Notebook_1_startup.ipynb

{
 "cells": [
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "# Start-up\n",
    "\n",
    "In this notebook, we provide an overview of publication medatata and create the data frames for further analyses."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 1,
   "metadata": {},
   "outputs": [],
   "source": [
    "%matplotlib inline\n",
    "import matplotlib.pyplot as plt\n",
    "\n",
    "# magics and warnings\n",
    "%load_ext autoreload\n",
    "%autoreload 2\n",
    "import warnings; warnings.simplefilter('ignore')\n",
    "\n",
    "import os, random, codecs, json\n",
    "import pandas as pd\n",
    "import numpy as np\n",
    "\n",
    "seed = 99\n",
    "random.seed(seed)\n",
    "np.random.seed(seed)\n",
    "\n",
    "import nltk, sklearn\n",
    "import matplotlib.pyplot as plt\n",
    "from  matplotlib.ticker import FuncFormatter\n",
    "import seaborn as sns\n",
    "sns.set(style=\"white\")\n",
    "sns.set_context(\"paper\", font_scale=1.2, rc={\"lines.linewidth\": 2.5})"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 2,
   "metadata": {},
   "outputs": [],
   "source": [
    "# load publication metadata\n",
    "\n",
    "df_meta = pd.read_csv(\"../cwts_covid/datasets_output/df_pub.csv\",compression=\"gzip\")"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 3,
   "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>pub_id</th>\n",
       "      <th>title</th>\n",
       "      <th>abstract</th>\n",
       "      <th>publication_year</th>\n",
       "      <th>publication_month</th>\n",
       "      <th>journal</th>\n",
       "      <th>volume</th>\n",
       "      <th>issue</th>\n",
       "      <th>pages</th>\n",
       "      <th>doi</th>\n",
       "      <th>pmid</th>\n",
       "      <th>pmcid</th>\n",
       "      <th>dimensions_id</th>\n",
       "      <th>arxiv_id</th>\n",
       "      <th>timestamp</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>0</td>\n",
       "      <td>Coronavirus disease 2019 (COVID-19) and simult...</td>\n",
       "      <td>Coronavirus disease 2019 (COVID-19) is a recen...</td>\n",
       "      <td>2020.0</td>\n",
       "      <td>5.0</td>\n",
       "      <td>CardioVascular Journal of Africa</td>\n",
       "      <td>31</td>\n",
       "      <td>NaN</td>\n",
       "      <td>1-4</td>\n",
       "      <td>10-5830-cvja-2020-016</td>\n",
       "      <td>32490506.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>pub.1128171889</td>\n",
       "      <td>NaN</td>\n",
       "      <td>2020-07-02 10:54:27.347501</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>1</td>\n",
       "      <td>[Ten hot issues of breast cancer under the nov...</td>\n",
       "      <td>NaN</td>\n",
       "      <td>2020.0</td>\n",
       "      <td>2.0</td>\n",
       "      <td>Chinese medical journal</td>\n",
       "      <td>100</td>\n",
       "      <td>0</td>\n",
       "      <td>e002</td>\n",
       "      <td>10.0376/cma.j.issn.0376-2491.2020.0002</td>\n",
       "      <td>32036640.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>pub.1124777091</td>\n",
       "      <td>NaN</td>\n",
       "      <td>2020-07-02 10:54:27.347501</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>2</td>\n",
       "      <td>Cohesion in Distancing.</td>\n",
       "      <td>In isolation, we are physically apart; in soli...</td>\n",
       "      <td>2020.0</td>\n",
       "      <td>4.0</td>\n",
       "      <td>The AMA Journal of Ethic</td>\n",
       "      <td>22</td>\n",
       "      <td>4</td>\n",
       "      <td>e344-345</td>\n",
       "      <td>10.1001/amajethics.2020.344</td>\n",
       "      <td>32345430.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>pub.1127182341</td>\n",
       "      <td>NaN</td>\n",
       "      <td>2020-07-02 10:54:27.347501</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>3</td>\n",
       "      <td>Salvation in a Time of Plague.</td>\n",
       "      <td>Health workers offer their skills and care to ...</td>\n",
       "      <td>2020.0</td>\n",
       "      <td>5.0</td>\n",
       "      <td>The AMA Journal of Ethic</td>\n",
       "      <td>22</td>\n",
       "      <td>5</td>\n",
       "      <td>e441-445</td>\n",
       "      <td>10.1001/amajethics.2020.441</td>\n",
       "      <td>32449663.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>pub.1127905371</td>\n",
       "      <td>NaN</td>\n",
       "      <td>2020-07-02 10:54:27.347501</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>4</td>\n",
       "      <td>What Should Health Science Journalists Do in E...</td>\n",
       "      <td>Journalists have long covered outbreaks of inf...</td>\n",
       "      <td>2020.0</td>\n",
       "      <td>1.0</td>\n",
       "      <td>AMA journal of ethics</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>10.1001/amajethics.2020.55</td>\n",
       "      <td>31958392.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>2020-07-02 10:54:27.347501</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "   pub_id                                              title  \\\n",
       "0       0  Coronavirus disease 2019 (COVID-19) and simult...   \n",
       "1       1  [Ten hot issues of breast cancer under the nov...   \n",
       "2       2                            Cohesion in Distancing.   \n",
       "3       3                     Salvation in a Time of Plague.   \n",
       "4       4  What Should Health Science Journalists Do in E...   \n",
       "\n",
       "                                            abstract  publication_year  \\\n",
       "0  Coronavirus disease 2019 (COVID-19) is a recen...            2020.0   \n",
       "1                                                NaN            2020.0   \n",
       "2  In isolation, we are physically apart; in soli...            2020.0   \n",
       "3  Health workers offer their skills and care to ...            2020.0   \n",
       "4  Journalists have long covered outbreaks of inf...            2020.0   \n",
       "\n",
       "   publication_month                           journal volume issue     pages  \\\n",
       "0                5.0  CardioVascular Journal of Africa     31   NaN       1-4   \n",
       "1                2.0           Chinese medical journal    100     0      e002   \n",
       "2                4.0          The AMA Journal of Ethic     22     4  e344-345   \n",
       "3                5.0          The AMA Journal of Ethic     22     5  e441-445   \n",
       "4                1.0             AMA journal of ethics    NaN   NaN       NaN   \n",
       "\n",
       "                                      doi        pmid pmcid   dimensions_id  \\\n",
       "0                   10-5830-cvja-2020-016  32490506.0   NaN  pub.1128171889   \n",
       "1  10.0376/cma.j.issn.0376-2491.2020.0002  32036640.0   NaN  pub.1124777091   \n",
       "2             10.1001/amajethics.2020.344  32345430.0   NaN  pub.1127182341   \n",
       "3             10.1001/amajethics.2020.441  32449663.0   NaN  pub.1127905371   \n",
       "4              10.1001/amajethics.2020.55  31958392.0   NaN             NaN   \n",
       "\n",
       "  arxiv_id                   timestamp  \n",
       "0      NaN  2020-07-02 10:54:27.347501  \n",
       "1      NaN  2020-07-02 10:54:27.347501  \n",
       "2      NaN  2020-07-02 10:54:27.347501  \n",
       "3      NaN  2020-07-02 10:54:27.347501  \n",
       "4      NaN  2020-07-02 10:54:27.347501  "
      ]
     },
     "execution_count": 3,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df_meta.head()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 4,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "Index(['pub_id', 'title', 'abstract', 'publication_year', 'publication_month',\n",
       "       'journal', 'volume', 'issue', 'pages', 'doi', 'pmid', 'pmcid',\n",
       "       'dimensions_id', 'arxiv_id', 'timestamp'],\n",
       "      dtype='object')"
      ]
     },
     "execution_count": 4,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df_meta.columns"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 5,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "(160656, 15)"
      ]
     },
     "execution_count": 5,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df_meta.shape"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "#### Publication years"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 6,
   "metadata": {},
   "outputs": [],
   "source": [
    "import re\n",
    "\n",
    "def clean_year(s):\n",
    "    if pd.isna(s):\n",
    "        return np.nan\n",
    "    if not (s>1900):\n",
    "        return np.nan\n",
    "    elif s>2020:\n",
    "        return 2020\n",
    "    return s\n",
    "\n",
    "df_meta[\"publication_year\"] = df_meta[\"publication_year\"].apply(clean_year)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 7,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "count    160644.000000\n",
       "mean       2015.180822\n",
       "std           7.054152\n",
       "min        1901.000000\n",
       "25%        2012.000000\n",
       "50%        2018.000000\n",
       "75%        2020.000000\n",
       "max        2020.000000\n",
       "Name: publication_year, dtype: float64"
      ]
     },
     "execution_count": 7,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df_meta.publication_year.describe()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 128,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "(72795, 16)"
      ]
     },
     "execution_count": 128,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df_meta[df_meta.publication_year>2019].shape"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 110,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 432x288 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "b = sns.distplot(df_meta.publication_year, bins=60, kde=False)\n",
    "b.set_xlabel(\"Publication year\",fontsize=15)\n",
    "b.set_ylabel(\"Publication count\",fontsize=15)\n",
    "b.tick_params(labelsize=12)\n",
    "plt.tight_layout()\n",
    "plt.savefig(\"figures/meta_pub_year_all.pdf\")"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 111,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 432x288 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "b = sns.distplot([int(y) for y in df_meta[df_meta.publication_year>1999].publication_year.tolist() if y], bins=21, kde=False)\n",
    "b.set_xlabel(\"Publication year\",fontsize=15)\n",
    "b.set_ylabel(\"Publication count\",fontsize=15)\n",
    "b.tick_params(labelsize=12)\n",
    "plt.gca().xaxis.set_major_formatter(FuncFormatter(lambda x, _: int(x)))\n",
    "plt.tight_layout()\n",
    "plt.savefig(\"figures/meta_pub_year_2000.pdf\")"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "#### Detect language"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 10,
   "metadata": {},
   "outputs": [],
   "source": [
    "from langdetect import detect\n",
    "from langdetect import DetectorFactory\n",
    "DetectorFactory.seed = seed"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 11,
   "metadata": {},
   "outputs": [],
   "source": [
    "df_meta[\"title\"] = df_meta[\"title\"].fillna('')\n",
    "df_meta[\"abstract\"] = df_meta[\"abstract\"].fillna('')\n",
    "df_meta[\"title_abstract\"] = df_meta.title +\" \"+df_meta.abstract"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 12,
   "metadata": {},
   "outputs": [],
   "source": [
    "df_meta[\"lang\"] = None"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 13,
   "metadata": {},
   "outputs": [],
   "source": [
    "def detect_lang(txt):\n",
    "    try:\n",
    "        return detect(txt)\n",
    "    except:\n",
    "        return None"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 14,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "CPU times: user 19min 9s, sys: 25.3 s, total: 19min 34s\n",
      "Wall time: 19min 42s\n"
     ]
    }
   ],
   "source": [
    "%%time\n",
    "\n",
    "df_meta[\"lang\"] = df_meta[\"title_abstract\"].apply(detect_lang)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 15,
   "metadata": {},
   "outputs": [],
   "source": [
    "df_meta.drop(columns=\"title_abstract\", inplace=True)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 16,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 432x288 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "# languages\n",
    "\n",
    "df_sub = df_meta[df_meta.lang.isin(df_meta.lang.value_counts()[:10].index.tolist())]\n",
    "b = sns.countplot(y=\"lang\", data=df_sub, order=df_sub['lang'].value_counts().index)\n",
    "#b.axes.set_title(\"Title\",fontsize=50)\n",
    "b.set_xlabel(\"Count\",fontsize=15)\n",
    "b.set_ylabel(\"Language\",fontsize=15)\n",
    "b.tick_params(labelsize=12)\n",
    "plt.tight_layout()\n",
    "plt.savefig(\"figures/meta_lang.pdf\")"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## Dimensions"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 17,
   "metadata": {},
   "outputs": [],
   "source": [
    "# load Dimensions data (you will need to download it on your own)\n",
    "\n",
    "directory_name = \"../cwts_covid/datasets_output/json_dimensions_cwts\"\n",
    "\n",
    "all_dimensions = list()\n",
    "for root, dirs, files in os.walk(directory_name):\n",
    "    for file in files:\n",
    "        if \".json\" in file:\n",
    "            all_data = codecs.open(os.path.join(root,file)).read()\n",
    "            for record in all_data.split(\"\\n\"):\n",
    "                if record:\n",
    "                    all_dimensions.append(json.loads(record))"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 18,
   "metadata": {
    "scrolled": false
   },
   "outputs": [],
   "source": [
    "#all_dimensions[0]"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 19,
   "metadata": {},
   "outputs": [],
   "source": [
    "df_dimensions = pd.DataFrame.from_dict({\n",
    "    \"id\":[r[\"id\"] for r in all_dimensions],\n",
    "    \"altmetric_id\":[r[\"altmetric_id\"] for r in all_dimensions],\n",
    "    \"year\":[r[\"year\"] for r in all_dimensions],\n",
    "    \"month\":[int(r[\"publication_date\"][5:7]) for r in all_dimensions],\n",
    "    \"publication_date\":[r[\"publication_date\"] for r in all_dimensions],\n",
    "    \"publication_type\":[r[\"publication_type\"] for r in all_dimensions],\n",
    "    \"doi\":[r[\"doi\"] for r in all_dimensions],\n",
    "    \"pmid\":[r[\"pmid\"] for r in all_dimensions],\n",
    "    \"issn\":[r[\"journal\"][\"issn\"] for r in all_dimensions],\n",
    "    \"times_cited\":[r[\"times_cited\"] for r in all_dimensions],\n",
    "    \"relative_citation_ratio\":[r[\"relative_citation_ratio\"] for r in all_dimensions],\n",
    "    \"for_top\":[r[\"for\"][0][\"first_level\"][\"name\"] if len(r[\"for\"])>0 else \"\" for r in all_dimensions],\n",
    "    \"for_bottom\":[r[\"for\"][0][\"second_level\"][\"name\"] if len(r[\"for\"])>0 else \"\" for r in all_dimensions]\n",
    "})"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 20,
   "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>id</th>\n",
       "      <th>altmetric_id</th>\n",
       "      <th>year</th>\n",
       "      <th>month</th>\n",
       "      <th>publication_date</th>\n",
       "      <th>publication_type</th>\n",
       "      <th>doi</th>\n",
       "      <th>pmid</th>\n",
       "      <th>issn</th>\n",
       "      <th>times_cited</th>\n",
       "      <th>relative_citation_ratio</th>\n",
       "      <th>for_top</th>\n",
       "      <th>for_bottom</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>pub.1127982992</td>\n",
       "      <td>83013868.0</td>\n",
       "      <td>2020</td>\n",
       "      <td>5</td>\n",
       "      <td>2020-05-01</td>\n",
       "      <td>article</td>\n",
       "      <td>10.1053/j.gastro.2020.05.066</td>\n",
       "      <td>32479824</td>\n",
       "      <td>0016-5085</td>\n",
       "      <td>0</td>\n",
       "      <td>NaN</td>\n",
       "      <td></td>\n",
       "      <td></td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>pub.1127467922</td>\n",
       "      <td>0.0</td>\n",
       "      <td>2020</td>\n",
       "      <td>5</td>\n",
       "      <td>2020-05-01</td>\n",
       "      <td>article</td>\n",
       "      <td>10.1053/j.jvca.2020.04.061</td>\n",
       "      <td>32507459</td>\n",
       "      <td>1053-0770</td>\n",
       "      <td>0</td>\n",
       "      <td>NaN</td>\n",
       "      <td></td>\n",
       "      <td></td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>pub.1127651503</td>\n",
       "      <td>82256754.0</td>\n",
       "      <td>2020</td>\n",
       "      <td>5</td>\n",
       "      <td>2020-05-01</td>\n",
       "      <td>article</td>\n",
       "      <td>10.1053/j.gastro.2020.05.037</td>\n",
       "      <td>32425228</td>\n",
       "      <td>0016-5085</td>\n",
       "      <td>0</td>\n",
       "      <td>NaN</td>\n",
       "      <td></td>\n",
       "      <td></td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>pub.1127316115</td>\n",
       "      <td>0.0</td>\n",
       "      <td>2020</td>\n",
       "      <td>5</td>\n",
       "      <td>2020-05-01</td>\n",
       "      <td>article</td>\n",
       "      <td>10.1053/j.gastro.2020.04.061</td>\n",
       "      <td>32371115</td>\n",
       "      <td>0016-5085</td>\n",
       "      <td>0</td>\n",
       "      <td>NaN</td>\n",
       "      <td></td>\n",
       "      <td></td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>pub.1127684826</td>\n",
       "      <td>82268373.0</td>\n",
       "      <td>2020</td>\n",
       "      <td>5</td>\n",
       "      <td>2020-05-01</td>\n",
       "      <td>article</td>\n",
       "      <td>10.1053/j.gastro.2020.05.032</td>\n",
       "      <td>32425234</td>\n",
       "      <td>0016-5085</td>\n",
       "      <td>7</td>\n",
       "      <td>NaN</td>\n",
       "      <td>Medical and Health Sciences</td>\n",
       "      <td>Clinical Sciences</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "               id  altmetric_id  year  month publication_date  \\\n",
       "0  pub.1127982992    83013868.0  2020      5       2020-05-01   \n",
       "1  pub.1127467922           0.0  2020      5       2020-05-01   \n",
       "2  pub.1127651503    82256754.0  2020      5       2020-05-01   \n",
       "3  pub.1127316115           0.0  2020      5       2020-05-01   \n",
       "4  pub.1127684826    82268373.0  2020      5       2020-05-01   \n",
       "\n",
       "  publication_type                           doi      pmid       issn  \\\n",
