From 9739054a74cc22960d93d299a3aadf29523c1037 Mon Sep 17 00:00:00 2001
From: Andrea Mannocci <andremann@libero.it>
Date: Thu, 29 Apr 2021 18:50:02 +0200
Subject: [PATCH] new try with supervisioned ML

---
 notebooks/01-Exploration.ipynb      | 2041 ++++++++++++----------
 notebooks/02-Spam filter.ipynb      | 1096 ------------
 notebooks/03-Machine Learning.ipynb | 1028 -----------
 notebooks/03-Supervised.ipynb       | 2464 +++++++++++++++++++++++++++
 4 files changed, 3602 insertions(+), 3027 deletions(-)
 delete mode 100644 notebooks/02-Spam filter.ipynb
 delete mode 100644 notebooks/03-Machine Learning.ipynb
 create mode 100644 notebooks/03-Supervised.ipynb

diff --git a/notebooks/01-Exploration.ipynb b/notebooks/01-Exploration.ipynb
index 7280a4b..7573fc0 100644
--- a/notebooks/01-Exploration.ipynb
+++ b/notebooks/01-Exploration.ipynb
@@ -20,7 +20,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 114,
+   "execution_count": 1,
    "metadata": {},
    "outputs": [
     {
@@ -190,7 +190,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 221,
+   "execution_count": 5,
    "metadata": {},
    "outputs": [
     {
@@ -480,7 +480,7 @@
        "4         <NA>             2  "
       ]
      },
-     "execution_count": 221,
+     "execution_count": 5,
      "metadata": {},
      "output_type": "execute_result"
     }
@@ -532,6 +532,7 @@
        "      <th>family_name</th>\n",
        "      <th>biography</th>\n",
        "      <th>other_names</th>\n",
+       "      <th>urls</th>\n",
        "      <th>primary_email</th>\n",
        "      <th>keywords</th>\n",
        "      <th>external_ids</th>\n",
@@ -567,8 +568,9 @@
        "      <td>mannocci</td>\n",
        "      <td>data scientist &amp; researcher; scholarly knowled...</td>\n",
        "      <td>NaN</td>\n",
+       "      <td>[[personal website, https://andremann.github.i...</td>\n",
        "      <td>andrea.mannocci@isti.cnr.it</td>\n",
-       "      <td>[science of science, open science, research in...</td>\n",
+       "      <td>[research infrastructures, scholarly knowledge...</td>\n",
        "      <td>[[scopus author id, 55233589900]]</td>\n",
        "      <td>[[information engineering, ph.d., università d...</td>\n",
        "      <td>[[research associate, istituto di scienza e te...</td>\n",
@@ -605,11 +607,14 @@
        "                                                 biography other_names  \\\n",
        "3073261  data scientist & researcher; scholarly knowled...         NaN   \n",
        "\n",
+       "                                                      urls  \\\n",
+       "3073261  [[personal website, https://andremann.github.i...   \n",
+       "\n",
        "                       primary_email  \\\n",
        "3073261  andrea.mannocci@isti.cnr.it   \n",
        "\n",
        "                                                  keywords  \\\n",
-       "3073261  [science of science, open science, research in...   \n",
+       "3073261  [research infrastructures, scholarly knowledge...   \n",
        "\n",
        "                              external_ids  \\\n",
        "3073261  [[scopus author id, 55233589900]]   \n",
@@ -678,6 +683,7 @@
        "      <th>family_name</th>\n",
        "      <th>biography</th>\n",
        "      <th>other_names</th>\n",
+       "      <th>urls</th>\n",
        "      <th>primary_email</th>\n",
        "      <th>keywords</th>\n",
        "      <th>external_ids</th>\n",
@@ -713,8 +719,9 @@
        "      <td>whatsapp</td>\n",
        "      <td>&lt;NA&gt;</td>\n",
        "      <td>NaN</td>\n",
+       "      <td>[[otherwhatsapp, https://otherwhatsapp.com/], ...</td>\n",
        "      <td>&lt;NA&gt;</td>\n",
-       "      <td>[whatsapp gb apk, whatsapp gb, whatsapp gb bai...</td>\n",
+       "      <td>[whatsapp gb 2020, whatsapp gb apk, whatsapp g...</td>\n",
        "      <td>NaN</td>\n",
        "      <td>NaN</td>\n",
        "      <td>NaN</td>\n",
@@ -745,11 +752,14 @@
        "                       orcid  verified_email  verified_primary_email  \\\n",
        "9887272  0000-0001-6997-9470            True                    True   \n",
        "\n",
-       "        given_names family_name biography other_names primary_email  \\\n",
-       "9887272       other    whatsapp      <NA>         NaN          <NA>   \n",
+       "        given_names family_name biography other_names  \\\n",
+       "9887272       other    whatsapp      <NA>         NaN   \n",
+       "\n",
+       "                                                      urls primary_email  \\\n",
+       "9887272  [[otherwhatsapp, https://otherwhatsapp.com/], ...          <NA>   \n",
        "\n",
        "                                                  keywords external_ids  \\\n",
-       "9887272  [whatsapp gb apk, whatsapp gb, whatsapp gb bai...          NaN   \n",
+       "9887272  [whatsapp gb 2020, whatsapp gb apk, whatsapp g...          NaN   \n",
        "\n",
        "        education employment  n_works works_source  \\\n",
        "9887272       NaN        NaN        0          NaN   \n",
@@ -783,7 +793,7 @@
    "cell_type": "code",
    "execution_count": 8,
    "metadata": {
-    "scrolled": true
+    "scrolled": false
    },
    "outputs": [
     {
@@ -796,6 +806,7 @@
        "family_name               10671715\n",
        "biography                   354015\n",
        "other_names                 554684\n",
+       "urls                        715067\n",
        "primary_email               124722\n",
        "keywords                    649637\n",
        "external_ids               1308598\n",
@@ -841,7 +852,7 @@
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-       "top       0000-0003-4717-4481\n",
+       "top       0000-0002-2510-4696\n",
        "freq                        1\n",
        "Name: orcid, dtype: object"
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@@ -950,6 +961,7 @@
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        "      <th>biography</th>\n",
        "      <th>other_names</th>\n",
+       "      <th>urls</th>\n",
        "      <th>primary_email</th>\n",
        "      <th>keywords</th>\n",
        "      <th>external_ids</th>\n",
@@ -985,6 +997,7 @@
        "      <td>warasart</td>\n",
        "      <td>&lt;NA&gt;</td>\n",
        "      <td>NaN</td>\n",
+       "      <td>NaN</td>\n",
        "      <td>maykin@owasp.org</td>\n",
        "      <td>NaN</td>\n",
        "      <td>NaN</td>\n",
@@ -1018,6 +1031,7 @@
        "      <td>warasart</td>\n",
        "      <td>&lt;NA&gt;</td>\n",
        "      <td>NaN</td>\n",
+       "      <td>NaN</td>\n",
        "      <td>maykin@owasp.org</td>\n",
        "      <td>NaN</td>\n",
        "      <td>NaN</td>\n",
@@ -1051,9 +1065,9 @@
        "7543981  0000-0002-0836-2271            True                    True   \n",
        "9316843  0000-0001-9855-1676            True                    True   \n",
        "\n",
-       "        given_names family_name biography other_names     primary_email  \\\n",
-       "7543981      maykin    warasart      <NA>         NaN  maykin@owasp.org   \n",
-       "9316843      maykin    warasart      <NA>         NaN  maykin@owasp.org   \n",
+       "        given_names family_name biography other_names urls     primary_email  \\\n",
+       "7543981      maykin    warasart      <NA>         NaN  NaN  maykin@owasp.org   \n",
+       "9316843      maykin    warasart      <NA>         NaN  NaN  maykin@owasp.org   \n",
        "\n",
        "        keywords external_ids education employment  n_works works_source  \\\n",
        "7543981      NaN          NaN       NaN        NaN        0          NaN   \n",
@@ -1118,6 +1132,7 @@
        "      <th>family_name</th>\n",
        "      <th>biography</th>\n",
        "      <th>other_names</th>\n",
+       "      <th>urls</th>\n",
        "      <th>primary_email</th>\n",
        "      <th>keywords</th>\n",
        "      <th>external_ids</th>\n",
@@ -1153,6 +1168,7 @@
        "      <td>perçin</td>\n",
        "      <td>&lt;NA&gt;</td>\n",
        "      <td>NaN</td>\n",
+       "      <td>NaN</td>\n",
        "      <td>opercin@erbakan.edu.tr</td>\n",
        "      <td>NaN</td>\n",
        "      <td>NaN</td>\n",
@@ -1186,6 +1202,7 @@
        "      <td>perçin</td>\n",
        "      <td>&lt;NA&gt;</td>\n",
        "      <td>NaN</td>\n",
+       "      <td>NaN</td>\n",
        "      <td>opercin@erbakan.edu.tr</td>\n",
        "      <td>NaN</td>\n",
        "      <td>NaN</td>\n",
@@ -1219,13 +1236,13 @@
        "347852   0000-0002-2232-9638            True                    True   \n",
        "1681787  0000-0003-0033-0918            True                    True   \n",
        "\n",
-       "        given_names family_name biography other_names           primary_email  \\\n",
-       "347852        osman      perçin      <NA>         NaN  opercin@erbakan.edu.tr   \n",
-       "1681787       osman      perçin      <NA>         NaN  opercin@erbakan.edu.tr   \n",
+       "        given_names family_name biography other_names urls  \\\n",
+       "347852        osman      perçin      <NA>         NaN  NaN   \n",
+       "1681787       osman      perçin      <NA>         NaN  NaN   \n",
        "\n",
-       "        keywords external_ids education  \\\n",
-       "347852       NaN          NaN       NaN   \n",
-       "1681787      NaN          NaN       NaN   \n",
+       "                  primary_email keywords external_ids education  \\\n",
+       "347852   opercin@erbakan.edu.tr      NaN          NaN       NaN   \n",
+       "1681787  opercin@erbakan.edu.tr      NaN          NaN       NaN   \n",
        "\n",
        "                                                employment  n_works  \\\n",
        "347852                                                 NaN        0   \n",
@@ -1290,6 +1307,7 @@
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        "      <th>biography</th>\n",
        "      <th>other_names</th>\n",
+       "      <th>urls</th>\n",
        "      <th>primary_email</th>\n",
        "      <th>keywords</th>\n",
        "      <th>external_ids</th>\n",
@@ -1325,8 +1343,9 @@
        "      <td>davey</td>\n",
        "      <td>&lt;NA&gt;</td>\n",
        "      <td>NaN</td>\n",
+       "      <td>NaN</td>\n",
        "      <td>patrick.davey@monash.edu</td>\n",
-       "      <td>[inorganic chemistry, radiopharmaceuticals, ra...</td>\n",
+       "      <td>[radiopharmaceuticals, bioinorganic chemistry,...</td>\n",
        "      <td>NaN</td>\n",
        "      <td>NaN</td>\n",
        "      <td>[[phd student, monash university, melbourne, ,...</td>\n",
@@ -1358,6 +1377,7 @@
        "      <td>davey</td>\n",
        "      <td>&lt;NA&gt;</td>\n",
        "      <td>NaN</td>\n",
+       "      <td>NaN</td>\n",
        "      <td>patrick.davey@monash.edu</td>\n",
        "      <td>NaN</td>\n",
        "      <td>NaN</td>\n",
@@ -1391,16 +1411,16 @@
        "954085   0000-0002-9158-1757            True                    True   \n",
        "5590332  0000-0002-8774-0030            True                    True   \n",
        "\n",
-       "        given_names family_name biography other_names  \\\n",
-       "954085      patrick       davey      <NA>         NaN   \n",
-       "5590332     patrick       davey      <NA>         NaN   \n",
+       "        given_names family_name biography other_names urls  \\\n",
+       "954085      patrick       davey      <NA>         NaN  NaN   \n",
+       "5590332     patrick       davey      <NA>         NaN  NaN   \n",
        "\n",
        "                    primary_email  \\\n",
        "954085   patrick.davey@monash.edu   \n",
        "5590332  patrick.davey@monash.edu   \n",
        "\n",
        "                                                  keywords external_ids  \\\n",
-       "954085   [inorganic chemistry, radiopharmaceuticals, ra...          NaN   \n",
+       "954085   [radiopharmaceuticals, bioinorganic chemistry,...          NaN   \n",
        "5590332                                                NaN          NaN   \n",
        "\n",
        "        education                                         employment  n_works  \\\n",
@@ -2476,9 +2496,9 @@
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        "                            \n",
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@@ -2566,6 +2586,7 @@
        "      <th>family_name</th>\n",
        "      <th>biography</th>\n",
        "      <th>other_names</th>\n",
+       "      <th>urls</th>\n",
        "      <th>primary_email</th>\n",
        "      <th>keywords</th>\n",
        "      <th>external_ids</th>\n",
@@ -2601,6 +2622,7 @@
        "      <td>teixeira júnior</td>\n",
        "      <td>&lt;NA&gt;</td>\n",
        "      <td>[teixeira, antônio gilvan, júnior, antonio gil...</td>\n",
+       "      <td>[[research gate, https://www.researchgate.net/...</td>\n",
        "      <td>gilvan.junior@aluno.ufca.edu.br</td>\n",
        "      <td>[ethicis; medicine; infectology; neurology; ne...</td>\n",
        "      <td>[[scopus author id, 56647743200], [scopus auth...</td>\n",
@@ -2634,6 +2656,7 @@
        "      <td>tan shing loong</td>\n",
        "      <td>&lt;NA&gt;</td>\n",
        "      <td>NaN</td>\n",
+       "      <td>NaN</td>\n",
        "      <td>aaron.tanshingloong@wadh.ox.ac.uk</td>\n",
        "      <td>NaN</td>\n",
        "      <td>NaN</td>\n",
@@ -2667,6 +2690,7 @@
        "      <td>solanki</td>\n",
        "      <td>&lt;NA&gt;</td>\n",
        "      <td>NaN</td>\n",
+       "      <td>[[github, https://github.com/abhisheksolanki],...</td>\n",
        "      <td>&lt;NA&gt;</td>\n",
        "      <td>NaN</td>\n",
        "      <td>NaN</td>\n",
@@ -2700,6 +2724,7 @@
        "      <td>arra</td>\n",
        "      <td>&lt;NA&gt;</td>\n",
        "      <td>NaN</td>\n",
+       "      <td>NaN</td>\n",
        "      <td>&lt;NA&gt;</td>\n",
        "      <td>NaN</td>\n",
        "      <td>NaN</td>\n",
@@ -2733,6 +2758,7 @@
        "      <td>ronzani</td>\n",
        "      <td>&lt;NA&gt;</td>\n",
        "      <td>NaN</td>\n",
+       "      <td>NaN</td>\n",
        "      <td>alberto@aronza.com</td>\n",
        "      <td>NaN</td>\n",
        "      <td>NaN</td>\n",
@@ -2783,6 +2809,13 @@
        "497                                                NaN   \n",
        "869                                                NaN   \n",
        "\n",
+       "                                                  urls  \\\n",
+       "251  [[research gate, https://www.researchgate.net/...   \n",
+       "316                                                NaN   \n",
+       "433  [[github, https://github.com/abhisheksolanki],...   \n",
+       "497                                                NaN   \n",
+       "869                                                NaN   \n",
+       "\n",
        "                         primary_email  \\\n",
        "251    gilvan.junior@aluno.ufca.edu.br   \n",
        "316  aaron.tanshingloong@wadh.ox.ac.uk   \n",
@@ -3777,9 +3810,9 @@
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        "                            \n",
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@@ -4841,6 +4874,7 @@
        "      <th>family_name</th>\n",
        "      <th>biography</th>\n",
        "      <th>other_names</th>\n",
+       "      <th>urls</th>\n",
        "      <th>primary_email</th>\n",
        "      <th>keywords</th>\n",
        "      <th>external_ids</th>\n",
@@ -4876,6 +4910,7 @@
        "      <td>solanki</td>\n",
        "      <td>&lt;NA&gt;</td>\n",
        "      <td>NaN</td>\n",
+       "      <td>[[github, https://github.com/abhisheksolanki],...</td>\n",
        "      <td>&lt;NA&gt;</td>\n",
        "      <td>NaN</td>\n",
        "      <td>NaN</td>\n",
@@ -4909,6 +4944,7 @@
        "      <td>arra</td>\n",
        "      <td>&lt;NA&gt;</td>\n",
        "      <td>NaN</td>\n",
+       "      <td>NaN</td>\n",
        "      <td>&lt;NA&gt;</td>\n",
        "      <td>NaN</td>\n",
        "      <td>NaN</td>\n",
@@ -4942,8 +4978,9 @@
        "      <td>echeverry velásquez</td>\n",
        "      <td>alejandra echeverry is an industrial electrici...</td>\n",
        "      <td>NaN</td>\n",
+       "      <td>NaN</td>\n",
        "      <td>&lt;NA&gt;</td>\n",
-       "      <td>[control, science, technology, innovation, ren...</td>\n",
+       "      <td>[innovation, renewable, technology, engineerin...</td>\n",
        "      <td>NaN</td>\n",
        "      <td>[[, electrical engineer, institución universit...</td>\n",
        "      <td>[[professor, institución universitaria pascual...</td>\n",
@@ -4975,6 +5012,7 @@
        "      <td>tesoniero</td>\n",
        "      <td>&lt;NA&gt;</td>\n",
        "      <td>NaN</td>\n",
+       "      <td>NaN</td>\n",
        "      <td>&lt;NA&gt;</td>\n",
        "      <td>NaN</td>\n",
        "      <td>[[researcherid, d-9056-2015]]</td>\n",
@@ -5008,8 +5046,9 @@
        "      <td>yildirim</td>\n",
        "      <td>&lt;NA&gt;</td>\n",
        "      <td>NaN</td>\n",
+       "      <td>NaN</td>\n",
        "      <td>&lt;NA&gt;</td>\n",
-       "      <td>[natural chemistry, pharmacognosy, chemical en...</td>\n",
+       "      <td>[natural chemistry, chemical engineering, phar...</td>\n",
        "      <td>NaN</td>\n",
        "      <td>[[business management, master of science, ista...</td>\n",
        "      <td>NaN</td>\n",
@@ -5064,6 +5103,7 @@
        "      <td>...</td>\n",
        "      <td>...</td>\n",
        "      <td>...</td>\n",
+       "      <td>...</td>\n",
        "    </tr>\n",
        "    <tr>\n",
        "      <th>10985816</th>\n",
@@ -5074,6 +5114,7 @@
        "      <td>walk</td>\n",
        "      <td>&lt;NA&gt;</td>\n",
        "      <td>NaN</td>\n",
+       "      <td>[[, https://www.physik.fu-berlin.de/en/einrich...</td>\n",
        "      <td>&lt;NA&gt;</td>\n",
        "      <td>NaN</td>\n",
        "      <td>NaN</td>\n",
@@ -5107,6 +5148,7 @@
        "      <td>vandevelde</td>\n",
        "      <td>&lt;NA&gt;</td>\n",
        "      <td>NaN</td>\n",
+       "      <td>[[linkedin, http://www.linkedin.com/in/raf-van...</td>\n",
        "      <td>&lt;NA&gt;</td>\n",
        "      <td>NaN</td>\n",
        "      <td>NaN</td>\n",
@@ -5140,6 +5182,7 @@
        "      <td>finelli</td>\n",
        "      <td>&lt;NA&gt;</td>\n",
        "      <td>NaN</td>\n",
+       "      <td>NaN</td>\n",
        "      <td>&lt;NA&gt;</td>\n",
        "      <td>NaN</td>\n",
        "      <td>NaN</td>\n",
@@ -5173,6 +5216,7 @@
        "      <td>de almeida araújo</td>\n",
        "      <td>&lt;NA&gt;</td>\n",
        "      <td>NaN</td>\n",
+       "      <td>NaN</td>\n",
        "      <td>&lt;NA&gt;</td>\n",
        "      <td>NaN</td>\n",
        "      <td>NaN</td>\n",
@@ -5206,8 +5250,9 @@
        "      <td>ahmed</td>\n",
        "      <td>&lt;NA&gt;</td>\n",
        "      <td>NaN</td>\n",
+       "      <td>NaN</td>\n",
        "      <td>&lt;NA&gt;</td>\n",
-       "      <td>[atomistic simulation, ai chips, graphene, dee...</td>\n",
+       "      <td>[thin films, graphene, ai chips, deep learning...</td>\n",
        "      <td>NaN</td>\n",
        "      <td>NaN</td>\n",
        "      <td>[[post-doctor, zhejiang university, hangzhou, ...</td>\n",
@@ -5232,7 +5277,7 @@
        "    </tr>\n",
        "  </tbody>\n",
        "</table>\n",
-       "<p>19814 rows × 30 columns</p>\n",
+       "<p>19814 rows × 31 columns</p>\n",
        "</div>"
       ],
       "text/plain": [
@@ -5275,18 +5320,31 @@
        "10987829                                               <NA>         NaN   \n",
        "10988444                                               <NA>         NaN   \n",
        "\n",
-       "         primary_email                                           keywords  \\\n",
-       "433               <NA>                                                NaN   \n",
-       "497               <NA>                                                NaN   \n",
-       "898               <NA>  [control, science, technology, innovation, ren...   \n",
-       "1719              <NA>                                                NaN   \n",
-       "6829              <NA>  [natural chemistry, pharmacognosy, chemical en...   \n",
-       "...                ...                                                ...   \n",
-       "10985816          <NA>                                                NaN   \n",
-       "10986027          <NA>                                                NaN   \n",
-       "10987501          <NA>                                                NaN   \n",
-       "10987829          <NA>                                                NaN   \n",
-       "10988444          <NA>  [atomistic simulation, ai chips, graphene, dee...   \n",
+       "                                                       urls primary_email  \\\n",
+       "433       [[github, https://github.com/abhisheksolanki],...          <NA>   \n",
+       "497                                                     NaN          <NA>   \n",
+       "898                                                     NaN          <NA>   \n",
+       "1719                                                    NaN          <NA>   \n",
+       "6829                                                    NaN          <NA>   \n",
+       "...                                                     ...           ...   \n",
+       "10985816  [[, https://www.physik.fu-berlin.de/en/einrich...          <NA>   \n",
+       "10986027  [[linkedin, http://www.linkedin.com/in/raf-van...          <NA>   \n",
+       "10987501                                                NaN          <NA>   \n",
+       "10987829                                                NaN          <NA>   \n",
+       "10988444                                                NaN          <NA>   \n",
+       "\n",
+       "                                                   keywords  \\\n",
+       "433                                                     NaN   \n",
+       "497                                                     NaN   \n",
+       "898       [innovation, renewable, technology, engineerin...   \n",
+       "1719                                                    NaN   \n",
+       "6829      [natural chemistry, chemical engineering, phar...   \n",
+       "...                                                     ...   \n",
+       "10985816                                                NaN   \n",
+       "10986027                                                NaN   \n",
+       "10987501                                                NaN   \n",
+       "10987829                                                NaN   \n",
+       "10988444  [thin films, graphene, ai chips, deep learning...   \n",
        "\n",
        "                           external_ids  \\\n",
        "433                                 NaN   \n",
@@ -5392,7 +5450,7 @@
        "10987829            2             1  \n",
        "10988444         <NA>             1  \n",
        "\n",
-       "[19814 rows x 30 columns]"
+       "[19814 rows x 31 columns]"
       ]
      },
      "execution_count": 23,
@@ -5486,6 +5544,7 @@
        "      <th>family_name</th>\n",
        "      <th>biography</th>\n",
        "      <th>other_names</th>\n",
+       "      <th>urls</th>\n",
        "      <th>primary_email</th>\n",
        "      <th>keywords</th>\n",
        "      <th>external_ids</th>\n",
@@ -5518,7 +5577,7 @@
       ],
       "text/plain": [
        "Empty DataFrame\n",
-       "Columns: [orcid, verified_email, verified_primary_email, given_names, family_name, biography, other_names, primary_email, keywords, external_ids, education, employment, n_works, works_source, activation_date, last_update_date, n_doi, n_arxiv, n_pmc, n_other_pids, label, primary_email_domain, other_email_domains, url_domains, n_emails, n_urls, n_ids, n_keywords, n_education, n_employment]\n",
+       "Columns: [orcid, verified_email, verified_primary_email, given_names, family_name, biography, other_names, urls, primary_email, keywords, external_ids, education, employment, n_works, works_source, activation_date, last_update_date, n_doi, n_arxiv, n_pmc, n_other_pids, label, primary_email_domain, other_email_domains, url_domains, n_emails, n_urls, n_ids, n_keywords, n_education, n_employment]\n",
        "Index: []"
       ]
      },
@@ -5564,6 +5623,7 @@
        "      <th>family_name</th>\n",
        "      <th>biography</th>\n",
        "      <th>other_names</th>\n",
+       "      <th>urls</th>\n",
        "      <th>primary_email</th>\n",
        "      <th>keywords</th>\n",
        "      <th>external_ids</th>\n",
@@ -5599,6 +5659,7 @@
        "      <td>&lt;NA&gt;</td>\n",
        "      <td>&lt;NA&gt;</td>\n",
        "      <td>NaN</td>\n",
+       "      <td>[[kth profile, https://www.kth.se/profile/toma...</td>\n",
        "      <td>&lt;NA&gt;</td>\n",
        "      <td>NaN</td>\n",
        "      <td>NaN</td>\n",
@@ -5632,6 +5693,7 @@
        "      <td>&lt;NA&gt;</td>\n",
        "      <td>&lt;NA&gt;</td>\n",
        "      <td>[fontana, milena da silva]</td>\n",
+       "      <td>[[currículo lattes, http://buscatextual.cnpq.b...</td>\n",
        "      <td>&lt;NA&gt;</td>\n",
        "      <td>[educação; informática; matemática.]</td>\n",
        "      <td>NaN</td>\n",
@@ -5665,8 +5727,9 @@
        "      <td>&lt;NA&gt;</td>\n",
        "      <td>investigador de la universidad de oviedo. depa...</td>\n",
        "      <td>NaN</td>\n",
+       "      <td>[[cv ignacio fernandez sarasola, https://www.u...</td>\n",
        "      <td>&lt;NA&gt;</td>\n",
-       "      <td>[history of political thought, constitutional ...</td>\n",
+       "      <td>[constitutional law, constitutional history, h...</td>\n",
        "      <td>[[scopus author id, 54394231000]]</td>\n",
        "      <td>[[public law, ph doctor, university of oviedo,...</td>\n",
        "      <td>[[professor of constitutional law, university ...</td>\n",
@@ -5698,8 +5761,9 @@
        "      <td>&lt;NA&gt;</td>\n",
        "      <td>&lt;NA&gt;</td>\n",
        "      <td>NaN</td>\n",
+       "      <td>[[currículo lattes, https://wwws.cnpq.br/cvlat...</td>\n",
        "      <td>&lt;NA&gt;</td>\n",
-       "      <td>[migration, culture cell, prostate cancer]</td>\n",
+       "      <td>[migration, prostate cancer, culture cell]</td>\n",
        "      <td>[[researcherid, p-2223-2018]]</td>\n",
        "      <td>[[morfologia, , universidade estadual paulista...</td>\n",
        "      <td>[[, universidade estadual paulista (unesp), in...</td>\n",
@@ -5731,6 +5795,7 @@
        "      <td>manriquez paisig</td>\n",
        "      <td>&lt;NA&gt;</td>\n",
        "      <td>NaN</td>\n",
+       "      <td>[[canal de youtube, https://www.youtube.com/ch...</td>\n",
        "      <td>&lt;NA&gt;</td>\n",
        "      <td>NaN</td>\n",
        "      <td>NaN</td>\n",
@@ -5781,18 +5846,25 @@
        "46                                                <NA>   \n",
        "158                                               <NA>   \n",
        "\n",
-       "                    other_names primary_email  \\\n",
-       "6                           NaN          <NA>   \n",
-       "11   [fontana, milena da silva]          <NA>   \n",
-       "29                          NaN          <NA>   \n",
-       "46                          NaN          <NA>   \n",
-       "158                         NaN          <NA>   \n",
+       "                    other_names  \\\n",
+       "6                           NaN   \n",
+       "11   [fontana, milena da silva]   \n",
+       "29                          NaN   \n",
+       "46                          NaN   \n",
+       "158                         NaN   \n",
+       "\n",
+       "                                                  urls primary_email  \\\n",
+       "6    [[kth profile, https://www.kth.se/profile/toma...          <NA>   \n",
+       "11   [[currículo lattes, http://buscatextual.cnpq.b...          <NA>   \n",
+       "29   [[cv ignacio fernandez sarasola, https://www.u...          <NA>   \n",
+       "46   [[currículo lattes, https://wwws.cnpq.br/cvlat...          <NA>   \n",
+       "158  [[canal de youtube, https://www.youtube.com/ch...          <NA>   \n",
        "\n",
        "                                              keywords  \\\n",
        "6                                                  NaN   \n",
        "11                [educação; informática; matemática.]   \n",
-       "29   [history of political thought, constitutional ...   \n",
-       "46          [migration, culture cell, prostate cancer]   \n",
+       "29   [constitutional law, constitutional history, h...   \n",
+       "46          [migration, prostate cancer, culture cell]   \n",
        "158                                                NaN   \n",
        "\n",
        "                          external_ids  \\\n",
@@ -7024,9 +7096,9 @@
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@@ -8159,6 +8231,7 @@
        "      <th>family_name</th>\n",
        "      <th>biography</th>\n",
        "      <th>other_names</th>\n",
+       "      <th>urls</th>\n",
        "      <th>primary_email</th>\n",
        "      <th>keywords</th>\n",
        "      <th>external_ids</th>\n",
@@ -8194,8 +8267,9 @@
        "      <td>aziz</td>\n",
        "      <td>abdul aziz was born on may 25, 1973, in brebes...</td>\n",
        "      <td>[abdul aziz, aziz, abdul, aziz, a., aziz, abd,...</td>\n",
+       "      <td>[[google scholar, https://scholar.google.com/c...</td>\n",
        "      <td>&lt;NA&gt;</td>\n",
-       "      <td>[ilmu ekonomi, ekonomi islam, etika bisnis isl...</td>\n",
+       "      <td>[etika bisnis islam, ekonomi islam, metodologi...</td>\n",
        "      <td>NaN</td>\n",
        "      <td>[[ilmu ekonomi, dr, universitas borobudur, jak...</td>\n",
        "      <td>[[assisten professor/dr, institut agama islam ...</td>\n",
@@ -8227,8 +8301,9 @@
        "      <td>romaniuk</td>\n",
        "      <td>professor of electronics and communications en...</td>\n",
        "      <td>[r.romaniuk, r.s.romaniuk, ryszard romaniuk, r...</td>\n",
+       "      <td>[[scholar google, http://scholar.google.pl/cit...</td>\n",
        "      <td>rrom@ise.pw.edu.pl</td>\n",
-       "      <td>[research systems, measurement systems, photon...</td>\n",
+       "      <td>[photonics, research systems, telecommunicatio...</td>\n",
        "      <td>[[isni, 0000000071432485], [researcherid, b-91...</td>\n",
        "      <td>[[faculty of electronics and information techn...</td>\n",
        "      <td>[[professor, institute director, politechnika ...</td>\n",
@@ -8260,8 +8335,9 @@
        "      <td>babulak</td>\n",
        "      <td>professor eduard babulak is accomplished inter...</td>\n",
        "      <td>[professor eduard babulak]</td>\n",
+       "      <td>[[honorary chair, chief mentor &amp; senior adviso...</td>\n",
        "      <td>&lt;NA&gt;</td>\n",
-       "      <td>[internet of things, next generation of ict an...</td>\n",
+       "      <td>[future cyberspace, intelligent transport syst...</td>\n",
