...</td>\n      <td>...</td>\n      <td>...</td>\n    </tr>\n    <tr>\n      <th>79</th>\n      <td>2015</td>\n      <td>393759</td>\n      <td>ch_all</td>\n      <td>ch</td>\n      <td>all</td>\n    </tr>\n    <tr>\n      <th>80</th>\n      <td>2014</td>\n      <td>362784</td>\n      <td>ch_all</td>\n      <td>ch</td>\n      <td>all</td>\n    </tr>\n    <tr>\n      <th>81</th>\n      <td>2013</td>\n      <td>329772</td>\n      <td>ch_all</td>\n      <td>ch</td>\n      <td>all</td>\n    </tr>\n    <tr>\n      <th>82</th>\n      <td>2012</td>\n      <td>299804</td>\n      <td>ch_all</td>\n      <td>ch</td>\n      <td>all</td>\n    </tr>\n    <tr>\n      <th>83</th>\n      <td>2011</td>\n      <td>263715</td>\n      <td>ch_all</td>\n      <td>ch</td>\n      <td>all</td>\n    </tr>\n  </tbody>\n</table>\n<p>84 rows × 5 columns</p>\n</div>"
     },
     "execution_count": 13,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "agg_df[\"region\"] = agg_df[\"name\"].apply(lambda x: x.split(\"_\")[0])\n",
    "agg_df[\"field\"] = agg_df[\"name\"].apply(lambda x: x.split(\"_\")[-1])\n",
    "agg_df"
   ],
   "metadata": {
    "collapsed": false,
    "pycharm": {
     "name": "#%%\n"
    }
   }
  },
  {
   "cell_type": "code",
   "execution_count": 34,
   "outputs": [
    {
     "data": {
      "text/plain": "Text(0.5, 1.0, 'Number of WOS indexed piublications')"
     },
     "execution_count": 34,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "text/plain": "<Figure size 640x480 with 1 Axes>",
      "image/png": "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
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "g = sns.lineplot(agg_df[agg_df[\"field\"]==\"all\"],x=\"Publication Years\" ,y=\"Record Count\", hue=\"region\")\n",
    "g.ticklabel_format(style='plain', axis='y',useOffset=False)\n",
    "g.set_title(\"Number of WOS indexed piublications\")"
   ],
   "metadata": {
    "collapsed": false,
    "pycharm": {
     "name": "#%%\n"
    }
   }
  },
  {
   "cell_type": "code",
   "execution_count": 33,
   "outputs": [
    {
     "data": {
      "text/plain": "Text(0.5, 1.0, 'AI-related publications')"
     },
     "execution_count": 33,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "text/plain": "<Figure size 640x480 with 1 Axes>",
      "image/png": "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
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "g = sns.lineplot(agg_df[agg_df[\"field\"]==\"kwds\"],x=\"Publication Years\" ,y=\"Record Count\", hue=\"region\")\n",
    "g.set_title(\"AI-related publications\")"
   ],
   "metadata": {
    "collapsed": false,
    "pycharm": {
     "name": "#%%\n"
    }
   }
  },
  {
   "cell_type": "code",
   "execution_count": 36,
   "outputs": [
    {
     "data": {
      "text/plain": "Text(0.5, 1.0, 'AI-related publications\\n(without worldwide trend)')"
     },
     "execution_count": 36,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "text/plain": "<Figure size 640x480 with 1 Axes>",
      "image/png": "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
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "g = sns.lineplot(agg_df[((agg_df[\"field\"]==\"kwds\")&(agg_df[\"region\"]!=\"worldwide\"))],x=\"Publication Years\" ,y=\"Record Count\", hue=\"region\")\n",
    "g.set_title(\"AI-related publications\\n(without worldwide trend)\")"
   ],
   "metadata": {
    "collapsed": false,
    "pycharm": {
     "name": "#%%\n"
    }
   }
  },
  {
   "cell_type": "code",
   "execution_count": 55,
   "outputs": [],
   "source": [
    "agg_df_p = agg_df[agg_df[\"field\"]==\"kwds\"].merge(\n",
    "    agg_df[agg_df[\"field\"]==\"all\"].rename(columns={\"Record Count\":\"All\"}),\n",
    "    on=[\"Publication Years\",\"region\"]).merge(\n",
    "    agg_df[agg_df[\"region\"]==\"worldwide\"][[\"Publication Years\",\"Record Count\"]].rename(columns={\"Record Count\":\"Worldwide\"}),\n",