       "0          article  10.1053/j.gastro.2020.05.066  32479824  0016-5085   \n",
       "1          article    10.1053/j.jvca.2020.04.061  32507459  1053-0770   \n",
       "2          article  10.1053/j.gastro.2020.05.037  32425228  0016-5085   \n",
       "3          article  10.1053/j.gastro.2020.04.061  32371115  0016-5085   \n",
       "4          article  10.1053/j.gastro.2020.05.032  32425234  0016-5085   \n",
       "\n",
       "   times_cited  relative_citation_ratio                      for_top  \\\n",
       "0            0                      NaN                                \n",
       "1            0                      NaN                                \n",
       "2            0                      NaN                                \n",
       "3            0                      NaN                                \n",
       "4            7                      NaN  Medical and Health Sciences   \n",
       "\n",
       "          for_bottom  \n",
       "0                     \n",
       "1                     \n",
       "2                     \n",
       "3                     \n",
       "4  Clinical Sciences  "
      ]
     },
     "execution_count": 20,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df_dimensions.head()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 21,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "id                          object\n",
       "altmetric_id               float64\n",
       "year                         int64\n",
       "month                        int64\n",
       "publication_date            object\n",
       "publication_type            object\n",
       "doi                         object\n",
       "pmid                        object\n",
       "issn                        object\n",
       "times_cited                  int64\n",
       "relative_citation_ratio    float64\n",
       "for_top                     object\n",
       "for_bottom                  object\n",
       "dtype: object"
      ]
     },
     "execution_count": 21,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df_dimensions.dtypes"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 22,
   "metadata": {},
   "outputs": [],
   "source": [
    "# We only focus on publications with DOI or PMID since Altmetrics data is limited to those\n",
    "# to check:\n",
    "# df_dimensions[pd.isnull(df_dimensions.doi) & pd.isnull(df_dimensions.pmid) & pd.notnull(df_dimensions.altmetric_id)]"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 23,
   "metadata": {},
   "outputs": [],
   "source": [
    "df_dimensions.pmid = df_dimensions.pmid.astype(float)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 24,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "(150749, 13)"
      ]
     },
     "execution_count": 24,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df_dimensions.shape"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 25,
   "metadata": {},
   "outputs": [],
   "source": [
    "df_joined_doi = df_meta[pd.notnull(df_meta.doi)].merge(df_dimensions[pd.notnull(df_dimensions.doi)], how=\"inner\", suffixes=('','_y'), left_on=\"doi\", right_on=\"doi\", copy=False)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 26,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "(138290, 28)"
      ]
     },
     "execution_count": 26,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df_joined_doi.shape"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 27,
   "metadata": {},
   "outputs": [],
   "source": [
    "df_joined_pmid = df_meta[pd.isnull(df_meta.doi) & pd.notnull(df_meta.pmid)].merge(df_dimensions[pd.isnull(df_dimensions.doi) & pd.notnull(df_dimensions.pmid)], how=\"inner\", suffixes=('','_y'), left_on=\"pmid\", right_on=\"pmid\", copy=False)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 28,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "(3493, 28)"
      ]
     },
     "execution_count": 28,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df_joined_pmid.shape"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 29,
   "metadata": {},
   "outputs": [],
   "source": [
    "df_joined = pd.concat([df_joined_doi,df_joined_pmid])\n",
    "df_joined = df_joined[df_joined.columns.drop([\"doi_y\",\"pmid_y\"])]"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 30,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<style scoped>\n",
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       "        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>pub_id</th>\n",
       "      <th>title</th>\n",
       "      <th>abstract</th>\n",
       "      <th>publication_year</th>\n",
       "      <th>publication_month</th>\n",
       "      <th>journal</th>\n",
       "      <th>volume</th>\n",
       "      <th>issue</th>\n",
       "      <th>pages</th>\n",
       "      <th>doi</th>\n",
       "      <th>...</th>\n",
       "      <th>altmetric_id</th>\n",
       "      <th>year</th>\n",
       "      <th>month</th>\n",
       "      <th>publication_date</th>\n",
       "      <th>publication_type</th>\n",
       "      <th>issn</th>\n",
       "      <th>times_cited</th>\n",
       "      <th>relative_citation_ratio</th>\n",
       "      <th>for_top</th>\n",
       "      <th>for_bottom</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>0</td>\n",
       "      <td>Coronavirus disease 2019 (COVID-19) and simult...</td>\n",
       "      <td>Coronavirus disease 2019 (COVID-19) is a recen...</td>\n",
       "      <td>2020.0</td>\n",
       "      <td>5.0</td>\n",
       "      <td>CardioVascular Journal of Africa</td>\n",
       "      <td>31</td>\n",
       "      <td>NaN</td>\n",
       "      <td>1-4</td>\n",
       "      <td>10-5830-cvja-2020-016</td>\n",
       "      <td>...</td>\n",
       "      <td>0.0</td>\n",
       "      <td>2020</td>\n",
       "      <td>5</td>\n",
       "      <td>2020-05-05</td>\n",
       "      <td>article</td>\n",
       "      <td>1995-1892</td>\n",
       "      <td>0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>Medical and Health Sciences</td>\n",
       "      <td>Cardiorespiratory Medicine and Haematology</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>0</td>\n",
       "      <td>Coronavirus disease 2019 (COVID-19) and simult...</td>\n",
       "      <td>Coronavirus disease 2019 (COVID-19) is a recen...</td>\n",
       "      <td>2020.0</td>\n",
       "      <td>5.0</td>\n",
       "      <td>CardioVascular Journal of Africa</td>\n",
       "      <td>31</td>\n",
       "      <td>NaN</td>\n",
       "      <td>1-4</td>\n",
       "      <td>10-5830-cvja-2020-016</td>\n",
       "      <td>...</td>\n",
       "      <td>0.0</td>\n",
       "      <td>2020</td>\n",
       "      <td>5</td>\n",
       "      <td>2020-05-05</td>\n",
       "      <td>article</td>\n",
       "      <td>1995-1892</td>\n",
       "      <td>0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>Medical and Health Sciences</td>\n",
       "      <td>Cardiorespiratory Medicine and Haematology</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>1</td>\n",
       "      <td>[Ten hot issues of breast cancer under the nov...</td>\n",
       "      <td></td>\n",
       "      <td>2020.0</td>\n",
       "      <td>2.0</td>\n",
       "      <td>Chinese medical journal</td>\n",
       "      <td>100</td>\n",
       "      <td>0</td>\n",
       "      <td>e002</td>\n",
       "      <td>10.0376/cma.j.issn.0376-2491.2020.0002</td>\n",
       "      <td>...</td>\n",
       "      <td>75778970.0</td>\n",
       "      <td>2020</td>\n",
       "      <td>2</td>\n",
       "      <td>2020-02-10</td>\n",
       "      <td>article</td>\n",
       "      <td>0376-2491</td>\n",
       "      <td>0</td>\n",
       "      <td>NaN</td>\n",
       "      <td></td>\n",
       "      <td></td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>2</td>\n",
       "      <td>Cohesion in Distancing.</td>\n",
       "      <td>In isolation, we are physically apart; in soli...</td>\n",
       "      <td>2020.0</td>\n",
       "      <td>4.0</td>\n",
       "      <td>The AMA Journal of Ethic</td>\n",
       "      <td>22</td>\n",
       "      <td>4</td>\n",
       "      <td>e344-345</td>\n",
       "      <td>10.1001/amajethics.2020.344</td>\n",
       "      <td>...</td>\n",
       "      <td>78676044.0</td>\n",
       "      <td>2020</td>\n",
       "      <td>4</td>\n",
       "      <td>2020-04-01</td>\n",
       "      <td>article</td>\n",
       "      <td>2376-6980</td>\n",
       "      <td>1</td>\n",
       "      <td>NaN</td>\n",
       "      <td></td>\n",
       "      <td></td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>3</td>\n",
       "      <td>Salvation in a Time of Plague.</td>\n",
       "      <td>Health workers offer their skills and care to ...</td>\n",
       "      <td>2020.0</td>\n",
       "      <td>5.0</td>\n",
       "      <td>The AMA Journal of Ethic</td>\n",
       "      <td>22</td>\n",
       "      <td>5</td>\n",
       "      <td>e441-445</td>\n",
       "      <td>10.1001/amajethics.2020.441</td>\n",
       "      <td>...</td>\n",
       "      <td>80348292.0</td>\n",
       "      <td>2020</td>\n",
       "      <td>5</td>\n",
       "      <td>2020-05-01</td>\n",
       "      <td>article</td>\n",
       "      <td>2376-6980</td>\n",
       "      <td>0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>Medical and Health Sciences</td>\n",
       "      <td>Public Health and Health Services</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "<p>5 rows × 27 columns</p>\n",
       "</div>"
      ],
      "text/plain": [
       "   pub_id                                              title  \\\n",
       "0       0  Coronavirus disease 2019 (COVID-19) and simult...   \n",
       "1       0  Coronavirus disease 2019 (COVID-19) and simult...   \n",
       "2       1  [Ten hot issues of breast cancer under the nov...   \n",
       "3       2                            Cohesion in Distancing.   \n",
       "4       3                     Salvation in a Time of Plague.   \n",
       "\n",
       "                                            abstract  publication_year  \\\n",
       "0  Coronavirus disease 2019 (COVID-19) is a recen...            2020.0   \n",
       "1  Coronavirus disease 2019 (COVID-19) is a recen...            2020.0   \n",
       "2                                                               2020.0   \n",
       "3  In isolation, we are physically apart; in soli...            2020.0   \n",
       "4  Health workers offer their skills and care to ...            2020.0   \n",
       "\n",
       "   publication_month                           journal volume issue     pages  \\\n",
       "0                5.0  CardioVascular Journal of Africa     31   NaN       1-4   \n",
       "1                5.0  CardioVascular Journal of Africa     31   NaN       1-4   \n",
       "2                2.0           Chinese medical journal    100     0      e002   \n",
       "3                4.0          The AMA Journal of Ethic     22     4  e344-345   \n",
       "4                5.0          The AMA Journal of Ethic     22     5  e441-445   \n",
       "\n",
       "                                      doi  ...  altmetric_id  year month  \\\n",
       "0                   10-5830-cvja-2020-016  ...           0.0  2020     5   \n",
       "1                   10-5830-cvja-2020-016  ...           0.0  2020     5   \n",
       "2  10.0376/cma.j.issn.0376-2491.2020.0002  ...    75778970.0  2020     2   \n",
       "3             10.1001/amajethics.2020.344  ...    78676044.0  2020     4   \n",
       "4             10.1001/amajethics.2020.441  ...    80348292.0  2020     5   \n",
       "\n",
       "  publication_date publication_type       issn times_cited  \\\n",
       "0       2020-05-05          article  1995-1892           0   \n",
       "1       2020-05-05          article  1995-1892           0   \n",
       "2       2020-02-10          article  0376-2491           0   \n",
       "3       2020-04-01          article  2376-6980           1   \n",
       "4       2020-05-01          article  2376-6980           0   \n",
       "\n",
       "   relative_citation_ratio                      for_top  \\\n",
       "0                      NaN  Medical and Health Sciences   \n",
       "1                      NaN  Medical and Health Sciences   \n",
       "2                      NaN                                \n",
       "3                      NaN                                \n",
       "4                      NaN  Medical and Health Sciences   \n",
       "\n",
       "                                   for_bottom  \n",
       "0  Cardiorespiratory Medicine and Haematology  \n",
       "1  Cardiorespiratory Medicine and Haematology  \n",
       "2                                              \n",
       "3                                              \n",
       "4           Public Health and Health Services  \n",
       "\n",
       "[5 rows x 27 columns]"
      ]
     },
     "execution_count": 30,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df_joined.head()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 31,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "(141783, 27)"
      ]
     },
     "execution_count": 31,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df_joined.shape"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 32,
   "metadata": {},
   "outputs": [],
   "source": [
    "df_joined = df_joined.groupby(\"pub_id\").first().reset_index()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 33,
   "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>pub_id</th>\n",
       "      <th>title</th>\n",
       "      <th>abstract</th>\n",
       "      <th>publication_year</th>\n",
       "      <th>publication_month</th>\n",
       "      <th>journal</th>\n",
       "      <th>volume</th>\n",
       "      <th>issue</th>\n",
       "      <th>pages</th>\n",
       "      <th>doi</th>\n",
       "      <th>...</th>\n",
       "      <th>altmetric_id</th>\n",
       "      <th>year</th>\n",
       "      <th>month</th>\n",
       "      <th>publication_date</th>\n",
       "      <th>publication_type</th>\n",
       "      <th>issn</th>\n",
       "      <th>times_cited</th>\n",
       "      <th>relative_citation_ratio</th>\n",
       "      <th>for_top</th>\n",
       "      <th>for_bottom</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>28533</th>\n",
       "      <td>29534</td>\n",
       "      <td>Chapter 11 Detection of Analytes on Arrays/Mic...</td>\n",
       "      <td>Publisher Summary Microarrays/arrays/DNA chips...</td>\n",
       "      <td>2011.0</td>\n",
       "      <td>12.0</td>\n",
       "      <td>Handbook of Biosensors and Biosensor Kinetics</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>10.1016/b978-0-444-53262-6.00011-5</td>\n",
       "      <td>...</td>\n",
       "      <td>0.0</td>\n",
       "      <td>2011</td>\n",
       "      <td>1</td>\n",
       "      <td>2011-01-01</td>\n",
       "      <td>chapter</td>\n",
       "      <td>None</td>\n",
       "      <td>0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>Chemical Sciences</td>\n",
       "      <td>Physical Chemistry (incl. Structural)</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "<p>1 rows × 27 columns</p>\n",
       "</div>"
      ],
      "text/plain": [
       "       pub_id                                              title  \\\n",
       "28533   29534  Chapter 11 Detection of Analytes on Arrays/Mic...   \n",
       "\n",
       "                                                abstract  publication_year  \\\n",
       "28533  Publisher Summary Microarrays/arrays/DNA chips...            2011.0   \n",
       "\n",
       "       publication_month                                        journal  \\\n",
       "28533               12.0  Handbook of Biosensors and Biosensor Kinetics   \n",
       "\n",
       "      volume issue pages                                 doi  ...  \\\n",
       "28533    NaN   NaN   NaN  10.1016/b978-0-444-53262-6.00011-5  ...   \n",
       "\n",
       "       altmetric_id  year month publication_date publication_type  issn  \\\n",
       "28533           0.0  2011     1       2011-01-01          chapter  None   \n",
       "\n",
       "      times_cited  relative_citation_ratio            for_top  \\\n",
       "28533           0                      NaN  Chemical Sciences   \n",
       "\n",
       "                                  for_bottom  \n",
       "28533  Physical Chemistry (incl. Structural)  \n",
       "\n",
       "[1 rows x 27 columns]"
      ]
     },
     "execution_count": 33,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df_joined[df_joined.pub_id==29534]"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 34,
   "metadata": {},
   "outputs": [],
   "source": [
    "# Most publications are in Dimensions via DOI or PMID: we focus on these"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 35,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "(141224, 27)"
      ]
     },
     "execution_count": 35,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df_joined.shape"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 36,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "(160656, 16)"
      ]
     },
     "execution_count": 36,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df_meta.shape"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 37,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 432x288 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "# publication typology\n",
    "\n",
    "df_sub = df_joined[df_joined.publication_type.isin(df_joined.publication_type.value_counts()[:10].index.tolist())]\n",
    "b = sns.countplot(y=\"publication_type\", data=df_sub, order=df_sub['publication_type'].value_counts().index)\n",
    "#b.axes.set_title(\"Title\",fontsize=50)\n",
    "b.set_xlabel(\"Count\",fontsize=15)\n",
    "b.set_ylabel(\"Publication typology\",fontsize=15)\n",
    "b.tick_params(labelsize=12)\n",
    "plt.tight_layout()\n",
    "plt.savefig(\"figures/dim_pub_type.pdf\")"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "#### Citation counts"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 112,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 432x288 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "# scatter of citations vs time of publication\n",
    "\n",
    "sns.scatterplot(df_joined.publication_year.to_list(),df_joined.times_cited.to_list())\n",
    "plt.xlabel(\"Publication year\", fontsize=15)\n",