        "      <td>[[scopus author id, 6506867432], [researcherid...</td>\n",
        "      <td>[[information technology, doctor habilitated (...</td>\n",
        "      <td>[[consultant, horizon 2020 framework programme...</td>\n",
@@ -8293,8 +8369,9 @@
        "      <td>гусев</td>\n",
        "      <td>surname, name gusev  alexander leonidovichdate...</td>\n",
        "      <td>[alexander l. gusev , alexander leonidovich gu...</td>\n",
+       "      <td>[[a.l. gusev  alternative energy and ecology, ...</td>\n",
        "      <td>&lt;NA&gt;</td>\n",
-       "      <td>[nanomaterials and nanocomposites, supercapaci...</td>\n",
+       "      <td>[technologies of purification of aggressive ga...</td>\n",
        "      <td>[[researcherid, f-8048-2014], [scopus author i...</td>\n",
        "      <td>[[chemical technology and cryogenic-vacuum tec...</td>\n",
        "      <td>[[general director, scientific technical centr...</td>\n",
@@ -8326,8 +8403,9 @@
        "      <td>canaza choque</td>\n",
        "      <td>docente-investigador social. maestrando en der...</td>\n",
        "      <td>[franklin américo canaza-choque , franklin a. ...</td>\n",
+       "      <td>[[consejo nacional de ciencia, tecnología e in...</td>\n",
        "      <td>leo_123fa@hotmail.com</td>\n",
-       "      <td>[filosofía; educación; políticas de desarrollo...</td>\n",
+       "      <td>[justicia global; democracia; derechos humanos...</td>\n",
        "      <td>[[researcherid, p-8613-2018], [loop profile, 8...</td>\n",
        "      <td>[[facultad de ciencias de la educación , maest...</td>\n",
        "      <td>[[investigador social, universidad católica de...</td>\n",
@@ -8359,8 +8437,9 @@
        "      <td>duperré</td>\n",
        "      <td>gustavo norberto duperré graduated in arts and...</td>\n",
        "      <td>[gustavo norberto duperré, duperré, g. n., gus...</td>\n",
+       "      <td>[[gis in cultural heritage - icomos românia, h...</td>\n",
        "      <td>gustavo.duperre@usal.edu.ar</td>\n",
-       "      <td>[sciences of antiquity, cultural heritage, ear...</td>\n",
+       "      <td>[history of art, international cooperation, hu...</td>\n",
        "      <td>[[scopus author id, 57195936346], [researcheri...</td>\n",
        "      <td>[[programme in history, history of art and ter...</td>\n",
        "      <td>[[titular professor, dirección general de cult...</td>\n",
@@ -8392,8 +8471,9 @@
        "      <td>olea</td>\n",
        "      <td>pós-doutorado em gestão ambiental pela univers...</td>\n",
        "      <td>[ munhoz, pelayo olea,  olea, pelayo,  olea, p...</td>\n",
+       "      <td>[[currículo lattes, http://lattes.cnpq.br/6209...</td>\n",
        "      <td>&lt;NA&gt;</td>\n",
-       "      <td>[inovação, sustentabilidade, empreendedorismo]</td>\n",
+       "      <td>[empreendedorismo, sustentabilidade, inovação]</td>\n",
        "      <td>[[scopus author id, 55175503300], [researcheri...</td>\n",
        "      <td>[[, postdoctoral in environmental sustainabili...</td>\n",
        "      <td>[[professor, universidade federal do rio grand...</td>\n",
@@ -8425,6 +8505,7 @@
        "      <td>catral sanabria</td>\n",
        "      <td>my education is in computer science, mathemati...</td>\n",
        "      <td>NaN</td>\n",
+       "      <td>[[researchgate adolfo catral , https://www.res...</td>\n",
        "      <td>&lt;NA&gt;</td>\n",
        "      <td>NaN</td>\n",
        "      <td>[[loop profile, 747193]]</td>\n",
@@ -8458,8 +8539,9 @@
        "      <td>dispensary</td>\n",
        "      <td>we procure and deliver premium cannabis strain...</td>\n",
        "      <td>[we procure and deliver premium cannabis strai...</td>\n",
+       "      <td>[[find your cannabis &amp; marijuana dispensary , ...</td>\n",
        "      <td>&lt;NA&gt;</td>\n",
-       "      <td>[marijuana, canabis dispensary, marijuana stoc...</td>\n",
+       "      <td>[marijuana dispensary, cannabis community, mar...</td>\n",
        "      <td>NaN</td>\n",
        "      <td>NaN</td>\n",
        "      <td>NaN</td>\n",
@@ -8491,8 +8573,9 @@
        "      <td>spychala</td>\n",
        "      <td>jaroslaw spychala has received a doctoral degr...</td>\n",
        "      <td>[jaroslaw jozef spychala]</td>\n",
+       "      <td>[[resume, http://www.biowebspin.com/wp-content...</td>\n",
        "      <td>&lt;NA&gt;</td>\n",
-       "      <td>[organic chemistry, medicinal and pharmaceutic...</td>\n",
+       "      <td>[organic chemistry, photochemistry, biochemist...</td>\n",
        "      <td>[[scopus author id, 7006745874]]</td>\n",
        "      <td>[[department of chemistry, postdoctoral associ...</td>\n",
        "      <td>[[assistant professor, adam mickiewicz univers...</td>\n",
@@ -8524,6 +8607,7 @@
        "      <td>beltrán mancilla</td>\n",
        "      <td>juan de dios beltrán mancilla (*) filósofo aut...</td>\n",
        "      <td>[juan de dios beltrán mancilla, filósofo autod...</td>\n",
+       "      <td>[[01.- juan de dios beltrán mancilla. teoría o...</td>\n",
        "      <td>&lt;NA&gt;</td>\n",
        "      <td>[filosofia medicina arquitectura economía dere...</td>\n",
        "      <td>NaN</td>\n",
@@ -8557,8 +8641,9 @@
        "      <td>b d</td>\n",
        "      <td>dr. parameshachari b dacm distinguished speake...</td>\n",
        "      <td>[dr. parameshachari b d]</td>\n",
+       "      <td>[[gsssietw,mysuru, http://geethashishu.in/], [...</td>\n",
        "      <td>&lt;NA&gt;</td>\n",
-       "      <td>[honorary secretary| iete mysuru centre, profe...</td>\n",
+       "      <td>[mysore region coordinator|ieee bangalore sect...</td>\n",
        "      <td>[[researcherid, f-7045-2018], [scopus author i...</td>\n",
        "      <td>[[electronics and communication engineering, p...</td>\n",
        "      <td>[[acm distinguished speaker (volunteer), assoc...</td>\n",
@@ -8590,8 +8675,9 @@
        "      <td>jaelani</td>\n",
        "      <td>all my papers can be downloaded from portal:re...</td>\n",
        "      <td>[jaelani, a., jaelani, aan]</td>\n",
+       "      <td>[[microsoft academic research, https://academi...</td>\n",
        "      <td>aan_jaelani@syekhnurjati.ac.id</td>\n",
-       "      <td>[tourism industry, public finance &amp; budgeting,...</td>\n",
+       "      <td>[history of islamic economic thought, islamic ...</td>\n",
        "      <td>[[scopus author id, 57195963463], [loop profil...</td>\n",
        "      <td>[[post graduate, s3/dr, universitas islam nege...</td>\n",
        "      <td>[[dr, institut agama islam negeri syekh nurjat...</td>\n",
@@ -8679,6 +8765,21 @@
        "10486212                           [dr. parameshachari b d]   \n",
        "10652632                        [jaelani, a., jaelani, aan]   \n",
        "\n",
+       "                                                       urls  \\\n",
+       "1025713   [[google scholar, https://scholar.google.com/c...   \n",
+       "2743648   [[scholar google, http://scholar.google.pl/cit...   \n",
+       "3011724   [[honorary chair, chief mentor & senior adviso...   \n",
+       "3881064   [[a.l. gusev  alternative energy and ecology, ...   \n",
+       "7466062   [[consejo nacional de ciencia, tecnología e in...   \n",
+       "7517096   [[gis in cultural heritage - icomos românia, h...   \n",
+       "8068275   [[currículo lattes, http://lattes.cnpq.br/6209...   \n",
+       "8184260   [[researchgate adolfo catral , https://www.res...   \n",
+       "8791256   [[find your cannabis & marijuana dispensary , ...   \n",
+       "10174509  [[resume, http://www.biowebspin.com/wp-content...   \n",
+       "10257808  [[01.- juan de dios beltrán mancilla. teoría o...   \n",
+       "10486212  [[gsssietw,mysuru, http://geethashishu.in/], [...   \n",
+       "10652632  [[microsoft academic research, https://academi...   \n",
+       "\n",
        "                           primary_email  \\\n",
        "1025713                             <NA>   \n",
        "2743648               rrom@ise.pw.edu.pl   \n",
@@ -8695,19 +8796,19 @@
        "10652632  aan_jaelani@syekhnurjati.ac.id   \n",
        "\n",
        "                                                   keywords  \\\n",
-       "1025713   [ilmu ekonomi, ekonomi islam, etika bisnis isl...   \n",
-       "2743648   [research systems, measurement systems, photon...   \n",
-       "3011724   [internet of things, next generation of ict an...   \n",
-       "3881064   [nanomaterials and nanocomposites, supercapaci...   \n",
-       "7466062   [filosofía; educación; políticas de desarrollo...   \n",
-       "7517096   [sciences of antiquity, cultural heritage, ear...   \n",
-       "8068275      [inovação, sustentabilidade, empreendedorismo]   \n",
+       "1025713   [etika bisnis islam, ekonomi islam, metodologi...   \n",
+       "2743648   [photonics, research systems, telecommunicatio...   \n",
+       "3011724   [future cyberspace, intelligent transport syst...   \n",
+       "3881064   [technologies of purification of aggressive ga...   \n",
+       "7466062   [justicia global; democracia; derechos humanos...   \n",
+       "7517096   [history of art, international cooperation, hu...   \n",
+       "8068275      [empreendedorismo, sustentabilidade, inovação]   \n",
        "8184260                                                 NaN   \n",
-       "8791256   [marijuana, canabis dispensary, marijuana stoc...   \n",
-       "10174509  [organic chemistry, medicinal and pharmaceutic...   \n",
+       "8791256   [marijuana dispensary, cannabis community, mar...   \n",
+       "10174509  [organic chemistry, photochemistry, biochemist...   \n",
        "10257808  [filosofia medicina arquitectura economía dere...   \n",
-       "10486212  [honorary secretary| iete mysuru centre, profe...   \n",
-       "10652632  [tourism industry, public finance & budgeting,...   \n",
+       "10486212  [mysore region coordinator|ieee bangalore sect...   \n",
+       "10652632  [history of islamic economic thought, islamic ...   \n",
        "\n",
        "                                               external_ids  \\\n",
        "1025713                                                 NaN   \n",
@@ -8889,6 +8990,7 @@
        "      <th>family_name</th>\n",
        "      <th>biography</th>\n",
        "      <th>other_names</th>\n",
+       "      <th>urls</th>\n",
        "      <th>primary_email</th>\n",
        "      <th>keywords</th>\n",
        "      <th>external_ids</th>\n",
@@ -8924,8 +9026,9 @@
        "      <td>goryayinov</td>\n",
        "      <td>&lt;NA&gt;</td>\n",
        "      <td>[алексей николаевич горяинов, о.м.горяїнов, а....</td>\n",
+       "      <td>[[сайт університету, http://khntusg.com.ua/], ...</td>\n",
        "      <td>&lt;NA&gt;</td>\n",
-       "      <td>[diagnostics, transport, logistics]</td>\n",
+       "      <td>[logistics, diagnostics, transport]</td>\n",
        "      <td>[[researcherid, i-7977-2016]]</td>\n",
        "      <td>[[, дистанционный курс «ctl.sc2x: supply chain...</td>\n",
        "      <td>[[docent, kharkiv petro vasylenko national tec...</td>\n",
@@ -8957,6 +9060,7 @@
        "      <td>malahayati</td>\n",
        "      <td>google scholar</td>\n",
        "      <td>NaN</td>\n",
+       "      <td>[[google scholar, https://scholar.google.com/c...</td>\n",
        "      <td>&lt;NA&gt;</td>\n",
        "      <td>NaN</td>\n",
        "      <td>[[researcherid, q-3861-2017]]</td>\n",
@@ -8990,8 +9094,9 @@
        "      <td>barrera</td>\n",
        "      <td>im individual inventor, and this is my work; s...</td>\n",
        "      <td>[retrodynamic, novelinflow]</td>\n",
+       "      <td>[[*wordpress blog state of the art novel inflo...</td>\n",
        "      <td>&lt;NA&gt;</td>\n",
-       "      <td>[engineering, gearturbine, technology, power, ...</td>\n",
+       "      <td>[innovation, mechanical, gearturbine, technolo...</td>\n",
        "      <td>[[loop profile, 394457]]</td>\n",
        "      <td>NaN</td>\n",
        "      <td>NaN</td>\n",
@@ -9023,8 +9128,9 @@
        "      <td>hernández-león</td>\n",
        "      <td>&lt;NA&gt;</td>\n",
        "      <td>[nuria h. león, nuria hernández león, hernánde...</td>\n",
+       "      <td>[[participation in virtual stand as an entrepr...</td>\n",
        "      <td>&lt;NA&gt;</td>\n",
-       "      <td>[icts, human resources, psychology of organiza...</td>\n",
+       "      <td>[psychology of organizations, business managem...</td>\n",
        "      <td>NaN</td>\n",
        "      <td>[[, course: social skills, university of salam...</td>\n",
        "      <td>[[merchandise reception and expedition trainer...</td>\n",
@@ -9056,8 +9162,9 @@
        "      <td>ismail</td>\n",
        "      <td>born in penang, malaysia in 1971, dr. mohd had...</td>\n",
        "      <td>[ndum (national defence university of malaysia)]</td>\n",
+       "      <td>[[1) google scholar, https://scholar.google.co...</td>\n",
        "      <td>&lt;NA&gt;</td>\n",
-       "      <td>[wsn, design of network ip address, network ma...</td>\n",
+       "      <td>[network management, voice over ip, design of ...</td>\n",
        "      <td>[[scopus author id, 24372977800], [researcheri...</td>\n",
        "      <td>NaN</td>\n",
        "      <td>[[lecturer, universiti pertahanan nasional mal...</td>\n",
@@ -9112,6 +9219,7 @@
        "      <td>...</td>\n",
        "      <td>...</td>\n",
        "      <td>...</td>\n",
+       "      <td>...</td>\n",
        "    </tr>\n",
        "    <tr>\n",
        "      <th>10579801</th>\n",
@@ -9122,8 +9230,9 @@
        "      <td>ohara</td>\n",
        "      <td>systematics, evolutionary biology, and the his...</td>\n",
        "      <td>[r. o’hara, r.j. o’hara, robert o’hara, robert...</td>\n",
+       "      <td>[[robert j. o’hara (home), http://rjohara.net]...</td>\n",
        "      <td>&lt;NA&gt;</td>\n",
-       "      <td>[evolutionary biology, education, new england ...</td>\n",
+       "      <td>[evolutionary biology, new england genealogy, ...</td>\n",
        "      <td>[[isni, 0000000138200102], [researcherid, b-47...</td>\n",
        "      <td>[[biology, ph.d., harvard university, cambridg...</td>\n",
        "      <td>NaN</td>\n",
@@ -9155,8 +9264,9 @@
        "      <td>perveen</td>\n",
        "      <td>prof. dr. shagufta perveen is a professor at k...</td>\n",
        "      <td>NaN</td>\n",
+       "      <td>[[personal website, http://www.shaguftaperveen...</td>\n",
        "      <td>shagufta792000@yahoo.com</td>\n",
-       "      <td>[shagufta perveen msu, shagufta perveen uk, sh...</td>\n",
+       "      <td>[shagufta perveen professor, shagufta perveen ...</td>\n",
        "      <td>NaN</td>\n",
        "      <td>[[hej research institute of chemistry, phd che...</td>\n",
        "      <td>[[professor, king saud university college of p...</td>\n",
@@ -9188,8 +9298,9 @@
        "      <td>bastani</td>\n",
        "      <td>&lt;NA&gt;</td>\n",
        "      <td>[s. bastani, سوسن باستانی]</td>\n",
+       "      <td>[[scopus , https://www.scopus.com/authid/detai...</td>\n",
        "      <td>sbastani@alzahra.ac.ir</td>\n",
-       "      <td>[fuzzy logic, personal networks, social networ...</td>\n",
+       "      <td>[social networks, fuzzy logic, personal networ...</td>\n",
        "      <td>[[scopus author id, 16642098400]]</td>\n",
        "      <td>[[sociology, ph.d., university of toronto, tor...</td>\n",
        "      <td>[[professor, alzahra university, tehran, vanak...</td>\n",
@@ -9221,6 +9332,7 @@
        "      <td>kariuki</td>\n",
        "      <td>caroline holds a phd in economics from curtin ...</td>\n",
        "      <td>NaN</td>\n",
+       "      <td>[[scopus profile, https://www.scopus.com/dashb...</td>\n",
        "      <td>&lt;NA&gt;</td>\n",
        "      <td>[applied economics, financial economics, devel...</td>\n",
        "      <td>NaN</td>\n",
@@ -9254,6 +9366,7 @@
        "      <td>kyaw hlaing</td>\n",
        "      <td>&lt;NA&gt;</td>\n",
        "      <td>[dr myo kyaw hlaing]</td>\n",
+       "      <td>[[facebook, https://www.facebook.com/myo.hlain...</td>\n",
        "      <td>&lt;NA&gt;</td>\n",
        "      <td>[economic geology]</td>\n",
        "      <td>NaN</td>\n",
@@ -9280,7 +9393,7 @@
        "    </tr>\n",
        "  </tbody>\n",
        "</table>\n",
-       "<p>140 rows × 30 columns</p>\n",
+       "<p>140 rows × 31 columns</p>\n",
        "</div>"
       ],
       "text/plain": [
@@ -9336,6 +9449,19 @@
        "10807839                                                NaN   \n",
        "10911966                               [dr myo kyaw hlaing]   \n",
        "\n",
+       "                                                       urls  \\\n",
+       "47439     [[сайт університету, http://khntusg.com.ua/], ...   \n",
+       "72557     [[google scholar, https://scholar.google.com/c...   \n",
+       "94081     [[*wordpress blog state of the art novel inflo...   \n",
+       "261673    [[participation in virtual stand as an entrepr...   \n",
+       "326211    [[1) google scholar, https://scholar.google.co...   \n",
+       "...                                                     ...   \n",
+       "10579801  [[robert j. o’hara (home), http://rjohara.net]...   \n",
+       "10590882  [[personal website, http://www.shaguftaperveen...   \n",
+       "10766062  [[scopus , https://www.scopus.com/authid/detai...   \n",
+       "10807839  [[scopus profile, https://www.scopus.com/dashb...   \n",
+       "10911966  [[facebook, https://www.facebook.com/myo.hlain...   \n",
+       "\n",
        "                     primary_email  \\\n",
        "47439                         <NA>   \n",
        "72557                         <NA>   \n",
@@ -9350,15 +9476,15 @@
        "10911966                      <NA>   \n",
        "\n",
        "                                                   keywords  \\\n",
-       "47439                   [diagnostics, transport, logistics]   \n",
+       "47439                   [logistics, diagnostics, transport]   \n",
        "72557                                                   NaN   \n",
-       "94081     [engineering, gearturbine, technology, power, ...   \n",
-       "261673    [icts, human resources, psychology of organiza...   \n",
-       "326211    [wsn, design of network ip address, network ma...   \n",
+       "94081     [innovation, mechanical, gearturbine, technolo...   \n",
+       "261673    [psychology of organizations, business managem...   \n",
+       "326211    [network management, voice over ip, design of ...   \n",
        "...                                                     ...   \n",
-       "10579801  [evolutionary biology, education, new england ...   \n",
-       "10590882  [shagufta perveen msu, shagufta perveen uk, sh...   \n",
-       "10766062  [fuzzy logic, personal networks, social networ...   \n",
+       "10579801  [evolutionary biology, new england genealogy, ...   \n",
+       "10590882  [shagufta perveen professor, shagufta perveen ...   \n",
+       "10766062  [social networks, fuzzy logic, personal networ...   \n",
        "10807839  [applied economics, financial economics, devel...   \n",
        "10911966                                 [economic geology]   \n",
        "\n",
@@ -9466,7 +9592,7 @@
        "10807839   <NA>           4            3             6  \n",
        "10911966   <NA>           1         <NA>             2  \n",
        "\n",
-       "[140 rows x 30 columns]"
+       "[140 rows x 31 columns]"
       ]
      },
      "execution_count": 34,
@@ -9513,6 +9639,7 @@
        "      <th>family_name</th>\n",
        "      <th>biography</th>\n",
        "      <th>other_names</th>\n",
+       "      <th>urls</th>\n",
        "      <th>primary_email</th>\n",
        "      <th>keywords</th>\n",
        "      <th>external_ids</th>\n",
@@ -9548,8 +9675,9 @@
        "      <td>goryayinov</td>\n",
        "      <td>&lt;NA&gt;</td>\n",
        "      <td>[алексей николаевич горяинов, о.м.горяїнов, а....</td>\n",
+       "      <td>[[сайт університету, http://khntusg.com.ua/], ...</td>\n",
        "      <td>&lt;NA&gt;</td>\n",
-       "      <td>[diagnostics, transport, logistics]</td>\n",
+       "      <td>[logistics, diagnostics, transport]</td>\n",
        "      <td>[[researcherid, i-7977-2016]]</td>\n",
        "      <td>[[, дистанционный курс «ctl.sc2x: supply chain...</td>\n",
        "      <td>[[docent, kharkiv petro vasylenko national tec...</td>\n",
@@ -9581,6 +9709,7 @@
        "      <td>malahayati</td>\n",
        "      <td>google scholar</td>\n",
        "      <td>NaN</td>\n",
+       "      <td>[[google scholar, https://scholar.google.com/c...</td>\n",
        "      <td>&lt;NA&gt;</td>\n",
        "      <td>NaN</td>\n",
        "      <td>[[researcherid, q-3861-2017]]</td>\n",
@@ -9614,8 +9743,9 @@
        "      <td>barrera</td>\n",
        "      <td>im individual inventor, and this is my work; s...</td>\n",
        "      <td>[retrodynamic, novelinflow]</td>\n",
+       "      <td>[[*wordpress blog state of the art novel inflo...</td>\n",
        "      <td>&lt;NA&gt;</td>\n",
-       "      <td>[engineering, gearturbine, technology, power, ...</td>\n",
+       "      <td>[innovation, mechanical, gearturbine, technolo...</td>\n",
        "      <td>[[loop profile, 394457]]</td>\n",
        "      <td>NaN</td>\n",
        "      <td>NaN</td>\n",
@@ -9647,8 +9777,9 @@
        "      <td>hernández-león</td>\n",
        "      <td>&lt;NA&gt;</td>\n",
        "      <td>[nuria h. león, nuria hernández león, hernánde...</td>\n",
+       "      <td>[[participation in virtual stand as an entrepr...</td>\n",
        "      <td>&lt;NA&gt;</td>\n",
-       "      <td>[icts, human resources, psychology of organiza...</td>\n",
+       "      <td>[psychology of organizations, business managem...</td>\n",
        "      <td>NaN</td>\n",
        "      <td>[[, course: social skills, university of salam...</td>\n",
        "      <td>[[merchandise reception and expedition trainer...</td>\n",
@@ -9680,8 +9811,9 @@
        "      <td>ismail</td>\n",
        "      <td>born in penang, malaysia in 1971, dr. mohd had...</td>\n",
        "      <td>[ndum (national defence university of malaysia)]</td>\n",
+       "      <td>[[1) google scholar, https://scholar.google.co...</td>\n",
        "      <td>&lt;NA&gt;</td>\n",
-       "      <td>[wsn, design of network ip address, network ma...</td>\n",
+       "      <td>[network management, voice over ip, design of ...</td>\n",
        "      <td>[[scopus author id, 24372977800], [researcheri...</td>\n",
        "      <td>NaN</td>\n",
        "      <td>[[lecturer, universiti pertahanan nasional mal...</td>\n",
@@ -9736,6 +9868,7 @@
        "      <td>...</td>\n",
        "      <td>...</td>\n",
        "      <td>...</td>\n",
+       "      <td>...</td>\n",
        "    </tr>\n",
        "    <tr>\n",
        "      <th>135</th>\n",
@@ -9746,8 +9879,9 @@
        "      <td>ohara</td>\n",
        "      <td>systematics, evolutionary biology, and the his...</td>\n",
        "      <td>[r. o’hara, r.j. o’hara, robert o’hara, robert...</td>\n",
+       "      <td>[[robert j. o’hara (home), http://rjohara.net]...</td>\n",
        "      <td>&lt;NA&gt;</td>\n",
-       "      <td>[evolutionary biology, education, new england ...</td>\n",
+       "      <td>[evolutionary biology, new england genealogy, ...</td>\n",
        "      <td>[[isni, 0000000138200102], [researcherid, b-47...</td>\n",
        "      <td>[[biology, ph.d., harvard university, cambridg...</td>\n",
        "      <td>NaN</td>\n",
@@ -9779,8 +9913,9 @@
        "      <td>perveen</td>\n",
        "      <td>prof. dr. shagufta perveen is a professor at k...</td>\n",
        "      <td>NaN</td>\n",
+       "      <td>[[personal website, http://www.shaguftaperveen...</td>\n",
        "      <td>shagufta792000@yahoo.com</td>\n",
-       "      <td>[shagufta perveen msu, shagufta perveen uk, sh...</td>\n",
+       "      <td>[shagufta perveen professor, shagufta perveen ...</td>\n",
        "      <td>NaN</td>\n",
        "      <td>[[hej research institute of chemistry, phd che...</td>\n",
        "      <td>[[professor, king saud university college of p...</td>\n",
@@ -9812,8 +9947,9 @@
        "      <td>bastani</td>\n",
        "      <td>&lt;NA&gt;</td>\n",
        "      <td>[s. bastani, سوسن باستانی]</td>\n",
+       "      <td>[[scopus , https://www.scopus.com/authid/detai...</td>\n",
        "      <td>sbastani@alzahra.ac.ir</td>\n",
-       "      <td>[fuzzy logic, personal networks, social networ...</td>\n",
+       "      <td>[social networks, fuzzy logic, personal networ...</td>\n",
        "      <td>[[scopus author id, 16642098400]]</td>\n",
        "      <td>[[sociology, ph.d., university of toronto, tor...</td>\n",
        "      <td>[[professor, alzahra university, tehran, vanak...</td>\n",
@@ -9845,6 +9981,7 @@
        "      <td>kariuki</td>\n",
        "      <td>caroline holds a phd in economics from curtin ...</td>\n",
        "      <td>NaN</td>\n",
+       "      <td>[[scopus profile, https://www.scopus.com/dashb...</td>\n",
        "      <td>&lt;NA&gt;</td>\n",
        "      <td>[applied economics, financial economics, devel...</td>\n",
        "      <td>NaN</td>\n",
@@ -9878,6 +10015,7 @@
        "      <td>kyaw hlaing</td>\n",
        "      <td>&lt;NA&gt;</td>\n",
        "      <td>[dr myo kyaw hlaing]</td>\n",
+       "      <td>[[facebook, https://www.facebook.com/myo.hlain...</td>\n",
        "      <td>&lt;NA&gt;</td>\n",
        "      <td>[economic geology]</td>\n",
        "      <td>NaN</td>\n",
@@ -9904,7 +10042,7 @@
        "    </tr>\n",
        "  </tbody>\n",
        "</table>\n",
-       "<p>140 rows × 30 columns</p>\n",
+       "<p>140 rows × 31 columns</p>\n",
        "</div>"
       ],
       "text/plain": [
@@ -9960,6 +10098,19 @@
        "138                                                NaN   \n",
        "139                               [dr myo kyaw hlaing]   \n",
        "\n",
+       "                                                  urls  \\\n",
+       "0    [[сайт університету, http://khntusg.com.ua/], ...   \n",
+       "1    [[google scholar, https://scholar.google.com/c...   \n",
+       "2    [[*wordpress blog state of the art novel inflo...   \n",
+       "3    [[participation in virtual stand as an entrepr...   \n",
+       "4    [[1) google scholar, https://scholar.google.co...   \n",
+       "..                                                 ...   \n",
+       "135  [[robert j. o’hara (home), http://rjohara.net]...   \n",
+       "136  [[personal website, http://www.shaguftaperveen...   \n",
+       "137  [[scopus , https://www.scopus.com/authid/detai...   \n",
+       "138  [[scopus profile, https://www.scopus.com/dashb...   \n",
+       "139  [[facebook, https://www.facebook.com/myo.hlain...   \n",
+       "\n",
        "                primary_email  \\\n",
        "0                        <NA>   \n",
        "1                        <NA>   \n",
@@ -9974,15 +10125,15 @@
        "139                      <NA>   \n",
        "\n",
        "                                              keywords  \\\n",
-       "0                  [diagnostics, transport, logistics]   \n",
+       "0                  [logistics, diagnostics, transport]   \n",
        "1                                                  NaN   \n",
-       "2    [engineering, gearturbine, technology, power, ...   \n",
-       "3    [icts, human resources, psychology of organiza...   \n",
-       "4    [wsn, design of network ip address, network ma...   \n",
+       "2    [innovation, mechanical, gearturbine, technolo...   \n",
+       "3    [psychology of organizations, business managem...   \n",
+       "4    [network management, voice over ip, design of ...   \n",
        "..                                                 ...   \n",
-       "135  [evolutionary biology, education, new england ...   \n",
-       "136  [shagufta perveen msu, shagufta perveen uk, sh...   \n",
-       "137  [fuzzy logic, personal networks, social networ...   \n",
+       "135  [evolutionary biology, new england genealogy, ...   \n",
+       "136  [shagufta perveen professor, shagufta perveen ...   \n",
+       "137  [social networks, fuzzy logic, personal networ...   \n",
        "138  [applied economics, financial economics, devel...   \n",
        "139                                 [economic geology]   \n",
        "\n",
@@ -10090,7 +10241,7 @@
        "138   <NA>           4            3             6  \n",
        "139   <NA>           1         <NA>             2  \n",
        "\n",
-       "[140 rows x 30 columns]"
+       "[140 rows x 31 columns]"
       ]
      },
      "execution_count": 35,
@@ -10138,6 +10289,7 @@
        "      <th>family_name</th>\n",
        "      <th>biography</th>\n",
        "      <th>other_names</th>\n",
+       "      <th>urls</th>\n",
        "      <th>primary_email</th>\n",
        "      <th>keywords</th>\n",
        "      <th>external_ids</th>\n",
@@ -10173,8 +10325,9 @@
        "      <td>goryayinov</td>\n",
        "      <td>&lt;NA&gt;</td>\n",
        "      <td>[алексей николаевич горяинов, о.м.горяїнов, а....</td>\n",
+       "      <td>[[сайт університету, http://khntusg.com.ua/], ...</td>\n",
        "      <td>&lt;NA&gt;</td>\n",
-       "      <td>[diagnostics, transport, logistics]</td>\n",
+       "      <td>[logistics, diagnostics, transport]</td>\n",
        "      <td>[[researcherid, i-7977-2016]]</td>\n",
        "      <td>[[, дистанционный курс «ctl.sc2x: supply chain...</td>\n",
        "      <td>[[docent, kharkiv petro vasylenko national tec...</td>\n",
@@ -10206,6 +10359,7 @@
        "      <td>malahayati</td>\n",
        "      <td>google scholar</td>\n",
        "      <td>NaN</td>\n",
+       "      <td>[[google scholar, https://scholar.google.com/c...</td>\n",
        "      <td>&lt;NA&gt;</td>\n",
        "      <td>NaN</td>\n",
        "      <td>[[researcherid, q-3861-2017]]</td>\n",
@@ -10239,8 +10393,9 @@
        "      <td>barrera</td>\n",
        "      <td>im individual inventor, and this is my work; s...</td>\n",
        "      <td>[retrodynamic, novelinflow]</td>\n",
+       "      <td>[[*wordpress blog state of the art novel inflo...</td>\n",
        "      <td>&lt;NA&gt;</td>\n",
-       "      <td>[engineering, gearturbine, technology, power, ...</td>\n",
+       "      <td>[innovation, mechanical, gearturbine, technolo...</td>\n",
        "      <td>[[loop profile, 394457]]</td>\n",
        "      <td>NaN</td>\n",
        "      <td>NaN</td>\n",
@@ -10272,8 +10427,9 @@
        "      <td>hernández-león</td>\n",
        "      <td>&lt;NA&gt;</td>\n",
        "      <td>[nuria h. león, nuria hernández león, hernánde...</td>\n",
+       "      <td>[[participation in virtual stand as an entrepr...</td>\n",
        "      <td>&lt;NA&gt;</td>\n",
-       "      <td>[icts, human resources, psychology of organiza...</td>\n",
+       "      <td>[psychology of organizations, business managem...</td>\n",
        "      <td>NaN</td>\n",