    "    on=\"Publication Years\")\n",
    "agg_df_p[\"percent\"] = agg_df_p[\"Record Count\"]/agg_df_p[\"All\"]\n",
    "agg_df_p[\"share\"] = agg_df_p[\"Record Count\"]/agg_df_p[\"Worldwide\"]"
   ],
   "metadata": {
    "collapsed": false,
    "pycharm": {
     "name": "#%%\n"
    }
   }
  },
  {
   "cell_type": "code",
   "execution_count": 56,
   "outputs": [
    {
     "data": {
      "text/plain": "Text(0.5, 1.0, 'Focus on AI-related publications\\n(percent of publications of the yearly output)')"
     },
     "execution_count": 56,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "text/plain": "<Figure size 640x480 with 1 Axes>",
      "image/png": "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
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "g = sns.lineplot(agg_df_p,x=\"Publication Years\" ,y=\"percent\", hue=\"region\")\n",
    "g.set_title(\"Focus on AI-related publications\\n(percent of publications of the yearly output)\")"
   ],
   "metadata": {
    "collapsed": false,
    "pycharm": {
     "name": "#%%\n"
    }
   }
  },
  {
   "cell_type": "code",
   "execution_count": 61,
   "outputs": [
    {
     "data": {
      "text/plain": "Text(0.5, 1.0, 'Share of publications of the worldwide AI-related output')"
     },
     "execution_count": 61,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "text/plain": "<Figure size 640x480 with 1 Axes>",
      "image/png": "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
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "g = sns.lineplot(agg_df_p,x=\"Publication Years\" ,y=\"share\", hue=\"region\")\n",
    "g.set_title(\"Share of publications of the worldwide AI-related output\")"
   ],
   "metadata": {
    "collapsed": false,
    "pycharm": {
     "name": "#%%\n"
    }
   }
  },
  {
   "cell_type": "code",
   "execution_count": 54,
   "outputs": [
    {
     "data": {
      "text/plain": "    Publication Years  Record Count         name_x    region field_x      All   \n0                2021         43927        eu_kwds        eu    kwds   914776  \\\n1                2021         55254  eu+assoc_kwds  eu+assoc    kwds  1136750   \n2                2021         63992        ch_kwds        ch    kwds   748798   \n3                2022         43361        eu_kwds        eu    kwds   800220   \n4                2022         54467  eu+assoc_kwds  eu+assoc    kwds   986893   \n5                2022         79078        ch_kwds        ch    kwds   801793   \n6                2020         34956        eu_kwds        eu    kwds   886298   \n7                2020         43969  eu+assoc_kwds  eu+assoc    kwds  1104653   \n8                2020         49861        ch_kwds        ch    kwds   668057   \n9                2019         31006        eu_kwds        eu    kwds   890256   \n10               2019         38935  eu+assoc_kwds  eu+assoc    kwds  1116403   \n11               2019         42111        ch_kwds        ch    kwds   630002   \n12               2018         23854        eu_kwds        eu    kwds   833011   \n13               2018         29913  eu+assoc_kwds  eu+assoc    kwds  1043953   \n14               2018         30454        ch_kwds        ch    kwds   534539   \n15               2017         18429        eu_kwds        eu    kwds   752558   \n16               2017         22878  eu+assoc_kwds  eu+assoc    kwds   945964   \n17               2017         21664        ch_kwds        ch    kwds   474295   \n18               2016         16178        eu_kwds        eu    kwds   741454   \n19               2016         19724  eu+assoc_kwds  eu+assoc    kwds   928272   \n20               2016         17436        ch_kwds        ch    kwds   439134   \n21               2015         14628        eu_kwds        eu    kwds   717129   \n22               2015         17655  eu+assoc_kwds  eu+assoc    kwds   901491   \n23               