    "plt.ylabel(\"Number of citations\", fontsize=15)\n",
    "b.tick_params(labelsize=12)\n",
    "plt.tight_layout()\n",
    "plt.savefig(\"figures/dim_citations_year.pdf\")"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 40,
   "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>title</th>\n",
       "      <th>times_cited</th>\n",
       "      <th>relative_citation_ratio</th>\n",
       "      <th>journal</th>\n",
       "      <th>publication_year</th>\n",
       "      <th>doi</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>56043</th>\n",
       "      <td>Clinical features of patients infected with 20...</td>\n",
       "      <td>5508</td>\n",
       "      <td>NaN</td>\n",
       "      <td>The Lancet</td>\n",
       "      <td>2020.0</td>\n",
       "      <td>10.1016/s0140-6736(20)30183-5</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>74499</th>\n",
       "      <td>Biological roles of oligosaccharides: all of t...</td>\n",
       "      <td>4021</td>\n",
       "      <td>92.34</td>\n",
       "      <td>Glycobiology</td>\n",
       "      <td>1993.0</td>\n",
       "      <td>10.1093/glycob/3.2.97</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>77301</th>\n",
       "      <td>Surviving sepsis campaign: international guide...</td>\n",
       "      <td>3998</td>\n",
       "      <td>205.11</td>\n",
       "      <td>Critical care medicine</td>\n",
       "      <td>2013.0</td>\n",
       "      <td>10.1097/ccm.0b013e31827e83af</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>72001</th>\n",
       "      <td>Infectious Diseases Society of America/America...</td>\n",
       "      <td>3967</td>\n",
       "      <td>111.15</td>\n",
       "      <td>Clin Infect Dis</td>\n",
       "      <td>2007.0</td>\n",
       "      <td>10.1086/511159</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>55735</th>\n",
       "      <td>Epidemiology and causes of preterm birth</td>\n",
       "      <td>3680</td>\n",
       "      <td>120.06</td>\n",
       "      <td>The Lancet</td>\n",
       "      <td>2008.0</td>\n",
       "      <td>10.1016/s0140-6736(08)60074-4</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>68485</th>\n",
       "      <td>Clinical Characteristics of Coronavirus Diseas...</td>\n",
       "      <td>3278</td>\n",
       "      <td>NaN</td>\n",
       "      <td>New England Journal of Medicine</td>\n",
       "      <td>2020.0</td>\n",
       "      <td>10.1056/nejmoa2002032</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>68481</th>\n",
       "      <td>A Novel Coronavirus from Patients with Pneumon...</td>\n",
       "      <td>3250</td>\n",
       "      <td>NaN</td>\n",
       "      <td>New England Journal of Medicine</td>\n",
       "      <td>2020.0</td>\n",
       "      <td>10.1056/nejmoa2001017</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>277</th>\n",
       "      <td>Clinical Characteristics of 138 Hospitalized P...</td>\n",
       "      <td>3220</td>\n",
       "      <td>NaN</td>\n",
       "      <td>JAMA</td>\n",
       "      <td>2020.0</td>\n",
       "      <td>10.1001/jama.2020.1585</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>68466</th>\n",
       "      <td>Randomized assessment of rapid endovascular tr...</td>\n",
       "      <td>3079</td>\n",
       "      <td>197.01</td>\n",
       "      <td>The New England journal of medicine</td>\n",
       "      <td>2015.0</td>\n",
       "      <td>10.1056/nejmoa1414905</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>13119</th>\n",
       "      <td>Surviving Sepsis Campaign: International Guide...</td>\n",
       "      <td>2962</td>\n",
       "      <td>147.71</td>\n",
       "      <td>Intensive Care Med</td>\n",
       "      <td>2013.0</td>\n",
       "      <td>10.1007/s00134-012-2769-8</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "                                                   title  times_cited  \\\n",
       "56043  Clinical features of patients infected with 20...         5508   \n",
       "74499  Biological roles of oligosaccharides: all of t...         4021   \n",
       "77301  Surviving sepsis campaign: international guide...         3998   \n",
       "72001  Infectious Diseases Society of America/America...         3967   \n",
       "55735           Epidemiology and causes of preterm birth         3680   \n",
       "68485  Clinical Characteristics of Coronavirus Diseas...         3278   \n",
       "68481  A Novel Coronavirus from Patients with Pneumon...         3250   \n",
       "277    Clinical Characteristics of 138 Hospitalized P...         3220   \n",
       "68466  Randomized assessment of rapid endovascular tr...         3079   \n",
       "13119  Surviving Sepsis Campaign: International Guide...         2962   \n",
       "\n",
       "       relative_citation_ratio                              journal  \\\n",
       "56043                      NaN                           The Lancet   \n",
       "74499                    92.34                         Glycobiology   \n",
       "77301                   205.11               Critical care medicine   \n",
       "72001                   111.15                      Clin Infect Dis   \n",
       "55735                   120.06                           The Lancet   \n",
       "68485                      NaN      New England Journal of Medicine   \n",
       "68481                      NaN      New England Journal of Medicine   \n",
       "277                        NaN                                 JAMA   \n",
       "68466                   197.01  The New England journal of medicine   \n",
       "13119                   147.71                   Intensive Care Med   \n",
       "\n",
       "       publication_year                            doi  \n",
       "56043            2020.0  10.1016/s0140-6736(20)30183-5  \n",
       "74499            1993.0          10.1093/glycob/3.2.97  \n",
       "77301            2013.0   10.1097/ccm.0b013e31827e83af  \n",
       "72001            2007.0                 10.1086/511159  \n",
       "55735            2008.0  10.1016/s0140-6736(08)60074-4  \n",
       "68485            2020.0          10.1056/nejmoa2002032  \n",
       "68481            2020.0          10.1056/nejmoa2001017  \n",
       "277              2020.0         10.1001/jama.2020.1585  \n",
       "68466            2015.0          10.1056/nejmoa1414905  \n",
       "13119            2013.0      10.1007/s00134-012-2769-8  "
      ]
     },
     "execution_count": 40,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "# most cited papers\n",
    "\n",
    "df_joined[[\"title\",\"times_cited\",\"relative_citation_ratio\",\"journal\",\"publication_year\",\"doi\"]].sort_values(\"times_cited\",ascending=False).head(10)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 41,
   "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>title</th>\n",
       "      <th>times_cited</th>\n",
       "      <th>relative_citation_ratio</th>\n",
       "      <th>journal</th>\n",
       "      <th>publication_year</th>\n",
       "      <th>doi</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>56043</th>\n",
       "      <td>Clinical features of patients infected with 20...</td>\n",
       "      <td>5508</td>\n",
       "      <td>NaN</td>\n",
       "      <td>The Lancet</td>\n",
       "      <td>2020.0</td>\n",
       "      <td>10.1016/s0140-6736(20)30183-5</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>68485</th>\n",
       "      <td>Clinical Characteristics of Coronavirus Diseas...</td>\n",
       "      <td>3278</td>\n",
       "      <td>NaN</td>\n",
       "      <td>New England Journal of Medicine</td>\n",
       "      <td>2020.0</td>\n",
       "      <td>10.1056/nejmoa2002032</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>68481</th>\n",
       "      <td>A Novel Coronavirus from Patients with Pneumon...</td>\n",
       "      <td>3250</td>\n",
       "      <td>NaN</td>\n",
       "      <td>New England Journal of Medicine</td>\n",
       "      <td>2020.0</td>\n",
       "      <td>10.1056/nejmoa2001017</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>277</th>\n",
       "      <td>Clinical Characteristics of 138 Hospitalized P...</td>\n",
       "      <td>3220</td>\n",
       "      <td>NaN</td>\n",
       "      <td>JAMA</td>\n",
       "      <td>2020.0</td>\n",
       "      <td>10.1001/jama.2020.1585</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>56047</th>\n",
       "      <td>Epidemiological and clinical characteristics o...</td>\n",
       "      <td>2762</td>\n",
       "      <td>NaN</td>\n",
       "      <td>The Lancet</td>\n",
       "      <td>2020.0</td>\n",
       "      <td>10.1016/s0140-6736(20)30211-7</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>56120</th>\n",
       "      <td>Clinical course and risk factors for mortality...</td>\n",
       "      <td>2464</td>\n",
       "      <td>NaN</td>\n",
       "      <td>The Lancet</td>\n",
       "      <td>2020.0</td>\n",
       "      <td>10.1016/s0140-6736(20)30566-3</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>68484</th>\n",
       "      <td>Early Transmission Dynamics in Wuhan, China, o...</td>\n",
       "      <td>2399</td>\n",
       "      <td>NaN</td>\n",
       "      <td>New England Journal of Medicine</td>\n",
       "      <td>2020.0</td>\n",
       "      <td>10.1056/nejmoa2001316</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>65299</th>\n",
       "      <td>A pneumonia outbreak associated with a new cor...</td>\n",
       "      <td>2115</td>\n",
       "      <td>NaN</td>\n",
       "      <td>Nature</td>\n",
       "      <td>2020.0</td>\n",
       "      <td>10.1038/s41586-020-2012-7</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>295</th>\n",
       "      <td>Characteristics of and Important Lessons From ...</td>\n",
       "      <td>2042</td>\n",
       "      <td>NaN</td>\n",
       "      <td>JAMA</td>\n",
       "      <td>2020.0</td>\n",
       "      <td>10.1001/jama.2020.2648</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>56037</th>\n",
       "      <td>A familial cluster of pneumonia associated wit...</td>\n",
       "      <td>1485</td>\n",
       "      <td>NaN</td>\n",
       "      <td>The Lancet</td>\n",
       "      <td>2020.0</td>\n",
       "      <td>10.1016/s0140-6736(20)30154-9</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "                                                   title  times_cited  \\\n",
       "56043  Clinical features of patients infected with 20...         5508   \n",
       "68485  Clinical Characteristics of Coronavirus Diseas...         3278   \n",
       "68481  A Novel Coronavirus from Patients with Pneumon...         3250   \n",
       "277    Clinical Characteristics of 138 Hospitalized P...         3220   \n",
       "56047  Epidemiological and clinical characteristics o...         2762   \n",
       "56120  Clinical course and risk factors for mortality...         2464   \n",
       "68484  Early Transmission Dynamics in Wuhan, China, o...         2399   \n",
       "65299  A pneumonia outbreak associated with a new cor...         2115   \n",
       "295    Characteristics of and Important Lessons From ...         2042   \n",
       "56037  A familial cluster of pneumonia associated wit...         1485   \n",
       "\n",
       "       relative_citation_ratio                          journal  \\\n",
       "56043                      NaN                       The Lancet   \n",
       "68485                      NaN  New England Journal of Medicine   \n",
       "68481                      NaN  New England Journal of Medicine   \n",
       "277                        NaN                             JAMA   \n",
       "56047                      NaN                       The Lancet   \n",
       "56120                      NaN                       The Lancet   \n",
       "68484                      NaN  New England Journal of Medicine   \n",
       "65299                      NaN                           Nature   \n",
       "295                        NaN                             JAMA   \n",
       "56037                      NaN                       The Lancet   \n",
       "\n",
       "       publication_year                            doi  \n",
       "56043            2020.0  10.1016/s0140-6736(20)30183-5  \n",
       "68485            2020.0          10.1056/nejmoa2002032  \n",
       "68481            2020.0          10.1056/nejmoa2001017  \n",
       "277              2020.0         10.1001/jama.2020.1585  \n",
       "56047            2020.0  10.1016/s0140-6736(20)30211-7  \n",
       "56120            2020.0  10.1016/s0140-6736(20)30566-3  \n",
       "68484            2020.0          10.1056/nejmoa2001316  \n",
       "65299            2020.0      10.1038/s41586-020-2012-7  \n",
       "295              2020.0         10.1001/jama.2020.2648  \n",
       "56037            2020.0  10.1016/s0140-6736(20)30154-9  "
      ]
     },
     "execution_count": 41,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "# same but in 2020; note that duplicates are due to SI or pre-prints with different PMIDs\n",
    "\n",
    "df_joined[df_joined.publication_year>2019][[\"title\",\"times_cited\",\"relative_citation_ratio\",\"journal\",\"publication_year\",\"doi\"]].sort_values(\"times_cited\",ascending=False).head(10)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 42,
   "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>times_cited</th>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>journal</th>\n",
       "      <th></th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>The Lancet</th>\n",
       "      <td>51215</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>PLoS One</th>\n",
       "      <td>40269</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Nature</th>\n",
       "      <td>39599</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Virology</th>\n",
       "      <td>36643</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Emerg Infect Dis</th>\n",
       "      <td>35280</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Journal of virology</th>\n",
       "      <td>33933</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>JAMA</th>\n",
       "      <td>28512</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Surgical endoscopy</th>\n",
       "      <td>23332</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Lancet</th>\n",
       "      <td>22943</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>PLoS Pathog</th>\n",
       "      <td>22751</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "                     times_cited\n",
       "journal                         \n",
       "The Lancet                 51215\n",
       "PLoS One                   40269\n",
       "Nature                     39599\n",
       "Virology                   36643\n",
       "Emerg Infect Dis           35280\n",
       "Journal of virology        33933\n",
       "JAMA                       28512\n",
       "Surgical endoscopy         23332\n",
       "Lancet                     22943\n",
       "PLoS Pathog                22751"
      ]
     },
     "execution_count": 42,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "# most cited journals\n",
    "\n",
    "df_joined[['journal','times_cited']].groupby('journal').sum().sort_values('times_cited',ascending=False).head(10)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## Altmetrics"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 43,
   "metadata": {},
   "outputs": [],
   "source": [
    "# load Altmetrics data (you will need to download it on your own)\n",
    "\n",
    "directory_name = \"../cwts_covid/datasets_output/json_altmetrics_cwts\"\n",
    "\n",
    "all_altmetrics = list()\n",
    "for root, dirs, files in os.walk(directory_name):\n",
    "    for file in files:\n",
    "        if \".json\" in file:\n",
    "            all_altmetrics.append(json.loads(codecs.open(os.path.join(root,file)).read()))"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 44,
   "metadata": {
    "scrolled": false
   },
   "outputs": [],
   "source": [
    "#all_altmetrics[1]"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 45,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "101662"
      ]
     },
     "execution_count": 45,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "len(all_altmetrics)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 46,
   "metadata": {},
   "outputs": [],
   "source": [
    "df_altmetrics = pd.DataFrame.from_dict({\n",
    "    \"altmetric_id\":[r[\"altmetric_id\"] if \"altmetric_id\" in r.keys() else None for r in all_altmetrics],\n",
    "    \"counts_mendeley\":[r[\"counts\"][\"readers\"][\"mendeley\"] if \"readers\" in r[\"counts\"].keys() else 0 for r in all_altmetrics],\n",
    "    \"counts_news\":[r[\"counts\"][\"news\"][\"posts_count\"] if \"news\" in r[\"counts\"].keys() else 0 for r in all_altmetrics],\n",
    "    \"counts_blogs\":[r[\"counts\"][\"blogs\"][\"posts_count\"] if \"blogs\" in r[\"counts\"].keys() else 0 for r in all_altmetrics],\n",
    "    \"counts_facebook\":[r[\"counts\"][\"facebook\"][\"posts_count\"] if \"facebook\" in r[\"counts\"].keys() else 0 for r in all_altmetrics],\n",
    "    \"counts_policy\":[r[\"counts\"][\"policy\"][\"posts_count\"] if \"policy\" in r[\"counts\"].keys() else 0 for r in all_altmetrics],\n",
    "    \"counts_wikipedia\":[r[\"counts\"][\"wikipedia\"][\"posts_count\"] if \"wikipedia\" in r[\"counts\"].keys() else 0 for r in all_altmetrics],\n",
    "    \"counts_twitter_count\":[r[\"counts\"][\"twitter\"][\"posts_count\"] if \"twitter\" in r[\"counts\"].keys() else 0 for r in all_altmetrics],\n",
    "    \"counts_twitter_unique\":[r[\"counts\"][\"twitter\"][\"unique_users_count\"] if \"twitter\" in r[\"counts\"].keys() else 0 for r in all_altmetrics],\n",
    "    \"counts_total\":[r[\"counts\"][\"total\"][\"posts_count\"] if \"total\" in r[\"counts\"].keys() else 0 for r in all_altmetrics],\n",
    "    \"doi\":[r[\"citation\"][\"doi\"] if \"doi\" in r[\"citation\"] else None for r in all_altmetrics],\n",
    "    \"pmid\":[r[\"citation\"][\"pmid\"] if \"pmid\" in r[\"citation\"] else None for r in all_altmetrics],\n",
    "    \"year\":[int(r[\"citation\"][\"pubdate\"][:4]) if \"pubdate\" in r[\"citation\"] else None for r in all_altmetrics],\n",
    "    \"title\":[r[\"citation\"][\"title\"] if \"title\" in r[\"citation\"] else None for r in all_altmetrics],\n",
    "    #\"abstract\":[r[\"citation\"][\"abstract\"] if \"abstract\" in r[\"citation\"] else None for r in all_altmetrics],\n",