        "      <td>[[, course: social skills, university of salam...</td>\n",
        "      <td>[[merchandise reception and expedition trainer...</td>\n",
@@ -10305,6 +10461,7 @@
        "      <td>sarmento</td>\n",
        "      <td>clara sarmento holds an aggregation in cultura...</td>\n",
        "      <td>NaN</td>\n",
+       "      <td>[[centre for intercultural studies, http://www...</td>\n",
        "      <td>&lt;NA&gt;</td>\n",
        "      <td>[ethnography, portuguese culture and literatur...</td>\n",
        "      <td>[[ciência id, d418-d6f8-7d49]]</td>\n",
@@ -10361,6 +10518,7 @@
        "      <td>...</td>\n",
        "      <td>...</td>\n",
        "      <td>...</td>\n",
+       "      <td>...</td>\n",
        "    </tr>\n",
        "    <tr>\n",
        "      <th>133</th>\n",
@@ -10371,8 +10529,9 @@
        "      <td>ahmed</td>\n",
        "      <td>sheikh saifullah ahmed is a full-time lecturer...</td>\n",
        "      <td>NaN</td>\n",
+       "      <td>[[academia.edu, https://independent.academia.e...</td>\n",
        "      <td>saifullahahmedku@gmail.com</td>\n",
-       "      <td>[post-truth, postmodern literature, critical t...</td>\n",
+       "      <td>[postmodern literature, south asian literature...</td>\n",
        "      <td>NaN</td>\n",
        "      <td>[[english discipline , ma &amp; ba in english , kh...</td>\n",
        "      <td>[[lecturer , international university of busin...</td>\n",
@@ -10404,6 +10563,7 @@
        "      <td>protocol</td>\n",
        "      <td>&lt;NA&gt;</td>\n",
        "      <td>NaN</td>\n",
+       "      <td>[[about, https://about.me/textprotocol], [figm...</td>\n",
        "      <td>&lt;NA&gt;</td>\n",
        "      <td>NaN</td>\n",
        "      <td>NaN</td>\n",
@@ -10437,8 +10597,9 @@
        "      <td>ohara</td>\n",
        "      <td>systematics, evolutionary biology, and the his...</td>\n",
        "      <td>[r. o’hara, r.j. o’hara, robert o’hara, robert...</td>\n",
+       "      <td>[[robert j. o’hara (home), http://rjohara.net]...</td>\n",
        "      <td>&lt;NA&gt;</td>\n",
-       "      <td>[evolutionary biology, education, new england ...</td>\n",
+       "      <td>[evolutionary biology, new england genealogy, ...</td>\n",
        "      <td>[[isni, 0000000138200102], [researcherid, b-47...</td>\n",
        "      <td>[[biology, ph.d., harvard university, cambridg...</td>\n",
        "      <td>NaN</td>\n",
@@ -10470,6 +10631,7 @@
        "      <td>kariuki</td>\n",
        "      <td>caroline holds a phd in economics from curtin ...</td>\n",
        "      <td>NaN</td>\n",
+       "      <td>[[scopus profile, https://www.scopus.com/dashb...</td>\n",
        "      <td>&lt;NA&gt;</td>\n",
        "      <td>[applied economics, financial economics, devel...</td>\n",
        "      <td>NaN</td>\n",
@@ -10503,6 +10665,7 @@
        "      <td>kyaw hlaing</td>\n",
        "      <td>&lt;NA&gt;</td>\n",
        "      <td>[dr myo kyaw hlaing]</td>\n",
+       "      <td>[[facebook, https://www.facebook.com/myo.hlain...</td>\n",
        "      <td>&lt;NA&gt;</td>\n",
        "      <td>[economic geology]</td>\n",
        "      <td>NaN</td>\n",
@@ -10529,7 +10692,7 @@
        "    </tr>\n",
        "  </tbody>\n",
        "</table>\n",
-       "<p>113 rows × 30 columns</p>\n",
+       "<p>113 rows × 31 columns</p>\n",
        "</div>"
       ],
       "text/plain": [
@@ -10585,6 +10748,19 @@
        "138                                                NaN   \n",
        "139                               [dr myo kyaw hlaing]   \n",
        "\n",
+       "                                                  urls  \\\n",
+       "0    [[сайт університету, http://khntusg.com.ua/], ...   \n",
+       "1    [[google scholar, https://scholar.google.com/c...   \n",
+       "2    [[*wordpress blog state of the art novel inflo...   \n",
+       "3    [[participation in virtual stand as an entrepr...   \n",
+       "5    [[centre for intercultural studies, http://www...   \n",
+       "..                                                 ...   \n",
+       "133  [[academia.edu, https://independent.academia.e...   \n",
+       "134  [[about, https://about.me/textprotocol], [figm...   \n",
+       "135  [[robert j. o’hara (home), http://rjohara.net]...   \n",
+       "138  [[scopus profile, https://www.scopus.com/dashb...   \n",
+       "139  [[facebook, https://www.facebook.com/myo.hlain...   \n",
+       "\n",
        "                  primary_email  \\\n",
        "0                          <NA>   \n",
        "1                          <NA>   \n",
@@ -10599,15 +10775,15 @@
        "139                        <NA>   \n",
        "\n",
        "                                              keywords  \\\n",
-       "0                  [diagnostics, transport, logistics]   \n",
+       "0                  [logistics, diagnostics, transport]   \n",
        "1                                                  NaN   \n",
-       "2    [engineering, gearturbine, technology, power, ...   \n",
-       "3    [icts, human resources, psychology of organiza...   \n",
+       "2    [innovation, mechanical, gearturbine, technolo...   \n",
+       "3    [psychology of organizations, business managem...   \n",
        "5    [ethnography, portuguese culture and literatur...   \n",
        "..                                                 ...   \n",
-       "133  [post-truth, postmodern literature, critical t...   \n",
+       "133  [postmodern literature, south asian literature...   \n",
        "134                                                NaN   \n",
-       "135  [evolutionary biology, education, new england ...   \n",
+       "135  [evolutionary biology, new england genealogy, ...   \n",
        "138  [applied economics, financial economics, devel...   \n",
        "139                                 [economic geology]   \n",
        "\n",
@@ -10715,7 +10891,7 @@
        "138   <NA>           4            3             6  \n",
        "139   <NA>           1         <NA>             2  \n",
        "\n",
-       "[113 rows x 30 columns]"
+       "[113 rows x 31 columns]"
       ]
      },
      "execution_count": 36,
@@ -10736,7 +10912,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 166,
+   "execution_count": 37,
    "metadata": {},
    "outputs": [],
    "source": [
@@ -10746,7 +10922,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 223,
+   "execution_count": 38,
    "metadata": {},
    "outputs": [],
    "source": [
@@ -10756,7 +10932,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 171,
+   "execution_count": 39,
    "metadata": {},
    "outputs": [
     {
@@ -10868,7 +11044,7 @@
        "[98933 rows x 2 columns]"
       ]
      },
-     "execution_count": 171,
+     "execution_count": 39,
      "metadata": {},
      "output_type": "execute_result"
     }
@@ -10879,7 +11055,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 172,
+   "execution_count": 40,
    "metadata": {},
    "outputs": [
     {
@@ -10890,7 +11066,7 @@
        "Name: grid.451498.5, dtype: object"
       ]
      },
-     "execution_count": 172,
+     "execution_count": 40,
      "metadata": {},
      "output_type": "execute_result"
     }
@@ -10901,7 +11077,7 @@
   },
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@@ -11029,7 +11205,7 @@
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@@ -11038,7 +11214,7 @@
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@@ -11050,7 +11226,7 @@
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@@ -11066,7 +11242,7 @@
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@@ -11084,7 +11260,7 @@
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@@ -11094,7 +11270,7 @@
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@@ -11103,7 +11279,7 @@
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@@ -11113,7 +11289,7 @@
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@@ -11125,7 +11301,7 @@
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\"zerolinewidth\": 2}}}, \"title\": {\"text\": \"Top 30 works_source\"}, \"xaxis\": {\"range\": [-0.5, 29.5], \"tickangle\": 45, \"tickfont\": {\"size\": 12}}},                        {\"responsive\": true}                    ).then(function(){\n",
        "                            \n",
-       "var gd = document.getElementById('0a4b955c-97e3-4ada-9140-d2b523c59c6b');\n",
+       "var gd = document.getElementById('6d9236a8-5441-4d60-b1cd-8f0384a22e75');\n",
        "var x = new MutationObserver(function (mutations, observer) {{\n",
        "        var display = window.getComputedStyle(gd).display;\n",
        "        if (!display || display === 'none') {{\n",
@@ -12078,7 +12254,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 43,
+   "execution_count": 52,
    "metadata": {},
    "outputs": [
     {
@@ -12184,7 +12360,7 @@
        "[342 rows x 2 columns]"
       ]
      },
-     "execution_count": 43,
+     "execution_count": 52,
      "metadata": {},
      "output_type": "execute_result"
     }
@@ -12196,7 +12372,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 44,
+   "execution_count": 53,
    "metadata": {},
    "outputs": [],
    "source": [
@@ -12206,7 +12382,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 45,
+   "execution_count": 54,
    "metadata": {},
    "outputs": [],
    "source": [
@@ -12218,7 +12394,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 46,
+   "execution_count": 55,
    "metadata": {},
    "outputs": [],
    "source": [
@@ -12227,7 +12403,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 47,
+   "execution_count": 56,
    "metadata": {},
    "outputs": [],
    "source": [
@@ -12236,7 +12412,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 48,
+   "execution_count": 57,
    "metadata": {},
    "outputs": [
     {
@@ -12267,6 +12443,7 @@
        "      <th>family_name</th>\n",
        "      <th>biography</th>\n",
        "      <th>other_names</th>\n",
+       "      <th>urls</th>\n",
        "      <th>primary_email</th>\n",
        "      <th>keywords</th>\n",
        "      <th>external_ids</th>\n",
@@ -12305,6 +12482,7 @@
        "      <td>&lt;NA&gt;</td>\n",
        "      <td>&lt;NA&gt;</td>\n",
        "      <td>NaN</td>\n",
+       "      <td>NaN</td>\n",
        "      <td>&lt;NA&gt;</td>\n",
        "      <td>NaN</td>\n",
        "      <td>NaN</td>\n",
@@ -12341,6 +12519,7 @@
        "      <td>&lt;NA&gt;</td>\n",
        "      <td>&lt;NA&gt;</td>\n",
        "      <td>[v.i. yurtaev; v. yurtaev]</td>\n",
+       "      <td>NaN</td>\n",
        "      <td>&lt;NA&gt;</td>\n",
        "      <td>NaN</td>\n",
        "      <td>NaN</td>\n",
@@ -12377,6 +12556,7 @@
        "      <td>&lt;NA&gt;</td>\n",
        "      <td>&lt;NA&gt;</td>\n",
        "      <td>NaN</td>\n",
+       "      <td>NaN</td>\n",
        "      <td>&lt;NA&gt;</td>\n",
        "      <td>NaN</td>\n",
        "      <td>NaN</td>\n",
@@ -12413,6 +12593,7 @@
        "      <td>&lt;NA&gt;</td>\n",
        "      <td>&lt;NA&gt;</td>\n",
        "      <td>NaN</td>\n",
+       "      <td>NaN</td>\n",
        "      <td>&lt;NA&gt;</td>\n",
        "      <td>NaN</td>\n",
        "      <td>NaN</td>\n",
@@ -12449,6 +12630,7 @@
        "      <td>&lt;NA&gt;</td>\n",
        "      <td>&lt;NA&gt;</td>\n",
        "      <td>NaN</td>\n",
+       "      <td>NaN</td>\n",
        "      <td>&lt;NA&gt;</td>\n",
        "      <td>NaN</td>\n",
        "      <td>NaN</td>\n",
@@ -12488,57 +12670,57 @@
        "3  0000-0001-6220-5683            True                    True        <NA>   \n",
        "4  0000-0001-7071-8294            True                    True        <NA>   \n",
        "\n",
-       "  family_name biography                 other_names primary_email keywords  \\\n",
-       "0        <NA>      <NA>                         NaN          <NA>      NaN   \n",
-       "1        <NA>      <NA>  [v.i. yurtaev; v. yurtaev]          <NA>      NaN   \n",
-       "2        <NA>      <NA>                         NaN          <NA>      NaN   \n",
-       "3        <NA>      <NA>                         NaN          <NA>      NaN   \n",
-       "4        <NA>      <NA>                         NaN          <NA>      NaN   \n",
+       "  family_name biography                 other_names urls primary_email  \\\n",
+       "0        <NA>      <NA>                         NaN  NaN          <NA>   \n",
+       "1        <NA>      <NA>  [v.i. yurtaev; v. yurtaev]  NaN          <NA>   \n",
+       "2        <NA>      <NA>                         NaN  NaN          <NA>   \n",
+       "3        <NA>      <NA>                         NaN  NaN          <NA>   \n",
+       "4        <NA>      <NA>                         NaN  NaN          <NA>   \n",
        "\n",
-       "  external_ids education                                         employment  \\\n",
-       "0          NaN       NaN                                                NaN   \n",
-       "1          NaN       NaN  [[professor, peoples friendship university of ...   \n",
-       "2          NaN       NaN                                                NaN   \n",
-       "3          NaN       NaN  [[research scientist, new york university abu ...   \n",
-       "4          NaN       NaN  [[researcher (academic), universidad de zarago...   \n",
+       "  keywords external_ids education  \\\n",
+       "0      NaN          NaN       NaN   \n",
+       "1      NaN          NaN       NaN   \n",
+       "2      NaN          NaN       NaN   \n",
+       "3      NaN          NaN       NaN   \n",
+       "4      NaN          NaN       NaN   \n",
        "\n",
-       "   n_works works_source                  activation_date  \\\n",
-       "0        0          NaN 2018-03-02 09:29:16.528000+00:00   \n",
-       "1        0          NaN 2018-04-03 07:50:23.358000+00:00   \n",
-       "2        0          NaN 2019-12-11 15:31:56.388000+00:00   \n",
-       "3        0          NaN 2015-08-18 12:36:45.307000+00:00   \n",
-       "4        0          NaN 2014-03-10 13:22:01.966000+00:00   \n",
+       "                                          employment  n_works works_source  \\\n",
+       "0                                                NaN        0          NaN   \n",
+       "1  [[professor, peoples friendship university of ...        0          NaN   \n",
+       "2                                                NaN        0          NaN   \n",
+       "3  [[research scientist, new york university abu ...        0          NaN   \n",
+       "4  [[researcher (academic), universidad de zarago...        0          NaN   \n",
        "\n",
-       "                  last_update_date  n_doi  n_arxiv  n_pmc  n_other_pids  \\\n",
-       "0 2018-03-02 09:43:07.551000+00:00      0        0      0             0   \n",
-       "1 2020-03-18 09:42:44.753000+00:00      0        0      0             0   \n",
-       "2 2020-01-28 15:34:17.309000+00:00      0        0      0             0   \n",
-       "3 2020-09-23 13:37:54.180000+00:00      0        0      0             0   \n",
-       "4 2016-06-14 22:17:54.470000+00:00      0        0      0             0   \n",
+       "                   activation_date                 last_update_date  n_doi  \\\n",
+       "0 2018-03-02 09:29:16.528000+00:00 2018-03-02 09:43:07.551000+00:00      0   \n",
+       "1 2018-04-03 07:50:23.358000+00:00 2020-03-18 09:42:44.753000+00:00      0   \n",
+       "2 2019-12-11 15:31:56.388000+00:00 2020-01-28 15:34:17.309000+00:00      0   \n",
+       "3 2015-08-18 12:36:45.307000+00:00 2020-09-23 13:37:54.180000+00:00      0   \n",
+       "4 2014-03-10 13:22:01.966000+00:00 2016-06-14 22:17:54.470000+00:00      0   \n",
        "\n",
-       "   label primary_email_domain other_email_domains url_domains  n_emails  \\\n",
-       "0  False                  NaN                 NaN         NaN      <NA>   \n",
-       "1  False                  NaN                 NaN         NaN      <NA>   \n",
-       "2  False                  NaN                 NaN         NaN      <NA>   \n",
-       "3  False                  NaN                 NaN         NaN      <NA>   \n",
-       "4  False                  NaN                 NaN         NaN      <NA>   \n",
+       "   n_arxiv  n_pmc  n_other_pids  label primary_email_domain  \\\n",
+       "0        0      0             0  False                  NaN   \n",
+       "1        0      0             0  False                  NaN   \n",
+       "2        0      0             0  False                  NaN   \n",
+       "3        0      0             0  False                  NaN   \n",
+       "4        0      0             0  False                  NaN   \n",
        "\n",
-       "   n_urls  n_ids  n_keywords  n_education  n_employment ext_works_source  \\\n",
-       "0    <NA>   <NA>        <NA>         <NA>          <NA>              NaN   \n",
-       "1    <NA>   <NA>        <NA>         <NA>             1              NaN   \n",
-       "2    <NA>   <NA>        <NA>         <NA>          <NA>              NaN   \n",
-       "3    <NA>   <NA>        <NA>         <NA>             1              NaN   \n",
-       "4    <NA>   <NA>        <NA>         <NA>             2              NaN   \n",
+       "  other_email_domains url_domains  n_emails  n_urls  n_ids  n_keywords  \\\n",
+       "0                 NaN         NaN      <NA>    <NA>   <NA>        <NA>   \n",
+       "1                 NaN         NaN      <NA>    <NA>   <NA>        <NA>   \n",
+       "2                 NaN         NaN      <NA>    <NA>   <NA>        <NA>   \n",
+       "3                 NaN         NaN      <NA>    <NA>   <NA>        <NA>   \n",
+       "4                 NaN         NaN      <NA>    <NA>   <NA>        <NA>   \n",
        "\n",
-       "   n_ext_work_source authoritative  \n",
-       "0               <NA>         False  \n",
-       "1               <NA>         False  \n",
-       "2               <NA>         False  \n",
-       "3               <NA>         False  \n",
-       "4               <NA>         False  "
+       "   n_education  n_employment ext_works_source  n_ext_work_source authoritative  \n",
+       "0         <NA>          <NA>              NaN               <NA>         False  \n",
+       "1         <NA>             1              NaN               <NA>         False  \n",
+       "2         <NA>          <NA>              NaN               <NA>         False  \n",
+       "3         <NA>             1              NaN               <NA>         False  \n",
+       "4         <NA>             2              NaN               <NA>         False  "
       ]
      },
-     "execution_count": 48,
+     "execution_count": 57,
      "metadata": {},
      "output_type": "execute_result"
     }
@@ -12563,7 +12745,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 49,
+   "execution_count": 58,
    "metadata": {},
    "outputs": [
     {
@@ -12580,7 +12762,7 @@
        "Name: n_ids, dtype: float64"
       ]
      },
-     "execution_count": 49,
+     "execution_count": 58,
      "metadata": {},
      "output_type": "execute_result"
     }
@@ -12591,7 +12773,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 50,
+   "execution_count": 59,
    "metadata": {},
    "outputs": [
     {
@@ -12622,6 +12804,7 @@
        "      <th>family_name</th>\n",
        "      <th>biography</th>\n",
        "      <th>other_names</th>\n",
+       "      <th>urls</th>\n",
        "      <th>primary_email</th>\n",
        "      <th>keywords</th>\n",
        "      <th>external_ids</th>\n",
@@ -12660,6 +12843,7 @@
        "      <td>williams</td>\n",
        "      <td>&lt;NA&gt;</td>\n",
        "      <td>NaN</td>\n",
+       "      <td>[[aston university profile page, https://resea...</td>\n",
        "      <td>&lt;NA&gt;</td>\n",
        "      <td>NaN</td>\n",
        "      <td>[[scopus author id,  55553733518], [scopus aut...</td>\n",
@@ -12695,11 +12879,14 @@
        "                       orcid  verified_email  verified_primary_email  \\\n",
        "3896226  0000-0002-9554-6633            True                    True   \n",
        "\n",
-       "        given_names family_name biography other_names primary_email keywords  \\\n",
-       "3896226      john a    williams      <NA>         NaN          <NA>      NaN   \n",
+       "        given_names family_name biography other_names  \\\n",
+       "3896226      john a    williams      <NA>         NaN   \n",
        "\n",
-       "                                              external_ids education  \\\n",
-       "3896226  [[scopus author id,  55553733518], [scopus aut...       NaN   \n",
+       "                                                      urls primary_email  \\\n",
+       "3896226  [[aston university profile page, https://resea...          <NA>   \n",
+       "\n",
+       "        keywords                                       external_ids education  \\\n",
+       "3896226      NaN  [[scopus author id,  55553733518], [scopus aut...       NaN   \n",
        "\n",
        "                                                employment  n_works  \\\n",
        "3896226  [[, aston university, birmingham, , gb, 1722, ...       92   \n",
@@ -12720,7 +12907,7 @@
        "3896226  [aston research explorer]                  1          True  "
       ]
      },
-     "execution_count": 50,
+     "execution_count": 59,
      "metadata": {},
      "output_type": "execute_result"
     }
@@ -12731,7 +12918,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 51,
+   "execution_count": 60,
    "metadata": {},
    "outputs": [],
    "source": [
@@ -12740,7 +12927,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 52,
+   "execution_count": 61,
    "metadata": {},
    "outputs": [],
    "source": [
@@ -12749,7 +12936,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 53,
+   "execution_count": 62,
    "metadata": {},
    "outputs": [
     {
@@ -12822,7 +13009,7 @@
        "64  0000-0002-7397-5824   [scopus author id, 8399842800]  scopus author id"
       ]
      },
-     "execution_count": 53,
+     "execution_count": 62,
      "metadata": {},
      "output_type": "execute_result"
     }
@@ -12833,7 +13020,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 54,
+   "execution_count": 63,
    "metadata": {},
    "outputs": [],
    "source": [
@@ -12842,7 +13029,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 55,
+   "execution_count": 64,
    "metadata": {},
    "outputs": [
     {
@@ -13775,9 +13962,9 @@
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        "                            \n",
-       "var gd = document.getElementById('2572cb2c-1b94-4da5-af62-2c861756d816');\n",
+       "var gd = document.getElementById('fedcd004-9a2e-404e-8d7b-54e6110f8a39');\n",
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@@ -13824,7 +14011,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 56,
+   "execution_count": 65,
    "metadata": {},
    "outputs": [
     {
@@ -13845,7 +14032,7 @@
        "       'profile system identifier', 'custom'], dtype=object)"
       ]
      },
-     "execution_count": 56,
+     "execution_count": 65,
      "metadata": {},
      "output_type": "execute_result"
     }
@@ -13870,7 +14057,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 57,
+   "execution_count": 66,
    "metadata": {},
    "outputs": [
     {
@@ -13976,7 +14163,7 @@
        "[10989649 rows x 2 columns]"
       ]
      },
-     "execution_count": 57,
+     "execution_count": 66,
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@@ -13988,7 +14175,7 @@
   },
   {
    "cell_type": "code",
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+   "execution_count": 67,
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@@ -15095,7 +15282,7 @@
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        "                            \n",
-       "var gd = document.getElementById('61129bea-0dba-4d3f-8d15-c0d72e988c34');\n",
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@@ -16091,7 +16278,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 61,
+   "execution_count": 70,
    "metadata": {},
    "outputs": [
     {
@@ -16108,7 +16295,7 @@
        "Name: n_education, dtype: float64"
       ]
      },
-     "execution_count": 61,
+     "execution_count": 70,
      "metadata": {},
      "output_type": "execute_result"
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@@ -16119,7 +16306,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 62,
+   "execution_count": 71,
    "metadata": {},
    "outputs": [
     {
@@ -16150,6 +16337,7 @@
        "      <th>family_name</th>\n",
        "      <th>biography</th>\n",
        "      <th>other_names</th>\n",
+       "      <th>urls</th>\n",
        "      <th>primary_email</th>\n",
        "      <th>keywords</th>\n",
        "      <th>external_ids</th>\n",
@@ -16188,8 +16376,9 @@
        "      <td>galvez-sánchez</td>\n",
        "      <td>my name is carmen maria galvez sánchez. i´m a ...</td>\n",
        "      <td>NaN</td>\n",
+       "      <td>NaN</td>\n",
        "      <td>&lt;NA&gt;</td>\n",
-       "      <td>[gender-based violence, fibromyalgia, quantita...</td>\n",
+       "      <td>[fibromyalgia, qualitative research, quantitat...</td>\n",
        "      <td>[[loop profile, 509331], [scopus author id, 57...</td>\n",
        "      <td>[[psychology, 2019-2020 course. degree in psyc...</td>\n",
        "      <td>[[researcher and teaching staff. postdoctoral ...</td>\n",
@@ -16226,11 +16415,11 @@
        "            given_names     family_name  \\\n",
        "10536169  phd. carmen m  galvez-sánchez   \n",
        "\n",
-       "                                                  biography other_names  \\\n",
-       "10536169  my name is carmen maria galvez sánchez. i´m a ...         NaN   \n",
+       "                                                  biography other_names urls  \\\n",
+       "10536169  my name is carmen maria galvez sánchez. i´m a ...         NaN  NaN   \n",
        "\n",
        "         primary_email                                           keywords  \\\n",
-       "10536169          <NA>  [gender-based violence, fibromyalgia, quantita...   \n",
+       "10536169          <NA>  [fibromyalgia, qualitative research, quantitat...   \n",
        "\n",
        "                                               external_ids  \\\n",
        "10536169  [[loop profile, 509331], [scopus author id, 57...   \n",
@@ -16263,7 +16452,7 @@
        "10536169                  4          True  "
       ]
      },
-     "execution_count": 62,
+     "execution_count": 71,
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@@ -16274,7 +16463,7 @@
   },
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+   "execution_count": 72,
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@@ -16393,7 +16582,7 @@
        "[4434439 rows x 2 columns]"
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-     "execution_count": 63,
+     "execution_count": 72,
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@@ -16405,7 +16594,7 @@
   },
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+   "execution_count": 73,
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@@ -16414,7 +16603,7 @@
   },
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    "source": [
@@ -16423,7 +16612,7 @@
   },
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+   "execution_count": 75,
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@@ -16529,7 +16718,7 @@
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-     "execution_count": 68,
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@@ -16540,7 +16729,7 @@
   },
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@@ -16550,7 +16739,7 @@
   },
   {
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-   "execution_count": 70,
+   "execution_count": 77,
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     {
@@ -16581,6 +16770,7 @@
        "      <th>family_name</th>\n",
        "      <th>biography</th>\n",
        "      <th>other_names</th>\n",
+       "      <th>urls</th>\n",
        "      <th>primary_email</th>\n",
        "      <th>keywords</th>\n",
        "      <th>external_ids</th>\n",
@@ -16620,8 +16810,9 @@
        "      <td>&lt;NA&gt;</td>\n",
        "      <td>&lt;NA&gt;</td>\n",
        "      <td>NaN</td>\n",
+       "      <td>[[currículo lattes, https://wwws.cnpq.br/cvlat...</td>\n",
        "      <td>&lt;NA&gt;</td>\n",
-       "      <td>[migration, culture cell, prostate cancer]</td>\n",
+       "      <td>[migration, prostate cancer, culture cell]</td>\n",
        "      <td>[[researcherid, p-2223-2018]]</td>\n",
        "      <td>[[morfologia, , universidade estadual paulista...</td>\n",
        "      <td>[[, universidade estadual paulista (unesp), in...</td>\n",
@@ -16657,6 +16848,7 @@
        "      <td>inci</td>\n",
        "      <td>i am a professor of finance at bryant universi...</td>\n",
        "      <td>NaN</td>\n",
+       "      <td>NaN</td>\n",
        "      <td>&lt;NA&gt;</td>\n",
        "      <td>NaN</td>\n",
        "      <td>[[researcherid, b-5471-2018], [scopus author i...</td>\n",
@@ -16694,6 +16886,7 @@
        "      <td>asis pata</td>\n",
        "      <td>&lt;NA&gt;</td>\n",
        "      <td>NaN</td>\n",
+       "      <td>NaN</td>\n",
        "      <td>&lt;NA&gt;</td>\n",
        "      <td>NaN</td>\n",
        "      <td>NaN</td>\n",
@@ -16731,6 +16924,7 @@
        "      <td>muhammad</td>\n",
        "      <td>&lt;NA&gt;</td>\n",
        "      <td>NaN</td>\n",
+       "      <td>NaN</td>\n",
        "      <td>&lt;NA&gt;</td>\n",
        "      <td>NaN</td>\n",
        "      <td>NaN</td>\n",
@@ -16768,6 +16962,7 @@
        "      <td>mamadou</td>\n",
        "      <td>&lt;NA&gt;</td>\n",
        "      <td>NaN</td>\n",
+       "      <td>NaN</td>\n",
        "      <td>&lt;NA&gt;</td>\n",
        "      <td>NaN</td>\n",
        "      <td>NaN</td>\n",
@@ -16832,6 +17027,7 @@
        "      <td>...</td>\n",
        "      <td>...</td>\n",
        "      <td>...</td>\n",
+       "      <td>...</td>\n",
        "    </tr>\n",
        "    <tr>\n",
        "      <th>10989595</th>\n",
@@ -16842,8 +17038,9 @@
        "      <td>cázares-marinero</td>\n",
        "      <td>&lt;NA&gt;</td>\n",
        "      <td>[josé cázares]</td>\n",
+       "      <td>[[linkedin, https://www.linkedin.com/feed/], [...</td>\n",
        "      <td>&lt;NA&gt;</td>\n",
-       "      <td>[chemistry, chemical biology, industrial chemi...</td>\n",
+       "      <td>[industrial chemistry, chemistry, chemical bio...</td>\n",
        "      <td>[[researcherid, h-2597-2013], [scopus author i...</td>\n",
        "      <td>[[charles friedel, postdoc, école nationale su...</td>\n",
        "      <td>[[mtc, polioles, mexico, , mx, , ], [head of r...</td>\n",
@@ -16879,8 +17076,9 @@
        "      <td>&lt;NA&gt;</td>\n",
        "      <td>mestranda em tecnologia na saúde e foi aluna o...</td>\n",
        "      <td>[luana bastos morey]</td>\n",
+       "      <td>[[site da equipe unidos pela saúde  (voluntári...</td>\n",
        "      <td>&lt;NA&gt;</td>\n",
-       "      <td>[tradução; língua espanhol; língua portuguesa;...</td>\n",
+       "      <td>[libras; língua de sinais brasileira, tradução...</td>\n",