2015         14191        ch_kwds        ch    kwds   393759   \n24               2014         12615        eu_kwds        eu    kwds   695713   \n25               2014         15308  eu+assoc_kwds  eu+assoc    kwds   871908   \n26               2014         12000        ch_kwds        ch    kwds   362784   \n27               2013         10979        eu_kwds        eu    kwds   659641   \n28               2013         13136  eu+assoc_kwds  eu+assoc    kwds   834592   \n29               2013          9424        ch_kwds        ch    kwds   329772   \n30               2012          9626        eu_kwds        eu    kwds   631054   \n31               2012         11557  eu+assoc_kwds  eu+assoc    kwds   798881   \n32               2012          8547        ch_kwds        ch    kwds   299804   \n33               2011          9293        eu_kwds        eu    kwds   610960   \n34               2011         11044  eu+assoc_kwds  eu+assoc    kwds   773469   \n35               2011          7382        ch_kwds        ch    kwds   263715   \n\n          name_y field_y  Worldwide   percent     share  \n0         eu_all     all     197916  0.048019  0.221948  \n1   eu+assoc_all     all     197916  0.048607  0.279179  \n2         ch_all     all     197916  0.085460  0.323329  \n3         eu_all     all     211014  0.054186  0.205489  \n4   eu+assoc_all     all     211014  0.055190  0.258120  \n5         ch_all     all     211014  0.098626  0.374752  \n6         eu_all     all     160472  0.039440  0.217832  \n7   eu+assoc_all     all     160472  0.039803  0.273998  \n8         ch_all     all     160472  0.074636  0.310715  \n9         eu_all     all     142010  0.034828  0.218337  \n10  eu+assoc_all     all     142010  0.034875  0.274171  \n11        ch_all     all     142010  0.066843  0.296535  \n12        eu_all     all     109746  0.028636  0.217356  \n13  eu+assoc_all     all     109746  0.028654  0.272566  \n14        ch_all     all     109746  0.056972  0.277495  \n15        eu_all     all      81974  0.024488  0.224815  \n16  eu+assoc_all     all      8197
      "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>Publication Years</th>\n      <th>Record Count</th>\n      <th>name_x</th>\n      <th>region</th>\n      <th>field_x</th>\n      <th>All</th>\n      <th>name_y</th>\n      <th>field_y</th>\n      <th>Worldwide</th>\n      <th>percent</th>\n      <th>share</th>\n    </tr>\n  </thead>\n  <tbody>\n    <tr>\n      <th>0</th>\n      <td>2021</td>\n      <td>43927</td>\n      <td>eu_kwds</td>\n      <td>eu</td>\n      <td>kwds</td>\n      <td>914776</td>\n      <td>eu_all</td>\n      <td>all</td>\n      <td>197916</td>\n      <td>0.048019</td>\n      <td>0.221948</td>\n    </tr>\n    <tr>\n      <th>1</th>\n      <td>2021</td>\n      <td>55254</td>\n      <td>eu+assoc_kwds</td>\n      <td>eu+assoc</td>\n      <td>kwds</td>\n      <td>1136750</td>\n      <td>eu+assoc_all</td>\n      <td>all</td>\n      <td>197916</td>\n      <td>0.048607</td>\n      <td>0.279179</td>\n    </tr>\n    <tr>\n      <th>2</th>\n      <td>2021</td>\n      <td>63992</td>\n      <td>ch_kwds</td>\n      <td>ch</td>\n      <td>kwds</td>\n      <td>748798</td>\n      <td>ch_all</td>\n      <td>all</td>\n      <td>197916</td>\n      <td>0.085460</td>\n      <td>0.323329</td>\n    </tr>\n    <tr>\n      <th>3</th>\n      <td>2022</td>\n      <td>43361</td>\n      <td>eu_kwds</td>\n      <td>eu</td>\n      <td>kwds</td>\n      <td>800220</td>\n      <td>eu_all</td>\n      <td>all</td>\n      <td>211014</td>\n      <td>0.054186</td>\n      <td>0.205489</td>\n    </tr>\n    <tr>\n      <th>4</th>\n      <td>2022</td>\n      <td>54467</td>\n      <td>eu+assoc_kwds</td>\n      <td>eu+assoc</td>\n      <td>kwds</td>\n      <td>986893</td>\n      <td>eu+assoc_all</td>\n      <td>all</td>\n      <td>211014</td>\n      <td>0.055190</td>\n      <td>0.258120</td>\n    </tr>\n    <tr>\n      <th>5</th>\n      <td>2022</td>\n      <td>79078</td>\n      <td>ch_kwds</td>\n      <td>ch</td>\n      <td>kwds</td>\n      <td>801793</td>\n      <td>ch_all</td>\n      <td>all</td>\n      <td>211014</td>\n      <td>0.098626</td>\n      <td>0.374752</td>\n    </tr>\n    <tr>\n      <th>6</th>\n      <td>2020</td>\n      <td>34956</td>\n      <td>eu_kwds</td>\n      <td>eu</td>\n      <td>kwds</td>\n      <td>886298</td>\n      <td>eu_all</td>\n      <td>all</td>\n      <td>160472</td>\n      <td>0.039440</td>\n      <td>0.217832</td>\n    </tr>\n    <tr>\n      <th>7</th>\n      <td>2020</td>\n      <td>43969</td>\n      <td>eu+assoc_kwds</td>\n      <td>eu+assoc</td>\n      <td>kwds</td>\n      <td>1104653</td>\n      <td>eu+assoc_all</td>\n      <td>all</td>\n      <td>160472</td>\n      <td>0.039803</td>\n      <td>0.273998</td>\n    </tr>\n    <tr>\n      <th>8</th>\n      <td>2020</td>\n      <td>49861</td>\n      <td>ch_kwds</td>\n      <td>ch</td>\n      <td>kwds</td>\n      <td>668057</td>\n      <td>ch_all</td>\n      <td>all</td>\n      <td>160472</td>\n      <td>0.074636</td>\n      <td>0.310715</td>\n    </tr>\n    <tr>\n      <th>9</th>\n      <td>2019</td>\n      <td>31006</td>\n      <td>eu_kwds</td>\n      <td>eu</td>\n      <td>kwds</td>\n      <td>890256</td>\n      <td>eu_all</td>\n      <td>all</td>\n      <td>142010</td>\n      <td>0.034828</td>\n      <td>0.218337</td>\n    </tr>\n    <tr>\n      <th>10</th>\n      <td>2019</td>\n      <td>38935</td>\n      <td>eu+assoc_kwds</td>\n      <td>eu+assoc</td>\n      <td>kwds</td>\n      <td>1116403</td>\n      <td>eu+assoc_all</td>\n      <td>all</td>\n      <td>142010</td>\n      <td>0.034875</td>\n      <td>0.274171</td>\n    </tr>\n    <tr>\n      <th>11</th>\n      <td>2019</td>\n      <td>42111</td>\n      <td>ch_kwds</td>\n      <td>ch</td>\n      <td>kwds</td>\n      <td>630002</td>\n      <td>ch_all</td>\n      <td>all</td>
     },
     "execution_count": 54,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "agg_df_p"
   ],
   "metadata": {
    "collapsed": false,
    "pycharm": {
     "name": "#%%\n"
    }
   }
  },
  {
   "cell_type": "code",
   "execution_count": 60,
   "outputs": [
    {
     "data": {
      "text/plain": "    Record Count  Worldwide     share\n0          43927     197916  0.221948\n1          55254     197916  0.279179\n2          63992     197916  0.323329\n3          43361     211014  0.205489\n4          54467     211014  0.258120\n5          79078     211014  0.374752\n6          34956     160472  0.217832\n7          43969     160472  0.273998\n8          49861     160472  0.310715\n9          31006     142010  0.218337\n10         38935     142010  0.274171\n11         42111     142010  0.296535\n12         23854     109746  0.217356\n13         29913     109746  0.272566\n14         30454     109746  0.277495\n15         18429      81974  0.224815\n16         22878      81974  0.279088\n17         21664      81974  0.264279\n18         16178      68538  0.236044\n19         19724      68538  0.287782\n20         17436      68538  0.254399\n21         14628      59591  0.245473\n22         17655      59591  0.296270\n23         14191      59591  0.238140\n24         12615      51174  0.246512\n25         15308      51174  0.299136\n26         12000      51174  0.234494\n27         10979      42229  0.259987\n28         13136      42229  0.311066\n29          9424      42229  0.223164\n30          9626      37054  0.259783\n31         11557      37054  0.311896\n32          8547      37054  0.230663\n33          9293      33189  0.280002\n34         11044      33189  0.332761\n35          7382      33189  0.222423",