    "    \"altmetric_score\":[r[\"altmetric_score\"][\"score\"] for r in all_altmetrics],\n",
    "    \"member_of_the_public\":[r[\"demographics\"][\"poster_types\"][\"member_of_the_public\"] if \"demographics\" in r.keys() and isinstance(r[\"demographics\"],dict) and \"poster_types\" in r[\"demographics\"].keys() and \"member_of_the_public\" in r[\"demographics\"][\"poster_types\"].keys() else 0 for r in all_altmetrics],\n",
    "    \"researcher\":[r[\"demographics\"][\"poster_types\"][\"researcher\"] if \"demographics\" in r.keys() and isinstance(r[\"demographics\"],dict) and \"poster_types\" in r[\"demographics\"].keys() and \"researcher\" in r[\"demographics\"][\"poster_types\"].keys() else 0 for r in all_altmetrics],\n",
    "    \"practitioner\":[r[\"demographics\"][\"poster_types\"][\"practitioner\"] if \"demographics\" in r.keys() and isinstance(r[\"demographics\"],dict) and \"poster_types\" in r[\"demographics\"].keys() and \"practitioner\" in r[\"demographics\"][\"poster_types\"].keys() else 0 for r in all_altmetrics],\n",
    "    \"science_communicator\":[r[\"demographics\"][\"poster_types\"][\"science_communicator\"] if \"demographics\" in r.keys() and isinstance(r[\"demographics\"],dict) and \"poster_types\" in r[\"demographics\"].keys() and \"science_communicator\" in r[\"demographics\"][\"poster_types\"].keys() else 0 for r in all_altmetrics]\n",
    "})"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 47,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "(101662, 19)"
      ]
     },
     "execution_count": 47,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df_altmetrics.shape"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 48,
   "metadata": {},
   "outputs": [],
   "source": [
    "df_altmetrics['counts_mendeley'] = df_altmetrics['counts_mendeley'].astype(float)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 49,
   "metadata": {},
   "outputs": [],
   "source": [
    "# aggregate possible duplicates by summing their values up\n",
    "# this is the recommended approach by Altmetric\n",
    "\n",
    "df_altmetrics_aggr = df_altmetrics[['altmetric_id', 'counts_mendeley', 'counts_news', 'counts_blogs',\n",
    "       'counts_facebook', 'counts_policy', 'counts_wikipedia',\n",
    "       'counts_twitter_count', 'counts_twitter_unique', 'counts_total', 'altmetric_score', 'member_of_the_public',\n",
    "       'researcher', 'practitioner', 'science_communicator']].groupby(\"altmetric_id\").agg('sum')"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 50,
   "metadata": {},
   "outputs": [],
   "source": [
    "df_altmetrics = df_altmetrics[['altmetric_id', 'doi',\n",
    "       'pmid', 'year', 'title']].merge(df_altmetrics_aggr, how=\"inner\", left_on=\"altmetric_id\", right_on=\"altmetric_id\")"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 51,
   "metadata": {},
   "outputs": [],
   "source": [
    "df_altmetrics.drop_duplicates('altmetric_id',inplace=True)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 52,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "(94600, 19)"
      ]
     },
     "execution_count": 52,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df_altmetrics.shape"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 53,
   "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>altmetric_id</th>\n",
       "      <th>doi</th>\n",
       "      <th>pmid</th>\n",
       "      <th>year</th>\n",
       "      <th>title</th>\n",
       "      <th>counts_mendeley</th>\n",
       "      <th>counts_news</th>\n",
       "      <th>counts_blogs</th>\n",
       "      <th>counts_facebook</th>\n",
       "      <th>counts_policy</th>\n",
       "      <th>counts_wikipedia</th>\n",
       "      <th>counts_twitter_count</th>\n",
       "      <th>counts_twitter_unique</th>\n",
       "      <th>counts_total</th>\n",
       "      <th>altmetric_score</th>\n",
       "      <th>member_of_the_public</th>\n",
       "      <th>researcher</th>\n",
       "      <th>practitioner</th>\n",
       "      <th>science_communicator</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>66870</th>\n",
       "      <td>390412.0</td>\n",
       "      <td>10.1086/511159</td>\n",
       "      <td>17278083</td>\n",
       "      <td>2007.0</td>\n",
       "      <td>Infectious Diseases Society of America/America...</td>\n",
       "      <td>3592.0</td>\n",
       "      <td>12</td>\n",
       "      <td>16</td>\n",
       "      <td>2</td>\n",
       "      <td>4</td>\n",
       "      <td>8</td>\n",
       "      <td>52</td>\n",
       "      <td>48</td>\n",
       "      <td>95</td>\n",
       "      <td>140.344</td>\n",
       "      <td>35</td>\n",
       "      <td>2</td>\n",
       "      <td>11</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "       altmetric_id             doi      pmid    year  \\\n",
       "66870      390412.0  10.1086/511159  17278083  2007.0   \n",
       "\n",
       "                                                   title  counts_mendeley  \\\n",
       "66870  Infectious Diseases Society of America/America...           3592.0   \n",
       "\n",
       "       counts_news  counts_blogs  counts_facebook  counts_policy  \\\n",
       "66870           12            16                2              4   \n",
       "\n",
       "       counts_wikipedia  counts_twitter_count  counts_twitter_unique  \\\n",
       "66870                 8                    52                     48   \n",
       "\n",
       "       counts_total  altmetric_score  member_of_the_public  researcher  \\\n",
       "66870            95          140.344                    35           2   \n",
       "\n",
       "       practitioner  science_communicator  \n",
       "66870            11                     0  "
      ]
     },
     "execution_count": 53,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df_altmetrics[df_altmetrics.doi==\"10.1086/511159\"]"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 54,
   "metadata": {
    "scrolled": false
   },
   "outputs": [],
   "source": [
    "#all_altmetrics[26239]"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 55,
   "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>altmetric_id</th>\n",
       "      <th>doi</th>\n",
       "      <th>pmid</th>\n",
       "      <th>year</th>\n",
       "      <th>title</th>\n",
       "      <th>counts_mendeley</th>\n",
       "      <th>counts_news</th>\n",
       "      <th>counts_blogs</th>\n",
       "      <th>counts_facebook</th>\n",
       "      <th>counts_policy</th>\n",
       "      <th>counts_wikipedia</th>\n",
       "      <th>counts_twitter_count</th>\n",
       "      <th>counts_twitter_unique</th>\n",
       "      <th>counts_total</th>\n",
       "      <th>altmetric_score</th>\n",
       "      <th>member_of_the_public</th>\n",
       "      <th>researcher</th>\n",
       "      <th>practitioner</th>\n",
       "      <th>science_communicator</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>81491533.0</td>\n",
       "      <td>10.1016/j.eclinm.2020.100374</td>\n",
       "      <td>32368727</td>\n",
       "      <td>2020.0</td>\n",
       "      <td>Testing for COVID-19 in patients with cancer</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>2</td>\n",
       "      <td>2</td>\n",
       "      <td>2</td>\n",
       "      <td>0.75</td>\n",
       "      <td>1</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>44518982.0</td>\n",
       "      <td>10.1128/aem.00551-18</td>\n",
       "      <td>29625986</td>\n",
       "      <td>2018.0</td>\n",
       "      <td>Survival of the Enveloped Virus Phi6 in Drople...</td>\n",
       "      <td>63.0</td>\n",
       "      <td>1</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>12</td>\n",
       "      <td>7</td>\n",
       "      <td>14</td>\n",
       "      <td>20.53</td>\n",
       "      <td>7</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>82780392.0</td>\n",
       "      <td>10.1101/2020.05.25.20108852</td>\n",
       "      <td>None</td>\n",
       "      <td>NaN</td>\n",
       "      <td>Impaired T cell functions along with elevated ...</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>6</td>\n",
       "      <td>6</td>\n",
       "      <td>6</td>\n",
       "      <td>3.75</td>\n",
       "      <td>6</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>41664421.0</td>\n",
       "      <td>10.1007/bf01310699</td>\n",
       "      <td>1689994</td>\n",
       "      <td>1990.0</td>\n",
       "      <td>Mapping of viral epitopes with prokaryotic exp...</td>\n",
       "      <td>2.0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>5</td>\n",
       "      <td>3.00</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>83745499.0</td>\n",
       "      <td>10.1530/edm-20-0028</td>\n",
       "      <td>32408269</td>\n",
       "      <td>2020.0</td>\n",
       "      <td>Milk-alkali syndrome: a ‘quick ease’ or a ‘lon...</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>2</td>\n",
       "      <td>2</td>\n",
       "      <td>2</td>\n",
       "      <td>1.50</td>\n",
       "      <td>2</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "   altmetric_id                           doi      pmid    year  \\\n",
       "0    81491533.0  10.1016/j.eclinm.2020.100374  32368727  2020.0   \n",
       "1    44518982.0          10.1128/aem.00551-18  29625986  2018.0   \n",
       "2    82780392.0   10.1101/2020.05.25.20108852      None     NaN   \n",
       "3    41664421.0            10.1007/bf01310699   1689994  1990.0   \n",
       "4    83745499.0           10.1530/edm-20-0028  32408269  2020.0   \n",
       "\n",
       "                                               title  counts_mendeley  \\\n",
       "0       Testing for COVID-19 in patients with cancer              0.0   \n",
       "1  Survival of the Enveloped Virus Phi6 in Drople...             63.0   \n",
       "2  Impaired T cell functions along with elevated ...              0.0   \n",
       "3  Mapping of viral epitopes with prokaryotic exp...              2.0   \n",
       "4  Milk-alkali syndrome: a ‘quick ease’ or a ‘lon...              0.0   \n",
       "\n",
       "   counts_news  counts_blogs  counts_facebook  counts_policy  \\\n",
       "0            0             0                0              0   \n",
       "1            1             1                0              0   \n",
       "2            0             0                0              0   \n",
       "3            0             0                0              0   \n",
       "4            0             0                0              0   \n",
       "\n",
       "   counts_wikipedia  counts_twitter_count  counts_twitter_unique  \\\n",
       "0                 0                     2                      2   \n",
       "1                 0                    12                      7   \n",
       "2                 0                     6                      6   \n",
       "3                 0                     0                      0   \n",
       "4                 0                     2                      2   \n",
       "\n",
       "   counts_total  altmetric_score  member_of_the_public  researcher  \\\n",
       "0             2             0.75                     1           1   \n",
       "1            14            20.53                     7           0   \n",
       "2             6             3.75                     6           0   \n",
       "3             5             3.00                     0           0   \n",
       "4             2             1.50                     2           0   \n",
       "\n",
       "   practitioner  science_communicator  \n",
       "0             0                     0  \n",
       "1             0                     0  \n",
       "2             0                     0  \n",
       "3             0                     0  \n",
       "4             0                     0  "
      ]
     },
     "execution_count": 55,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df_altmetrics.head()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 56,
   "metadata": {},
   "outputs": [],
   "source": [
    "# Extract Wikipedia data frames\n",
    "from datetime import date\n",
    "#>>> date.fromisoformat('2019-12-04')\n",
    "\n",
    "dois = list()\n",
    "altmetric_ids = list()\n",
    "wikipedia_ids = list()\n",
    "wikipedia_titles = list()\n",
    "wikipedia_urls = list()\n",
    "wikipedia_langs = list()\n",
    "wikipedia_summaries = list()\n",
    "wikipedia_postedons = list()\n",
    "\n",
    "for a in all_altmetrics:\n",
    "    if \"counts\" in a.keys():\n",
    "        if \"wikipedia\" in a[\"counts\"].keys():\n",
    "            for w in a[\"posts\"][\"wikipedia\"]:\n",
    "                try:\n",
    "                    if \"doi\" in a[\"citation\"].keys():\n",
    "                        dois.append(a[\"citation\"][\"doi\"])\n",
    "                    else:\n",
    "                        dois.append(None)\n",
    "                    altmetric_ids.append(a[\"altmetric_id\"])\n",
    "                    wiki_id = w[\"page_url\"].split(\"curid=\")[-1]\n",
    "                    wikipedia_ids.append(wiki_id)\n",
    "                    wikipedia_titles.append(w[\"title\"])\n",
    "                    wikipedia_urls.append(w[\"page_url\"])\n",
    "                    wikipedia_langs.append(w[\"wiki_lang\"])\n",
    "                    if \"summary\" in w.keys():\n",
    "                        wikipedia_summaries.append(w[\"summary\"])\n",
    "                    else:\n",
    "                        wikipedia_summaries.append(\"\")\n",
    "                    wikipedia_postedons.append(date.fromisoformat(w[\"posted_on\"].split(\"T\")[0]))\n",
    "                except:\n",
    "                    print(w)\n",
    "                    continue"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 57,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "6044"
      ]
     },
     "execution_count": 57,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "len(wikipedia_ids)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 58,
   "metadata": {},
   "outputs": [],
   "source": [
    "df_wikipedia = pd.DataFrame.from_dict({\n",
    "    \"wikipedia_id\": wikipedia_ids,\n",
    "    \"title\": wikipedia_titles,\n",
    "    \"page_url\": wikipedia_urls,\n",
    "    \"lang\": wikipedia_langs,\n",
    "    \"summary\": wikipedia_summaries\n",
    "})"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 59,
   "metadata": {},
   "outputs": [],
   "source": [
    "df_wikipedia = df_wikipedia.groupby('wikipedia_id').first()\n",
    "df_wikipedia.reset_index(inplace=True)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 60,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "(2846, 5)"
      ]
     },
     "execution_count": 60,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df_wikipedia.shape"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 61,
   "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>wikipedia_id</th>\n",
       "      <th>title</th>\n",
       "      <th>page_url</th>\n",
       "      <th>lang</th>\n",
       "      <th>summary</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>10008283</td>\n",
       "      <td>Basigin</td>\n",
       "      <td>http://en.wikipedia.org/?curid=10008283</td>\n",
       "      <td>en</td>\n",
       "      <td>Basigin (BSG) also known as extracellular matr...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>1001343</td>\n",
       "      <td>Electrodermal activity</td>\n",
       "      <td>http://en.wikipedia.org/?curid=1001343</td>\n",
       "      <td>en</td>\n",
       "      <td>Electrodermal activity (EDA) is the property o...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>1001882</td>\n",
       "      <td>Simon &amp; Schuster</td>\n",
       "      <td>http://en.wikipedia.org/?curid=1001882</td>\n",
       "      <td>en</td>\n",
       "      <td>Simon &amp; Schuster, a subsidiary of ViacomCBS, i...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>1003982</td>\n",
       "      <td>Dual-use technology</td>\n",
       "      <td>http://en.wikipedia.org/?curid=1003982</td>\n",
       "      <td>en</td>\n",
       "      <td>-European Commission, Trade Topics, Dual Use|a...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>10044864</td>\n",
       "      <td>Research question</td>\n",
       "      <td>http://en.wikipedia.org/?curid=10044864</td>\n",
       "      <td>en</td>\n",
       "      <td>A research question is the objective of a stud...</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "  wikipedia_id                   title  \\\n",
       "0     10008283                 Basigin   \n",
       "1      1001343  Electrodermal activity   \n",
       "2      1001882        Simon & Schuster   \n",
       "3      1003982     Dual-use technology   \n",
       "4     10044864       Research question   \n",
       "\n",
       "                                  page_url lang  \\\n",
       "0  http://en.wikipedia.org/?curid=10008283   en   \n",
       "1   http://en.wikipedia.org/?curid=1001343   en   \n",
       "2   http://en.wikipedia.org/?curid=1001882   en   \n",
       "3   http://en.wikipedia.org/?curid=1003982   en   \n",
       "4  http://en.wikipedia.org/?curid=10044864   en   \n",
       "\n",
       "                                             summary  \n",
       "0  Basigin (BSG) also known as extracellular matr...  \n",
       "1  Electrodermal activity (EDA) is the property o...  \n",
       "2  Simon & Schuster, a subsidiary of ViacomCBS, i...  \n",
       "3  -European Commission, Trade Topics, Dual Use|a...  \n",
       "4  A research question is the objective of a stud...  "
      ]
     },
     "execution_count": 61,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df_wikipedia.head()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 62,
   "metadata": {},
   "outputs": [],
   "source": [
    "def to_ym(d):\n",
    "    if d.month < 10:\n",
    "        return str(d.year)+\"-0\"+str(d.month)\n",
    "    return str(d.year)+\"-\"+str(d.month)\n",
    "\n",
    "df_alt_to_wiki = pd.DataFrame.from_dict({\n",
    "    \"doi\": dois,\n",
    "    \"altmetric_id\": altmetric_ids,\n",
    "    \"wikipedia_id\": wikipedia_ids,\n",
    "    \"posted_on\": wikipedia_postedons,\n",
    "    \"posted_on_year\": [d.year for d in wikipedia_postedons],\n",
    "    \"posted_on_month\": [d.month for d in wikipedia_postedons],\n",