        "      <td>NaN</td>\n",
        "      <td>[[pós-graduação em tecnologia em saúde stricto...</td>\n",
        "      <td>[[professora de espanhol e português para estr...</td>\n",
@@ -16916,8 +17114,9 @@
        "      <td>antypenko</td>\n",
        "      <td>the phd degree of pharmacy was received under ...</td>\n",
        "      <td>[lyudmila nikolaevna antipenko (russian transl...</td>\n",
+       "      <td>NaN</td>\n",
        "      <td>&lt;NA&gt;</td>\n",
-       "      <td>[structure elucidation, organic synthesis, val...</td>\n",
+       "      <td>[organic synthesis, structure elucidation, pha...</td>\n",
        "      <td>[[scopus author id, 55070809900], [researcheri...</td>\n",
        "      <td>[[centre for nanomaterials, advanced technolog...</td>\n",
        "      <td>[[visiting scientist, north dakota state unive...</td>\n",
@@ -16953,8 +17152,9 @@
        "      <td>teixeira</td>\n",
        "      <td>2005 - phd, university of coimbrajuly 2009-jun...</td>\n",
        "      <td>NaN</td>\n",
+       "      <td>NaN</td>\n",
        "      <td>&lt;NA&gt;</td>\n",
-       "      <td>[estua, heavy metals, steroid hormones, ecotox...</td>\n",
+       "      <td>[heavy metals, climate change, ecotoxicology, ...</td>\n",
        "      <td>[[researcherid, i-6863-2013], [scopus author i...</td>\n",
        "      <td>[[, phd, university of coimbra, coimbra, , pt,...</td>\n",
        "      <td>[[senior researcher, university of coimbra, co...</td>\n",
@@ -16990,6 +17190,7 @@
        "      <td>wang</td>\n",
        "      <td>youxia wang (1995-), native of zunyi, guizhou ...</td>\n",
        "      <td>NaN</td>\n",
+       "      <td>NaN</td>\n",
        "      <td>&lt;NA&gt;</td>\n",
        "      <td>NaN</td>\n",
        "      <td>NaN</td>\n",
@@ -17020,7 +17221,7 @@
        "    </tr>\n",
        "  </tbody>\n",
        "</table>\n",
-       "<p>641229 rows × 34 columns</p>\n",
+       "<p>641229 rows × 35 columns</p>\n",
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       "text/plain": [
@@ -17063,30 +17264,43 @@
        "10989619  2005 - phd, university of coimbrajuly 2009-jun...   \n",
        "10989644  youxia wang (1995-), native of zunyi, guizhou ...   \n",
        "\n",
-       "                                                other_names primary_email  \\\n",
-       "46                                                      NaN          <NA>   \n",
-       "74                                                      NaN          <NA>   \n",
-       "88                                                      NaN          <NA>   \n",
-       "98                                                      NaN          <NA>   \n",
-       "101                                                     NaN          <NA>   \n",
-       "...                                                     ...           ...   \n",
-       "10989595                                     [josé cázares]          <NA>   \n",
-       "10989603                               [luana bastos morey]          <NA>   \n",
-       "10989605  [lyudmila nikolaevna antipenko (russian transl...          <NA>   \n",
-       "10989619                                                NaN          <NA>   \n",
-       "10989644                                                NaN          <NA>   \n",
-       "\n",
-       "                                                   keywords  \\\n",
-       "46               [migration, culture cell, prostate cancer]   \n",
+       "                                                other_names  \\\n",
+       "46                                                      NaN   \n",
        "74                                                      NaN   \n",
        "88                                                      NaN   \n",
        "98                                                      NaN   \n",
        "101                                                     NaN   \n",
        "...                                                     ...   \n",
-       "10989595  [chemistry, chemical biology, industrial chemi...   \n",
-       "10989603  [tradução; língua espanhol; língua portuguesa;...   \n",
-       "10989605  [structure elucidation, organic synthesis, val...   \n",
-       "10989619  [estua, heavy metals, steroid hormones, ecotox...   \n",
+       "10989595                                     [josé cázares]   \n",
+       "10989603                               [luana bastos morey]   \n",
+       "10989605  [lyudmila nikolaevna antipenko (russian transl...   \n",
+       "10989619                                                NaN   \n",
+       "10989644                                                NaN   \n",
+       "\n",
+       "                                                       urls primary_email  \\\n",
+       "46        [[currículo lattes, https://wwws.cnpq.br/cvlat...          <NA>   \n",
+       "74                                                      NaN          <NA>   \n",
+       "88                                                      NaN          <NA>   \n",
+       "98                                                      NaN          <NA>   \n",
+       "101                                                     NaN          <NA>   \n",
+       "...                                                     ...           ...   \n",
+       "10989595  [[linkedin, https://www.linkedin.com/feed/], [...          <NA>   \n",
+       "10989603  [[site da equipe unidos pela saúde  (voluntári...          <NA>   \n",
+       "10989605                                                NaN          <NA>   \n",
+       "10989619                                                NaN          <NA>   \n",
+       "10989644                                                NaN          <NA>   \n",
+       "\n",
+       "                                                   keywords  \\\n",
+       "46               [migration, prostate cancer, culture cell]   \n",
+       "74                                                      NaN   \n",
+       "88                                                      NaN   \n",
+       "98                                                      NaN   \n",
+       "101                                                     NaN   \n",
+       "...                                                     ...   \n",
+       "10989595  [industrial chemistry, chemistry, chemical bio...   \n",
+       "10989603  [libras; língua de sinais brasileira, tradução...   \n",
+       "10989605  [organic synthesis, structure elucidation, pha...   \n",
+       "10989619  [heavy metals, climate change, ecotoxicology, ...   \n",
        "10989644                                                NaN   \n",
        "\n",
        "                                               external_ids  \\\n",
@@ -17232,10 +17446,10 @@
        "10989619                  4          True                0.0  \n",
        "10989644               <NA>         False                1.0  \n",
        "\n",
-       "[641229 rows x 34 columns]"
+       "[641229 rows x 35 columns]"
       ]
      },
-     "execution_count": 70,
+     "execution_count": 77,
      "metadata": {},
      "output_type": "execute_result"
     }
@@ -17253,7 +17467,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 71,
+   "execution_count": 78,
    "metadata": {},
    "outputs": [
     {
@@ -17270,7 +17484,7 @@
        "Name: n_employment, dtype: float64"
       ]
      },
-     "execution_count": 71,
+     "execution_count": 78,
      "metadata": {},
      "output_type": "execute_result"
     }
@@ -17281,7 +17495,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 72,
+   "execution_count": 79,
    "metadata": {},
    "outputs": [
     {
@@ -17312,6 +17526,7 @@
        "      <th>family_name</th>\n",
        "      <th>biography</th>\n",
        "      <th>other_names</th>\n",
+       "      <th>urls</th>\n",
        "      <th>primary_email</th>\n",
        "      <th>keywords</th>\n",
        "      <th>external_ids</th>\n",
@@ -17351,8 +17566,9 @@
        "      <td>tang</td>\n",
        "      <td>&lt;NA&gt;</td>\n",
        "      <td>[唐本忠]</td>\n",
+       "      <td>[[homepage, http://ihome.ust.hk/~tangbenz/]]</td>\n",
        "      <td>tangbenz@ust.hk</td>\n",
-       "      <td>[nanotechnology, fluorescent biosensors, optic...</td>\n",
+       "      <td>[light-emitting molecules, polymer chemistry, ...</td>\n",
        "      <td>[[hkust profile, tang-benzhong], [researcherid...</td>\n",
        "      <td>[[department of chemistry and faculty of pharm...</td>\n",
        "      <td>[[chair professor, division of biomedical engi...</td>\n",
@@ -17387,11 +17603,14 @@
        "                       orcid  verified_email  verified_primary_email  \\\n",
        "8289432  0000-0002-0293-964X            True                    True   \n",
        "\n",
-       "        given_names family_name biography other_names    primary_email  \\\n",
-       "8289432   ben zhong        tang      <NA>       [唐本忠]  tangbenz@ust.hk   \n",
+       "        given_names family_name biography other_names  \\\n",
+       "8289432   ben zhong        tang      <NA>       [唐本忠]   \n",
+       "\n",
+       "                                                 urls    primary_email  \\\n",
+       "8289432  [[homepage, http://ihome.ust.hk/~tangbenz/]]  tangbenz@ust.hk   \n",
        "\n",
        "                                                  keywords  \\\n",
-       "8289432  [nanotechnology, fluorescent biosensors, optic...   \n",
+       "8289432  [light-emitting molecules, polymer chemistry, ...   \n",
        "\n",
        "                                              external_ids  \\\n",
        "8289432  [[hkust profile, tang-benzhong], [researcherid...   \n",
@@ -17418,7 +17637,7 @@
        "8289432       [crossref]                  1          True                3.0  "
       ]
      },
-     "execution_count": 72,
+     "execution_count": 79,
      "metadata": {},
      "output_type": "execute_result"
     }
@@ -17436,7 +17655,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 73,
+   "execution_count": 80,
    "metadata": {},
    "outputs": [
     {
@@ -17555,7 +17774,7 @@
        "[4462243 rows x 2 columns]"
       ]
      },
-     "execution_count": 73,
+     "execution_count": 80,
      "metadata": {},
      "output_type": "execute_result"
     }
@@ -17567,7 +17786,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 74,
+   "execution_count": 81,
    "metadata": {},
    "outputs": [],
    "source": [
@@ -17576,7 +17795,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 75,
+   "execution_count": 82,
    "metadata": {},
    "outputs": [],
    "source": [
@@ -17585,7 +17804,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 76,
+   "execution_count": 83,
    "metadata": {},
    "outputs": [
     {
@@ -17691,7 +17910,7 @@
        "[2680488 rows x 2 columns]"
       ]
      },
-     "execution_count": 76,
+     "execution_count": 83,
      "metadata": {},
      "output_type": "execute_result"
     }
@@ -17702,7 +17921,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 77,
+   "execution_count": 84,
    "metadata": {},
    "outputs": [],
    "source": [
@@ -17712,7 +17931,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 78,
+   "execution_count": 85,
    "metadata": {},
    "outputs": [
     {
@@ -17743,6 +17962,7 @@
        "      <th>family_name</th>\n",
        "      <th>biography</th>\n",
        "      <th>other_names</th>\n",
+       "      <th>urls</th>\n",
        "      <th>primary_email</th>\n",
        "      <th>keywords</th>\n",
        "      <th>external_ids</th>\n",
@@ -17783,6 +18003,7 @@
        "      <td>&lt;NA&gt;</td>\n",
        "      <td>&lt;NA&gt;</td>\n",
        "      <td>NaN</td>\n",
+       "      <td>NaN</td>\n",
        "      <td>&lt;NA&gt;</td>\n",
        "      <td>NaN</td>\n",
        "      <td>NaN</td>\n",
@@ -17821,6 +18042,7 @@
        "      <td>&lt;NA&gt;</td>\n",
        "      <td>&lt;NA&gt;</td>\n",
        "      <td>NaN</td>\n",
+       "      <td>NaN</td>\n",
        "      <td>&lt;NA&gt;</td>\n",
        "      <td>NaN</td>\n",
        "      <td>NaN</td>\n",
@@ -17859,6 +18081,7 @@
        "      <td>&lt;NA&gt;</td>\n",
        "      <td>&lt;NA&gt;</td>\n",
        "      <td>NaN</td>\n",
+       "      <td>[[kth profile, https://www.kth.se/profile/toma...</td>\n",
        "      <td>&lt;NA&gt;</td>\n",
        "      <td>NaN</td>\n",
        "      <td>NaN</td>\n",
@@ -17897,6 +18120,7 @@
        "      <td>&lt;NA&gt;</td>\n",
        "      <td>&lt;NA&gt;</td>\n",
        "      <td>[fontana, milena da silva]</td>\n",
+       "      <td>[[currículo lattes, http://buscatextual.cnpq.b...</td>\n",
        "      <td>&lt;NA&gt;</td>\n",
        "      <td>[educação; informática; matemática.]</td>\n",
        "      <td>NaN</td>\n",
@@ -17935,6 +18159,7 @@
        "      <td>&lt;NA&gt;</td>\n",
        "      <td>&lt;NA&gt;</td>\n",
        "      <td>NaN</td>\n",
+       "      <td>NaN</td>\n",
        "      <td>&lt;NA&gt;</td>\n",
        "      <td>NaN</td>\n",
        "      <td>NaN</td>\n",
@@ -18001,6 +18226,7 @@
        "      <td>...</td>\n",
        "      <td>...</td>\n",
        "      <td>...</td>\n",
+       "      <td>...</td>\n",
        "    </tr>\n",
        "    <tr>\n",
        "      <th>10989632</th>\n",
@@ -18011,6 +18237,7 @@
        "      <td>staugaard</td>\n",
        "      <td>&lt;NA&gt;</td>\n",
        "      <td>NaN</td>\n",
+       "      <td>[[aarhus university profile page, http://pure....</td>\n",
        "      <td>&lt;NA&gt;</td>\n",
        "      <td>NaN</td>\n",
        "      <td>NaN</td>\n",
@@ -18049,6 +18276,7 @@
        "      <td>jain</td>\n",
        "      <td>&lt;NA&gt;</td>\n",
        "      <td>NaN</td>\n",
+       "      <td>NaN</td>\n",
        "      <td>&lt;NA&gt;</td>\n",
        "      <td>[pet/ct specialist; nuclear medicine physician...</td>\n",
        "      <td>NaN</td>\n",
@@ -18087,8 +18315,9 @@
        "      <td>mackay</td>\n",
        "      <td>&lt;NA&gt;</td>\n",
        "      <td>[tiffany russel sia]</td>\n",
+       "      <td>[[social neuroscience website profile, http://...</td>\n",
        "      <td>&lt;NA&gt;</td>\n",
-       "      <td>[prostate cancer, oxytocin, pet/ct, gpc-1, gal...</td>\n",
+       "      <td>[microfluidics, spect, fluorine-18, cancer, cl...</td>\n",
        "      <td>[[researcherid, a-2121-2017]]</td>\n",
        "      <td>[[faculty of medicine, master in pharmaceutica...</td>\n",
        "      <td>[[clinical project lead, minomic international...</td>\n",
@@ -18125,6 +18354,7 @@
        "      <td>krishnan</td>\n",
        "      <td>&lt;NA&gt;</td>\n",
        "      <td>NaN</td>\n",
+       "      <td>NaN</td>\n",
        "      <td>&lt;NA&gt;</td>\n",
        "      <td>NaN</td>\n",
        "      <td>NaN</td>\n",
@@ -18163,6 +18393,7 @@
        "      <td>calamari</td>\n",
        "      <td>&lt;NA&gt;</td>\n",
        "      <td>NaN</td>\n",
+       "      <td>NaN</td>\n",
        "      <td>&lt;NA&gt;</td>\n",
        "      <td>NaN</td>\n",
        "      <td>NaN</td>\n",
@@ -18194,7 +18425,7 @@
        "    </tr>\n",
        "  </tbody>\n",
        "</table>\n",
-       "<p>1036967 rows × 35 columns</p>\n",
+       "<p>1036967 rows × 36 columns</p>\n",
        "</div>"
       ],
       "text/plain": [
@@ -18224,18 +18455,31 @@
        "10989639       vijay    krishnan      <NA>                         NaN   \n",
        "10989645     zachary    calamari      <NA>                         NaN   \n",
        "\n",
-       "         primary_email                                           keywords  \\\n",
-       "3                 <NA>                                                NaN   \n",
-       "4                 <NA>                                                NaN   \n",
-       "6                 <NA>                                                NaN   \n",
-       "11                <NA>               [educação; informática; matemática.]   \n",
-       "38                <NA>                                                NaN   \n",
-       "...                ...                                                ...   \n",
-       "10989632          <NA>                                                NaN   \n",
-       "10989634          <NA>  [pet/ct specialist; nuclear medicine physician...   \n",
-       "10989636          <NA>  [prostate cancer, oxytocin, pet/ct, gpc-1, gal...   \n",
-       "10989639          <NA>                                                NaN   \n",
-       "10989645          <NA>                                                NaN   \n",
+       "                                                       urls primary_email  \\\n",
+       "3                                                       NaN          <NA>   \n",
+       "4                                                       NaN          <NA>   \n",
+       "6         [[kth profile, https://www.kth.se/profile/toma...          <NA>   \n",
+       "11        [[currículo lattes, http://buscatextual.cnpq.b...          <NA>   \n",
+       "38                                                      NaN          <NA>   \n",
+       "...                                                     ...           ...   \n",
+       "10989632  [[aarhus university profile page, http://pure....          <NA>   \n",
+       "10989634                                                NaN          <NA>   \n",
+       "10989636  [[social neuroscience website profile, http://...          <NA>   \n",
+       "10989639                                                NaN          <NA>   \n",
+       "10989645                                                NaN          <NA>   \n",
+       "\n",
+       "                                                   keywords  \\\n",
+       "3                                                       NaN   \n",
+       "4                                                       NaN   \n",
+       "6                                                       NaN   \n",
+       "11                     [educação; informática; matemática.]   \n",
+       "38                                                      NaN   \n",
+       "...                                                     ...   \n",
+       "10989632                                                NaN   \n",
+       "10989634  [pet/ct specialist; nuclear medicine physician...   \n",
+       "10989636  [microfluidics, spect, fluorine-18, cancer, cl...   \n",
+       "10989639                                                NaN   \n",
+       "10989645                                                NaN   \n",
        "\n",
        "                           external_ids  \\\n",
        "3                                   NaN   \n",
@@ -18367,10 +18611,10 @@
        "10989639          True                2.0                 3.0  \n",
        "10989645          True                2.0                 0.0  \n",
        "\n",
-       "[1036967 rows x 35 columns]"
+       "[1036967 rows x 36 columns]"
       ]
      },
-     "execution_count": 78,
+     "execution_count": 85,
      "metadata": {},
      "output_type": "execute_result"
     }
@@ -18388,7 +18632,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 79,
+   "execution_count": 86,
    "metadata": {},
    "outputs": [],
    "source": [
@@ -18397,7 +18641,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 80,
+   "execution_count": 87,
    "metadata": {},
    "outputs": [
     {
@@ -18410,7 +18654,7 @@
        "Name: biography, dtype: object"
       ]
      },
-     "execution_count": 80,
+     "execution_count": 87,
      "metadata": {},
      "output_type": "execute_result"
     }
@@ -18428,7 +18672,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 81,
+   "execution_count": 88,
    "metadata": {},
    "outputs": [],
    "source": [
@@ -18437,7 +18681,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 82,
+   "execution_count": 89,
    "metadata": {},
    "outputs": [],
    "source": [
@@ -18446,7 +18690,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 83,
+   "execution_count": 90,
    "metadata": {},
    "outputs": [],
    "source": [
@@ -18462,7 +18706,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 84,
+   "execution_count": 91,
    "metadata": {},
    "outputs": [
     {
@@ -18493,6 +18737,7 @@
        "      <th>family_name</th>\n",
        "      <th>biography</th>\n",
        "      <th>other_names</th>\n",
+       "      <th>urls</th>\n",
        "      <th>primary_email</th>\n",
        "      <th>keywords</th>\n",
        "      <th>external_ids</th>\n",
@@ -18536,6 +18781,7 @@
        "      <td>title loans</td>\n",
        "      <td>car title loans are a more straightforward way...</td>\n",
        "      <td>[premium car title loans]</td>\n",
+       "      <td>[[website, https://premiumcartitleloans.com/up...</td>\n",
        "      <td>&lt;NA&gt;</td>\n",
        "      <td>[car title loan upland]</td>\n",
        "      <td>NaN</td>\n",
@@ -18577,6 +18823,7 @@
        "      <td>title loans</td>\n",
        "      <td>car title loans are a more straightforward way...</td>\n",
        "      <td>[premium car title loans]</td>\n",
+       "      <td>[[website, https://premiumcartitleloans.com/sa...</td>\n",
        "      <td>&lt;NA&gt;</td>\n",
        "      <td>[car title loan saratoga]</td>\n",
        "      <td>NaN</td>\n",
@@ -18618,6 +18865,7 @@
        "      <td>title loans</td>\n",
        "      <td>car title loans are a more straightforward way...</td>\n",
        "      <td>[premium car title loans]</td>\n",
+       "      <td>[[website, https://premiumcartitleloans.com/vi...</td>\n",
        "      <td>&lt;NA&gt;</td>\n",
        "      <td>[car title loan victorville]</td>\n",
        "      <td>NaN</td>\n",
@@ -18659,6 +18907,7 @@
        "      <td>title loans</td>\n",
        "      <td>car title loans are a more straightforward way...</td>\n",
        "      <td>NaN</td>\n",
+       "      <td>[[premium car title loans powder springs, http...</td>\n",
        "      <td>&lt;NA&gt;</td>\n",
        "      <td>NaN</td>\n",
        "      <td>NaN</td>\n",
@@ -18700,6 +18949,7 @@
        "      <td>title loans</td>\n",
        "      <td>car title loans are a more straightforward way...</td>\n",
        "      <td>[loan agency]</td>\n",
+       "      <td>[[premium car title loans, https://premiumcart...</td>\n",
        "      <td>&lt;NA&gt;</td>\n",
        "      <td>[title loan on car, car title loan north ogden...</td>\n",
        "      <td>NaN</td>\n",
@@ -18772,6 +19022,7 @@
        "      <td>...</td>\n",
        "      <td>...</td>\n",
        "      <td>...</td>\n",
+       "      <td>...</td>\n",
        "    </tr>\n",
        "    <tr>\n",
        "      <th>10875416</th>\n",
@@ -18782,6 +19033,7 @@
        "      <td>title loans</td>\n",
        "      <td>car title loans are a more straightforward way...</td>\n",
        "      <td>[premium car title loans]</td>\n",
+       "      <td>[[website, https://premiumcartitleloans.com/cl...</td>\n",
        "      <td>&lt;NA&gt;</td>\n",
        "      <td>[car title loan clovis]</td>\n",
        "      <td>NaN</td>\n",
@@ -18823,6 +19075,7 @@
        "      <td>title loans</td>\n",
        "      <td>car title loans are a more straightforward way...</td>\n",
        "      <td>[premium car title loans]</td>\n",
+       "      <td>[[website, https://premiumcartitleloans.com/es...</td>\n",
        "      <td>&lt;NA&gt;</td>\n",
        "      <td>[car title loan escondido]</td>\n",
        "      <td>NaN</td>\n",
@@ -18864,6 +19117,7 @@
        "      <td>title loans</td>\n",
        "      <td>car title loans are a more straightforward way...</td>\n",
        "      <td>[premium car title loans]</td>\n",
+       "      <td>[[website, https://premiumcartitleloans.com/sa...</td>\n",
        "      <td>&lt;NA&gt;</td>\n",
        "      <td>[car title loan san rafael]</td>\n",
        "      <td>NaN</td>\n",
@@ -18905,6 +19159,7 @@
        "      <td>title loans</td>\n",
        "      <td>car title loans are a more straightforward way...</td>\n",
        "      <td>[premium car title loans]</td>\n",
+       "      <td>[[website, https://premiumcartitleloans.com/sa...</td>\n",
        "      <td>&lt;NA&gt;</td>\n",
        "      <td>[car title loan san juan capistrano]</td>\n",
        "      <td>NaN</td>\n",
@@ -18946,6 +19201,7 @@
        "      <td>title loans</td>\n",
        "      <td>car title loans are a more straightforward way...</td>\n",
        "      <td>[premium car title loans]</td>\n",
+       "      <td>[[website, https://premiumcartitleloans.com/mo...</td>\n",
        "      <td>&lt;NA&gt;</td>\n",
        "      <td>[car title loan mount pleasant]</td>\n",
        "      <td>NaN</td>\n",
@@ -18980,7 +19236,7 @@
        "    </tr>\n",
        "  </tbody>\n",
        "</table>\n",
-       "<p>421 rows × 38 columns</p>\n",
+       "<p>421 rows × 39 columns</p>\n",
        "</div>"
       ],
       "text/plain": [
@@ -19023,18 +19279,31 @@
        "10933381  car title loans are a more straightforward way...   \n",
        "10985986  car title loans are a more straightforward way...   \n",
        "\n",
-       "                        other_names primary_email  \\\n",
-       "51306     [premium car title loans]          <NA>   \n",
-       "51307     [premium car title loans]          <NA>   \n",
-       "106024    [premium car title loans]          <NA>   \n",
-       "108770                          NaN          <NA>   \n",
-       "108771                [loan agency]          <NA>   \n",
-       "...                             ...           ...   \n",
-       "10875416  [premium car title loans]          <NA>   \n",
-       "10878239  [premium car title loans]          <NA>   \n",
-       "10933380  [premium car title loans]          <NA>   \n",
-       "10933381  [premium car title loans]          <NA>   \n",
-       "10985986  [premium car title loans]          <NA>   \n",
+       "                        other_names  \\\n",
+       "51306     [premium car title loans]   \n",
+       "51307     [premium car title loans]   \n",
+       "106024    [premium car title loans]   \n",
+       "108770                          NaN   \n",
+       "108771                [loan agency]   \n",
+       "...                             ...   \n",
+       "10875416  [premium car title loans]   \n",
+       "10878239  [premium car title loans]   \n",
+       "10933380  [premium car title loans]   \n",
+       "10933381  [premium car title loans]   \n",
+       "10985986  [premium car title loans]   \n",
+       "\n",
+       "                                                       urls primary_email  \\\n",
+       "51306     [[website, https://premiumcartitleloans.com/up...          <NA>   \n",
+       "51307     [[website, https://premiumcartitleloans.com/sa...          <NA>   \n",
+       "106024    [[website, https://premiumcartitleloans.com/vi...          <NA>   \n",
+       "108770    [[premium car title loans powder springs, http...          <NA>   \n",
+       "108771    [[premium car title loans, https://premiumcart...          <NA>   \n",
+       "...                                                     ...           ...   \n",
+       "10875416  [[website, https://premiumcartitleloans.com/cl...          <NA>   \n",
+       "10878239  [[website, https://premiumcartitleloans.com/es...          <NA>   \n",
+       "10933380  [[website, https://premiumcartitleloans.com/sa...          <NA>   \n",
+       "10933381  [[website, https://premiumcartitleloans.com/sa...          <NA>   \n",
+       "10985986  [[website, https://premiumcartitleloans.com/mo...          <NA>   \n",
        "\n",
        "                                                   keywords external_ids  \\\n",
        "51306                               [car title loan upland]          NaN   \n",
@@ -19153,10 +19422,10 @@
        "10933381               85.0  \n",
        "10985986               85.0  \n",
        "\n",
-       "[421 rows x 38 columns]"
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@@ -19174,7 +19443,7 @@
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    "source": [
@@ -19193,7 +19462,7 @@
   },
   {
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-   "execution_count": 86,
+   "execution_count": 93,
    "metadata": {
     "scrolled": true
    },
@@ -19226,6 +19495,7 @@
        "      <th>family_name</th>\n",
        "      <th>biography</th>\n",
        "      <th>other_names</th>\n",
+       "      <th>urls</th>\n",
        "      <th>primary_email</th>\n",
        "      <th>keywords</th>\n",
        "      <th>external_ids</th>\n",
@@ -19269,6 +19539,7 @@
        "      <td>record</td>\n",
        "      <td>make your practice easy with a professional so...</td>\n",
        "      <td>NaN</td>\n",
+       "      <td>[[aesthetic record, https://www.aestheticrecor...</td>\n",
        "      <td>&lt;NA&gt;</td>\n",
        "      <td>NaN</td>\n",
        "      <td>NaN</td>\n",
@@ -19310,6 +19581,7 @@
        "      <td>ruiz-bravo lopez</td>\n",
        "      <td>personal docente e investigador de la universi...</td>\n",
        "      <td>NaN</td>\n",
+       "      <td>[[id personal sica, http://investigacion.ugr.e...</td>\n",
        "      <td>&lt;NA&gt;</td>\n",
        "      <td>NaN</td>\n",
        "      <td>NaN</td>\n",
@@ -19351,6 +19623,7 @@
        "      <td>spahn</td>\n",
        "      <td>research administrator</td>\n",
        "      <td>NaN</td>\n",
+       "      <td>NaN</td>\n",
        "      <td>&lt;NA&gt;</td>\n",
        "      <td>NaN</td>\n",
        "      <td>NaN</td>\n",
@@ -19392,6 +19665,7 @@
        "      <td>martinez</td>\n",
        "      <td>personal docente e investigador de la universi...</td>\n",
        "      <td>NaN</td>\n",
+       "      <td>[[id personal sica, http://investigacion.ugr.e...</td>\n",
        "      <td>&lt;NA&gt;</td>\n",
        "      <td>NaN</td>\n",
        "      <td>[[researcherid, e-9723-2016]]</td>\n",
@@ -19433,6 +19707,7 @@
        "      <td>ortega bernaldo de quiros</td>\n",
        "      <td>personal docente e investigador de la universi...</td>\n",
        "      <td>NaN</td>\n",
+       "      <td>[[id personal sica, http://investigacion.ugr.e...</td>\n",
        "      <td>&lt;NA&gt;</td>\n",
        "      <td>NaN</td>\n",
        "      <td>NaN</td>\n",
@@ -19505,6 +19780,7 @@
        "      <td>...</td>\n",
        "      <td>...</td>\n",
        "      <td>...</td>\n",
+       "      <td>...</td>\n",
        "    </tr>\n",
        "    <tr>\n",
        "      <th>10988461</th>\n",
@@ -19515,6 +19791,7 @@
        "      <td>lopez-viota gallardo</td>\n",
        "      <td>personal docente e investigador de la universi...</td>\n",
        "      <td>NaN</td>\n",
+       "      <td>[[id personal sica, http://investigacion.ugr.e...</td>\n",
        "      <td>mlvg@ugr.es</td>\n",
        "      <td>NaN</td>\n",
        "      <td>NaN</td>\n",
@@ -19556,6 +19833,7 @@
        "      <td>gonzález pérez</td>\n",
        "      <td>personal docente e investigador de la universi...</td>\n",
        "      <td>NaN</td>\n",