      "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>Record Count</th>\n      <th>Worldwide</th>\n      <th>share</th>\n    </tr>\n  </thead>\n  <tbody>\n    <tr>\n      <th>0</th>\n      <td>43927</td>\n      <td>197916</td>\n      <td>0.221948</td>\n    </tr>\n    <tr>\n      <th>1</th>\n      <td>55254</td>\n      <td>197916</td>\n      <td>0.279179</td>\n    </tr>\n    <tr>\n      <th>2</th>\n      <td>63992</td>\n      <td>197916</td>\n      <td>0.323329</td>\n    </tr>\n    <tr>\n      <th>3</th>\n      <td>43361</td>\n      <td>211014</td>\n      <td>0.205489</td>\n    </tr>\n    <tr>\n      <th>4</th>\n      <td>54467</td>\n      <td>211014</td>\n      <td>0.258120</td>\n    </tr>\n    <tr>\n      <th>5</th>\n      <td>79078</td>\n      <td>211014</td>\n      <td>0.374752</td>\n    </tr>\n    <tr>\n      <th>6</th>\n      <td>34956</td>\n      <td>160472</td>\n      <td>0.217832</td>\n    </tr>\n    <tr>\n      <th>7</th>\n      <td>43969</td>\n      <td>160472</td>\n      <td>0.273998</td>\n    </tr>\n    <tr>\n      <th>8</th>\n      <td>49861</td>\n      <td>160472</td>\n      <td>0.310715</td>\n    </tr>\n    <tr>\n      <th>9</th>\n      <td>31006</td>\n      <td>142010</td>\n      <td>0.218337</td>\n    </tr>\n    <tr>\n      <th>10</th>\n      <td>38935</td>\n      <td>142010</td>\n      <td>0.274171</td>\n    </tr>\n    <tr>\n      <th>11</th>\n      <td>42111</td>\n      <td>142010</td>\n      <td>0.296535</td>\n    </tr>\n    <tr>\n      <th>12</th>\n      <td>23854</td>\n      <td>109746</td>\n      <td>0.217356</td>\n    </tr>\n    <tr>\n      <th>13</th>\n      <td>29913</td>\n      <td>109746</td>\n      <td>0.272566</td>\n    </tr>\n    <tr>\n      <th>14</th>\n      <td>30454</td>\n      <td>109746</td>\n      <td>0.277495</td>\n    </tr>\n    <tr>\n      <th>15</th>\n      <td>18429</td>\n      <td>81974</td>\n      <td>0.224815</td>\n    </tr>\n    <tr>\n      <th>16</th>\n      <td>22878</td>\n      <td>81974</td>\n      <td>0.279088</td>\n    </tr>\n    <tr>\n      <th>17</th>\n      <td>21664</td>\n      <td>81974</td>\n      <td>0.264279</td>\n    </tr>\n    <tr>\n      <th>18</th>\n      <td>16178</td>\n      <td>68538</td>\n      <td>0.236044</td>\n    </tr>\n    <tr>\n      <th>19</th>\n      <td>19724</td>\n      <td>68538</td>\n      <td>0.287782</td>\n    </tr>\n    <tr>\n      <th>20</th>\n      <td>17436</td>\n      <td>68538</td>\n      <td>0.254399</td>\n    </tr>\n    <tr>\n      <th>21</th>\n      <td>14628</td>\n      <td>59591</td>\n      <td>0.245473</td>\n    </tr>\n    <tr>\n      <th>22</th>\n      <td>17655</td>\n      <td>59591</td>\n      <td>0.296270</td>\n    </tr>\n    <tr>\n      <th>23</th>\n      <td>14191</td>\n      <td>59591</td>\n      <td>0.238140</td>\n    </tr>\n    <tr>\n      <th>24</th>\n      <td>12615</td>\n      <td>51174</td>\n      <td>0.246512</td>\n    </tr>\n    <tr>\n      <th>25</th>\n      <td>15308</td>\n      <td>51174</td>\n      <td>0.299136</td>\n    </tr>\n    <tr>\n      <th>26</th>\n      <td>12000</td>\n      <td>51174</td>\n      <td>0.234494</td>\n    </tr>\n    <tr>\n      <th>27</th>\n      <td>10979</td>\n      <td>42229</td>\n      <td>0.259987</td>\n    </tr>\n    <tr>\n      <th>28</th>\n      <td>13136</td>\n      <td>42229</td>\n      <td>0.311066</td>\n    </tr>\n    <tr>\n      <th>29</th>\n      <td>9424</td>\n      <td>42229</td>\n      <td>0.223164</td>\n    </tr>\n    <tr>\n      <th>30</th>\n      <td>9626</td>\n      <td>37054</td>\n      <td>0.259783</td>\n    </tr>\n    <tr>\n      <th>31</th>\n      <td>11557</td>\n      <td>37054</td>\n      <td>0.311896</td>\n    </tr>\n    <tr>\n      <th>32</th>\n      <td>8547</td>\n      <td>37054</td>\n      <td>0.230663</td>\n    </tr>\n    <tr
     },
     "execution_count": 60,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "agg_df_p[[\"Record Count\",\"Worldwide\",\"share\"]]"
   ],
   "metadata": {
    "collapsed": false,
    "pycharm": {
     "name": "#%%\n"
    }
   }
  }
 ],
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