    "    \"posted_on_ym\": [to_ym(d) for d in wikipedia_postedons]\n",
    "})"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 63,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "(6044, 7)"
      ]
     },
     "execution_count": 63,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df_alt_to_wiki.shape"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 64,
   "metadata": {},
   "outputs": [],
   "source": [
    "df_alt_to_wiki.drop_duplicates(inplace=True)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 65,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "(5400, 7)"
      ]
     },
     "execution_count": 65,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df_alt_to_wiki.shape"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 66,
   "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>doi</th>\n",
       "      <th>altmetric_id</th>\n",
       "      <th>wikipedia_id</th>\n",
       "      <th>posted_on</th>\n",
       "      <th>posted_on_year</th>\n",
       "      <th>posted_on_month</th>\n",
       "      <th>posted_on_ym</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>10.1016/j.chom.2009.05.012</td>\n",
       "      <td>13617964</td>\n",
       "      <td>46181852</td>\n",
       "      <td>2016-11-15</td>\n",
       "      <td>2016</td>\n",
       "      <td>11</td>\n",
       "      <td>2016-11</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>10.1176/appi.ajp.2015.14101251</td>\n",
       "      <td>4189075</td>\n",
       "      <td>185272</td>\n",
       "      <td>2020-04-02</td>\n",
       "      <td>2020</td>\n",
       "      <td>4</td>\n",
       "      <td>2020-04</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>10.1172/jci139642</td>\n",
       "      <td>80916940</td>\n",
       "      <td>2257429</td>\n",
       "      <td>2020-05-24</td>\n",
       "      <td>2020</td>\n",
       "      <td>5</td>\n",
       "      <td>2020-05</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>10.1038/439509a</td>\n",
       "      <td>755882</td>\n",
       "      <td>244113</td>\n",
       "      <td>2008-07-11</td>\n",
       "      <td>2008</td>\n",
       "      <td>7</td>\n",
       "      <td>2008-07</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>5</th>\n",
       "      <td>10.1371/journal.pone.0233588</td>\n",
       "      <td>82350953</td>\n",
       "      <td>63423368</td>\n",
       "      <td>2020-06-12</td>\n",
       "      <td>2020</td>\n",
       "      <td>6</td>\n",
       "      <td>2020-06</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "                              doi  altmetric_id wikipedia_id   posted_on  \\\n",
       "0      10.1016/j.chom.2009.05.012      13617964     46181852  2016-11-15   \n",
       "1  10.1176/appi.ajp.2015.14101251       4189075       185272  2020-04-02   \n",
       "2               10.1172/jci139642      80916940      2257429  2020-05-24   \n",
       "4                 10.1038/439509a        755882       244113  2008-07-11   \n",
       "5    10.1371/journal.pone.0233588      82350953     63423368  2020-06-12   \n",
       "\n",
       "   posted_on_year  posted_on_month posted_on_ym  \n",
       "0            2016               11      2016-11  \n",
       "1            2020                4      2020-04  \n",
       "2            2020                5      2020-05  \n",
       "4            2008                7      2008-07  \n",
       "5            2020                6      2020-06  "
      ]
     },
     "execution_count": 66,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df_alt_to_wiki.head()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 113,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 432x288 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "# year posted_on actions histogram\n",
    "\n",
    "#plt.figure(figsize=(10,5))\n",
    "b = sns.countplot(x=\"posted_on_year\", data=df_alt_to_wiki, color=\"skyblue\")\n",
    "b.set_xticklabels(b.get_xticklabels(), rotation=45)\n",
    "b.set_xlabel(\"Year\",fontsize=15)\n",
    "b.set_ylabel(\"Number of citations\",fontsize=15)\n",
    "b.tick_params(labelsize=12)\n",
    "plt.tight_layout()\n",
    "plt.savefig(\"figures/wiki_postedon_year.pdf\")"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 135,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 720x360 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "# month-year posted_on actions histogram\n",
    "\n",
    "since_when = 2018\n",
    "plt.figure(figsize=(10,5))\n",
    "b = sns.countplot(x=\"posted_on_ym\", data=df_alt_to_wiki[(df_alt_to_wiki.posted_on_year>=since_when)&(df_alt_to_wiki.posted_on_ym!=\"2020-07\")], order=sorted(df_alt_to_wiki[(df_alt_to_wiki.posted_on_year>=since_when)&(df_alt_to_wiki.posted_on_ym!=\"2020-07\")].posted_on_ym.unique()), color=\"skyblue\")\n",
    "b.set_xticklabels(b.get_xticklabels(), rotation=45)\n",
    "b.set_xlabel(\"Year-Month\",fontsize=15)\n",
    "b.set_ylabel(\"Number of citations\",fontsize=15)\n",
    "b.tick_params(labelsize=12)\n",
    "#plt.xlim((\"2018-01\",\"2020-06\"))\n",
    "plt.tight_layout()\n",
    "plt.savefig(\"figures/wiki_postedon_year_month.pdf\")"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 115,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 720x360 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "# publication years of articles cited by Wikipedia by posted_on action \n",
    "#(i.e., with duplicates for multiple posted_on actions on different Wikipedia pages)\n",
    "\n",
    "since_when = 2020\n",
    "from_when = 2000\n",
    "\n",
    "df_alt_to_wiki_joined_altmetrics = df_alt_to_wiki.merge(df_altmetrics, how=\"left\", left_on=\"altmetric_id\", right_on=\"altmetric_id\")\n",
    "plt.figure(figsize=(10,5))\n",
    "#sns.distplot([int(l) for l in df_alt_to_wiki_joined_altmetrics[(df_alt_to_wiki_joined_altmetrics.year>=from_when)].year.to_list()], bins=20, color=\"skyblue\", kde=False, label=\"All\")\n",
    "sns.distplot([int(l) for l in df_alt_to_wiki_joined_altmetrics[(df_alt_to_wiki_joined_altmetrics.posted_on_year<since_when) & (df_alt_to_wiki_joined_altmetrics.year>=from_when)].year.to_list()], bins=20, color=\"green\", kde=False, label=\"Before %d\"%since_when)\n",
    "b = sns.distplot([int(l) for l in df_alt_to_wiki_joined_altmetrics[(df_alt_to_wiki_joined_altmetrics.posted_on_year>=since_when) & (df_alt_to_wiki_joined_altmetrics.year>=from_when)].year.to_list()], bins=20, color=\"blue\", kde=False, label=\"On %d\"%since_when)\n",
    "b.set_xlabel(\"Publication year\",fontsize=15)\n",
    "b.set_ylabel(\"Number of citations\",fontsize=15)\n",
    "b.tick_params(labelsize=12)\n",
    "plt.gca().xaxis.set_major_formatter(FuncFormatter(lambda x, _: int(x)))\n",
    "plt.legend(fontsize=15)\n",
    "plt.tight_layout()\n",
    "plt.savefig(\"figures/wiki_year_postedon.pdf\")"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 116,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 432x288 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "# publication years of articles cited by Wikipedia\n",
    "\n",
    "#plt.figure(figsize=(10,5))\n",
    "#sns.distplot(df_meta[df_meta.publication_year>1979].publication_year, color=\"skyblue\", bins=39, label=\"All\", norm_hist=False, kde=False)\n",
    "b = sns.distplot(df_alt_to_wiki_joined_altmetrics[df_alt_to_wiki_joined_altmetrics.year>1979].groupby(\"altmetric_id\").first().reset_index().year, bins=39, label=\"In Wikipedia\", norm_hist=False, kde=False)\n",
    "plt.gca().xaxis.set_major_formatter(FuncFormatter(lambda x, _: int(x)))\n",
    "#b.set_xticklabels(b.get_xticklabels(), rotation=45)\n",
    "b.set_xlabel(\"Publication year\",fontsize=15)\n",
    "b.set_ylabel(\"Publication count\",fontsize=15)\n",
    "b.tick_params(labelsize=12)\n",
    "#plt.legend(fontsize=15)\n",
    "plt.tight_layout()\n",
    "#plt.savefig(\"figures/wiki_year_both.pdf\")\n",
    "plt.savefig(\"figures/wiki_year.pdf\")"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 129,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "2003 0.06833956219967965\n",
      "2004 0.04782608695652174\n",
      "2005 0.08129784907036092\n",
      "2006 0.07147862648913805\n",
      "2007 0.07318840579710145\n",
      "2008 0.05421861409104088\n",
      "2009 0.05313523042054898\n",
      "2010 0.04479140005119017\n",
      "2011 0.04286365709074327\n",
      "2012 0.04892086330935252\n",
      "2013 0.040428472702142365\n",
      "2014 0.029791761665906673\n",
      "2015 0.03323823109843081\n",
      "2016 0.0284805751417116\n",
      "2017 0.026099290780141844\n",
      "2018 0.02062780269058296\n",
      "2019 0.019018583042973287\n",
      "2020 0.011607940105776496\n"
     ]
    }
   ],
   "source": [
    "# Fraction of cited papers per year\n",
    "coverage_by_year = list()\n",
    "since_when = 2003\n",
    "for y in range(since_when,2021):\n",
    "    cov = df_alt_to_wiki_joined_altmetrics[df_alt_to_wiki_joined_altmetrics.year==y].shape[0]/df_meta[df_meta.publication_year==y].shape[0]\n",
    "    coverage_by_year.append(cov)\n",
    "    print(y,cov)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 120,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 432x288 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "b = sns.scatterplot([y for y in range(since_when,2021)],coverage_by_year,s=70)\n",
    "b.set_xlabel(\"Year\",fontsize=15)\n",
    "b.set_ylabel(\"Fraction of COVID-19 literature\\ncited from Wikipedia\",fontsize=15)\n",
    "b.set_xticklabels(range(since_when,2021),rotation=45)\n",
    "b.tick_params(labelsize=12)\n",
    "plt.gca().xaxis.set_major_formatter(FuncFormatter(lambda x, _: int(x)))\n",
    "plt.ylim((0,0.1))\n",
    "plt.tight_layout()\n",
    "plt.savefig(\"figures/wiki_fraction_year.pdf\")"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 74,
   "metadata": {},
   "outputs": [],
   "source": [
    "# most Wiki cited papers"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 75,
   "metadata": {},
   "outputs": [],
   "source": [
    "df_top_cited = df_alt_to_wiki.groupby(\"doi\").agg('count').sort_values('wikipedia_id',ascending=False)[:20]\n",
    "df_top_cited.reset_index(inplace=True)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 144,
   "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>doi</th>\n",
       "      <th>wikipedia_id</th>\n",
       "      <th>title</th>\n",
       "      <th>publication_year</th>\n",
       "      <th>journal</th>\n",
       "      <th>times_cited</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>10.3390/info11050263</td>\n",
       "      <td>67</td>\n",
       "      <td>Modeling Popularity and Reliability of Sources...</td>\n",
       "      <td>2020.0</td>\n",
       "      <td>Information</td>\n",
       "      <td>1.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>10.1007/s00705-012-1299-6</td>\n",
       "      <td>18</td>\n",
       "      <td>Ratification vote on taxonomic proposals to th...</td>\n",
       "      <td>2012.0</td>\n",
       "      <td>Arch Virol</td>\n",
       "      <td>210.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>10.1007/978-1-4939-2438-7_1</td>\n",
       "      <td>15</td>\n",
       "      <td>Coronaviruses: An Overview of Their Replicatio...</td>\n",
       "      <td>2015.0</td>\n",
       "      <td>Methods in Molecular Biology</td>\n",
       "      <td>395.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>10.3390/v2081803</td>\n",
       "      <td>15</td>\n",
       "      <td>Coronavirus Genomics and Bioinformatics Analysis</td>\n",
       "      <td>2010.0</td>\n",
       "      <td>Viruses</td>\n",
       "      <td>143.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>10.1016/s0140-6736(20)30183-5</td>\n",
       "      <td>13</td>\n",
       "      <td>Clinical features of patients infected with 20...</td>\n",
       "      <td>2020.0</td>\n",
       "      <td>The Lancet</td>\n",
       "      <td>5508.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>5</th>\n",
       "      <td>10.3390/su12104295</td>\n",
       "      <td>12</td>\n",
       "      <td>An Integrated Planning Framework for Sustainab...</td>\n",
       "      <td>2020.0</td>\n",
       "      <td>Sustainability</td>\n",
       "      <td>1.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>6</th>\n",
       "      <td>10.1002/med.20081</td>\n",
       "      <td>12</td>\n",
       "      <td>The regulation of HIV‐1 transcription: Molecul...</td>\n",
       "      <td>2006.0</td>\n",
       "      <td>Med Res Rev</td>\n",
       "      <td>93.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>7</th>\n",
       "      <td>10.1056/nejmoa2001316</td>\n",
       "      <td>11</td>\n",
       "      <td>Early Transmission Dynamics in Wuhan, China, o...</td>\n",
       "      <td>2020.0</td>\n",
       "      <td>New England Journal of Medicine</td>\n",
       "      <td>2399.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>8</th>\n",
       "      <td>10.3390/v11020174</td>\n",
       "      <td>11</td>\n",
       "      <td>Global Epidemiology of Bat Coronaviruses</td>\n",
       "      <td>2019.0</td>\n",
       "      <td>Viruses</td>\n",
       "      <td>39.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>9</th>\n",
       "      <td>10.1056/nejmoa2001191</td>\n",
       "      <td>11</td>\n",
       "      <td>First Case of 2019 Novel Coronavirus in the Un...</td>\n",
       "      <td>2020.0</td>\n",
       "      <td>New England Journal of Medicine</td>\n",
       "      <td>1127.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>10</th>\n",
       "      <td>10.1083/jcb.148.5.931</td>\n",
       "      <td>10</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>11</th>\n",
       "      <td>10.1038/s41586-020-2012-7</td>\n",
       "      <td>10</td>\n",
       "      <td>A pneumonia outbreak associated with a new cor...</td>\n",
       "      <td>2020.0</td>\n",
       "      <td>Nature</td>\n",
       "      <td>2115.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>12</th>\n",
       "      <td>10.1016/s2215-0366(19)30401-8</td>\n",
       "      <td>9</td>\n",
       "      <td>Cannabinoids for the treatment of mental disor...</td>\n",
       "      <td>2019.0</td>\n",
       "      <td>The lancet. Psychiatry</td>\n",
       "      <td>37.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>13</th>\n",
       "      <td>10.1128/jvi.06540-11</td>\n",
       "      <td>9</td>\n",
       "      <td>Discovery of seven novel Mammalian and avian c...</td>\n",
       "      <td>2012.0</td>\n",
       "      <td>Journal of virology</td>\n",
       "      <td>453.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>14</th>\n",
       "      <td>10.1038/s41591-020-0820-9</td>\n",
       "      <td>9</td>\n",
       "      <td>The proximal origin of SARS-CoV-2</td>\n",
       "      <td>2020.0</td>\n",
       "      <td>Nature Medicine</td>\n",
       "      <td>411.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>15</th>\n",
       "      <td>10.1001/jama.2016.17324</td>\n",
       "      <td>8</td>\n",
       "      <td>Prevalence of Depression, Depressive Symptoms,...</td>\n",
       "      <td>2016.0</td>\n",
       "      <td>JAMA</td>\n",
       "      <td>398.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>16</th>\n",
       "      <td>10.1016/s0140-6736(20)31180-6</td>\n",
       "      <td>8</td>\n",
       "      <td>Hydroxychloroquine or chloroquine with or with...</td>\n",
       "      <td>2020.0</td>\n",
       "      <td>The Lancet</td>\n",
       "      <td>84.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>17</th>\n",
       "      <td>10.1016/j.pnpbp.2006.01.008</td>\n",
       "      <td>8</td>\n",
       "      <td>Human brain evolution and the “Neuroevolutiona...</td>\n",
       "      <td>2006.0</td>\n",
       "      <td>Prog Neuropsychopharmacol Biol Psychiatry</td>\n",
       "      <td>63.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>18</th>\n",
       "      <td>10.1016/s0140-6736(20)30567-5</td>\n",
       "      <td>8</td>\n",
       "      <td>How will country-based mitigation measures inf...</td>\n",
       "      <td>2020.0</td>\n",
       "      <td>The Lancet</td>\n",
       "      <td>303.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>19</th>\n",
       "      <td>10.1086/511159</td>\n",
       "      <td>8</td>\n",
       "      <td>Infectious Diseases Society of America/America...</td>\n",
       "      <td>2007.0</td>\n",
       "      <td>Clin Infect Dis</td>\n",
       "      <td>3967.0</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "                              doi  wikipedia_id  \\\n",
       "0            10.3390/info11050263            67   \n",
       "1       10.1007/s00705-012-1299-6            18   \n",
       "2     10.1007/978-1-4939-2438-7_1            15   \n",
       "3                10.3390/v2081803            15   \n",
       "4   10.1016/s0140-6736(20)30183-5            13   \n",
       "5              10.3390/su12104295            12   \n",
       "6               10.1002/med.20081            12   \n",
       "7           10.1056/nejmoa2001316            11   \n",
       "8               10.3390/v11020174            11   \n",
       "9           10.1056/nejmoa2001191            11   \n",
       "10          10.1083/jcb.148.5.931            10   \n",
       "11      10.1038/s41586-020-2012-7            10   \n",
       "12  10.1016/s2215-0366(19)30401-8             9   \n",
       "13           10.1128/jvi.06540-11             9   \n",
       "14      10.1038/s41591-020-0820-9             9   \n",
       "15        10.1001/jama.2016.17324             8   \n",
       "16  10.1016/s0140-6736(20)31180-6             8   \n",
       "17    10.1016/j.pnpbp.2006.01.008             8   \n",
       "18  10.1016/s0140-6736(20)30567-5             8   \n",
       "19                 10.1086/511159             8   \n",
       "\n",
       "                                                title  publication_year  \\\n",
       "0   Modeling Popularity and Reliability of Sources...            2020.0   \n",
       "1   Ratification vote on taxonomic proposals to th...            2012.0   \n",
       "2   Coronaviruses: An Overview of Their Replicatio...            2015.0   \n",
       "3    Coronavirus Genomics and Bioinformatics Analysis            2010.0   \n",
       "4   Clinical features of patients infected with 20...            2020.0   \n",
       "5   An Integrated Planning Framework for Sustainab...            2020.0   \n",
       "6   The regulation of HIV‐1 transcription: Molecul...            2006.0   \n",