+       "      <td>[[departamento de filología hispánica y clásic...</td>\n",
        "      <td>&lt;NA&gt;</td>\n",
        "      <td>NaN</td>\n",
        "      <td>NaN</td>\n",
@@ -19597,6 +19875,7 @@
        "      <td>lynsey</td>\n",
        "      <td>een korte inleiding op waterverwarmingstoestel...</td>\n",
        "      <td>NaN</td>\n",
+       "      <td>[[een korte inleiding op waterverwarmingstoest...</td>\n",
        "      <td>&lt;NA&gt;</td>\n",
        "      <td>NaN</td>\n",
        "      <td>NaN</td>\n",
@@ -19638,6 +19917,7 @@
        "      <td>star</td>\n",
        "      <td>tentu saja semua permainan yang disediakan aka...</td>\n",
        "      <td>NaN</td>\n",
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        "      <td>&lt;NA&gt;</td>\n",
        "      <td>NaN</td>\n",
        "      <td>NaN</td>\n",
@@ -19679,6 +19959,7 @@
        "      <td>cesar</td>\n",
        "      <td>welcome to my page! im still finding my way ar...</td>\n",
        "      <td>NaN</td>\n",
+       "      <td>[[lotterytogel, http://139.59.245.36]]</td>\n",
        "      <td>&lt;NA&gt;</td>\n",
        "      <td>NaN</td>\n",
        "      <td>NaN</td>\n",
@@ -19713,7 +19994,7 @@
        "    </tr>\n",
        "  </tbody>\n",
        "</table>\n",
-       "<p>19571 rows × 38 columns</p>\n",
+       "<p>19571 rows × 39 columns</p>\n",
        "</div>"
       ],
       "text/plain": [
@@ -19756,18 +20037,31 @@
        "10988929  tentu saja semua permainan yang disediakan aka...         NaN   \n",
        "10989073  welcome to my page! im still finding my way ar...         NaN   \n",
        "\n",
-       "         primary_email keywords                   external_ids  \\\n",
-       "613               <NA>      NaN                            NaN   \n",
-       "1145              <NA>      NaN                            NaN   \n",
-       "1519              <NA>      NaN                            NaN   \n",
-       "2269              <NA>      NaN  [[researcherid, e-9723-2016]]   \n",
-       "6163              <NA>      NaN                            NaN   \n",
-       "...                ...      ...                            ...   \n",
-       "10988461   mlvg@ugr.es      NaN                            NaN   \n",
-       "10988510          <NA>      NaN                            NaN   \n",
-       "10988922          <NA>      NaN                            NaN   \n",
-       "10988929          <NA>      NaN                            NaN   \n",
-       "10989073          <NA>      NaN                            NaN   \n",
+       "                                                       urls primary_email  \\\n",
+       "613       [[aesthetic record, https://www.aestheticrecor...          <NA>   \n",
+       "1145      [[id personal sica, http://investigacion.ugr.e...          <NA>   \n",
+       "1519                                                    NaN          <NA>   \n",
+       "2269      [[id personal sica, http://investigacion.ugr.e...          <NA>   \n",
+       "6163      [[id personal sica, http://investigacion.ugr.e...          <NA>   \n",
+       "...                                                     ...           ...   \n",
+       "10988461  [[id personal sica, http://investigacion.ugr.e...   mlvg@ugr.es   \n",
+       "10988510  [[departamento de filología hispánica y clásic...          <NA>   \n",
+       "10988922  [[een korte inleiding op waterverwarmingstoest...          <NA>   \n",
+       "10988929  [[bola88, https://sites.google.com/view/bola88...          <NA>   \n",
+       "10989073             [[lotterytogel, http://139.59.245.36]]          <NA>   \n",
+       "\n",
+       "         keywords                   external_ids  \\\n",
+       "613           NaN                            NaN   \n",
+       "1145          NaN                            NaN   \n",
+       "1519          NaN                            NaN   \n",
+       "2269          NaN  [[researcherid, e-9723-2016]]   \n",
+       "6163          NaN                            NaN   \n",
+       "...           ...                            ...   \n",
+       "10988461      NaN                            NaN   \n",
+       "10988510      NaN                            NaN   \n",
+       "10988922      NaN                            NaN   \n",
+       "10988929      NaN                            NaN   \n",
+       "10989073      NaN                            NaN   \n",
        "\n",
        "                                                  education  \\\n",
        "613                                                     NaN   \n",
@@ -19899,10 +20193,10 @@
        "10988929                    1.0               24.0  \n",
        "10989073                    2.0               21.0  \n",
        "\n",
-       "[19571 rows x 38 columns]"
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-     "execution_count": 86,
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@@ -19913,7 +20207,7 @@
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@@ -20012,7 +20306,7 @@
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@@ -20035,7 +20329,7 @@
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@@ -20046,7 +20340,7 @@
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@@ -20079,7 +20373,7 @@
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@@ -21018,9 +21312,9 @@
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\"linecolor\": \"white\", \"ticks\": \"\", \"title\": {\"standoff\": 15}, \"zerolinecolor\": \"white\", \"zerolinewidth\": 2}}}, \"title\": {\"text\": \"Activation date distribution for all dup bios\"}, \"xaxis\": {\"tickangle\": 45, \"tickfont\": {\"size\": 12}}},                        {\"responsive\": true}                    ).then(function(){\n",
        "                            \n",
-       "var gd = document.getElementById('3a57f18d-0642-4b14-a315-06f59980c2e0');\n",
+       "var gd = document.getElementById('618fdfdd-7e12-4800-8a93-2341d7f09eca');\n",
        "var x = new MutationObserver(function (mutations, observer) {{\n",
        "        var display = window.getComputedStyle(gd).display;\n",
        "        if (!display || display === 'none') {{\n",
@@ -62867,26 +63161,143 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 129,
+   "execution_count": 100,
    "metadata": {},
-   "outputs": [],
+   "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>activation_date</th>\n",
+       "      <th>orcid</th>\n",
+       "    </tr>\n",
+       "  </thead>\n",
+       "  <tbody>\n",
+       "    <tr>\n",
+       "      <th>0</th>\n",
+       "      <td>2020-01-01 00:00:00+00:00</td>\n",
+       "      <td>2276</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>1</th>\n",
+       "      <td>2020-01-02 00:00:00+00:00</td>\n",
+       "      <td>4963</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>2</th>\n",
+       "      <td>2020-01-03 00:00:00+00:00</td>\n",
+       "      <td>4751</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>3</th>\n",
+       "      <td>2020-01-04 00:00:00+00:00</td>\n",
+       "      <td>3283</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>4</th>\n",
+       "      <td>2020-01-05 00:00:00+00:00</td>\n",
+       "      <td>3075</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>...</th>\n",
+       "      <td>...</td>\n",
+       "      <td>...</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>361</th>\n",
+       "      <td>2020-12-27 00:00:00+00:00</td>\n",
+       "      <td>4498</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>362</th>\n",
+       "      <td>2020-12-28 00:00:00+00:00</td>\n",
+       "      <td>7215</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>363</th>\n",
+       "      <td>2020-12-29 00:00:00+00:00</td>\n",
+       "      <td>7126</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>364</th>\n",
+       "      <td>2020-12-30 00:00:00+00:00</td>\n",
+       "      <td>6826</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>365</th>\n",
+       "      <td>2020-12-31 00:00:00+00:00</td>\n",
+       "      <td>5398</td>\n",
+       "    </tr>\n",
+       "  </tbody>\n",
+       "</table>\n",
+       "<p>366 rows × 2 columns</p>\n",
+       "</div>"
+      ],
+      "text/plain": [
+       "              activation_date  orcid\n",
+       "0   2020-01-01 00:00:00+00:00   2276\n",
+       "1   2020-01-02 00:00:00+00:00   4963\n",
+       "2   2020-01-03 00:00:00+00:00   4751\n",
+       "3   2020-01-04 00:00:00+00:00   3283\n",
+       "4   2020-01-05 00:00:00+00:00   3075\n",
+       "..                        ...    ...\n",
+       "361 2020-12-27 00:00:00+00:00   4498\n",
+       "362 2020-12-28 00:00:00+00:00   7215\n",
+       "363 2020-12-29 00:00:00+00:00   7126\n",
+       "364 2020-12-30 00:00:00+00:00   6826\n",
+       "365 2020-12-31 00:00:00+00:00   5398\n",
+       "\n",
+       "[366 rows x 2 columns]"
+      ]
+     },
+     "execution_count": 100,
+     "metadata": {},
+     "output_type": "execute_result"
+    }
+   ],
    "source": [
-    "# YEAR = 2020\n",
-    "# data = [\n",
-    "#     go.Histogram(\n",
-    "#         x=df[df.activation_date.dt.year == YEAR]['activation_date'],\n",
-    "#         y=df[df.activation_date.dt.year == YEAR]['orcid'],\n",
-    "#         histfunc='count'\n",
-    "#     )\n",
-    "# ]\n",
-    "\n",
-    "# layout = go.Layout(\n",
-    "#     title='Activation date distribution (general) for %s' % YEAR,\n",
-    "#     xaxis=dict(tickangle=45, tickfont=dict(size=12))\n",
-    "# )\n",
-    "# fig = go.Figure(data=data, layout=layout)\n",
-    "# fig.update_traces(xbins_size='D1')\n",
-    "# plotly.offline.iplot(fig)"
+    "YEAR = 2020\n",
+    "df[df.activation_date.dt.year == YEAR].resample('1D', on='activation_date')['orcid'].count().reset_index()"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 101,
+   "metadata": {},
+   "outputs": [
+    {
+     "data": {
+      "image/png": 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\n",
+      "text/plain": [
+       "<Figure size 1152x432 with 1 Axes>"
+      ]
+     },
+     "metadata": {
+      "needs_background": "light"
+     },
+     "output_type": "display_data"
+    }
+   ],
+   "source": [
+    "plt.figure(figsize=(16, 6))\n",
+    "ax = sns.histplot(x='activation_date', data=df[df.activation_date.dt.year == YEAR], bins=366)"
    ]
   },
   {
@@ -62919,7 +63330,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 95,
+   "execution_count": 102,
    "metadata": {},
    "outputs": [
     {
@@ -62950,6 +63361,7 @@
        "      <th>family_name</th>\n",
        "      <th>biography</th>\n",
        "      <th>other_names</th>\n",
+       "      <th>urls</th>\n",
        "      <th>primary_email</th>\n",
        "      <th>keywords</th>\n",
        "      <th>external_ids</th>\n",
@@ -62993,6 +63405,7 @@
        "      <td>record</td>\n",
        "      <td>make your practice easy with a professional so...</td>\n",
        "      <td>NaN</td>\n",
+       "      <td>[[aesthetic record, https://www.aestheticrecor...</td>\n",
        "      <td>&lt;NA&gt;</td>\n",
        "      <td>NaN</td>\n",
        "      <td>NaN</td>\n",
@@ -63034,6 +63447,7 @@
        "      <td>windows &amp; doors</td>\n",
        "      <td>address:675 nw 116th street,miami, fl 33168pho...</td>\n",
        "      <td>NaN</td>\n",
+       "      <td>NaN</td>\n",
        "      <td>&lt;NA&gt;</td>\n",
        "      <td>NaN</td>\n",
        "      <td>NaN</td>\n",
@@ -63075,6 +63489,7 @@
        "      <td>ali</td>\n",
        "      <td>https://pakistanpropertyinfo.blogspot.com/2019...</td>\n",
        "      <td>NaN</td>\n",
+       "      <td>NaN</td>\n",
        "      <td>&lt;NA&gt;</td>\n",
        "      <td>NaN</td>\n",
        "      <td>NaN</td>\n",
@@ -63116,6 +63531,7 @@
        "      <td>hdtv</td>\n",
        "      <td>https://2017-oscar.com/https://2017-oscar.com/...</td>\n",
        "      <td>NaN</td>\n",
+       "      <td>NaN</td>\n",
        "      <td>&lt;NA&gt;</td>\n",
        "      <td>NaN</td>\n",
        "      <td>NaN</td>\n",
@@ -63157,6 +63573,7 @@
        "      <td>jolliff</td>\n",
        "      <td>presently, my favorite tv show is true detecti...</td>\n",
        "      <td>NaN</td>\n",
+       "      <td>[[https://www.webs.org.il, https://penzu.com/p...</td>\n",
        "      <td>&lt;NA&gt;</td>\n",
        "      <td>NaN</td>\n",
        "      <td>NaN</td>\n",
@@ -63229,6 +63646,7 @@
        "      <td>...</td>\n",
        "      <td>...</td>\n",
        "      <td>...</td>\n",
+       "      <td>...</td>\n",
        "    </tr>\n",
        "    <tr>\n",
        "      <th>10988314</th>\n",
@@ -63239,6 +63657,7 @@
        "      <td>edgar</td>\n",
        "      <td>im training to be a farm and home management a...</td>\n",
        "      <td>NaN</td>\n",
+       "      <td>[[tempe towing and recovery, https://brooksdhy...</td>\n",
        "      <td>&lt;NA&gt;</td>\n",
        "      <td>NaN</td>\n",
        "      <td>NaN</td>\n",
@@ -63280,6 +63699,7 @@
        "      <td>ruland</td>\n",
        "      <td>i believe in living life to the fullest and fo...</td>\n",
        "      <td>NaN</td>\n",
+       "      <td>[[wypożyczalnia samochodów cennik, https://ren...</td>\n",
        "      <td>&lt;NA&gt;</td>\n",
        "      <td>NaN</td>\n",
        "      <td>NaN</td>\n",
@@ -63321,6 +63741,7 @@
        "      <td>lynsey</td>\n",
        "      <td>een korte inleiding op waterverwarmingstoestel...</td>\n",
        "      <td>NaN</td>\n",
+       "      <td>[[een korte inleiding op waterverwarmingstoest...</td>\n",
        "      <td>&lt;NA&gt;</td>\n",
        "      <td>NaN</td>\n",
        "      <td>NaN</td>\n",
@@ -63362,6 +63783,7 @@
        "      <td>star</td>\n",
        "      <td>tentu saja semua permainan yang disediakan aka...</td>\n",
        "      <td>NaN</td>\n",
+       "      <td>[[bola88, https://sites.google.com/view/bola88...</td>\n",
        "      <td>&lt;NA&gt;</td>\n",
        "      <td>NaN</td>\n",
        "      <td>NaN</td>\n",
@@ -63403,6 +63825,7 @@
        "      <td>cesar</td>\n",
        "      <td>welcome to my page! im still finding my way ar...</td>\n",
        "      <td>NaN</td>\n",
+       "      <td>[[lotterytogel, http://139.59.245.36]]</td>\n",
        "      <td>&lt;NA&gt;</td>\n",
        "      <td>NaN</td>\n",
        "      <td>NaN</td>\n",
@@ -63437,7 +63860,7 @@
        "    </tr>\n",
        "  </tbody>\n",
        "</table>\n",
-       "<p>13663 rows × 38 columns</p>\n",
+       "<p>13663 rows × 39 columns</p>\n",
        "</div>"
       ],
       "text/plain": [
@@ -63480,114 +63903,127 @@
        "10988929  tentu saja semua permainan yang disediakan aka...         NaN   \n",
        "10989073  welcome to my page! im still finding my way ar...         NaN   \n",
        "\n",
-       "         primary_email keywords external_ids education employment  n_works  \\\n",
-       "613               <NA>      NaN          NaN       NaN        NaN        0   \n",
-       "17800             <NA>      NaN          NaN       NaN        NaN        0   \n",
-       "26513             <NA>      NaN          NaN       NaN        NaN        0   \n",
-       "27456             <NA>      NaN          NaN       NaN        NaN        0   \n",
-       "30196             <NA>      NaN          NaN       NaN        NaN        0   \n",
-       "...                ...      ...          ...       ...        ...      ...   \n",
-       "10988314          <NA>      NaN          NaN       NaN        NaN        0   \n",
-       "10988449          <NA>      NaN          NaN       NaN        NaN        0   \n",
-       "10988922          <NA>      NaN          NaN       NaN        NaN        0   \n",
-       "10988929          <NA>      NaN          NaN       NaN        NaN        0   \n",
-       "10989073          <NA>      NaN          NaN       NaN        NaN        0   \n",
+       "                                                       urls primary_email  \\\n",
+       "613       [[aesthetic record, https://www.aestheticrecor...          <NA>   \n",
+       "17800                                                   NaN          <NA>   \n",
+       "26513                                                   NaN          <NA>   \n",
+       "27456                                                   NaN          <NA>   \n",
+       "30196     [[https://www.webs.org.il, https://penzu.com/p...          <NA>   \n",
+       "...                                                     ...           ...   \n",
+       "10988314  [[tempe towing and recovery, https://brooksdhy...          <NA>   \n",
+       "10988449  [[wypożyczalnia samochodów cennik, https://ren...          <NA>   \n",
+       "10988922  [[een korte inleiding op waterverwarmingstoest...          <NA>   \n",
+       "10988929  [[bola88, https://sites.google.com/view/bola88...          <NA>   \n",
+       "10989073             [[lotterytogel, http://139.59.245.36]]          <NA>   \n",
        "\n",
-       "         works_source                  activation_date  \\\n",
-       "613               NaN 2020-09-28 09:13:52.705000+00:00   \n",
-       "17800             NaN 2019-11-28 14:32:35.172000+00:00   \n",
-       "26513             NaN 2019-03-09 00:35:08.585000+00:00   \n",
-       "27456             NaN 2017-02-21 06:14:06.156000+00:00   \n",
-       "30196             NaN 2020-12-15 02:38:31.259000+00:00   \n",
-       "...               ...                              ...   \n",
-       "10988314          NaN 2020-12-05 11:44:22.829000+00:00   \n",
-       "10988449          NaN 2020-11-28 14:17:14.721000+00:00   \n",
-       "10988922          NaN 2020-12-10 21:40:39.371000+00:00   \n",
-       "10988929          NaN 2020-11-24 13:18:00.296000+00:00   \n",
-       "10989073          NaN 2020-12-13 00:34:15.955000+00:00   \n",
+       "         keywords external_ids education employment  n_works works_source  \\\n",
+       "613           NaN          NaN       NaN        NaN        0          NaN   \n",
+       "17800         NaN          NaN       NaN        NaN        0          NaN   \n",
+       "26513         NaN          NaN       NaN        NaN        0          NaN   \n",
+       "27456         NaN          NaN       NaN        NaN        0          NaN   \n",
+       "30196         NaN          NaN       NaN        NaN        0          NaN   \n",
+       "...           ...          ...       ...        ...      ...          ...   \n",
+       "10988314      NaN          NaN       NaN        NaN        0          NaN   \n",
+       "10988449      NaN          NaN       NaN        NaN        0          NaN   \n",
+       "10988922      NaN          NaN       NaN        NaN        0          NaN   \n",
+       "10988929      NaN          NaN       NaN        NaN        0          NaN   \n",
+       "10989073      NaN          NaN       NaN        NaN        0          NaN   \n",
        "\n",
-       "                         last_update_date  n_doi  n_arxiv  n_pmc  \\\n",
-       "613      2020-09-28 09:17:36.855000+00:00      0        0      0   \n",
-       "17800    2019-11-28 14:40:07.022000+00:00      0        0      0   \n",
-       "26513    2019-03-09 00:36:05.087000+00:00      0        0      0   \n",
-       "27456    2017-02-21 06:41:12.010000+00:00      0        0      0   \n",
-       "30196    2020-12-15 02:40:41.464000+00:00      0        0      0   \n",
-       "...                                   ...    ...      ...    ...   \n",
-       "10988314 2020-12-05 11:49:30.839000+00:00      0        0      0   \n",
-       "10988449 2020-11-28 14:19:48.043000+00:00      0        0      0   \n",
-       "10988922 2020-12-10 21:49:33.129000+00:00      0        0      0   \n",
-       "10988929 2020-11-24 13:21:10.985000+00:00      0        0      0   \n",
-       "10989073 2020-12-13 00:37:21.793000+00:00      0        0      0   \n",
+       "                          activation_date                 last_update_date  \\\n",
+       "613      2020-09-28 09:13:52.705000+00:00 2020-09-28 09:17:36.855000+00:00   \n",
+       "17800    2019-11-28 14:32:35.172000+00:00 2019-11-28 14:40:07.022000+00:00   \n",
+       "26513    2019-03-09 00:35:08.585000+00:00 2019-03-09 00:36:05.087000+00:00   \n",
+       "27456    2017-02-21 06:14:06.156000+00:00 2017-02-21 06:41:12.010000+00:00   \n",
+       "30196    2020-12-15 02:38:31.259000+00:00 2020-12-15 02:40:41.464000+00:00   \n",
+       "...                                   ...                              ...   \n",
+       "10988314 2020-12-05 11:44:22.829000+00:00 2020-12-05 11:49:30.839000+00:00   \n",
+       "10988449 2020-11-28 14:17:14.721000+00:00 2020-11-28 14:19:48.043000+00:00   \n",
+       "10988922 2020-12-10 21:40:39.371000+00:00 2020-12-10 21:49:33.129000+00:00   \n",
+       "10988929 2020-11-24 13:18:00.296000+00:00 2020-11-24 13:21:10.985000+00:00   \n",
+       "10989073 2020-12-13 00:34:15.955000+00:00 2020-12-13 00:37:21.793000+00:00   \n",
        "\n",
-       "          n_other_pids  label primary_email_domain other_email_domains  \\\n",
-       "613                  0  False                  NaN                 NaN   \n",
-       "17800                0  False                  NaN                 NaN   \n",
-       "26513                0  False                  NaN                 NaN   \n",
-       "27456                0  False                  NaN                 NaN   \n",
-       "30196                0  False                  NaN                 NaN   \n",
-       "...                ...    ...                  ...                 ...   \n",
-       "10988314             0  False                  NaN                 NaN   \n",
-       "10988449             0  False                  NaN                 NaN   \n",
-       "10988922             0  False                  NaN                 NaN   \n",
-       "10988929             0  False                  NaN                 NaN   \n",
-       "10989073             0  False                  NaN                 NaN   \n",
+       "          n_doi  n_arxiv  n_pmc  n_other_pids  label primary_email_domain  \\\n",
+       "613           0        0      0             0  False                  NaN   \n",
+       "17800         0        0      0             0  False                  NaN   \n",
+       "26513         0        0      0             0  False                  NaN   \n",
+       "27456         0        0      0             0  False                  NaN   \n",
+       "30196         0        0      0             0  False                  NaN   \n",
+       "...         ...      ...    ...           ...    ...                  ...   \n",
+       "10988314      0        0      0             0  False                  NaN   \n",
+       "10988449      0        0      0             0  False                  NaN   \n",
+       "10988922      0        0      0             0  False                  NaN   \n",
+       "10988929      0        0      0             0  False                  NaN   \n",
+       "10989073      0        0      0             0  False                  NaN   \n",
        "\n",
-       "                       url_domains  n_emails  n_urls  n_ids  n_keywords  \\\n",
-       "613          [aestheticrecord.com]      <NA>       1   <NA>        <NA>   \n",
-       "17800                          NaN      <NA>    <NA>   <NA>        <NA>   \n",
-       "26513                          NaN      <NA>    <NA>   <NA>        <NA>   \n",
-       "27456                          NaN      <NA>    <NA>   <NA>        <NA>   \n",
-       "30196                  [penzu.com]      <NA>       1   <NA>        <NA>   \n",
-       "...                            ...       ...     ...    ...         ...   \n",
-       "10988314             [skyrock.com]      <NA>       1   <NA>        <NA>   \n",
-       "10988449           [renomacars.pl]      <NA>       1   <NA>        <NA>   \n",
-       "10988922  [zonneboilermagazijn.nl]      <NA>       1   <NA>        <NA>   \n",
-       "10988929              [google.com]      <NA>       1   <NA>        <NA>   \n",
-       "10989073           [139.59.245.36]      <NA>       1   <NA>        <NA>   \n",
+       "         other_email_domains               url_domains  n_emails  n_urls  \\\n",
+       "613                      NaN     [aestheticrecord.com]      <NA>       1   \n",
+       "17800                    NaN                       NaN      <NA>    <NA>   \n",
+       "26513                    NaN                       NaN      <NA>    <NA>   \n",
+       "27456                    NaN                       NaN      <NA>    <NA>   \n",
+       "30196                    NaN               [penzu.com]      <NA>       1   \n",
+       "...                      ...                       ...       ...     ...   \n",
+       "10988314                 NaN             [skyrock.com]      <NA>       1   \n",
+       "10988449                 NaN           [renomacars.pl]      <NA>       1   \n",
+       "10988922                 NaN  [zonneboilermagazijn.nl]      <NA>       1   \n",
+       "10988929                 NaN              [google.com]      <NA>       1   \n",
+       "10989073                 NaN           [139.59.245.36]      <NA>       1   \n",
        "\n",
-       "          n_education  n_employment ext_works_source  n_ext_work_source  \\\n",
-       "613              <NA>          <NA>              NaN               <NA>   \n",
-       "17800            <NA>          <NA>              NaN               <NA>   \n",
-       "26513            <NA>          <NA>              NaN               <NA>   \n",
-       "27456            <NA>          <NA>              NaN               <NA>   \n",
-       "30196            <NA>          <NA>              NaN               <NA>   \n",
-       "...               ...           ...              ...                ...   \n",
-       "10988314         <NA>          <NA>              NaN               <NA>   \n",
-       "10988449         <NA>          <NA>              NaN               <NA>   \n",
-       "10988922         <NA>          <NA>              NaN               <NA>   \n",
-       "10988929         <NA>          <NA>              NaN               <NA>   \n",
-       "10989073         <NA>          <NA>              NaN               <NA>   \n",
+       "          n_ids  n_keywords  n_education  n_employment ext_works_source  \\\n",
+       "613        <NA>        <NA>         <NA>          <NA>              NaN   \n",
+       "17800      <NA>        <NA>         <NA>          <NA>              NaN   \n",
+       "26513      <NA>        <NA>         <NA>          <NA>              NaN   \n",
+       "27456      <NA>        <NA>         <NA>          <NA>              NaN   \n",
+       "30196      <NA>        <NA>         <NA>          <NA>              NaN   \n",
+       "...         ...         ...          ...           ...              ...   \n",
+       "10988314   <NA>        <NA>         <NA>          <NA>              NaN   \n",
+       "10988449   <NA>        <NA>         <NA>          <NA>              NaN   \n",
+       "10988922   <NA>        <NA>         <NA>          <NA>              NaN   \n",
+       "10988929   <NA>        <NA>         <NA>          <NA>              NaN   \n",
+       "10989073   <NA>        <NA>         <NA>          <NA>              NaN   \n",
        "\n",
-       "         authoritative  n_valid_education  n_valid_employment  \\\n",
-       "613              False                NaN                 NaN   \n",
-       "17800            False                NaN                 NaN   \n",
-       "26513            False                NaN                 NaN   \n",
-       "27456            False                NaN                 NaN   \n",
-       "30196            False                NaN                 NaN   \n",
-       "...                ...                ...                 ...   \n",
-       "10988314         False                NaN                 NaN   \n",
-       "10988449         False                NaN                 NaN   \n",
-       "10988922         False                NaN                 NaN   \n",
-       "10988929         False                NaN                 NaN   \n",
-       "10989073         False                NaN                 NaN   \n",
+       "          n_ext_work_source authoritative  n_valid_education  \\\n",
+       "613                    <NA>         False                NaN   \n",
+       "17800                  <NA>         False                NaN   \n",
+       "26513                  <NA>         False                NaN   \n",
+       "27456                  <NA>         False                NaN   \n",
+       "30196                  <NA>         False                NaN   \n",
+       "...                     ...           ...                ...   \n",
+       "10988314               <NA>         False                NaN   \n",
+       "10988449               <NA>         False                NaN   \n",
+       "10988922               <NA>         False                NaN   \n",
+       "10988929               <NA>         False                NaN   \n",
+       "10989073               <NA>         False                NaN   \n",
        "\n",
-       "          biography_length  biography_n_sentences  biography_n_words  \n",
-       "613                    165                    2.0               28.0  \n",
-       "17800                  369                    1.0               60.0  \n",
-       "26513                   93                    1.0                3.0  \n",
-       "27456                   69                    1.0                7.0  \n",
-       "30196                   89                    2.0               20.0  \n",
-       "...                    ...                    ...                ...  \n",
-       "10988314                77                    2.0               17.0  \n",
-       "10988449                98                    1.0               21.0  \n",
-       "10988922               151                    1.0               22.0  \n",
-       "10988929               150                    1.0               24.0  \n",
-       "10989073                98                    2.0               21.0  \n",
+       "          n_valid_employment  biography_length  biography_n_sentences  \\\n",
+       "613                      NaN               165                    2.0   \n",
+       "17800                    NaN               369                    1.0   \n",
+       "26513                    NaN                93                    1.0   \n",
+       "27456                    NaN                69                    1.0   \n",
+       "30196                    NaN                89                    2.0   \n",
+       "...                      ...               ...                    ...   \n",
+       "10988314                 NaN                77                    2.0   \n",
+       "10988449                 NaN                98                    1.0   \n",
+       "10988922                 NaN               151                    1.0   \n",
+       "10988929                 NaN               150                    1.0   \n",
+       "10989073                 NaN                98                    2.0   \n",
        "\n",
-       "[13663 rows x 38 columns]"
+       "          biography_n_words  \n",
+       "613                    28.0  \n",
+       "17800                  60.0  \n",
+       "26513                   3.0  \n",
+       "27456                   7.0  \n",
+       "30196                  20.0  \n",
+       "...                     ...  \n",
+       "10988314               17.0  \n",
+       "10988449               21.0  \n",
+       "10988922               22.0  \n",
+       "10988929               24.0  \n",
+       "10989073               21.0  \n",
+       "\n",
+       "[13663 rows x 39 columns]"
       ]
      },
-     "execution_count": 95,
+     "execution_count": 102,
      "metadata": {},
      "output_type": "execute_result"
     }
@@ -63609,7 +64045,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 133,
+   "execution_count": 103,
    "metadata": {},
    "outputs": [],
    "source": [
@@ -63623,7 +64059,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 134,
+   "execution_count": 104,
    "metadata": {},
    "outputs": [
     {
@@ -64566,9 +65002,9 @@
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        "                            \n",
-       "var gd = document.getElementById('ef43c0af-ab5a-4169-b23e-f18a4fc2d99d');\n",
+       "var gd = document.getElementById('59451d05-5b06-4e60-b95d-4ecf4c2f26d4');\n",
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@@ -64616,110 +65052,9 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 153,
+   "execution_count": 105,
    "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>orcid</th>\n",
-       "    </tr>\n",
-       "    <tr>\n",
-       "      <th>url_domains</th>\n",
-       "      <th></th>\n",
-       "    </tr>\n",
-       "  </thead>\n",
-       "  <tbody>\n",
-       "    <tr>\n",
-       "      <th>linkedin.com</th>\n",
-       "      <td>78418</td>\n",
-       "    </tr>\n",
-       "    <tr>\n",
-       "      <th>researchgate.net</th>\n",
-       "      <td>67823</td>\n",
-       "    </tr>\n",
-       "    <tr>\n",
-       "      <th>google.com</th>\n",
-       "      <td>44804</td>\n",
-       "    </tr>\n",
-       "    <tr>\n",
-       "      <th>cnpq.br</th>\n",
-       "      <td>24635</td>\n",
-       "    </tr>\n",
-       "    <tr>\n",
-       "      <th>academia.edu</th>\n",
-       "      <td>21174</td>\n",
-       "    </tr>\n",
-       "    <tr>\n",
-       "      <th>...</th>\n",
-       "      <td>...</td>\n",
-       "    </tr>\n",
-       "    <tr>\n",
-       "      <th>gil-sanzlab.com</th>\n",
-       "      <td>1</td>\n",
-       "    </tr>\n",
-       "    <tr>\n",
-       "      <th>gilabola88.net</th>\n",
-       "      <td>1</td>\n",
-       "    </tr>\n",
-       "    <tr>\n",
-       "      <th>gilabs.com</th>\n",
-       "      <td>1</td>\n",
-       "    </tr>\n",
-       "    <tr>\n",
-       "      <th>giladfeldman.org</th>\n",
-       "      <td>1</td>\n",
-       "    </tr>\n",
-       "    <tr>\n",
-       "      <th>​ http</th>\n",
-       "      <td>1</td>\n",
-       "    </tr>\n",
-       "  </tbody>\n",
-       "</table>\n",
-       "<p>199625 rows × 1 columns</p>\n",
-       "</div>"
-      ],
-      "text/plain": [
-       "                  orcid\n",
-       "url_domains            \n",
-       "linkedin.com      78418\n",
-       "researchgate.net  67823\n",
-       "google.com        44804\n",
-       "cnpq.br           24635\n",
-       "academia.edu      21174\n",
-       "...                 ...\n",
-       "gil-sanzlab.com       1\n",
-       "gilabola88.net        1\n",
-       "gilabs.com            1\n",
-       "giladfeldman.org      1\n",
-       "​ http                1\n",
-       "\n",
-       "[199625 rows x 1 columns]"
-      ]
-     },
-     "execution_count": 153,
-     "metadata": {},
-     "output_type": "execute_result"
-    }
-   ],
+   "outputs": [],
    "source": [
     "top_urls = df[['orcid', 'url_domains']]\\\n",
     "                .explode('url_domains')\\\n",
@@ -64731,124 +65066,16 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 154,
+   "execution_count": 106,
    "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>orcid</th>\n",
-       "      <th>url_domains</th>\n",
-       "    </tr>\n",
-       "  </thead>\n",
-       "  <tbody>\n",
-       "    <tr>\n",
-       "      <th>0</th>\n",
-       "      <td>0000-0001-6097-3953</td>\n",
-       "      <td>NaN</td>\n",
-       "    </tr>\n",
-       "    <tr>\n",
-       "      <th>1</th>\n",
-       "      <td>0000-0001-6112-5550</td>\n",
-       "      <td>NaN</td>\n",
-       "    </tr>\n",
-       "    <tr>\n",
-       "      <th>2</th>\n",
-       "      <td>0000-0001-6152-2695</td>\n",
-       "      <td>NaN</td>\n",
-       "    </tr>\n",
-       "    <tr>\n",
-       "      <th>3</th>\n",
-       "      <td>0000-0001-6220-5683</td>\n",
-       "      <td>NaN</td>\n",
-       "    </tr>\n",
-       "    <tr>\n",
-       "      <th>4</th>\n",
-       "      <td>0000-0001-7071-8294</td>\n",
-       "      <td>NaN</td>\n",
-       "    </tr>\n",
-       "    <tr>\n",
-       "      <th>...</th>\n",
-       "      <td>...</td>\n",
-       "      <td>...</td>\n",
-       "    </tr>\n",
-       "    <tr>\n",
-       "      <th>10989644</th>\n",
-       "      <td>0000-0002-1686-1935</td>\n",
-       "      <td>NaN</td>\n",
-       "    </tr>\n",
-       "    <tr>\n",
-       "      <th>10989645</th>\n",
-       "      <td>0000-0002-3800-6331</td>\n",
-       "      <td>NaN</td>\n",
-       "    </tr>\n",
-       "    <tr>\n",
-       "      <th>10989646</th>\n",
-       "      <td>0000-0002-8783-5814</td>\n",
-       "      <td>NaN</td>\n",
-       "    </tr>\n",
-       "    <tr>\n",
-       "      <th>10989647</th>\n",
-       "      <td>0000-0002-7584-2283</td>\n",
-       "      <td>NaN</td>\n",
-       "    </tr>\n",
-       "    <tr>\n",
-       "      <th>10989648</th>\n",
-       "      <td>0000-0003-0529-3538</td>\n",
-       "      <td>NaN</td>\n",
-       "    </tr>\n",
-       "  </tbody>\n",
-       "</table>\n",
-       "<p>11300438 rows × 2 columns</p>\n",
-       "</div>"
-      ],
-      "text/plain": [
-       "                        orcid url_domains\n",
-       "0         0000-0001-6097-3953         NaN\n",
-       "1         0000-0001-6112-5550         NaN\n",
-       "2         0000-0001-6152-2695         NaN\n",
-       "3         0000-0001-6220-5683         NaN\n",
-       "4         0000-0001-7071-8294         NaN\n",
-       "...                       ...         ...\n",
-       "10989644  0000-0002-1686-1935         NaN\n",
-       "10989645  0000-0002-3800-6331         NaN\n",
-       "10989646  0000-0002-8783-5814         NaN\n",
-       "10989647  0000-0002-7584-2283         NaN\n",
-       "10989648  0000-0003-0529-3538         NaN\n",
-       "\n",
-       "[11300438 rows x 2 columns]"
-      ]
-     },
-     "execution_count": 154,
-     "metadata": {},
-     "output_type": "execute_result"
-    }
-   ],
+   "outputs": [],
    "source": [
     "exp = df[['orcid', 'url_domains']].explode('url_domains')"
    ]
   },
   {
    "cell_type": "code",
-   "execution_count": 157,
+   "execution_count": 107,
    "metadata": {},
    "outputs": [
     {
@@ -64954,7 +65181,7 @@
        "[548 rows x 2 columns]"
       ]
      },
-     "execution_count": 157,
+     "execution_count": 107,
      "metadata": {},
      "output_type": "execute_result"
     }
@@ -64965,7 +65192,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 158,
+   "execution_count": 108,
    "metadata": {},
    "outputs": [
     {
@@ -64996,6 +65223,7 @@
        "      <th>family_name</th>\n",
        "      <th>biography</th>\n",
        "      <th>other_names</th>\n",
+       "      <th>urls</th>\n",
        "      <th>primary_email</th>\n",
        "      <th>keywords</th>\n",
        "      <th>external_ids</th>\n",
@@ -65027,9 +65255,6 @@
        "      <th>biography_length</th>\n",
        "      <th>biography_n_sentences</th>\n",
        "      <th>biography_n_words</th>\n",
-       "      <th>date_diff</th>\n",
-       "      <th>ref_year</th>\n",
-       "      <th>date_stale</th>\n",
        "    </tr>\n",
        "  </thead>\n",
        "  <tbody>\n",
@@ -65042,6 +65267,7 @@
        "      <td>esterly</td>\n",
        "      <td>when parents tackle additional dedications out...</td>\n",
        "      <td>NaN</td>\n",
+       "      <td>[[idiaitera mathimata, http://manuelknhe509.lu...</td>\n",
        "      <td>&lt;NA&gt;</td>\n",
        "      <td>NaN</td>\n",
        "      <td>NaN</td>\n",
@@ -65073,9 +65299,6 @@
        "      <td>150</td>\n",
        "      <td>1.0</td>\n",
        "      <td>25.0</td>\n",
-       "      <td>0.018288</td>\n",
-       "      <td>2020</td>\n",
-       "      <td>116.515419</td>\n",
        "    </tr>\n",
        "  </tbody>\n",
        "</table>\n",
@@ -65091,32 +65314,35 @@
        "                                                biography other_names  \\\n",
        "142061  when parents tackle additional dedications out...         NaN   \n",
        "\n",
-       "       primary_email keywords external_ids education employment  n_works  \\\n",
-       "142061          <NA>      NaN          NaN       NaN        NaN        0   \n",
+       "                                                     urls primary_email  \\\n",
+       "142061  [[idiaitera mathimata, http://manuelknhe509.lu...          <NA>   \n",
        "\n",
-       "       works_source                  activation_date  \\\n",
-       "142061          NaN 2020-12-25 20:10:07.336000+00:00   \n",
+       "       keywords external_ids education employment  n_works works_source  \\\n",
+       "142061      NaN          NaN       NaN        NaN        0          NaN   \n",
        "\n",
-       "                       last_update_date  n_doi  n_arxiv  n_pmc  n_other_pids  \\\n",
-       "142061 2020-12-25 20:36:27.423000+00:00      0        0      0             0   \n",
+       "                        activation_date                 last_update_date  \\\n",
+       "142061 2020-12-25 20:10:07.336000+00:00 2020-12-25 20:36:27.423000+00:00   \n",
        "\n",
-       "        label primary_email_domain other_email_domains           url_domains  \\\n",
-       "142061  False                  NaN                 NaN  [lucialpiazzale.com]   \n",
+       "        n_doi  n_arxiv  n_pmc  n_other_pids  label primary_email_domain  \\\n",
+       "142061      0        0      0             0  False                  NaN   \n",
        "\n",
-       "        n_emails  n_urls  n_ids  n_keywords  n_education  n_employment  \\\n",
-       "142061      <NA>       1   <NA>        <NA>         <NA>          <NA>   \n",
+       "       other_email_domains           url_domains  n_emails  n_urls  n_ids  \\\n",
+       "142061                 NaN  [lucialpiazzale.com]      <NA>       1   <NA>   \n",
        "\n",
-       "       ext_works_source  n_ext_work_source authoritative  n_valid_education  \\\n",
-       "142061              NaN               <NA>         False                NaN   \n",
+       "        n_keywords  n_education  n_employment ext_works_source  \\\n",
+       "142061        <NA>         <NA>          <NA>              NaN   \n",
+       "\n",
+       "        n_ext_work_source authoritative  n_valid_education  \\\n",
+       "142061               <NA>         False                NaN   \n",
        "\n",
        "        n_valid_employment  biography_length  biography_n_sentences  \\\n",
        "142061                 NaN               150                    1.0   \n",
        "\n",
-       "        biography_n_words  date_diff  ref_year  date_stale  \n",
-       "142061               25.0   0.018288      2020  116.515419  "
+       "        biography_n_words  \n",
+       "142061               25.0  "
       ]
      },
-     "execution_count": 158,
+     "execution_count": 108,
      "metadata": {},
      "output_type": "execute_result"
     }
@@ -65134,7 +65360,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 96,
+   "execution_count": 109,
    "metadata": {},
    "outputs": [],
    "source": [
@@ -65143,7 +65369,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 97,
+   "execution_count": 110,
    "metadata": {},
    "outputs": [],
    "source": [
@@ -65156,7 +65382,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 98,
+   "execution_count": 111,
    "metadata": {},
    "outputs": [],
    "source": [
@@ -65165,7 +65391,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 99,
+   "execution_count": 112,
    "metadata": {},
    "outputs": [],
    "source": [
@@ -65174,7 +65400,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 100,
+   "execution_count": 113,
    "metadata": {},
    "outputs": [],
    "source": [
@@ -65183,7 +65409,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 101,
+   "execution_count": 114,
    "metadata": {},
    "outputs": [],
    "source": [
@@ -65192,7 +65418,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 102,
+   "execution_count": 115,
    "metadata": {},
    "outputs": [],
    "source": [
@@ -65215,7 +65441,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 103,
+   "execution_count": 116,
    "metadata": {},
    "outputs": [],
    "source": [
@@ -65224,7 +65450,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 104,
+   "execution_count": 117,
    "metadata": {},
    "outputs": [],
    "source": [
@@ -65247,7 +65473,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 105,
+   "execution_count": 118,
    "metadata": {},
    "outputs": [
     {
@@ -65256,7 +65482,7 @@
        "95398"
       ]
      },
-     "execution_count": 105,
+     "execution_count": 118,
      "metadata": {},
      "output_type": "execute_result"
     }
@@ -65267,7 +65493,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 106,
+   "execution_count": 119,
    "metadata": {},
    "outputs": [
     {
@@ -65276,7 +65502,7 @@
        "124216"
       ]
      },
-     "execution_count": 106,
+     "execution_count": 119,
      "metadata": {},
      "output_type": "execute_result"
     }
@@ -65287,7 +65513,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 107,
+   "execution_count": 120,
    "metadata": {},
    "outputs": [
     {
@@ -65296,7 +65522,7 @@
        "3428336"
       ]
      },
-     "execution_count": 107,
+     "execution_count": 120,
      "metadata": {},
      "output_type": "execute_result"
     }
@@ -65309,7 +65535,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 108,
+   "execution_count": 121,
    "metadata": {},
    "outputs": [
     {
@@ -65326,7 +65552,7 @@
        "Name: date_diff, dtype: float64"
       ]
      },
-     "execution_count": 108,
+     "execution_count": 121,
      "metadata": {},
      "output_type": "execute_result"
     }
@@ -65338,7 +65564,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 109,
+   "execution_count": 122,
    "metadata": {},
    "outputs": [
     {
@@ -65369,6 +65595,7 @@
        "      <th>family_name</th>\n",
        "      <th>biography</th>\n",
        "      <th>other_names</th>\n",
+       "      <th>urls</th>\n",
        "      <th>primary_email</th>\n",
        "      <th>keywords</th>\n",
        "      <th>external_ids</th>\n",
@@ -65413,6 +65640,7 @@
        "      <td>fiffe pérez</td>\n",
        "      <td>&lt;NA&gt;</td>\n",
        "      <td>NaN</td>\n",
+       "      <td>NaN</td>\n",
        "      <td>&lt;NA&gt;</td>\n",
        "      <td>NaN</td>\n",
        "      <td>NaN</td>\n",
@@ -65454,8 +65682,8 @@
        "                        orcid  verified_email  verified_primary_email  \\\n",
        "10771774  0000-0002-4035-0449           False                   False   \n",
        "\n",
-       "         given_names  family_name biography other_names primary_email  \\\n",
-       "10771774    aracelis  fiffe pérez      <NA>         NaN          <NA>   \n",
+       "         given_names  family_name biography other_names urls primary_email  \\\n",
+       "10771774    aracelis  fiffe pérez      <NA>         NaN  NaN          <NA>   \n",
        "\n",
        "         keywords external_ids education employment  n_works works_source  \\\n",
        "10771774      NaN          NaN       NaN        NaN        0          NaN   \n",
@@ -65482,7 +65710,7 @@
        "10771774  -0.000009  "
       ]
      },
-     "execution_count": 109,
+     "execution_count": 122,
      "metadata": {},
      "output_type": "execute_result"
     }
@@ -65493,7 +65721,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 110,
+   "execution_count": 123,
    "metadata": {},
    "outputs": [],
    "source": [
@@ -65502,7 +65730,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 111,
+   "execution_count": 124,
    "metadata": {},
    "outputs": [],
    "source": [
@@ -65511,7 +65739,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 112,
+   "execution_count": 125,
    "metadata": {},
    "outputs": [],
    "source": [
@@ -65531,7 +65759,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 115,
+   "execution_count": 126,
    "metadata": {},
    "outputs": [
     {
@@ -65554,7 +65782,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 116,
+   "execution_count": 127,
    "metadata": {},
    "outputs": [
     {
@@ -65579,24 +65807,24 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 117,
+   "execution_count": 128,
    "metadata": {},
    "outputs": [
     {
      "data": {
       "text/plain": [
        "count    1.098965e+07\n",
-       "mean     4.956143e+02\n",
+       "mean     5.036257e+02\n",
        "std      5.441444e+02\n",
-       "min      2.771697e+01\n",
-       "25%      7.902869e+01\n",
-       "50%      2.586001e+02\n",
-       "75%      7.215915e+02\n",
-       "max      2.967694e+03\n",
+       "min      3.572840e+01\n",
+       "25%      8.704012e+01\n",
+       "50%      2.666115e+02\n",
+       "75%      7.296030e+02\n",
+       "max      2.975705e+03\n",
        "Name: date_stale, dtype: float64"
       ]
      },
-     "execution_count": 117,
+     "execution_count": 128,
      "metadata": {},
      "output_type": "execute_result"
     }
@@ -65611,12 +65839,12 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 118,
+   "execution_count": 129,
    "metadata": {},
    "outputs": [
     {
      "data": {
-      "image/png": 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\n",
+      "image/png": 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\n",
       "text/plain": [
        "<Figure size 1152x432 with 1 Axes>"
       ]
@@ -65634,12 +65862,12 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 119,
+   "execution_count": 130,
    "metadata": {},
    "outputs": [
     {
      "data": {
-      "image/png": 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\n",
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\n",
       "text/plain": [
        "<Figure size 1152x432 with 1 Axes>"
       ]
@@ -65675,7 +65903,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 120,
+   "execution_count": 131,
    "metadata": {},
    "outputs": [
     {
@@ -65766,7 +65994,7 @@
            0.055840369923933694,
            0.17103410913261785,
            0.022658381195495434,
-           -0.26563296652477103
+           -0.26563296652477086
           ],
           [
            0.9649829131836175,
@@ -65816,7 +66044,7 @@
            0.13164682662703245,
            0.2791714236915975,
            -0.18761414495336803,
-           -0.10956754111570939
+           -0.10956754111570949
           ],
           [
            0.07259719921935885,
@@ -65841,7 +66069,7 @@
            0.10609112655491064,
            0.26550066134398,
            -0.17773494572670034,
-           -0.10498244037738991
+           -0.10498244037739002
           ],
           [
            0.0064613638682561435,
@@ -65866,7 +66094,7 @@
            0.003025339152373764,
            0.019756527828553628,
            -0.011377251319379719,
-           -0.010450007598058796
+           -0.010450007598058808
           ],
           [
            0.030614701011724112,
@@ -65891,7 +66119,7 @@
            0.038540356154355394,
            0.10708605224889314,
            -0.07142153774150983,
-           -0.04234941816473595
+           -0.04234941816473598
           ],
           [
            0.0606246420123506,
@@ -65916,7 +66144,7 @@
            0.10486157551396036,
            0.21995081618224488,
            -0.1460190598525363,
-           -0.08929201861156616
+           -0.08929201861156615
           ],
           [
            0.1240658917743258,
@@ -65941,7 +66169,7 @@
            0.0601029924210191,
            0.5071876289916429,
            -0.31637218163986053,
-           -0.23119989325527732
+           -0.2311998932552775
           ],
           [
            0.03267144560134065,
@@ -65991,7 +66219,7 @@
            0.19693868136073678,
            0.14482640798133928,
            -0.07613091173908271,
-           -0.08555532728488978
+           -0.08555532728488995
           ],
           [
            0.14475767748321952,
@@ -66016,7 +66244,7 @@
            0.12871309557991262,
            0.44112707302264015,
            -0.3033997683189775,
-           -0.16174776203112778
+           -0.16174776203112753
           ],
           [
            0.10243044622702734,
@@ -66041,7 +66269,7 @@
            0.21943621766746263,
            0.20608875126467818,
            -0.1375367447333582,
-           -0.08137348062024251
+           -0.08137348062024242
           ],
           [
            0.22284375415000315,
@@ -66066,7 +66294,7 @@
            0.16186377317319656,
            0.26707817114478954,
            -0.16270609288632273,
-           -0.12596524238530568
+           -0.12596524238530582
           ],
           [
            0.2240544946507108,
@@ -66116,7 +66344,7 @@
            0.13881467285061283,
            0.529277499531768,
            -0.304403202853194,
-           -0.28092138782966974
+           -0.2809213878296699
           ],
           [
            0.21764209610282456,
@@ -66141,7 +66369,7 @@
            0.14949976332317635,
            0.25718947605247133,
            -0.15297182983926474,
-           -0.12646564408587102
+           -0.1264656440858709
           ],
           [
            0.22363930402583765,
@@ -66166,7 +66394,7 @@
            0.165283657096934,
            0.3142004323600891,
            -0.1675052953620132,
-           -0.1838455776688462
+           -0.18384557766884607
           ],
           [
            0.055922574238810654,
@@ -66191,7 +66419,7 @@
            0.996227194122333,
            0.12230024994563019,
            -0.08115328238798254,
-           -0.04941584312492917
+           -0.04941584312492913
           ],
           [
            0.06465027511100795,
@@ -66216,7 +66444,7 @@
            0.891762751746278,
            0.11806407161670705,
            -0.07360446098797291,
-           -0.053720706289268436
+           -0.053720706289268456
           ],
           [
            0.055840369923933694,
@@ -66241,7 +66469,7 @@
            1,
            0.12103643791637957,
            -0.07999644631248218,
-           -0.04935382637731908
+           -0.04935382637731911
           ],
           [
            0.17103410913261785,
@@ -66266,7 +66494,7 @@
            0.12103643791637957,
            1,
            -0.7407291991512941,
-           -0.28771132570265834
+           -0.2877113257026588
           ],
           [
            0.022658381195495434,
@@ -66291,31 +66519,31 @@
            -0.07999644631248218,
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\"paper_bgcolor\": \"white\", \"plot_bgcolor\": \"#E5ECF6\", \"polar\": {\"angularaxis\": {\"gridcolor\": \"white\", \"linecolor\": \"white\", \"ticks\": \"\"}, \"bgcolor\": \"#E5ECF6\", \"radialaxis\": {\"gridcolor\": \"white\", \"linecolor\": \"white\", \"ticks\": \"\"}}, \"scene\": {\"xaxis\": {\"backgroundcolor\": \"#E5ECF6\", \"gridcolor\": \"white\", \"gridwidth\": 2, \"linecolor\": \"white\", \"showbackground\": true, \"ticks\": \"\", \"zerolinecolor\": \"white\"}, \"yaxis\": {\"backgroundcolor\": \"#E5ECF6\", \"gridcolor\": \"white\", \"gridwidth\": 2, \"linecolor\": \"white\", \"showbackground\": true, \"ticks\": \"\", \"zerolinecolor\": \"white\"}, \"zaxis\": {\"backgroundcolor\": \"#E5ECF6\", \"gridcolor\": \"white\", \"gridwidth\": 2, \"linecolor\": \"white\", \"showbackground\": true, \"ticks\": \"\", \"zerolinecolor\": \"white\"}}, \"shapedefaults\": {\"line\": {\"color\": \"#2a3f5f\"}}, \"ternary\": {\"aaxis\": {\"gridcolor\": \"white\", \"linecolor\": \"white\", \"ticks\": \"\"}, \"baxis\": {\"gridcolor\": \"white\", \"linecolor\": \"white\", \"ticks\": \"\"}, \"bgcolor\": \"#E5ECF6\", \"caxis\": {\"gridcolor\": \"white\", \"linecolor\": \"white\", \"ticks\": \"\"}}, \"title\": {\"x\": 0.05}, \"xaxis\": {\"automargin\": true, \"gridcolor\": \"white\", \"linecolor\": \"white\", \"ticks\": \"\", \"title\": {\"standoff\": 15}, \"zerolinecolor\": \"white\", \"zerolinewidth\": 2}, \"yaxis\": {\"automargin\": true, \"gridcolor\": \"white\", \"linecolor\": \"white\", \"ticks\": \"\", \"title\": {\"standoff\": 15}, \"zerolinecolor\": \"white\", \"zerolinewidth\": 2}}}, \"xaxis\": {\"anchor\": \"y\", \"constrain\": \"domain\", \"domain\": [0.0, 1.0], \"scaleanchor\": \"y\"}, \"yaxis\": {\"anchor\": \"x\", \"autorange\": \"reversed\", \"constrain\": \"domain\", \"domain\": [0.0, 1.0]}},                        {\"responsive\": true}                    ).then(function(){\n",
        "                            \n",
-       "var gd = document.getElementById('2aa48001-cbe2-4aa6-8f5c-349c06f0a393');\n",
+       "var gd = document.getElementById('5bdea0d6-a83a-45bd-ab89-01ae4e2452b2');\n",
        "var x = new MutationObserver(function (mutations, observer) {{\n",
        "        var display = window.getComputedStyle(gd).display;\n",
        "        if (!display || display === 'none') {{\n",
@@ -70352,29 +70580,16 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 123,
+   "execution_count": 137,
    "metadata": {},
    "outputs": [],
    "source": [
-    "# df[['verified_email', \n",
-    "#     'verified_primary_email', \n",
-    "#     'n_works', \n",
-    "#     'n_doi',\n",
-    "#     'n_arxiv', \n",
-    "#     'n_pmc', \n",
-    "#     'n_other_pids', \n",
-    "#     'n_emails', \n",
-    "#     'n_urls', \n",
-    "#     'n_ids', \n",
-    "#     'n_keywords', \n",
-    "#     'n_employment', \n",
-    "#     'n_education', \n",
-    "#     'label']].to_pickle('../data/processed/features.pkl')"
+    "# df.select_dtypes(include=['bool','number']).to_pickle('../data/processed/features.pkl')"
    ]
   },
   {
    "cell_type": "code",
-   "execution_count": 222,
+   "execution_count": 135,
    "metadata": {},
    "outputs": [
     {
@@ -70382,11 +70597,11 @@
      "output_type": "stream",
      "text": [
       "<class 'pandas.core.frame.DataFrame'>\n",
-      "RangeIndex: 10989649 entries, 0 to 10989648\n",
-      "Data columns (total 31 columns):\n",
+      "Int64Index: 10989649 entries, 0 to 10989648\n",
+      "Data columns (total 42 columns):\n",
       " #   Column                  Dtype              \n",
       "---  ------                  -----              \n",
-      " 0   orcid                   string             \n",
+      " 0   orcid                   object             \n",
       " 1   verified_email          bool               \n",
       " 2   verified_primary_email  bool               \n",
       " 3   given_names             string             \n",
@@ -70417,8 +70632,19 @@
       " 28  n_keywords              Int16              \n",
       " 29  n_education             Int16              \n",
       " 30  n_employment            Int16              \n",
-      "dtypes: Int16(11), bool(3), datetime64[ns, UTC](2), object(10), string(5)\n",
-      "memory usage: 1.8+ GB\n"
+      " 31  ext_works_source        object             \n",
+      " 32  n_ext_work_source       Int16              \n",
+      " 33  authoritative           object             \n",
+      " 34  n_valid_education       float64            \n",
+      " 35  n_valid_employment      float64            \n",
+      " 36  biography_length        Int64              \n",
+      " 37  biography_n_sentences   float64            \n",
+      " 38  biography_n_words       float64            \n",
+      " 39  date_diff               float64            \n",
+      " 40  ref_year                int64              \n",
+      " 41  date_stale              float64            \n",
+      "dtypes: Int16(12), Int64(1), bool(3), datetime64[ns, UTC](2), float64(6), int64(1), object(13), string(4)\n",
+      "memory usage: 2.7+ GB\n"
      ]
     }
    ],
@@ -70426,6 +70652,15 @@
     "df.info()"
    ]
   },
+  {
+   "cell_type": "code",
+   "execution_count": 161,
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "df[df.orcid.isin(FAKE_HEAP.values())].to_csv('../data/processed/fake_heap_index.csv', index=True, index_label='index')"
+   ]
+  },
   {
    "cell_type": "code",
    "execution_count": null,
diff --git a/notebooks/02-Spam filter.ipynb b/notebooks/02-Spam filter.ipynb
deleted file mode 100644
index 903ef75..0000000
--- a/notebooks/02-Spam filter.ipynb	
+++ /dev/null
@@ -1,1096 +0,0 @@
-{
- "cells": [
-  {
-   "cell_type": "markdown",
-   "metadata": {},
-   "source": [
-    "# Dataset preprocessing"
-   ]
-  },
-  {
-   "cell_type": "code",
-   "execution_count": 49,
-   "metadata": {},
-   "outputs": [],
-   "source": [
-    "import pandas as pd\n",
-    "import ast\n",
-    "import tldextract\n",
-    "import numpy"
-   ]
-  },
-  {
-   "cell_type": "code",
-   "execution_count": 50,
-   "metadata": {},
-   "outputs": [],
-   "source": [
-    "# Notable Solid ORCID iDs for debug purposes\n",
-    "AM = '0000-0002-5193-7851'\n",
-    "PP = '0000-0002-8588-4196'\n"
-   ]
-  },
-  {
-   "cell_type": "code",
-   "execution_count": 51,
-   "metadata": {},
-   "outputs": [],
-   "source": [
-    "# Notable fake ORCID iDs for debug purposes\n",
-    "SCAFFOLD = '0000-0001-5004-7761'\n",
-    "WHATSAPP = '0000-0001-6997-9470'\n"
-   ]
-  },
-  {
-   "cell_type": "code",
-   "execution_count": 52,
-   "metadata": {},
-   "outputs": [],
-   "source": [
-    "df = pd.read_csv('../data/raw/initial_info_whole.tsv', sep='\\t', header=0,\n",
-    "                         dtype = {'orcid': pd.StringDtype(), \n",
-    "                                  'claimed': bool, \n",
-    "                                  'verifyed email': bool, \n",
-    "                                  'verified primary email': bool,\n",
-    "                                  'given names': pd.StringDtype(),\n",
-    "                                  'family name': pd.StringDtype(),\n",
-    "                                  'biography': pd.StringDtype(),\n",
-    "                                  'other names': pd.StringDtype(),\n",
-    "                                  'researcher urls': pd.StringDtype(),\n",
-    "                                  'primary email': pd.StringDtype(),\n",
-    "                                  'other emails': pd.StringDtype(),\n",
-    "                                  'keywords': pd.StringDtype(),\n",