       "7   Early Transmission Dynamics in Wuhan, China, o...            2020.0   \n",
       "8            Global Epidemiology of Bat Coronaviruses            2019.0   \n",
       "9   First Case of 2019 Novel Coronavirus in the Un...            2020.0   \n",
       "10                                                NaN               NaN   \n",
       "11  A pneumonia outbreak associated with a new cor...            2020.0   \n",
       "12  Cannabinoids for the treatment of mental disor...            2019.0   \n",
       "13  Discovery of seven novel Mammalian and avian c...            2012.0   \n",
       "14                  The proximal origin of SARS-CoV-2            2020.0   \n",
       "15  Prevalence of Depression, Depressive Symptoms,...            2016.0   \n",
       "16  Hydroxychloroquine or chloroquine with or with...            2020.0   \n",
       "17  Human brain evolution and the “Neuroevolutiona...            2006.0   \n",
       "18  How will country-based mitigation measures inf...            2020.0   \n",
       "19  Infectious Diseases Society of America/America...            2007.0   \n",
       "\n",
       "                                      journal  times_cited  \n",
       "0                                 Information          1.0  \n",
       "1                                  Arch Virol        210.0  \n",
       "2                Methods in Molecular Biology        395.0  \n",
       "3                                     Viruses        143.0  \n",
       "4                                  The Lancet       5508.0  \n",
       "5                              Sustainability          1.0  \n",
       "6                                 Med Res Rev         93.0  \n",
       "7             New England Journal of Medicine       2399.0  \n",
       "8                                     Viruses         39.0  \n",
       "9             New England Journal of Medicine       1127.0  \n",
       "10                                        NaN          NaN  \n",
       "11                                     Nature       2115.0  \n",
       "12                     The lancet. Psychiatry         37.0  \n",
       "13                        Journal of virology        453.0  \n",
       "14                            Nature Medicine        411.0  \n",
       "15                                       JAMA        398.0  \n",
       "16                                 The Lancet         84.0  \n",
       "17  Prog Neuropsychopharmacol Biol Psychiatry         63.0  \n",
       "18                                 The Lancet        303.0  \n",
       "19                            Clin Infect Dis       3967.0  "
      ]
     },
     "execution_count": 144,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df_top_cited[[\"doi\",'wikipedia_id']].merge(df_joined, how=\"left\", right_on=\"doi\", left_on=\"doi\")[[\"doi\",\n",
    "    \"wikipedia_id\",\"title\",\"publication_year\",\"journal\",\"times_cited\"]]"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 138,
   "metadata": {},
   "outputs": [],
   "source": [
    "#print(df_top_cited[[\"doi\",'wikipedia_id']].merge(df_joined, how=\"left\", right_on=\"doi\", left_on=\"doi\")[[\n",
    "#    \"wikipedia_id\",\"doi\",\"title\",\"publication_year\",\"journal\",\"times_cited\"]].to_latex(index=False,bold_rows=True,caption=\"\",label=\"\"))"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 139,
   "metadata": {},
   "outputs": [],
   "source": [
    "# most citing Wiki articles"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 140,
   "metadata": {},
   "outputs": [],
   "source": [
    "df_top_citing = df_alt_to_wiki.groupby(\"wikipedia_id\").agg('count').sort_values('doi',ascending=False)[:20]\n",
    "df_top_citing.reset_index(inplace=True)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 141,
   "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>altmetric_id</th>\n",
       "      <th>wikipedia_id</th>\n",
       "      <th>title</th>\n",
       "      <th>page_url</th>\n",
       "      <th>lang</th>\n",
       "      <th>summary</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>62</td>\n",
       "      <td>201983</td>\n",
       "      <td>Coronavirus</td>\n",
       "      <td>http://en.wikipedia.org/?curid=201983</td>\n",
       "      <td>en</td>\n",
       "      <td>Coronaviruses are a group of related viruses t...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>59</td>\n",
       "      <td>62786585</td>\n",
       "      <td>Severe acute respiratory syndrome coronavirus 2</td>\n",
       "      <td>http://en.wikipedia.org/?curid=62786585</td>\n",
       "      <td>en</td>\n",
       "      <td>Severe acute respiratory syndrome coronavirus ...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>53</td>\n",
       "      <td>62750956</td>\n",
       "      <td>2019–20 Wuhan coronavirus outbreak</td>\n",
       "      <td>http://en.wikipedia.org/?curid=62750956</td>\n",
       "      <td>en</td>\n",
       "      <td>A new coronavirus, designated 2019-nCoV, was i...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>49</td>\n",
       "      <td>63030231</td>\n",
       "      <td>Coronavirus disease 2019</td>\n",
       "      <td>http://en.wikipedia.org/?curid=63030231</td>\n",
       "      <td>en</td>\n",
       "      <td>Common symptoms include fever, cough, fatigue,...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>39</td>\n",
       "      <td>63676463</td>\n",
       "      <td>2019–20 coronavirus pandemic/sandbox</td>\n",
       "      <td>http://en.wikipedia.org/?curid=63676463</td>\n",
       "      <td>en</td>\n",
       "      <td>The 2019–20 coronavirus pandemic is an ongoing...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>5</th>\n",
       "      <td>36</td>\n",
       "      <td>63430824</td>\n",
       "      <td>COVID-19 drug repurposing research</td>\n",
       "      <td>http://en.wikipedia.org/?curid=63430824</td>\n",
       "      <td>en</td>\n",
       "      <td>During the pandemic, several existing antivira...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>6</th>\n",
       "      <td>33</td>\n",
       "      <td>63895130</td>\n",
       "      <td>Paediatric multisystem inflammatory syndrome</td>\n",
       "      <td>http://en.wikipedia.org/?curid=63895130</td>\n",
       "      <td>en</td>\n",
       "      <td>Paediatric multisystem inflammatory syndrome (...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>7</th>\n",
       "      <td>32</td>\n",
       "      <td>211547</td>\n",
       "      <td>Severe acute respiratory syndrome-related coro...</td>\n",
       "      <td>http://en.wikipedia.org/?curid=211547</td>\n",
       "      <td>en</td>\n",
       "      <td>Severe acute respiratory syndrome-related coro...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>8</th>\n",
       "      <td>31</td>\n",
       "      <td>63319438</td>\n",
       "      <td>COVID-19 vaccine</td>\n",
       "      <td>http://en.wikipedia.org/?curid=63319438</td>\n",
       "      <td>en</td>\n",
       "      <td>A COVID-19 vaccine is a hypothetical vaccine a...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>9</th>\n",
       "      <td>30</td>\n",
       "      <td>63435931</td>\n",
       "      <td>COVID-19 drug development</td>\n",
       "      <td>http://en.wikipedia.org/?curid=63435931</td>\n",
       "      <td>en</td>\n",
       "      <td>COVID‑19 drug development is the research proc...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>10</th>\n",
       "      <td>34</td>\n",
       "      <td>39532251</td>\n",
       "      <td>Middle East respiratory syndrome</td>\n",
       "      <td>http://en.wikipedia.org/?curid=39532251</td>\n",
       "      <td>en</td>\n",
       "      <td>For PCR testing the WHO recommends obtaining s...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>11</th>\n",
       "      <td>28</td>\n",
       "      <td>19572217</td>\n",
       "      <td>Influenza</td>\n",
       "      <td>http://en.wikipedia.org/?curid=19572217</td>\n",
       "      <td>en</td>\n",
       "      <td>Influenza, commonly known as \"the flu\", is an ...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>12</th>\n",
       "      <td>25</td>\n",
       "      <td>63204759</td>\n",
       "      <td>COVID-19 testing</td>\n",
       "      <td>http://en.wikipedia.org/?curid=63204759</td>\n",
       "      <td>en</td>\n",
       "      <td>Due to limited testing, as of March 2020 no co...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>13</th>\n",
       "      <td>23</td>\n",
       "      <td>2717089</td>\n",
       "      <td>Angiotensin-converting enzyme 2</td>\n",
       "      <td>http://en.wikipedia.org/?curid=2717089</td>\n",
       "      <td>en</td>\n",
       "      <td>Angiotensin converting enzyme 2 (ACE2) is an e...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>14</th>\n",
       "      <td>24</td>\n",
       "      <td>22693252</td>\n",
       "      <td>Feline coronavirus</td>\n",
       "      <td>http://en.wikipedia.org/?curid=22693252</td>\n",
       "      <td>en</td>\n",
       "      <td>Feline coronavirus (FCoV) is a positive-strand...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>15</th>\n",
       "      <td>22</td>\n",
       "      <td>64144585</td>\n",
       "      <td>Management of COVID-19</td>\n",
       "      <td>http://en.wikipedia.org/?curid=64144585</td>\n",
       "      <td>en</td>\n",
       "      <td>People are managed with supportive care, which...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>16</th>\n",
       "      <td>22</td>\n",
       "      <td>4354646</td>\n",
       "      <td>Emergent virus</td>\n",
       "      <td>http://en.wikipedia.org/?curid=4354646</td>\n",
       "      <td>en</td>\n",
       "      <td>An emergent virus is a virus that either has n...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>17</th>\n",
       "      <td>21</td>\n",
       "      <td>10849236</td>\n",
       "      <td>Antibody-dependent enhancement</td>\n",
       "      <td>http://en.wikipedia.org/?curid=10849236</td>\n",
       "      <td>en</td>\n",
       "      <td>Antibody-dependent enhancement (ADE), sometime...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>18</th>\n",
       "      <td>20</td>\n",
       "      <td>196741</td>\n",
       "      <td>Severe acute respiratory syndrome</td>\n",
       "      <td>http://en.wikipedia.org/?curid=196741</td>\n",
       "      <td>en</td>\n",
       "      <td>Severe acute respiratory syndrome (SARS) is a ...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>19</th>\n",
       "      <td>20</td>\n",
       "      <td>64144627</td>\n",
       "      <td>Prognosis of COVID-19</td>\n",
       "      <td>http://en.wikipedia.org/?curid=64144627</td>\n",
       "      <td>en</td>\n",
       "      <td>The severity of COVID‑19 varies. The disease m...</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "    altmetric_id wikipedia_id  \\\n",
       "0             62       201983   \n",
       "1             59     62786585   \n",
       "2             53     62750956   \n",
       "3             49     63030231   \n",
       "4             39     63676463   \n",
       "5             36     63430824   \n",
       "6             33     63895130   \n",
       "7             32       211547   \n",
       "8             31     63319438   \n",
       "9             30     63435931   \n",
       "10            34     39532251   \n",
       "11            28     19572217   \n",
       "12            25     63204759   \n",
       "13            23      2717089   \n",
       "14            24     22693252   \n",
       "15            22     64144585   \n",
       "16            22      4354646   \n",
       "17            21     10849236   \n",
       "18            20       196741   \n",
       "19            20     64144627   \n",
       "\n",
       "                                                title  \\\n",
       "0                                         Coronavirus   \n",
       "1     Severe acute respiratory syndrome coronavirus 2   \n",
       "2                  2019–20 Wuhan coronavirus outbreak   \n",
       "3                            Coronavirus disease 2019   \n",
       "4                2019–20 coronavirus pandemic/sandbox   \n",
       "5                  COVID-19 drug repurposing research   \n",
       "6        Paediatric multisystem inflammatory syndrome   \n",
       "7   Severe acute respiratory syndrome-related coro...   \n",
       "8                                    COVID-19 vaccine   \n",
       "9                           COVID-19 drug development   \n",
       "10                   Middle East respiratory syndrome   \n",
       "11                                          Influenza   \n",
       "12                                   COVID-19 testing   \n",
       "13                    Angiotensin-converting enzyme 2   \n",
       "14                                 Feline coronavirus   \n",
       "15                             Management of COVID-19   \n",
       "16                                     Emergent virus   \n",
       "17                     Antibody-dependent enhancement   \n",
       "18                  Severe acute respiratory syndrome   \n",
       "19                              Prognosis of COVID-19   \n",
       "\n",
       "                                   page_url lang  \\\n",
       "0     http://en.wikipedia.org/?curid=201983   en   \n",
       "1   http://en.wikipedia.org/?curid=62786585   en   \n",
       "2   http://en.wikipedia.org/?curid=62750956   en   \n",
       "3   http://en.wikipedia.org/?curid=63030231   en   \n",
       "4   http://en.wikipedia.org/?curid=63676463   en   \n",
       "5   http://en.wikipedia.org/?curid=63430824   en   \n",
       "6   http://en.wikipedia.org/?curid=63895130   en   \n",
       "7     http://en.wikipedia.org/?curid=211547   en   \n",
       "8   http://en.wikipedia.org/?curid=63319438   en   \n",
       "9   http://en.wikipedia.org/?curid=63435931   en   \n",
       "10  http://en.wikipedia.org/?curid=39532251   en   \n",
       "11  http://en.wikipedia.org/?curid=19572217   en   \n",
       "12  http://en.wikipedia.org/?curid=63204759   en   \n",
       "13   http://en.wikipedia.org/?curid=2717089   en   \n",
       "14  http://en.wikipedia.org/?curid=22693252   en   \n",
       "15  http://en.wikipedia.org/?curid=64144585   en   \n",
       "16   http://en.wikipedia.org/?curid=4354646   en   \n",
       "17  http://en.wikipedia.org/?curid=10849236   en   \n",
       "18    http://en.wikipedia.org/?curid=196741   en   \n",
       "19  http://en.wikipedia.org/?curid=64144627   en   \n",
       "\n",
       "                                              summary  \n",
       "0   Coronaviruses are a group of related viruses t...  \n",
       "1   Severe acute respiratory syndrome coronavirus ...  \n",
       "2   A new coronavirus, designated 2019-nCoV, was i...  \n",
       "3   Common symptoms include fever, cough, fatigue,...  \n",
       "4   The 2019–20 coronavirus pandemic is an ongoing...  \n",
       "5   During the pandemic, several existing antivira...  \n",
       "6   Paediatric multisystem inflammatory syndrome (...  \n",
       "7   Severe acute respiratory syndrome-related coro...  \n",
       "8   A COVID-19 vaccine is a hypothetical vaccine a...  \n",
       "9   COVID‑19 drug development is the research proc...  \n",
       "10  For PCR testing the WHO recommends obtaining s...  \n",
       "11  Influenza, commonly known as \"the flu\", is an ...  \n",
       "12  Due to limited testing, as of March 2020 no co...  \n",
       "13  Angiotensin converting enzyme 2 (ACE2) is an e...  \n",
       "14  Feline coronavirus (FCoV) is a positive-strand...  \n",
       "15  People are managed with supportive care, which...  \n",
       "16  An emergent virus is a virus that either has n...  \n",
       "17  Antibody-dependent enhancement (ADE), sometime...  \n",
       "18  Severe acute respiratory syndrome (SARS) is a ...  \n",
       "19  The severity of COVID‑19 varies. The disease m...  "
      ]
     },
     "execution_count": 141,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df_top_citing[[\"altmetric_id\",'wikipedia_id']].merge(df_wikipedia, how=\"left\", right_on=\"wikipedia_id\", left_on=\"wikipedia_id\")[[\"altmetric_id\",\n",
    "    \"wikipedia_id\",\"title\",\"page_url\",\"lang\",\"summary\"]]"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 143,
   "metadata": {},
   "outputs": [],
   "source": [
    "#print(df_top_citing[[\"altmetric_id\",'wikipedia_id']].merge(df_wikipedia, how=\"left\", right_on=\"wikipedia_id\", left_on=\"wikipedia_id\")[[\"altmetric_id\",\n",
    "#    \"wikipedia_id\",\"title\",\"lang\"]].to_latex(index=False,bold_rows=True))"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "#### Finish merges and save"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 80,
   "metadata": {},
   "outputs": [],
   "source": [
    "df_altmetrics.pmid = pd.to_numeric(df_altmetrics.pmid)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 81,
   "metadata": {},
   "outputs": [],
   "source": [
    "## join with Altmetrics\n",
    "\n",
    "df_tmp_a = df_altmetrics[pd.isnull(df_altmetrics.doi)] \n",
    "df_tmp_j = df_joined[pd.isnull(df_joined.doi)] \n",
    "df_joined_all = df_joined[pd.notnull(df_joined.doi)].merge(df_altmetrics[pd.notnull(df_altmetrics.doi)], suffixes=('','_y'), how=\"left\", left_on=\"doi\", right_on=\"doi\")\n",
    "df_joined_all.drop(columns=['pmid_y', 'year_y', 'title_y'],inplace=True)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 82,
   "metadata": {},
   "outputs": [],
   "source": [
    "df_joined_tt = df_tmp_j.merge(df_tmp_a, how=\"left\", suffixes=('','_y'), left_on=\"pmid\", right_on=\"pmid\")\n",
    "df_joined_tt.drop(columns=[\"doi_y\", 'year_y', 'title_y'],inplace=True)\n",
    "df_joined_all = pd.concat([df_joined_all,df_joined_tt])\n",
    "df_joined_all.drop_duplicates(\"pub_id\",inplace=True)\n",
    "df_joined_all.reset_index(inplace=True,drop=True)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 83,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "(141224, 42)"
      ]
     },
     "execution_count": 83,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df_joined_all.shape"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 84,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "Index(['pub_id', 'title', 'abstract', 'publication_year', 'publication_month',\n",
       "       'journal', 'volume', 'issue', 'pages', 'doi', 'pmid', 'pmcid',\n",