-    "                                  'external identifiers': pd.StringDtype(),\n",
-    "                                  'education': pd.StringDtype(),\n",
-    "                                  'employments': pd.StringDtype(),\n",
-    "                                  'number of works': pd.Int16Dtype(),\n",
-    "                                  'works source': pd.StringDtype()})"
-   ]
-  },
-  {
-   "cell_type": "code",
-   "execution_count": 53,
-   "metadata": {},
-   "outputs": [],
-   "source": [
-    "df['given names'] = df['given names'].fillna('')\n",
-    "df['family name'] = df['family name'].fillna('')\n",
-    "df['biography'] = df['biography'].fillna('')\n",
-    "df['primary email'] = df['primary email'].fillna('')"
-   ]
-  },
-  {
-   "cell_type": "code",
-   "execution_count": 54,
-   "metadata": {},
-   "outputs": [],
-   "source": [
-    "df['other names'] = df['other names'].fillna('[]').apply(lambda x: ast.literal_eval(x))"
-   ]
-  },
-  {
-   "cell_type": "code",
-   "execution_count": 55,
-   "metadata": {},
-   "outputs": [],
-   "source": [
-    "df['keywords'] = df['keywords'].fillna('[]').apply(lambda x: ast.literal_eval(x))"
-   ]
-  },
-  {
-   "cell_type": "code",
-   "execution_count": 59,
-   "metadata": {},
-   "outputs": [],
-   "source": [
-    "df['url_domains'] = df['researcher urls'].apply(lambda lst: extract_url_domains(lst))"
-   ]
-  },
-  {
-   "cell_type": "code",
-   "execution_count": 57,
-   "metadata": {},
-   "outputs": [],
-   "source": [
-    "df['researcher urls'] = df['researcher urls'].fillna('[]').apply(lambda x: ast.literal_eval(x))"
-   ]
-  },
-  {
-   "cell_type": "code",
-   "execution_count": 58,
-   "metadata": {},
-   "outputs": [],
-   "source": [
-    "def extract_url_domains(lst):\n",
-    "    domains = []\n",
-    "    for e in lst:\n",
-    "        # e[0] is a string describing the url\n",
-    "        # e[1] is the url\n",
-    "        domain = tldextract.extract(e[1])\n",
-    "        domains.append(domain.registered_domain)\n",
-    "    return domains"
-   ]
-  },
-  {
-   "cell_type": "code",
-   "execution_count": 60,
-   "metadata": {},
-   "outputs": [],
-   "source": [
-    "df['education'] = df['education'].fillna('[]').apply(lambda x: ast.literal_eval(x))"
-   ]
-  },
-  {
-   "cell_type": "code",
-   "execution_count": 61,
-   "metadata": {},
-   "outputs": [],
-   "source": [
-    "def extract_education(lst):\n",
-    "    educations = []\n",
-    "    for e in lst:\n",
-    "        # e[0] degree\n",
-    "        # e[1] role\n",
-    "        # e[2] university\n",
-    "        # e[..] city, region, country, id, id_scheme\n",
-    "        educations.append(' '.join([e[0], e[1], e[2]]))\n",
-    "    return educations"
-   ]
-  },
-  {
-   "cell_type": "code",
-   "execution_count": 62,
-   "metadata": {},
-   "outputs": [],
-   "source": [
-    "df['employments'] = df['employments'].fillna('[]').apply(lambda x: ast.literal_eval(x))"
-   ]
-  },
-  {
-   "cell_type": "code",
-   "execution_count": 63,
-   "metadata": {},
-   "outputs": [],
-   "source": [
-    "def extract_employment(lst):\n",
-    "    res = []\n",
-    "    for e in lst:\n",
-    "        # e[0] role\n",
-    "        # e[1] institute\n",
-    "        # e[..] city, region, country, id, id_scheme\n",
-    "        res.append(' '.join([e[0], e[1]]))\n",
-    "    return res"
-   ]
-  },
-  {
-   "cell_type": "code",
-   "execution_count": 56,
-   "metadata": {},
-   "outputs": [],
-   "source": [
-    "df['other emails'] = df['other emails'].fillna('[]').apply(lambda x: ast.literal_eval(x))"
-   ]
-  },
-  {
-   "cell_type": "code",
-   "execution_count": 64,
-   "metadata": {},
-   "outputs": [],
-   "source": [
-    "def extract_email_domains(lst):\n",
-    "    res = []\n",
-    "    for email in lst:\n",
-    "        res.append(email.replace('@', ' '))\n",
-    "    return res"
-   ]
-  },
-  {
-   "cell_type": "code",
-   "execution_count": 81,
-   "metadata": {},
-   "outputs": [],
-   "source": [
-    "df['concat'] =  df['given names'] + ' ' + df['family name'] + '\\n' + \\\n",
-    "                df['other names'].apply(lambda x: ' '.join(x)) + '\\n' + \\\n",
-    "                df['primary email'].values[0].replace('@', ' ') + '\\n' + \\\n",
-    "                df['other emails'].apply(lambda x: ' '.join(extract_email_domains(x))) + '\\n' + \\\n",
-    "                df['biography'] + '\\n' + \\\n",
-    "                df['keywords'].apply(lambda x: ' - '.join(x)) + '\\n' + \\\n",
-    "                df['url_domains'].apply(lambda x: ' '.join(x)) + '\\n' + \\\n",
-    "                df['education'].apply(lambda x: '\\n'.join(extract_education(x))) + '\\n' + \\\n",
-    "                df['employments'].apply(lambda x: '\\n'.join(extract_employment(x)))"
-   ]
-  },
-  {
-   "cell_type": "code",
-   "execution_count": 82,
-   "metadata": {},
-   "outputs": [
-    {
-     "name": "stdout",
-     "output_type": "stream",
-     "text": [
-      "Andrea Mannocci\n",
-      "\n",
-      "\n",
-      "\n",
-      "\n",
-      "Data science  - science of science - scholarly knowledge mining - open science - research infrastructures\n",
-      "github.io twitter.com linkedin.com\n",
-      "Information engineering Ph.D. Università degli Studi di Pisa\n",
-      "Telematics engineering M.Sc. Universidad Carlos III de Madrid\n",
-      "Computer engineering M.Sc. Università degli Studi di Pisa\n",
-      "Computer engineering B.Sc. Università degli Studi di Pisa\n",
-      "Research Associate Istituto di Scienza e Tecnologie dellInformazione Alessandro Faedo Consiglio Nazionale delle Ricerche\n",
-      "Research Associate The Open University\n",
-      "Research assistant Istituto di Scienza e Tecnologie dellInformazione Alessandro Faedo Consiglio Nazionale delle Ricerche\n",
-      "Research assistant IMDEA Networks\n",
-      "Research assistant Syddansk Universitet\n"
-     ]
-    }
-   ],
-   "source": [
-    "print(df[df['orcid'] == AM]['concat'].values[0])"
-   ]
-  },
-  {
-   "cell_type": "code",
-   "execution_count": 19,
-   "metadata": {},
-   "outputs": [],
-   "source": [
-    "df.loc[df['number of works'] > 0, 'label'] = True"
-   ]
-  },
-  {
-   "cell_type": "code",
-   "execution_count": 20,
-   "metadata": {},
-   "outputs": [
-    {
-     "data": {
-      "text/html": [
-       "<div>\n",
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-       "\n",
-       "    .dataframe thead th {\n",
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-       "</style>\n",
-       "<table border=\"1\" class=\"dataframe\">\n",
-       "  <thead>\n",
-       "    <tr style=\"text-align: right;\">\n",
-       "      <th></th>\n",
-       "      <th>orcid</th>\n",
-       "      <th>claimed</th>\n",
-       "      <th>verifyed email</th>\n",
-       "      <th>verified primary email</th>\n",
-       "      <th>given names</th>\n",
-       "      <th>family name</th>\n",
-       "      <th>biography</th>\n",
-       "      <th>other names</th>\n",
-       "      <th>researcher urls</th>\n",
-       "      <th>primary email</th>\n",
-       "      <th>other emails</th>\n",
-       "      <th>keywords</th>\n",
-       "      <th>external identifiers</th>\n",
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-       "      <th>employments</th>\n",
-       "      <th>number of works</th>\n",
-       "      <th>works source</th>\n",
-       "      <th>url_domains</th>\n",
-       "      <th>concat</th>\n",
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-       "    </tr>\n",
-       "  </thead>\n",
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-       "    <tr>\n",
-       "      <th>8840413</th>\n",
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-       "      <td>True</td>\n",
-       "      <td>True</td>\n",
-       "      <td>True</td>\n",
-       "      <td>Andrea</td>\n",
-       "      <td>Mannocci</td>\n",
-       "      <td></td>\n",
-       "      <td>[]</td>\n",
-       "      <td>[[Personal website, https://andremann.github.i...</td>\n",
-       "      <td>andrea.mannocci@isti.cnr.it</td>\n",
-       "      <td>[]</td>\n",
-       "      <td>[Data science , science of science, scholarly ...</td>\n",
-       "      <td>[[\"Scopus Author ID\", \"55233589900\"]]</td>\n",
-       "      <td>[[Information engineering, Ph.D., Università d...</td>\n",
-       "      <td>[[Research Associate, Istituto di Scienza e Te...</td>\n",
-       "      <td>37</td>\n",
-       "      <td>[\"Scopus - Elsevier\", \"Crossref Metadata Searc...</td>\n",
-       "      <td>[github.io, twitter.com, linkedin.com]</td>\n",
-       "      <td>0000-0002-5193-7851\n",
-       "Andrea Mannocci\n",
-       "\n",
-       "andrea.ma...</td>\n",
-       "      <td>True</td>\n",
-       "    </tr>\n",
-       "  </tbody>\n",
-       "</table>\n",
-       "</div>"
-      ],
-      "text/plain": [
-       "                       orcid  claimed  verifyed email  verified primary email  \\\n",
-       "8840413  0000-0002-5193-7851     True            True                    True   \n",
-       "\n",
-       "        given names family name biography other names  \\\n",
-       "8840413      Andrea    Mannocci                    []   \n",
-       "\n",
-       "                                           researcher urls  \\\n",
-       "8840413  [[Personal website, https://andremann.github.i...   \n",
-       "\n",
-       "                       primary email other emails  \\\n",
-       "8840413  andrea.mannocci@isti.cnr.it           []   \n",
-       "\n",
-       "                                                  keywords  \\\n",
-       "8840413  [Data science , science of science, scholarly ...   \n",
-       "\n",
-       "                          external identifiers  \\\n",
-       "8840413  [[\"Scopus Author ID\", \"55233589900\"]]   \n",
-       "\n",
-       "                                                 education  \\\n",
-       "8840413  [[Information engineering, Ph.D., Università d...   \n",
-       "\n",
-       "                                               employments  number of works  \\\n",
-       "8840413  [[Research Associate, Istituto di Scienza e Te...               37   \n",
-       "\n",
-       "                                              works source  \\\n",
-       "8840413  [\"Scopus - Elsevier\", \"Crossref Metadata Searc...   \n",
-       "\n",
-       "                                    url_domains  \\\n",
-       "8840413  [github.io, twitter.com, linkedin.com]   \n",
-       "\n",
-       "                                                    concat label  \n",
-       "8840413  0000-0002-5193-7851\n",
-       "Andrea Mannocci\n",
-       "\n",
-       "andrea.ma...  True  "
-      ]
-     },
-     "execution_count": 20,
-     "metadata": {},
-     "output_type": "execute_result"
-    }
-   ],
-   "source": [
-    "df[df['orcid'] == AM]"
-   ]
-  },
-  {
-   "cell_type": "code",
-   "execution_count": 21,
-   "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",
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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>orcid</th>\n",
-       "      <th>claimed</th>\n",
-       "      <th>verifyed email</th>\n",
-       "      <th>verified primary email</th>\n",
-       "      <th>given names</th>\n",
-       "      <th>family name</th>\n",
-       "      <th>biography</th>\n",
-       "      <th>other names</th>\n",
-       "      <th>researcher urls</th>\n",
-       "      <th>primary email</th>\n",
-       "      <th>other emails</th>\n",
-       "      <th>keywords</th>\n",
-       "      <th>external identifiers</th>\n",
-       "      <th>education</th>\n",
-       "      <th>employments</th>\n",
-       "      <th>number of works</th>\n",
-       "      <th>works source</th>\n",
-       "      <th>url_domains</th>\n",
-       "      <th>concat</th>\n",
-       "      <th>label</th>\n",
-       "    </tr>\n",
-       "  </thead>\n",
-       "  <tbody>\n",
-       "    <tr>\n",
-       "      <th>14</th>\n",
-       "      <td>0000-0001-5004-7761</td>\n",
-       "      <td>True</td>\n",
-       "      <td>True</td>\n",
-       "      <td>True</td>\n",
-       "      <td>scaffolding</td>\n",
-       "      <td>hire</td>\n",
-       "      <td></td>\n",
-       "      <td>[The first feature that you have to check in t...</td>\n",
-       "      <td>[[scaffolding hire Wellington, https://www.tig...</td>\n",
-       "      <td></td>\n",
-       "      <td>[]</td>\n",
-       "      <td>[scaffolding hire Wellington]</td>\n",
-       "      <td>&lt;NA&gt;</td>\n",
-       "      <td>[]</td>\n",
-       "      <td>[]</td>\n",
-       "      <td>0</td>\n",
-       "      <td>&lt;NA&gt;</td>\n",
-       "      <td>[tigerscaffolds.co.nz]</td>\n",
-       "      <td>0000-0001-5004-7761\n",
-       "scaffolding hire\n",
-       "The first...</td>\n",
-       "      <td>NaN</td>\n",
-       "    </tr>\n",
-       "  </tbody>\n",
-       "</table>\n",
-       "</div>"
-      ],
-      "text/plain": [
-       "                  orcid  claimed  verifyed email  verified primary email  \\\n",
-       "14  0000-0001-5004-7761     True            True                    True   \n",
-       "\n",
-       "    given names family name biography  \\\n",
-       "14  scaffolding        hire             \n",
-       "\n",
-       "                                          other names  \\\n",
-       "14  [The first feature that you have to check in t...   \n",
-       "\n",
-       "                                      researcher urls primary email  \\\n",
-       "14  [[scaffolding hire Wellington, https://www.tig...                 \n",
-       "\n",
-       "   other emails                       keywords external identifiers education  \\\n",
-       "14           []  [scaffolding hire Wellington]                 <NA>        []   \n",
-       "\n",
-       "   employments  number of works works source             url_domains  \\\n",
-       "14          []                0         <NA>  [tigerscaffolds.co.nz]   \n",
-       "\n",
-       "                                               concat label  \n",
-       "14  0000-0001-5004-7761\n",
-       "scaffolding hire\n",
-       "The first...   NaN  "
-      ]
-     },
-     "execution_count": 21,
-     "metadata": {},
-     "output_type": "execute_result"
-    }
-   ],
-   "source": [
-    "df[df['orcid'] == SCAFFOLD]"
-   ]
-  },
-  {
-   "cell_type": "code",
-   "execution_count": 25,
-   "metadata": {},
-   "outputs": [
-    {
-     "data": {
-      "text/html": [
-       "<div>\n",
-       "<style scoped>\n",
-       "    .dataframe tbody tr th:only-of-type {\n",
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-       "\n",
-       "    .dataframe thead th {\n",
-       "        text-align: right;\n",
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-       "</style>\n",
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-       "  <thead>\n",
-       "    <tr style=\"text-align: right;\">\n",
-       "      <th></th>\n",
-       "      <th>concat</th>\n",
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-       "    </tr>\n",
-       "  </thead>\n",
-       "  <tbody>\n",
-       "    <tr>\n",
-       "      <th>0</th>\n",
-       "      <td>0000-0001-5000-2053\n",
-       "Jorge  Jaramillo Sanchez \n",
-       "...</td>\n",
-       "      <td>NaN</td>\n",
-       "    </tr>\n",
-       "    <tr>\n",
-       "      <th>1</th>\n",
-       "      <td>0000-0001-5000-6548\n",
-       "Wiseman Bekelesi</td>\n",
-       "      <td>NaN</td>\n",
-       "    </tr>\n",
-       "    <tr>\n",
-       "      <th>2</th>\n",
-       "      <td>0000-0001-5000-7962\n",
-       "ALICE INDIMULI</td>\n",
-       "      <td>NaN</td>\n",
-       "    </tr>\n",
-       "    <tr>\n",
-       "      <th>3</th>\n",
-       "      <td>0000-0001-5000-8586\n",
-       "shim ji yun</td>\n",
-       "      <td>NaN</td>\n",
-       "    </tr>\n",
-       "    <tr>\n",
-       "      <th>4</th>\n",
-       "      <td>0000-0001-5001-0256\n",
-       "Sandro Caramaschi</td>\n",
-       "      <td>NaN</td>\n",
-       "    </tr>\n",
-       "    <tr>\n",
-       "      <th>...</th>\n",
-       "      <td>...</td>\n",
-       "      <td>...</td>\n",
-       "    </tr>\n",
-       "    <tr>\n",
-       "      <th>10747035</th>\n",
-       "      <td>0000-0003-4998-1551\n",
-       "Animesh Ghosh</td>\n",
-       "      <td>NaN</td>\n",
-       "    </tr>\n",
-       "    <tr>\n",
-       "      <th>10747036</th>\n",
-       "      <td>0000-0003-4998-4111\n",
-       "Hawa Liberna</td>\n",
-       "      <td>NaN</td>\n",
-       "    </tr>\n",
-       "    <tr>\n",
-       "      <th>10747037</th>\n",
-       "      <td>0000-0003-4998-6045\n",
-       "Tongyi Men</td>\n",
-       "      <td>NaN</td>\n",
-       "    </tr>\n",
-       "    <tr>\n",
-       "      <th>10747038</th>\n",
-       "      <td>0000-0003-4998-8868\n",
-       "Charldon Wilken</td>\n",
-       "      <td>NaN</td>\n",
-       "    </tr>\n",
-       "    <tr>\n",
-       "      <th>10747039</th>\n",
-       "      <td>0000-0003-4999-7916\n",
-       "Tapas Bapu B.R.</td>\n",
-       "      <td>NaN</td>\n",
-       "    </tr>\n",
-       "  </tbody>\n",
-       "</table>\n",
-       "<p>10747040 rows × 2 columns</p>\n",
-       "</div>"
-      ],
-      "text/plain": [
-       "                                                     concat label\n",
-       "0         0000-0001-5000-2053\n",
-       "Jorge  Jaramillo Sanchez \n",
-       "...   NaN\n",
-       "1              0000-0001-5000-6548\n",
-       "Wiseman Bekelesi\n",
-       "\n",
-       "\n",
-       "\n",
-       "\n",
-       "\n",
-       "\n",
-       "\n",
-       "   NaN\n",
-       "2                0000-0001-5000-7962\n",
-       "ALICE INDIMULI\n",
-       "\n",
-       "\n",
-       "\n",
-       "\n",
-       "\n",
-       "\n",
-       "\n",
-       "   NaN\n",
-       "3                   0000-0001-5000-8586\n",
-       "shim ji yun\n",
-       "\n",
-       "\n",
-       "\n",
-       "\n",
-       "\n",
-       "\n",
-       "\n",
-       "   NaN\n",
-       "4             0000-0001-5001-0256\n",
-       "Sandro Caramaschi\n",
-       "\n",
-       "\n",
-       "\n",
-       "\n",
-       "\n",
-       "\n",
-       "\n",
-       "   NaN\n",
-       "...                                                     ...   ...\n",
-       "10747035          0000-0003-4998-1551\n",
-       "Animesh Ghosh\n",
-       "\n",
-       "\n",
-       "\n",
-       "\n",
-       "\n",
-       "\n",
-       "\n",
-       "   NaN\n",
-       "10747036           0000-0003-4998-4111\n",
-       "Hawa Liberna\n",
-       "\n",
-       "\n",
-       "\n",
-       "\n",
-       "\n",
-       "\n",
-       "\n",
-       "   NaN\n",
-       "10747037             0000-0003-4998-6045\n",
-       "Tongyi Men\n",
-       "\n",
-       "\n",
-       "\n",
-       "\n",
-       "\n",
-       "\n",
-       "\n",
-       "   NaN\n",
-       "10747038        0000-0003-4998-8868\n",
-       "Charldon Wilken\n",
-       "\n",
-       "\n",
-       "\n",
-       "\n",
-       "\n",
-       "\n",
-       "\n",
-       "   NaN\n",
-       "10747039        0000-0003-4999-7916\n",
-       "Tapas Bapu B.R.\n",
-       "\n",
-       "\n",
-       "\n",
-       "\n",
-       "\n",
-       "\n",
-       "\n",
-       "   NaN\n",
-       "\n",
-       "[10747040 rows x 2 columns]"
-      ]
-     },
-     "execution_count": 25,
-     "metadata": {},
-     "output_type": "execute_result"
-    }
-   ],
-   "source": [
-    "df = df[['orcid', 'concat', 'label']]\n",
-    "df"
-   ]
-  },
-  {
-   "cell_type": "markdown",
-   "metadata": {},
-   "source": [
-    "# Pre-trained spam filter as-is"
-   ]
-  },
-  {
-   "cell_type": "code",
-   "execution_count": 83,
-   "metadata": {},
-   "outputs": [
-    {
-     "ename": "ModuleNotFoundError",
-     "evalue": "No module named 'seaborn'",
-     "output_type": "error",
-     "traceback": [
-      "\u001b[0;31m---------------------------------------------------------------------------\u001b[0m",
-      "\u001b[0;31mModuleNotFoundError\u001b[0m                       Traceback (most recent call last)",
-      "\u001b[0;32m<ipython-input-83-72f6535bcb9f>\u001b[0m in \u001b[0;36m<module>\u001b[0;34m\u001b[0m\n\u001b[1;32m      4\u001b[0m \u001b[0;32mimport\u001b[0m \u001b[0mnumpy\u001b[0m \u001b[0;32mas\u001b[0m \u001b[0mnp\u001b[0m \u001b[0;31m# linear algebra\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m      5\u001b[0m \u001b[0;32mimport\u001b[0m \u001b[0mpandas\u001b[0m \u001b[0;32mas\u001b[0m \u001b[0mpd\u001b[0m \u001b[0;31m# data processing, CSV file I/O (e.g. pd.read_csv)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0;32m----> 6\u001b[0;31m \u001b[0;32mimport\u001b[0m \u001b[0mseaborn\u001b[0m \u001b[0;32mas\u001b[0m \u001b[0msns\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0m\u001b[1;32m      7\u001b[0m \u001b[0;32mimport\u001b[0m \u001b[0mmatplotlib\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0mpyplot\u001b[0m \u001b[0;32mas\u001b[0m \u001b[0mplt\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m      8\u001b[0m \u001b[0;32mfrom\u001b[0m \u001b[0mnltk\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0mcorpus\u001b[0m \u001b[0;32mimport\u001b[0m \u001b[0mstopwords\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n",
-      "\u001b[0;31mModuleNotFoundError\u001b[0m: No module named 'seaborn'"
-     ]
-    }
-   ],
-   "source": [
-    "import string\n",
-    "import torch\n",
-    "import transformers\n",
-    "import numpy as np # linear algebra\n",
-    "import pandas as pd # data processing, CSV file I/O (e.g. pd.read_csv)\n",
-    "import seaborn as sns\n",
-    "import matplotlib.pyplot as plt\n",
-    "from nltk.corpus import stopwords\n",
-    "from sklearn.manifold import TSNE\n",
-    "from nltk.tokenize import word_tokenize\n",
-    "from sklearn.ensemble import RandomForestClassifier\n",
-    "from sklearn.model_selection import train_test_split\n",
-    "from sklearn.metrics import classification_report, confusion_matrix, accuracy_score, roc_auc_score"
-   ]
-  },
-  {
-   "cell_type": "code",
-   "execution_count": null,
-   "metadata": {},
-   "outputs": [],
-   "source": []
-  },
-  {
-   "cell_type": "code",
-   "execution_count": null,
-   "metadata": {},
-   "outputs": [],
-   "source": []
-  },
-  {
-   "cell_type": "markdown",
-   "metadata": {},
-   "source": [
-    "# One-Class SVM"
-   ]
-  },
-  {
-   "cell_type": "code",
-   "execution_count": 41,
-   "metadata": {},
-   "outputs": [],
-   "source": [
-    "from sklearn.feature_extraction.text import TfidfVectorizer\n",
-    "from sklearn.svm import OneClassSVM\n",
-    "from sklearn.model_selection import train_test_split\n"
-   ]
-  },
-  {
-   "cell_type": "code",
-   "execution_count": 44,
-   "metadata": {},
-   "outputs": [
-    {
-     "name": "stderr",
-     "output_type": "stream",
-     "text": [
-      "<ipython-input-44-8393c5b42618>:3: SettingWithCopyWarning: \n",
-      "A value is trying to be set on a copy of a slice from a DataFrame.\n",
-      "Try using .loc[row_indexer,col_indexer] = value instead\n",
-      "\n",
-      "See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n",
-      "  samples['features'] = vectorizer.fit_transform(samples['concat'])\n"
-     ]
-    }
-   ],
-   "source": [
-    "samples = df[df['label'] == True]\n",
-    "vectorizer = TfidfVectorizer()\n",
-    "samples['features'] = vectorizer.fit_transform(samples['concat'])"
-   ]
-  },
-  {
-   "cell_type": "code",
-   "execution_count": 46,
-   "metadata": {},
-   "outputs": [
-    {
-     "data": {
-      "text/plain": [
-       "5             (0, 983769)\\t0.04916990678988556\\n  (0, 1177...\n",
-       "13            (0, 983769)\\t0.04916990678988556\\n  (0, 1177...\n",
-       "24            (0, 983769)\\t0.04916990678988556\\n  (0, 1177...\n",
-       "26            (0, 983769)\\t0.04916990678988556\\n  (0, 1177...\n",
-       "29            (0, 983769)\\t0.04916990678988556\\n  (0, 1177...\n",
-       "                                  ...                        \n",
-       "10747024      (0, 983769)\\t0.04916990678988556\\n  (0, 1177...\n",
-       "10747026      (0, 983769)\\t0.04916990678988556\\n  (0, 1177...\n",
-       "10747027      (0, 983769)\\t0.04916990678988556\\n  (0, 1177...\n",
-       "10747030      (0, 983769)\\t0.04916990678988556\\n  (0, 1177...\n",
-       "10747034      (0, 983769)\\t0.04916990678988556\\n  (0, 1177...\n",
-       "Name: features, Length: 2674451, dtype: object"
-      ]
-     },
-     "execution_count": 46,
-     "metadata": {},
-     "output_type": "execute_result"
-    }
-   ],
-   "source": [
-    "samples['features']"
-   ]
-  },
-  {
-   "cell_type": "code",
-   "execution_count": null,
-   "metadata": {},
-   "outputs": [],
-   "source": [
-    "trainX, testX, trainy, testy = train_test_split(samples['features'], samples['label'], test_size=0.7, random_state=3, stratify=y)"
-   ]
-  },
-  {
-   "cell_type": "code",
-   "execution_count": null,
-   "metadata": {},
-   "outputs": [],
-   "source": [
-    "model = OneClassSVM(gamma='scale', nu=0.01)\n",
-    "model.fit(trainX)"
-   ]
-  },
-  {
-   "cell_type": "markdown",
-   "metadata": {},
-   "source": [
-    "## Training"
-   ]
-  },
-  {
-   "cell_type": "code",
-   "execution_count": 118,
-   "metadata": {},
-   "outputs": [
-    {
-     "ename": "ValueError",
-     "evalue": "could not convert string to float: '0000-0001-5001-4994'",
-     "output_type": "error",
-     "traceback": [
-      "\u001b[0;31m---------------------------------------------------------------------------\u001b[0m",
-      "\u001b[0;31mValueError\u001b[0m                                Traceback (most recent call last)",
-      "\u001b[0;32m<ipython-input-118-78458a59bca9>\u001b[0m in \u001b[0;36m<module>\u001b[0;34m\u001b[0m\n\u001b[0;32m----> 1\u001b[0;31m \u001b[0mmodel\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0mfit\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0mdf\u001b[0m\u001b[0;34m[\u001b[0m\u001b[0mdf\u001b[0m\u001b[0;34m[\u001b[0m\u001b[0;34m'label'\u001b[0m\u001b[0;34m]\u001b[0m \u001b[0;34m==\u001b[0m \u001b[0;32mTrue\u001b[0m\u001b[0;34m]\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0m",
-      "\u001b[0;32m~/.virtualenvs/data-science/lib/python3.8/site-packages/sklearn/svm/_classes.py\u001b[0m in \u001b[0;36mfit\u001b[0;34m(self, X, y, sample_weight, **params)\u001b[0m\n\u001b[1;32m   1374\u001b[0m \u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m   1375\u001b[0m         \"\"\"\n\u001b[0;32m-> 1376\u001b[0;31m         super().fit(X, np.ones(_num_samples(X)),\n\u001b[0m\u001b[1;32m   1377\u001b[0m                     sample_weight=sample_weight, **params)\n\u001b[1;32m   1378\u001b[0m         \u001b[0mself\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0moffset_\u001b[0m \u001b[0;34m=\u001b[0m \u001b[0;34m-\u001b[0m\u001b[0mself\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0m_intercept_\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n",
-      "\u001b[0;32m~/.virtualenvs/data-science/lib/python3.8/site-packages/sklearn/svm/_base.py\u001b[0m in \u001b[0;36mfit\u001b[0;34m(self, X, y, sample_weight)\u001b[0m\n\u001b[1;32m    167\u001b[0m             \u001b[0mcheck_consistent_length\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0mX\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0my\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m    168\u001b[0m         \u001b[0;32melse\u001b[0m\u001b[0;34m:\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0;32m--> 169\u001b[0;31m             X, y = self._validate_data(X, y, dtype=np.float64,\n\u001b[0m\u001b[1;32m    170\u001b[0m                                        \u001b[0morder\u001b[0m\u001b[0;34m=\u001b[0m\u001b[0;34m'C'\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0maccept_sparse\u001b[0m\u001b[0;34m=\u001b[0m\u001b[0;34m'csr'\u001b[0m\u001b[0;34m,\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m    171\u001b[0m                                        accept_large_sparse=False)\n",
-      "\u001b[0;32m~/.virtualenvs/data-science/lib/python3.8/site-packages/sklearn/base.py\u001b[0m in \u001b[0;36m_validate_data\u001b[0;34m(self, X, y, reset, validate_separately, **check_params)\u001b[0m\n\u001b[1;32m    431\u001b[0m                 \u001b[0my\u001b[0m \u001b[0;34m=\u001b[0m \u001b[0mcheck_array\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0my\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0;34m**\u001b[0m\u001b[0mcheck_y_params\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m    432\u001b[0m             \u001b[0;32melse\u001b[0m\u001b[0;34m:\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0;32m--> 433\u001b[0;31m                 \u001b[0mX\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0my\u001b[0m \u001b[0;34m=\u001b[0m \u001b[0mcheck_X_y\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0mX\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0my\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0;34m**\u001b[0m\u001b[0mcheck_params\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0m\u001b[1;32m    434\u001b[0m             \u001b[0mout\u001b[0m \u001b[0;34m=\u001b[0m \u001b[0mX\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0my\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m    435\u001b[0m \u001b[0;34m\u001b[0m\u001b[0m\n",
-      "\u001b[0;32m~/.virtualenvs/data-science/lib/python3.8/site-packages/sklearn/utils/validation.py\u001b[0m in \u001b[0;36minner_f\u001b[0;34m(*args, **kwargs)\u001b[0m\n\u001b[1;32m     61\u001b[0m             \u001b[0mextra_args\u001b[0m \u001b[0;34m=\u001b[0m \u001b[0mlen\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0margs\u001b[0m\u001b[0;34m)\u001b[0m \u001b[0;34m-\u001b[0m \u001b[0mlen\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0mall_args\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m     62\u001b[0m             \u001b[0;32mif\u001b[0m \u001b[0mextra_args\u001b[0m \u001b[0;34m<=\u001b[0m \u001b[0;36m0\u001b[0m\u001b[0;34m:\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0;32m---> 63\u001b[0;31m                 \u001b[0;32mreturn\u001b[0m \u001b[0mf\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0;34m*\u001b[0m\u001b[0margs\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0;34m**\u001b[0m\u001b[0mkwargs\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0m\u001b[1;32m     64\u001b[0m \u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m     65\u001b[0m             \u001b[0;31m# extra_args > 0\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n",