       "       'dimensions_id', 'arxiv_id', 'timestamp', 'lang', 'id', 'altmetric_id',\n",
       "       'year', 'month', 'publication_date', 'publication_type', 'issn',\n",
       "       'times_cited', 'relative_citation_ratio', 'for_top', 'for_bottom',\n",
       "       'altmetric_id_y', 'counts_mendeley', 'counts_news', 'counts_blogs',\n",
       "       'counts_facebook', 'counts_policy', 'counts_wikipedia',\n",
       "       'counts_twitter_count', 'counts_twitter_unique', 'counts_total',\n",
       "       'altmetric_score', 'member_of_the_public', 'researcher', 'practitioner',\n",
       "       'science_communicator'],\n",
       "      dtype='object')"
      ]
     },
     "execution_count": 84,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df_joined_all.columns"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 85,
   "metadata": {},
   "outputs": [],
   "source": [
    "df_joined_all.drop(columns=[\"dimensions_id\",\"year\",\"month\",\"altmetric_id\",\"timestamp\"], inplace=True)\n",
    "df_joined_all.rename(columns={\"id\":\"dimensions_id\",\"altmetric_id_y\":\"altmetric_id\",\"counts_twitter_count\":\"counts_twitter\"}, inplace=True)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 86,
   "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>pub_id</th>\n",
       "      <th>title</th>\n",
       "      <th>abstract</th>\n",
       "      <th>publication_year</th>\n",
       "      <th>publication_month</th>\n",
       "      <th>journal</th>\n",
       "      <th>volume</th>\n",
       "      <th>issue</th>\n",
       "      <th>pages</th>\n",
       "      <th>doi</th>\n",
       "      <th>...</th>\n",
       "      <th>counts_policy</th>\n",
       "      <th>counts_wikipedia</th>\n",
       "      <th>counts_twitter</th>\n",
       "      <th>counts_twitter_unique</th>\n",
       "      <th>counts_total</th>\n",
       "      <th>altmetric_score</th>\n",
       "      <th>member_of_the_public</th>\n",
       "      <th>researcher</th>\n",
       "      <th>practitioner</th>\n",
       "      <th>science_communicator</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>28533</th>\n",
       "      <td>29534</td>\n",
       "      <td>Chapter 11 Detection of Analytes on Arrays/Mic...</td>\n",
       "      <td>Publisher Summary Microarrays/arrays/DNA chips...</td>\n",
       "      <td>2011.0</td>\n",
       "      <td>12.0</td>\n",
       "      <td>Handbook of Biosensors and Biosensor Kinetics</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>10.1016/b978-0-444-53262-6.00011-5</td>\n",
       "      <td>...</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "<p>1 rows × 37 columns</p>\n",
       "</div>"
      ],
      "text/plain": [
       "       pub_id                                              title  \\\n",
       "28533   29534  Chapter 11 Detection of Analytes on Arrays/Mic...   \n",
       "\n",
       "                                                abstract  publication_year  \\\n",
       "28533  Publisher Summary Microarrays/arrays/DNA chips...            2011.0   \n",
       "\n",
       "       publication_month                                        journal  \\\n",
       "28533               12.0  Handbook of Biosensors and Biosensor Kinetics   \n",
       "\n",
       "      volume issue pages                                 doi  ...  \\\n",
       "28533    NaN   NaN   NaN  10.1016/b978-0-444-53262-6.00011-5  ...   \n",
       "\n",
       "       counts_policy counts_wikipedia counts_twitter counts_twitter_unique  \\\n",
       "28533            NaN              NaN            NaN                   NaN   \n",
       "\n",
       "      counts_total altmetric_score member_of_the_public researcher  \\\n",
       "28533          NaN             NaN                  NaN        NaN   \n",
       "\n",
       "       practitioner  science_communicator  \n",
       "28533           NaN                   NaN  \n",
       "\n",
       "[1 rows x 37 columns]"
      ]
     },
     "execution_count": 86,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df_joined_all[df_joined_all.pub_id==29534]"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 87,
   "metadata": {},
   "outputs": [],
   "source": [
    "df_joined_all[\"in_wikipedia\"] = df_joined_all[\"counts_wikipedia\"]>0"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 88,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "(141224, 38)"
      ]
     },
     "execution_count": 88,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df_joined_all.shape"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 89,
   "metadata": {},
   "outputs": [],
   "source": [
    "df_posted_on_first = df_alt_to_wiki[[\"altmetric_id\",\"posted_on_year\"]].groupby(\"altmetric_id\").agg(min).reset_index()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 90,
   "metadata": {},
   "outputs": [],
   "source": [
    "df_joined_all = df_joined_all.merge(df_posted_on_first, how=\"left\", left_on=\"altmetric_id\", right_on=\"altmetric_id\")"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 91,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "0.019190070710088637"
      ]
     },
     "execution_count": 91,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df_joined_all[df_joined_all.in_wikipedia==True].shape[0]/df_meta.shape[0]"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 92,
   "metadata": {},
   "outputs": [],
   "source": [
    "# save to disk\n",
    "\n",
    "df_joined_all.to_csv(\"data/df_joined_all.csv\", compression=\"gzip\", index=False)\n",
    "df_meta.to_csv(\"data/df_meta.csv\", compression=\"gzip\", index=False)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### Analysis of time to be cited from publication"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 93,
   "metadata": {},
   "outputs": [],
   "source": [
    "# average time from publication to citations\n",
    "\n",
    "df_posted_on_first = df_alt_to_wiki[[\"altmetric_id\",\"posted_on_year\",\"posted_on_month\"]].groupby(\"altmetric_id\").agg(min).reset_index()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 94,
   "metadata": {},
   "outputs": [],
   "source": [
    "df_posted_on_first = df_posted_on_first.merge(df_joined_all, how=\"left\", right_on=\"altmetric_id\", left_on=\"altmetric_id\")"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 95,
   "metadata": {},
   "outputs": [],
   "source": [
    "df_posted_on_first[\"time_from_pub_to_wiki\"] = ((df_posted_on_first[\"posted_on_year_x\"]*12)+df_posted_on_first[\"posted_on_month\"]) - ((df_posted_on_first[\"publication_year\"]*12)+df_posted_on_first[\"publication_month\"])"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 96,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 432x288 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "sns.distplot(df_posted_on_first[\"time_from_pub_to_wiki\"], norm_hist=False, kde=False)\n",
    "plt.xlabel(\"Number of months from publication to first citation in Wikipedia\",fontsize=15)\n",
    "plt.ylabel(\"Count\",fontsize=15)\n",
    "plt.tick_params(labelsize=12)\n",
    "plt.tight_layout()\n",
    "plt.savefig(\"figures/nb1_time_from_pub_to_wiki_hist.pdf\")"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 97,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 432x288 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "sns.distplot(df_posted_on_first[df_posted_on_first.publication_year==2020][\"time_from_pub_to_wiki\"], color=\"green\", kde=True, norm_hist=True, kde_kws={\"shade\": True}, hist=False, label=\"Published in 2020\")\n",
    "sns.distplot(df_posted_on_first[(df_posted_on_first.publication_year<2020) & (df_posted_on_first.publication_year>1999)][\"time_from_pub_to_wiki\"], color=\"blue\", kde=True, norm_hist=True, kde_kws={\"shade\": True}, hist=False, label=\"Published before 2020\")\n",
    "plt.legend(fontsize=15)\n",
    "plt.xlabel(\"Number of months from publication to first citation in Wikipedia\",fontsize=15)\n",
    "plt.ylabel(\"Proportion\",fontsize=15)\n",
    "plt.tick_params(labelsize=12)\n",
    "plt.tight_layout()\n",
    "plt.savefig(\"figures/nb1_time_from_pub_to_wiki_hist_normed.pdf\")"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 98,
   "metadata": {},
   "outputs": [],
   "source": [
    "#df_posted_on_first[[\"time_from_pub_to_wiki\",\"posted_on_year_x\",\"posted_on_month\",\"publication_year\",\"publication_month\",\"in_wikipedia\"]]"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 127,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 576x360 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "from_year = 2001\n",
    "until_year = 2020\n",
    "posted_on_limit = 2020\n",
    "\n",
    "plt.figure(figsize=(8,5))\n",
    "sns.scatterplot(x=\"publication_year\", y=\"time_from_pub_to_wiki\", data=df_posted_on_first[(df_posted_on_first.publication_year>=from_year)&(df_posted_on_first.publication_year<=until_year)&(df_posted_on_first.posted_on_year_x<=posted_on_limit)][[\"publication_year\",\"time_from_pub_to_wiki\"]].groupby(\"publication_year\").agg(np.median).reset_index(), s=70, color=\"skyblue\", label=\"median\")\n",
    "b = sns.scatterplot(x=\"publication_year\", y=\"time_from_pub_to_wiki\", data=df_posted_on_first[(df_posted_on_first.publication_year>=from_year)&(df_posted_on_first.publication_year<=until_year)&(df_posted_on_first.posted_on_year_x<=posted_on_limit)][[\"publication_year\",\"time_from_pub_to_wiki\"]].groupby(\"publication_year\").agg(np.mean).reset_index(), s=70, color=\"red\", label=\"mean\")\n",
    "b.set_xticklabels(b.get_xticklabels(), rotation=45)\n",
    "plt.legend(fontsize=15)\n",
    "plt.ylabel(\"Number of months from publication\\nto a first citation in Wikipedia\",fontsize=16)\n",
    "plt.xlabel(\"Publication year\",fontsize=16)\n",
    "plt.xticks(range(from_year,until_year+1))\n",
    "plt.tick_params(labelsize=12)\n",
    "plt.axhline(y=0.0, color='black', linestyle='-', alpha=0.5)\n",
    "ax = plt.gca()\n",
    "ax.grid(True, axis='x')\n",
    "ax.xaxis.set_major_formatter(FuncFormatter(lambda x, _: int(x)))\n",
    "#plt.title(\"Number of months elapsed from publication to the first Wikipedia citation\", fontsize=17)\n",
    "plt.tight_layout()\n",
    "plt.savefig(\"figures/nb1_time_from_pub_to_wiki_avg_per_year.pdf\")"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 124,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 432x288 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "from_year = 2001\n",
    "until_year = 2020\n",
    "posted_on_limit = 2020\n",
    "\n",
    "#fig, ax = plt.subplots(figsize=(8,5))\n",
    "#fig, ax = plt.subplots()\n",
    "#sns.scatterplot(x=\"publication_year\", y=\"time_from_pub_to_wiki\", data=df_posted_on_first[(df_posted_on_first.publication_year>=from_year)&(df_posted_on_first.publication_year<=until_year)&(df_posted_on_first.posted_on_year_x<=posted_on_limit)][[\"publication_year\",\"time_from_pub_to_wiki\"]].groupby(\"publication_year\").agg(np.median).reset_index(), s=70, color=\"skyblue\", label=\"median\")\n",
    "#sns.violinplot(x=\"day\", y=\"total_bill\", hue=\"sex\",\n",
    "#                    data=tips, palette=\"Set2\", split=True,\n",
    "#                    scale=\"count\", inner=\"stick\")\n",
    "#a = sns.scatterplot(x=\"publication_year\", y=\"time_from_pub_to_wiki\", data=df_posted_on_first[(df_posted_on_first.publication_year>=from_year)&(df_posted_on_first.publication_year<=until_year)&(df_posted_on_first.posted_on_year_x<=posted_on_limit)][[\"publication_year\",\"time_from_pub_to_wiki\"]].groupby(\"publication_year\").agg(np.mean).reset_index(), s=70, color=\"red\", ax=ax)\n",
    "#ax2 = ax.twinx()\n",
    "#b = sns.catplot(x=\"publication_year\", y=\"time_from_pub_to_wiki\", data=df_posted_on_first[(df_posted_on_first.publication_year>=from_year)&(df_posted_on_first.publication_year<=until_year)&(df_posted_on_first.posted_on_year_x<=posted_on_limit)][[\"publication_year\",\"time_from_pub_to_wiki\"]], color=\"gray\", s=3)\n",
    "b = sns.violinplot(x=\"publication_year\", y=\"time_from_pub_to_wiki\", data=df_posted_on_first[(df_posted_on_first.publication_year>=from_year)&(df_posted_on_first.publication_year<=until_year)&(df_posted_on_first.posted_on_year_x<=posted_on_limit)][[\"publication_year\",\"time_from_pub_to_wiki\"]], color=\"skyblue\", s=3)\n",
    "b.set_xticklabels(range(from_year,until_year+1),rotation=45)\n",
    "plt.ylabel(\"Number of months\",fontsize=16)\n",
    "plt.xlabel(\"Publication year\",fontsize=16)\n",
    "plt.tick_params(labelsize=12)\n",
    "plt.axhline(y=0.0, color='black', linestyle='-', alpha=0.3)\n",
    "plt.tight_layout()\n",
    "plt.savefig(\"figures/nb1_time_from_pub_to_wiki_avg_per_year_violin.pdf\")"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 104,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "(72795, 16)"
      ]
     },
     "execution_count": 104,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df_meta[df_meta.publication_year==2020].shape"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 105,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
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       "\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_year</th>\n",
       "      <th>time_from_pub_to_wiki</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>1968.0</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>1970.0</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>1978.0</td>\n",
       "      <td>422.000000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>1979.0</td>\n",
       "      <td>491.000000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>1982.0</td>\n",
       "      <td>316.000000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>5</th>\n",
       "      <td>1983.0</td>\n",
       "      <td>435.000000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>6</th>\n",
       "      <td>1984.0</td>\n",
       "      <td>294.000000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>7</th>\n",
       "      <td>1985.0</td>\n",
       "      <td>358.000000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>8</th>\n",
       "      <td>1986.0</td>\n",
       "      <td>400.000000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>9</th>\n",
       "      <td>1987.0</td>\n",
       "      <td>310.000000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>10</th>\n",
       "      <td>1988.0</td>\n",
       "      <td>337.000000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>11</th>\n",
       "      <td>1989.0</td>\n",
       "      <td>359.000000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>12</th>\n",
       "      <td>1990.0</td>\n",
       "      <td>217.000000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>13</th>\n",
       "      <td>1991.0</td>\n",
       "      <td>295.333333</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>14</th>\n",
       "      <td>1992.0</td>\n",
       "      <td>204.666667</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>15</th>\n",
       "      <td>1993.0</td>\n",
       "      <td>260.750000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>16</th>\n",
       "      <td>1994.0</td>\n",
       "      <td>275.000000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>17</th>\n",
       "      <td>1995.0</td>\n",
       "      <td>225.000000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>18</th>\n",
       "      <td>1996.0</td>\n",
       "      <td>141.500000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>19</th>\n",
       "      <td>1997.0</td>\n",
       "      <td>180.666667</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>20</th>\n",
       "      <td>1998.0</td>\n",
       "      <td>152.250000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>21</th>\n",
       "      <td>1999.0</td>\n",
       "      <td>206.000000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>22</th>\n",
       "      <td>2000.0</td>\n",
       "      <td>155.333333</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>23</th>\n",
       "      <td>2001.0</td>\n",
       "      <td>165.000000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>24</th>\n",
       "      <td>2002.0</td>\n",
       "      <td>137.636364</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>25</th>\n",
       "      <td>2003.0</td>\n",
       "      <td>119.423077</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>26</th>\n",
       "      <td>2004.0</td>\n",
       "      <td>120.514706</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>27</th>\n",
       "      <td>2005.0</td>\n",
       "      <td>96.050633</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>28</th>\n",
       "      <td>2006.0</td>\n",
       "      <td>81.177215</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>29</th>\n",
       "      <td>2007.0</td>\n",
       "      <td>61.308824</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>30</th>\n",
       "      <td>2008.0</td>\n",
       "      <td>71.944444</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>31</th>\n",
       "      <td>2009.0</td>\n",
       "      <td>59.558140</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>32</th>\n",
       "      <td>2010.0</td>\n",
       "      <td>59.608696</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>33</th>\n",
       "      <td>2011.0</td>\n",
       "      <td>57.257732</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>34</th>\n",
       "      <td>2012.0</td>\n",
       "      <td>40.577982</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>35</th>\n",
       "      <td>2013.0</td>\n",
       "      <td>40.841584</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>36</th>\n",
       "      <td>2014.0</td>\n",
       "      <td>31.115702</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>37</th>\n",
       "      <td>2015.0</td>\n",
       "      <td>28.037383</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>38</th>\n",
       "      <td>2016.0</td>\n",
       "      <td>26.307018</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>39</th>\n",
       "      <td>2017.0</td>\n",
       "      <td>21.573171</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>40</th>\n",
       "      <td>2018.0</td>\n",
       "      <td>14.823529</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>41</th>\n",
       "      <td>2019.0</td>\n",
       "      <td>7.177083</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>42</th>\n",
       "      <td>2020.0</td>\n",
       "      <td>0.019444</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "    publication_year  time_from_pub_to_wiki\n",
       "0             1968.0                    NaN\n",
       "1             1970.0                    NaN\n",
       "2             1978.0             422.000000\n",
       "3             1979.0             491.000000\n",
       "4             1982.0             316.000000\n",
       "5             1983.0             435.000000\n",
       "6             1984.0             294.000000\n",
       "7             1985.0             358.000000\n",
       "8             1986.0             400.000000\n",
       "9             1987.0             310.000000\n",
       "10            1988.0             337.000000\n",
       "11            1989.0             359.000000\n",
       "12            1990.0             217.000000\n",
       "13            1991.0             295.333333\n",
       "14            1992.0             204.666667\n",
       "15            1993.0             260.750000\n",
       "16            1994.0             275.000000\n",
       "17            1995.0             225.000000\n",
       "18            1996.0             141.500000\n",
       "19            1997.0             180.666667\n",
       "20            1998.0             152.250000\n",
       "21            1999.0             206.000000\n",
       "22            2000.0             155.333333\n",
       "23            2001.0             165.000000\n",
       "24            2002.0             137.636364\n",
       "25            2003.0             119.423077\n",
       "26            2004.0             120.514706\n",
       "27            2005.0              96.050633\n",
       "28            2006.0              81.177215\n",
       "29            2007.0              61.308824\n",
       "30            2008.0              71.944444\n",
       "31            2009.0              59.558140\n",
       "32            2010.0              59.608696\n",
       "33            2011.0              57.257732\n",
       "34            2012.0              40.577982\n",
       "35            2013.0              40.841584\n",
       "36            2014.0              31.115702\n",
       "37            2015.0              28.037383\n",
       "38            2016.0              26.307018\n",
       "39            2017.0              21.573171\n",
       "40            2018.0              14.823529\n",
       "41            2019.0               7.177083\n",
       "42            2020.0               0.019444"
      ]
     },
     "execution_count": 105,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df_posted_on_first[[\"publication_year\",\"time_from_pub_to_wiki\"]].groupby(\"publication_year\").agg(np.mean).reset_index()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 106,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
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       "      <th>altmetric_id</th>\n",
       "      <th>posted_on_year_x</th>\n",
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       "      <th>pub_id</th>\n",
       "      <th>title</th>\n",
       "      <th>abstract</th>\n",
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       "      <th>journal</th>\n",
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       "  <tbody>\n",
       "    <tr>\n",
       "      <th>1203</th>\n",
       "      <td>3397958</td>\n",
       "      <td>2012</td>\n",
       "      <td>11</td>\n",
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       "      <td>In order to contain the COVID-19 pandemic, sev...</td>\n",
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       "      <td>5.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
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       "      <td>2012.0</td>\n",
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       "    <tr>\n",
       "      <th>2746</th>\n",
       "      <td>74005599</td>\n",
       "      <td>2020</td>\n",
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       "      <td>76827.0</td>\n",
       "      <td>Pneumonia of Unknown Etiology in Wuhan, China:...</td>\n",
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       "      <td>3.0</td>\n",
       "      <td>Journal of Travel Medicine</td>\n",
       "      <td>27</td>\n",
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       "      <td>535.0</td>\n",
       "      <td>623.0</td>\n",
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       "      <td>55.0</td>\n",
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       "      <th>2747</th>\n",
       "      <td>74006487</td>\n",
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       "      <td>2</td>\n",
       "      <td>32956.0</td>\n",
       "      <td>Comparison of broad-spectrum antiviral activit...</td>\n",
       "      <td>Rocaglates, a class of natural compounds isola...</td>\n",
       "      <td>2020.0</td>\n",
       "      <td>3.0</td>\n",
       "      <td>Antiviral Research</td>\n",
       "      <td>175</td>\n",
       "      <td>...</td>\n",
       "      <td>10.0</td>\n",
       "      <td>22.0</td>\n",
       "      <td>69.750</td>\n",
       "      <td>8.0</td>\n",
       "      <td>2.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>True</td>\n",
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       "    <tr>\n",
       "      <th>2771</th>\n",
       "      <td>74464078</td>\n",
       "      <td>2020</td>\n",
       "      <td>1</td>\n",
       "      <td>57176.0</td>\n",
       "      <td>Clinical features of patients infected with 20...</td>\n",
       "      <td>BACKGROUND: A recent cluster of pneumonia case...</td>\n",
       "      <td>2020.0</td>\n",
       "      <td>2.0</td>\n",
       "      <td>The Lancet</td>\n",
       "      <td>395</td>\n",
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       "      <td>15126.0</td>\n",
       "      <td>20644.0</td>\n",
       "      <td>14257.298</td>\n",
       "      <td>13709.0</td>\n",
       "      <td>688.0</td>\n",
       "      <td>511.0</td>\n",
       "      <td>211.0</td>\n",
       "      <td>True</td>\n",
       "      <td>2020.0</td>\n",
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       "      <th>2772</th>\n",
       "      <td>74464103</td>\n",
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       "      <td>57170.0</td>\n",
       "      <td>A familial cluster of pneumonia associated wit...</td>\n",
       "      <td>BACKGROUND: An ongoing outbreak of pneumonia a...</td>\n",
       "      <td>2020.0</td>\n",
       "      <td>2.0</td>\n",
       "      <td>The Lancet</td>\n",
       "      <td>395</td>\n",
       "      <td>...</td>\n",
       "      <td>4483.0</td>\n",
       "      <td>5339.0</td>\n",
       "      <td>4632.252</td>\n",
       "      <td>4073.0</td>\n",
       "      <td>216.0</td>\n",
       "      <td>147.0</td>\n",
       "      <td>45.0</td>\n",
       "      <td>True</td>\n",
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       "      <td>-1.0</td>\n",
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       "    <tr>\n",
       "      <th>...</th>\n",
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       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
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       "      <th>3543</th>\n",
       "      <td>82704653</td>\n",
       "      <td>2020</td>\n",
       "      <td>5</td>\n",
       "      <td>66352.0</td>\n",
       "      <td>Tail risk of contagious diseases</td>\n",
       "      <td>The COVID-19 pandemic has been a sobering remi...</td>\n",
       "      <td>2020.0</td>\n",
       "      <td>6.0</td>\n",
       "      <td>Nature Physics</td>\n",
       "      <td>16</td>\n",
       "      <td>...</td>\n",
       "      <td>698.0</td>\n",
       "      <td>788.0</td>\n",
       "      <td>508.662</td>\n",
       "      <td>563.0</td>\n",
       "      <td>106.0</td>\n",
       "      <td>17.0</td>\n",
       "      <td>12.0</td>\n",
       "      <td>True</td>\n",
       "      <td>2020.0</td>\n",
       "      <td>-1.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3554</th>\n",
       "      <td>82970555</td>\n",
       "      <td>2020</td>\n",
       "      <td>5</td>\n",
       "      <td>70487.0</td>\n",
       "      <td>Studies on the mechanism of general anesthesia</td>\n",
       "      <td>Inhaled anesthetics are a chemically diverse c...</td>\n",
       "      <td>2020.0</td>\n",
       "      <td>6.0</td>\n",
       "      <td>Proceedings of the National Academy of Science...</td>\n",
       "      <td>117</td>\n",
       "      <td>...</td>\n",
       "      <td>1335.0</td>\n",
       "      <td>1435.0</td>\n",
       "      <td>737.350</td>\n",
       "      <td>1252.0</td>\n",
       "      <td>55.0</td>\n",
       "      <td>22.0</td>\n",
       "      <td>6.0</td>\n",
       "      <td>True</td>\n",
       "      <td>2020.0</td>\n",
       "      <td>-1.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3557</th>\n",
       "      <td>83016981</td>\n",
       "      <td>2020</td>\n",
       "      <td>6</td>\n",
       "      <td>111617.0</td>\n",
       "      <td>Population vulnerability to COVID-19 in Europe...</td>\n",
       "      <td>Background: Evidence has emerged showing that ...</td>\n",
       "      <td>2020.0</td>\n",
       "      <td>12.0</td>\n",
       "      <td>Archives of Public Health</td>\n",
       "      <td>78</td>\n",
       "      <td>...</td>\n",
       "      <td>34.0</td>\n",
       "      <td>54.0</td>\n",
       "      <td>57.850</td>\n",
       "      <td>16.0</td>\n",
       "      <td>8.0</td>\n",
       "      <td>9.0</td>\n",
       "      <td>1.0</td>\n",
       "      <td>True</td>\n",
       "      <td>2020.0</td>\n",
       "      <td>-6.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3572</th>\n",
       "      <td>83355890</td>\n",
       "      <td>2020</td>\n",
       "      <td>6</td>\n",
       "      <td>111392.0</td>\n",
       "      <td>Acute myocarditis and multisystem inflammatory...</td>\n",
       "      <td>BACKGROUND: A recent increase in children admi...</td>\n",
       "      <td>2020.0</td>\n",
       "      <td>12.0</td>\n",
       "      <td>Annals of Intensive Care</td>\n",
       "      <td>10</td>\n",
       "      <td>...</td>\n",
       "      <td>26.0</td>\n",
       "      <td>29.0</td>\n",
       "      <td>17.350</td>\n",
       "      <td>10.0</td>\n",
       "      <td>4.0</td>\n",
       "      <td>11.0</td>\n",
       "      <td>1.0</td>\n",
       "      <td>True</td>\n",
       "      <td>2020.0</td>\n",
       "      <td>-6.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3597</th>\n",
       "      <td>83816645</td>\n",
       "      <td>2020</td>\n",
       "      <td>6</td>\n",
       "      <td>40566.0</td>\n",
       "      <td>COVID-19 and cardiovascular injury: A role for...</td>\n",
       "      <td></td>\n",
       "      <td>2020.0</td>\n",
       "      <td>8.0</td>\n",
       "      <td>International Journal of Cardiology</td>\n",
       "      <td>312</td>\n",
       "      <td>...</td>\n",
       "      <td>1.0</td>\n",
       "      <td>2.0</td>\n",
       "      <td>4.000</td>\n",
       "      <td>1.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>True</td>\n",
       "      <td>2020.0</td>\n",
       "      <td>-2.0</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "<p>180 rows × 42 columns</p>\n",
       "</div>"
      ],
      "text/plain": [
       "      altmetric_id  posted_on_year_x  posted_on_month    pub_id  \\\n",
       "1203       3397958              2012               11   91792.0   \n",
       "2746      74005599              2020                1   76827.0   \n",
       "2747      74006487              2020                2   32956.0   \n",
       "2771      74464078              2020                1   57176.0   \n",
       "2772      74464103              2020                1   57170.0   \n",
       "...            ...               ...              ...       ...   \n",
       "3543      82704653              2020                5   66352.0   \n",
       "3554      82970555              2020                5   70487.0   \n",
       "3557      83016981              2020                6  111617.0   \n",
       "3572      83355890              2020                6  111392.0   \n",
       "3597      83816645              2020                6   40566.0   \n",
       "\n",
       "                                                  title  \\\n",
       "1203  DHP Framework: Digital Health Passports Using ...   \n",
       "2746  Pneumonia of Unknown Etiology in Wuhan, China:...   \n",
       "2747  Comparison of broad-spectrum antiviral activit...   \n",
       "2771  Clinical features of patients infected with 20...   \n",
       "2772  A familial cluster of pneumonia associated wit...   \n",
       "...                                                 ...   \n",
       "3543                   Tail risk of contagious diseases   \n",
       "3554     Studies on the mechanism of general anesthesia   \n",
       "3557  Population vulnerability to COVID-19 in Europe...   \n",
       "3572  Acute myocarditis and multisystem inflammatory...   \n",
       "3597  COVID-19 and cardiovascular injury: A role for...   \n",
       "\n",
       "                                               abstract  publication_year  \\\n",
       "1203  In order to contain the COVID-19 pandemic, sev...            2020.0   \n",
       "2746  There is currently an outbreak of pneumonia of...            2020.0   \n",
       "2747  Rocaglates, a class of natural compounds isola...            2020.0   \n",
       "2771  BACKGROUND: A recent cluster of pneumonia case...            2020.0   \n",
       "2772  BACKGROUND: An ongoing outbreak of pneumonia a...            2020.0   \n",
       "...                                                 ...               ...   \n",
       "3543  The COVID-19 pandemic has been a sobering remi...            2020.0   \n",
       "3554  Inhaled anesthetics are a chemically diverse c...            2020.0   \n",
       "3557  Background: Evidence has emerged showing that ...            2020.0   \n",
       "3572  BACKGROUND: A recent increase in children admi...            2020.0   \n",
       "3597                                                               2020.0   \n",
       "\n",
       "      publication_month                                            journal  \\\n",
       "1203                5.0                                                NaN   \n",
       "2746                3.0                         Journal of Travel Medicine   \n",
       "2747                3.0                                 Antiviral Research   \n",
       "2771                2.0                                         The Lancet   \n",
       "2772                2.0                                         The Lancet   \n",
       "...                 ...                                                ...   \n",
       "3543                6.0                                     Nature Physics   \n",
       "3554                6.0  Proceedings of the National Academy of Science...   \n",
       "3557               12.0                          Archives of Public Health   \n",
       "3572               12.0                           Annals of Intensive Care   \n",
       "3597                8.0                International Journal of Cardiology   \n",
       "\n",
       "     volume  ... counts_twitter_unique counts_total altmetric_score  \\\n",
       "1203    NaN  ...                   0.0          1.0           3.000   \n",
       "2746     27  ...                 535.0        623.0         527.360   \n",
       "2747    175  ...                  10.0         22.0          69.750   \n",
       "2771    395  ...               15126.0      20644.0       14257.298   \n",
       "2772    395  ...                4483.0       5339.0        4632.252   \n",
       "...     ...  ...                   ...          ...             ...   \n",
       "3543     16  ...                 698.0        788.0         508.662   \n",
       "3554    117  ...                1335.0       1435.0         737.350   \n",
       "3557     78  ...                  34.0         54.0          57.850   \n",
       "3572     10  ...                  26.0         29.0          17.350   \n",
       "3597    312  ...                   1.0          2.0           4.000   \n",
       "\n",
       "      member_of_the_public researcher practitioner science_communicator  \\\n",
       "1203                   0.0        0.0          0.0                  0.0   \n",
       "2746                 435.0       55.0         36.0                  9.0   \n",
       "2747                   8.0        2.0          0.0                  0.0   \n",
       "2771               13709.0      688.0        511.0                211.0   \n",
       "2772                4073.0      216.0        147.0                 45.0   \n",
       "...                    ...        ...          ...                  ...   \n",
       "3543                 563.0      106.0         17.0                 12.0   \n",
       "3554                1252.0       55.0         22.0                  6.0   \n",
       "3557                  16.0        8.0          9.0                  1.0   \n",
       "3572                  10.0        4.0         11.0                  1.0   \n",
       "3597                   1.0        0.0          0.0                  0.0   \n",
       "\n",
       "     in_wikipedia posted_on_year_y time_from_pub_to_wiki  \n",
       "1203         True           2012.0                 -90.0  \n",
       "2746         True           2020.0                  -2.0  \n",
       "2747         True           2020.0                  -1.0  \n",
       "2771         True           2020.0                  -1.0  \n",
       "2772         True           2020.0                  -1.0  \n",
       "...           ...              ...                   ...  \n",
       "3543         True           2020.0                  -1.0  \n",
       "3554         True           2020.0                  -1.0  \n",
       "3557         True           2020.0                  -6.0  \n",
       "3572         True           2020.0                  -6.0  \n",
       "3597         True           2020.0                  -2.0  \n",
       "\n",
       "[180 rows x 42 columns]"
      ]
     },
     "execution_count": 106,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df_posted_on_first[(df_posted_on_first.publication_year==2020)&(df_posted_on_first.time_from_pub_to_wiki < 0)]"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": []
  }
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