-      "\u001b[0;32m~/.virtualenvs/data-science/lib/python3.8/site-packages/sklearn/utils/validation.py\u001b[0m in \u001b[0;36mcheck_X_y\u001b[0;34m(X, y, accept_sparse, accept_large_sparse, dtype, order, copy, force_all_finite, ensure_2d, allow_nd, multi_output, ensure_min_samples, ensure_min_features, y_numeric, estimator)\u001b[0m\n\u001b[1;32m    812\u001b[0m         \u001b[0;32mraise\u001b[0m \u001b[0mValueError\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0;34m\"y cannot be None\"\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m    813\u001b[0m \u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0;32m--> 814\u001b[0;31m     X = check_array(X, accept_sparse=accept_sparse,\n\u001b[0m\u001b[1;32m    815\u001b[0m                     \u001b[0maccept_large_sparse\u001b[0m\u001b[0;34m=\u001b[0m\u001b[0maccept_large_sparse\u001b[0m\u001b[0;34m,\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m    816\u001b[0m                     \u001b[0mdtype\u001b[0m\u001b[0;34m=\u001b[0m\u001b[0mdtype\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0morder\u001b[0m\u001b[0;34m=\u001b[0m\u001b[0morder\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0mcopy\u001b[0m\u001b[0;34m=\u001b[0m\u001b[0mcopy\u001b[0m\u001b[0;34m,\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n",
-      "\u001b[0;32m~/.virtualenvs/data-science/lib/python3.8/site-packages/sklearn/utils/validation.py\u001b[0m in \u001b[0;36minner_f\u001b[0;34m(*args, **kwargs)\u001b[0m\n\u001b[1;32m     61\u001b[0m             \u001b[0mextra_args\u001b[0m \u001b[0;34m=\u001b[0m \u001b[0mlen\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0margs\u001b[0m\u001b[0;34m)\u001b[0m \u001b[0;34m-\u001b[0m \u001b[0mlen\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0mall_args\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m     62\u001b[0m             \u001b[0;32mif\u001b[0m \u001b[0mextra_args\u001b[0m \u001b[0;34m<=\u001b[0m \u001b[0;36m0\u001b[0m\u001b[0;34m:\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0;32m---> 63\u001b[0;31m                 \u001b[0;32mreturn\u001b[0m \u001b[0mf\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0;34m*\u001b[0m\u001b[0margs\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0;34m**\u001b[0m\u001b[0mkwargs\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0m\u001b[1;32m     64\u001b[0m \u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m     65\u001b[0m             \u001b[0;31m# extra_args > 0\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n",
-      "\u001b[0;32m~/.virtualenvs/data-science/lib/python3.8/site-packages/sklearn/utils/validation.py\u001b[0m in \u001b[0;36mcheck_array\u001b[0;34m(array, accept_sparse, accept_large_sparse, dtype, order, copy, force_all_finite, ensure_2d, allow_nd, ensure_min_samples, ensure_min_features, estimator)\u001b[0m\n\u001b[1;32m    558\u001b[0m     \u001b[0;32mif\u001b[0m \u001b[0mhas_pd_integer_array\u001b[0m\u001b[0;34m:\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m    559\u001b[0m         \u001b[0;31m# If there are any pandas integer extension arrays,\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0;32m--> 560\u001b[0;31m         \u001b[0marray\u001b[0m \u001b[0;34m=\u001b[0m \u001b[0marray\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0mastype\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0mdtype\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0m\u001b[1;32m    561\u001b[0m \u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m    562\u001b[0m     \u001b[0;32mif\u001b[0m \u001b[0mforce_all_finite\u001b[0m \u001b[0;32mnot\u001b[0m \u001b[0;32min\u001b[0m \u001b[0;34m(\u001b[0m\u001b[0;32mTrue\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0;32mFalse\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0;34m'allow-nan'\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m:\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n",
-      "\u001b[0;32m~/.virtualenvs/data-science/lib/python3.8/site-packages/pandas/core/generic.py\u001b[0m in \u001b[0;36mastype\u001b[0;34m(self, dtype, copy, errors)\u001b[0m\n\u001b[1;32m   5875\u001b[0m         \u001b[0;32melse\u001b[0m\u001b[0;34m:\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m   5876\u001b[0m             \u001b[0;31m# else, only a single dtype is given\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0;32m-> 5877\u001b[0;31m             \u001b[0mnew_data\u001b[0m \u001b[0;34m=\u001b[0m \u001b[0mself\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0m_mgr\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0mastype\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0mdtype\u001b[0m\u001b[0;34m=\u001b[0m\u001b[0mdtype\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0mcopy\u001b[0m\u001b[0;34m=\u001b[0m\u001b[0mcopy\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0merrors\u001b[0m\u001b[0;34m=\u001b[0m\u001b[0merrors\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0m\u001b[1;32m   5878\u001b[0m             \u001b[0;32mreturn\u001b[0m \u001b[0mself\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0m_constructor\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0mnew_data\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0m__finalize__\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0mself\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0mmethod\u001b[0m\u001b[0;34m=\u001b[0m\u001b[0;34m\"astype\"\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m   5879\u001b[0m \u001b[0;34m\u001b[0m\u001b[0m\n",
-      "\u001b[0;32m~/.virtualenvs/data-science/lib/python3.8/site-packages/pandas/core/internals/managers.py\u001b[0m in \u001b[0;36mastype\u001b[0;34m(self, dtype, copy, errors)\u001b[0m\n\u001b[1;32m    629\u001b[0m         \u001b[0mself\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0mdtype\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0mcopy\u001b[0m\u001b[0;34m:\u001b[0m \u001b[0mbool\u001b[0m \u001b[0;34m=\u001b[0m \u001b[0;32mFalse\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0merrors\u001b[0m\u001b[0;34m:\u001b[0m \u001b[0mstr\u001b[0m \u001b[0;34m=\u001b[0m \u001b[0;34m\"raise\"\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m    630\u001b[0m     ) -> \"BlockManager\":\n\u001b[0;32m--> 631\u001b[0;31m         \u001b[0;32mreturn\u001b[0m \u001b[0mself\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0mapply\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0;34m\"astype\"\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0mdtype\u001b[0m\u001b[0;34m=\u001b[0m\u001b[0mdtype\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0mcopy\u001b[0m\u001b[0;34m=\u001b[0m\u001b[0mcopy\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0merrors\u001b[0m\u001b[0;34m=\u001b[0m\u001b[0merrors\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0m\u001b[1;32m    632\u001b[0m \u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m    633\u001b[0m     def convert(\n",
-      "\u001b[0;32m~/.virtualenvs/data-science/lib/python3.8/site-packages/pandas/core/internals/managers.py\u001b[0m in \u001b[0;36mapply\u001b[0;34m(self, f, align_keys, ignore_failures, **kwargs)\u001b[0m\n\u001b[1;32m    425\u001b[0m                     \u001b[0mapplied\u001b[0m \u001b[0;34m=\u001b[0m \u001b[0mb\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0mapply\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0mf\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0;34m**\u001b[0m\u001b[0mkwargs\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m    426\u001b[0m                 \u001b[0;32melse\u001b[0m\u001b[0;34m:\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0;32m--> 427\u001b[0;31m                     \u001b[0mapplied\u001b[0m \u001b[0;34m=\u001b[0m \u001b[0mgetattr\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0mb\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0mf\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0;34m**\u001b[0m\u001b[0mkwargs\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0m\u001b[1;32m    428\u001b[0m             \u001b[0;32mexcept\u001b[0m \u001b[0;34m(\u001b[0m\u001b[0mTypeError\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0mNotImplementedError\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m:\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m    429\u001b[0m                 \u001b[0;32mif\u001b[0m \u001b[0;32mnot\u001b[0m \u001b[0mignore_failures\u001b[0m\u001b[0;34m:\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n",
-      "\u001b[0;32m~/.virtualenvs/data-science/lib/python3.8/site-packages/pandas/core/internals/blocks.py\u001b[0m in \u001b[0;36mastype\u001b[0;34m(self, dtype, copy, errors)\u001b[0m\n\u001b[1;32m    646\u001b[0m         \u001b[0;32mif\u001b[0m \u001b[0mself\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0mis_extension\u001b[0m\u001b[0;34m:\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m    647\u001b[0m             \u001b[0;32mtry\u001b[0m\u001b[0;34m:\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0;32m--> 648\u001b[0;31m                 \u001b[0mvalues\u001b[0m \u001b[0;34m=\u001b[0m \u001b[0mself\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0mvalues\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0mastype\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0mdtype\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0m\u001b[1;32m    649\u001b[0m             \u001b[0;32mexcept\u001b[0m \u001b[0;34m(\u001b[0m\u001b[0mValueError\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0mTypeError\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m:\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m    650\u001b[0m                 \u001b[0;32mif\u001b[0m \u001b[0merrors\u001b[0m \u001b[0;34m==\u001b[0m \u001b[0;34m\"ignore\"\u001b[0m\u001b[0;34m:\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n",
-      "\u001b[0;32m~/.virtualenvs/data-science/lib/python3.8/site-packages/pandas/core/arrays/string_.py\u001b[0m in \u001b[0;36mastype\u001b[0;34m(self, dtype, copy)\u001b[0m\n\u001b[1;32m    306\u001b[0m             \u001b[0mmask\u001b[0m \u001b[0;34m=\u001b[0m \u001b[0mself\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0misna\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m    307\u001b[0m             \u001b[0marr\u001b[0m\u001b[0;34m[\u001b[0m\u001b[0mmask\u001b[0m\u001b[0;34m]\u001b[0m \u001b[0;34m=\u001b[0m \u001b[0;36m0\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0;32m--> 308\u001b[0;31m             \u001b[0mvalues\u001b[0m \u001b[0;34m=\u001b[0m \u001b[0marr\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0mastype\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0mdtype\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0m\u001b[1;32m    309\u001b[0m             \u001b[0mvalues\u001b[0m\u001b[0;34m[\u001b[0m\u001b[0mmask\u001b[0m\u001b[0;34m]\u001b[0m \u001b[0;34m=\u001b[0m \u001b[0mnp\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0mnan\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m    310\u001b[0m             \u001b[0;32mreturn\u001b[0m \u001b[0mvalues\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n",
-      "\u001b[0;31mValueError\u001b[0m: could not convert string to float: '0000-0001-5001-4994'"
-     ]
-    }
-   ],
-   "source": [
-    "model.fit(df[df['label'] == True])"
-   ]
-  },
-  {
-   "cell_type": "markdown",
-   "metadata": {},
-   "source": [
-    "## Evaluation"
-   ]
-  },
-  {
-   "cell_type": "code",
-   "execution_count": null,
-   "metadata": {},
-   "outputs": [],
-   "source": []
-  },
-  {
-   "cell_type": "code",
-   "execution_count": null,
-   "metadata": {},
-   "outputs": [],
-   "source": []
-  },
-  {
-   "cell_type": "code",
-   "execution_count": null,
-   "metadata": {},
-   "outputs": [],
-   "source": []
-  },
-  {
-   "cell_type": "code",
-   "execution_count": null,
-   "metadata": {},
-   "outputs": [],
-   "source": []
-  },
-  {
-   "cell_type": "markdown",
-   "metadata": {},
-   "source": [
-    "# BERT"
-   ]
-  },
-  {
-   "cell_type": "code",
-   "execution_count": 30,
-   "metadata": {},
-   "outputs": [],
-   "source": [
-    "# Language model Databunch\n",
-    "from fast_bert.data_lm import BertLMDataBunch\n",
-    "# Language model learner\n",
-    "from fast_bert.learner_lm import BertLMLearner\n",
-    "\n",
-    "from pathlib import Path\n",
-    "from box import Box\n",
-    "\n",
-    "import logging\n",
-    "logger = logging.getLogger()\n"
-   ]
-  },
-  {
-   "cell_type": "code",
-   "execution_count": 34,
-   "metadata": {},
-   "outputs": [],
-   "source": [
-    "# Box is a nice wrapper to create an object from a json dict\n",
-    "args = Box({\n",
-    "    \"seed\": 42,\n",
-    "    \"task_name\": 'imdb_reviews_lm',\n",
-    "    \"model_name\": 'roberta-base',\n",
-    "    \"model_type\": 'roberta',\n",
-    "    \"train_batch_size\": 16,\n",
-    "    \"learning_rate\": 4e-5,\n",
-    "    \"num_train_epochs\": 20,\n",
-    "    \"fp16\": True,\n",
-    "    \"fp16_opt_level\": \"O2\",\n",
-    "    \"warmup_steps\": 1000,\n",
-    "    \"logging_steps\": 0,\n",
-    "    \"max_seq_length\": 512,\n",
-    "    \"multi_gpu\": False\n",
-    "})\n",
-    "\n",
-    "DATA_PATH = Path('../data/processed')\n",
-    "LOG_PATH = Path('../logs')\n",
-    "MODEL_PATH = Path('../models/lm_model_{}/'.format(args.model_type))\n",
-    "\n",
-    "DATA_PATH.mkdir(exist_ok=True)\n",
-    "MODEL_PATH.mkdir(exist_ok=True)\n",
-    "LOG_PATH.mkdir(exist_ok=True)"
-   ]
-  },
-  {
-   "cell_type": "code",
-   "execution_count": 35,
-   "metadata": {},
-   "outputs": [
-    {
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-     "output_type": "error",
-     "traceback": [
-      "\u001b[0;31m---------------------------------------------------------------------------\u001b[0m",
-      "\u001b[0;31mUnicodeEncodeError\u001b[0m                        Traceback (most recent call last)",
-      "\u001b[0;32m<ipython-input-35-702486b1b84c>\u001b[0m in \u001b[0;36m<module>\u001b[0;34m\u001b[0m\n\u001b[0;32m----> 1\u001b[0;31m databunch_lm = BertLMDataBunch.from_raw_corpus(\n\u001b[0m\u001b[1;32m      2\u001b[0m     \u001b[0mdata_dir\u001b[0m\u001b[0;34m=\u001b[0m\u001b[0mDATA_PATH\u001b[0m\u001b[0;34m,\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m      3\u001b[0m     \u001b[0mtext_list\u001b[0m\u001b[0;34m=\u001b[0m\u001b[0mdf\u001b[0m\u001b[0;34m[\u001b[0m\u001b[0;34m'concat'\u001b[0m\u001b[0;34m]\u001b[0m\u001b[0;34m,\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m      4\u001b[0m     \u001b[0mtokenizer\u001b[0m\u001b[0;34m=\u001b[0m\u001b[0margs\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0mmodel_name\u001b[0m\u001b[0;34m,\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m      5\u001b[0m     \u001b[0mbatch_size_per_gpu\u001b[0m\u001b[0;34m=\u001b[0m\u001b[0margs\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0mtrain_batch_size\u001b[0m\u001b[0;34m,\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n",
-      "\u001b[0;32m~/.virtualenvs/data-science/lib/python3.8/site-packages/fast_bert/data_lm.py\u001b[0m in \u001b[0;36mfrom_raw_corpus\u001b[0;34m(data_dir, text_list, tokenizer, batch_size_per_gpu, max_seq_length, multi_gpu, test_size, model_type, logger, clear_cache, no_cache)\u001b[0m\n\u001b[1;32m    191\u001b[0m         )\n\u001b[1;32m    192\u001b[0m         \u001b[0;31m# Create train corpus\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0;32m--> 193\u001b[0;31m         \u001b[0mcreate_corpus\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0mtrain_list\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0mstr\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0mdata_dir\u001b[0m \u001b[0;34m/\u001b[0m \u001b[0mtrain_file\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0mlogger\u001b[0m\u001b[0;34m=\u001b[0m\u001b[0mlogger\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0m\u001b[1;32m    194\u001b[0m \u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m    195\u001b[0m         \u001b[0;31m# Create val corpus\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n",
-      "\u001b[0;32m~/.virtualenvs/data-science/lib/python3.8/site-packages/fast_bert/data_lm.py\u001b[0m in \u001b[0;36mcreate_corpus\u001b[0;34m(text_list, target_path, logger)\u001b[0m\n\u001b[1;32m     87\u001b[0m             \u001b[0mtext\u001b[0m \u001b[0;34m=\u001b[0m \u001b[0mtext\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0mstrip\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m     88\u001b[0m \u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0;32m---> 89\u001b[0;31m             \u001b[0mf\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0mwrite\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0mtext\u001b[0m \u001b[0;34m+\u001b[0m \u001b[0;34m\"\\n\"\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0m\u001b[1;32m     90\u001b[0m \u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m     91\u001b[0m \u001b[0;34m\u001b[0m\u001b[0m\n",
-      "\u001b[0;31mUnicodeEncodeError\u001b[0m: 'utf-8' codec can't encode characters in position 162-163: surrogates not allowed"
-     ]
-    }
-   ],
-   "source": [
-    "databunch_lm = BertLMDataBunch.from_raw_corpus(\n",
-    "    data_dir=DATA_PATH,\n",
-    "    text_list=df['concat'],\n",
-    "    tokenizer=args.model_name,\n",
-    "    batch_size_per_gpu=args.train_batch_size,\n",
-    "    max_seq_length=args.max_seq_length,\n",
-    "    multi_gpu=args.multi_gpu,\n",
-    "    model_type=args.model_type,\n",
-    "    logger=logger)"
-   ]
-  },
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-   "cell_type": "code",
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diff --git a/notebooks/03-Machine Learning.ipynb b/notebooks/03-Machine Learning.ipynb
deleted file mode 100644
index 0eed4e7..0000000
--- a/notebooks/03-Machine Learning.ipynb	
+++ /dev/null
@@ -1,1028 +0,0 @@
-{
- "cells": [
-  {
-   "cell_type": "code",
-   "execution_count": 2,
-   "metadata": {},
-   "outputs": [],
-   "source": [
-    "import ast\n",
-    "from urllib.parse import urlparse\n",
-    "import tldextract\n",
-    "\n",
-    "import pandas as pd\n",
-    "from sklearn.preprocessing import MultiLabelBinarizer\n",
-    "from sklearn.svm import OneClassSVM \n",
-    "from sklearn.model_selection import train_test_split\n",
-    "from sklearn.metrics import f1_score\n"
-   ]
-  },
-  {
-   "cell_type": "code",
-   "execution_count": 3,
-   "metadata": {},
-   "outputs": [],
-   "source": [
-    "df = pd.read_pickle('../data/processed/features.pkl')"
-   ]
-  },
-  {
-   "cell_type": "code",
-   "execution_count": 4,
-   "metadata": {},
-   "outputs": [
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-       "      <th></th>\n",
-       "      <th>verified_email</th>\n",
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-       "      <th>n_works</th>\n",
-       "      <th>n_doi</th>\n",
-       "      <th>n_arxiv</th>\n",
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-       "      <th>n_urls</th>\n",
-       "      <th>n_ids</th>\n",
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-       "</table>\n",
-       "<p>10989649 rows × 14 columns</p>\n",
-       "</div>"
-      ],
-      "text/plain": [
-       "          verified_email  verified_primary_email  n_works  n_doi  n_arxiv  \\\n",
-       "0                      0                       0        0      0        0   \n",
-       "1                      1                       1        0      0        0   \n",
-       "2                      1                       1        0      0        0   \n",
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-       "...                  ...                     ...      ...    ...      ...   \n",
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-       "\n",
-       "          n_pmc  n_other_pids  n_emails  n_urls  n_ids  n_keywords  \\\n",
-       "0             0             0       NaN     NaN    NaN         NaN   \n",
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-       "\n",
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-     "execution_count": 4,
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-  },
-  {
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-   "outputs": [],
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-    "df.fillna(0, inplace=True)"
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-       "<p>10989649 rows × 14 columns</p>\n",
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-       "          verified_email  verified_primary_email  n_works  n_doi  n_arxiv  \\\n",
-       "0                      0                       0        0      0        0   \n",
-       "1                      1                       1        0      0        0   \n",
-       "2                      1                       1        0      0        0   \n",
-       "3                      1                       1        0      0        0   \n",
-       "4                      1                       1        0      0        0   \n",
-       "...                  ...                     ...      ...    ...      ...   \n",
-       "10989644               1                       1        0      0        0   \n",
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-       "10989646               1                       1        0      0        0   \n",
-       "10989647               1                       1        0      0        0   \n",
-       "10989648               1                       1        0      0        0   \n",
-       "\n",
-       "          n_pmc  n_other_pids  n_emails  n_urls  n_ids  n_keywords  \\\n",
-       "0             0             0       0.0     0.0    0.0         0.0   \n",
-       "1             0             0       0.0     0.0    0.0         0.0   \n",
-       "2             0             0       0.0     0.0    0.0         0.0   \n",
-       "3             0             0       0.0     0.0    0.0         0.0   \n",
-       "4             0             0       0.0     0.0    0.0         0.0   \n",
-       "...         ...           ...       ...     ...    ...         ...   \n",
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-       "10989648      0             0       0.0     0.0    0.0         0.0   \n",
-       "\n",
-       "          n_employment  n_education  label  \n",
-       "0                  0.0          0.0      0  \n",
-       "1                  1.0          0.0      0  \n",
-       "2                  0.0          0.0      0  \n",
-       "3                  1.0          0.0      0  \n",
-       "4                  2.0          0.0      0  \n",
-       "...                ...          ...    ...  \n",
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-       "10989645           2.0          2.0      1  \n",
-       "10989646           0.0          0.0      0  \n",
-       "10989647           1.0          2.0      0  \n",
-       "10989648           0.0          0.0      0  \n",
-       "\n",
-       "[10989649 rows x 14 columns]"
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-     },
-     "execution_count": 6,
-     "metadata": {},
-     "output_type": "execute_result"
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-   ],
-   "source": [
-    "df"
-   ]
-  },
-  {
-   "cell_type": "code",
-   "execution_count": 7,
-   "metadata": {},
-   "outputs": [
-    {
-     "data": {
-      "text/plain": [
-       "verified_email            2664886\n",
-       "verified_primary_email    2664886\n",
-       "n_works                   2664886\n",
-       "n_doi                     2664886\n",
-       "n_arxiv                   2664886\n",
-       "n_pmc                     2664886\n",
-       "n_other_pids              2664886\n",
-       "n_emails                  2664886\n",
-       "n_urls                    2664886\n",
-       "n_ids                     2664886\n",
-       "n_keywords                2664886\n",
-       "n_employment              2664886\n",
-       "n_education               2664886\n",
-       "label                     2664886\n",
-       "dtype: int64"
-      ]
-     },
-     "execution_count": 7,
-     "metadata": {},
-     "output_type": "execute_result"
-    }
-   ],
-   "source": [
-    "df[df.label == 1].count()"
-   ]
-  },
-  {
-   "cell_type": "code",
-   "execution_count": 8,
-   "metadata": {},
-   "outputs": [
-    {
-     "data": {
-      "text/plain": [
-       "verified_email            8324763\n",
-       "verified_primary_email    8324763\n",
-       "n_works                   8324763\n",
-       "n_doi                     8324763\n",
-       "n_arxiv                   8324763\n",
-       "n_pmc                     8324763\n",
-       "n_other_pids              8324763\n",
-       "n_emails                  8324763\n",
-       "n_urls                    8324763\n",
-       "n_ids                     8324763\n",
-       "n_keywords                8324763\n",
-       "n_employment              8324763\n",
-       "n_education               8324763\n",
-       "label                     8324763\n",
-       "dtype: int64"
-      ]
-     },
-     "execution_count": 8,
-     "metadata": {},
-     "output_type": "execute_result"
-    }
-   ],
-   "source": [
-    "df[df.label == 0].count()"
-   ]
-  },
-  {
-   "cell_type": "code",
-   "execution_count": 10,
-   "metadata": {},
-   "outputs": [],
-   "source": [
-    "# split into train/test sets\n",
-    "X = df.loc[:,'verified_email':'n_education']\n",
-    "y = df['label']\n",
-    "trainX, testX, trainy, testy = train_test_split(X, y, train_size=0.5, random_state=2, stratify=y)"
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-   "execution_count": 11,
-   "metadata": {},
-   "outputs": [
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-       "      <th>4589084</th>\n",
-       "      <td>1</td>\n",
-       "      <td>1</td>\n",
-       "      <td>11</td>\n",
-       "      <td>0</td>\n",
-       "      <td>0</td>\n",
-       "      <td>0</td>\n",
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-       "      <td>1.0</td>\n",
-       "      <td>0.0</td>\n",
-       "    </tr>\n",
-       "  </tbody>\n",
-       "</table>\n",
-       "<p>5494824 rows × 13 columns</p>\n",
-       "</div>"
-      ],
-      "text/plain": [
-       "          verified_email  verified_primary_email  n_works  n_doi  n_arxiv  \\\n",
-       "6325067                1                       1        0      0        0   \n",
-       "6140551                1                       1        0      0        0   \n",
-       "3258315                1                       1        0      0        0   \n",
-       "10948983               1                       1        0      0        0   \n",
-       "10089158               1                       1        0      0        0   \n",
-       "...                  ...                     ...      ...    ...      ...   \n",
-       "2398808                0                       0        1      1        0   \n",
-       "3622839                1                       1        0      0        0   \n",
-       "1389679                1                       1        0      0        0   \n",
-       "6594722                0                       0        0      0        0   \n",
-       "4589084                1                       1       11      0        0   \n",
-       "\n",
-       "          n_pmc  n_other_pids  n_emails  n_urls  n_ids  n_keywords  \\\n",
-       "6325067       0             0       0.0     0.0    1.0         0.0   \n",
-       "6140551       0             0       0.0     0.0    0.0         0.0   \n",
-       "3258315       0             0       0.0     1.0    0.0         2.0   \n",
-       "10948983      0             0       0.0     0.0    0.0         0.0   \n",
-       "10089158      0             0       0.0     0.0    0.0         0.0   \n",
-       "...         ...           ...       ...     ...    ...         ...   \n",
-       "2398808       0             0       0.0     0.0    0.0         0.0   \n",
-       "3622839       0             0       0.0     0.0    0.0         0.0   \n",
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-       "6594722       0             0       0.0     0.0    0.0         0.0   \n",
-       "4589084       0             0       0.0     0.0    0.0         0.0   \n",
-       "\n",
-       "          n_employment  n_education  \n",
-       "6325067            1.0          1.0  \n",
-       "6140551            0.0          0.0  \n",
-       "3258315            0.0          0.0  \n",
-       "10948983           1.0          0.0  \n",
-       "10089158           0.0          0.0  \n",
-       "...                ...          ...  \n",
-       "2398808            0.0          0.0  \n",
-       "3622839            1.0          1.0  \n",
-       "1389679            0.0          0.0  \n",
-       "6594722            0.0          0.0  \n",
-       "4589084            1.0          0.0  \n",
-       "\n",
-       "[5494824 rows x 13 columns]"
-      ]
-     },
-     "execution_count": 11,
-     "metadata": {},
-     "output_type": "execute_result"
-    }
-   ],
-   "source": [
-    "trainX"
-   ]
-  },
-  {
-   "cell_type": "code",
-   "execution_count": null,
-   "metadata": {},
-   "outputs": [],
-   "source": [
-    "# define outlier detection model\n",
-    "model = OneClassSVM(gamma='scale', nu=0.5)\n",
-    "\n",
-    "# fit on majority class\n",
-    "trainX = trainX[trainy==1]\n",
-    "model.fit(trainX)"
-   ]
-  },
-  {
-   "cell_type": "code",
-   "execution_count": null,
-   "metadata": {},
-   "outputs": [],
-   "source": [
-    "# detect outliers in the test set\n",
-    "yhat = model.predict(testX)\n",
-    "\n",
-    "# mark inliers 1, outliers -1\n",
-    "testy[testy == 0] = -1\n",
-    "testy[testy == 1] = 1\n",
-    "\n",
-    "# calculate score\n",
-    "score = f1_score(testy, yhat, pos_label=-1)\n",
-    "print('F1 Score: %.3f' % score)"
-   ]
-  },
-  {
-   "cell_type": "code",
-   "execution_count": null,
-   "metadata": {},
-   "outputs": [],
-   "source": []
-  }
- ],
- "metadata": {
-  "kernelspec": {
-   "display_name": "Python 3",
-   "language": "python",
-   "name": "python3"
-  },
-  "language_info": {
-   "codemirror_mode": {
-    "name": "ipython",
-    "version": 3
-   },
-   "file_extension": ".py",
-   "mimetype": "text/x-python",
-   "name": "python",
-   "nbconvert_exporter": "python",
-   "pygments_lexer": "ipython3",
-   "version": "3.8.3"
-  }
- },
- "nbformat": 4,
- "nbformat_minor": 4
-}
diff --git a/notebooks/03-Supervised.ipynb b/notebooks/03-Supervised.ipynb
new file mode 100644
index 0000000..52f9136
--- /dev/null
+++ b/notebooks/03-Supervised.ipynb
@@ -0,0 +1,2464 @@
+{
+ "cells": [
+  {
+   "cell_type": "code",
+   "execution_count": 1,
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "import pandas as pd\n",
+    "\n",
+    "from sklearn.preprocessing import MultiLabelBinarizer\n",
+    "from sklearn.svm import OneClassSVM \n",
+    "from sklearn.model_selection import train_test_split\n",
+    "from sklearn.metrics import f1_score"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 2,
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "df = pd.read_pickle('../data/processed/features.pkl')"
+   ]
+  },
+  {
+   "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>verified_email</th>\n",
+       "      <th>verified_primary_email</th>\n",
+       "      <th>n_works</th>\n",
+       "      <th>n_doi</th>\n",
+       "      <th>n_arxiv</th>\n",
+       "      <th>n_pmc</th>\n",
+       "      <th>n_other_pids</th>\n",
+       "      <th>label</th>\n",
+       "      <th>n_emails</th>\n",
+       "      <th>n_urls</th>\n",
+       "      <th>...</th>\n",
+       "      <th>n_employment</th>\n",
+       "      <th>n_ext_work_source</th>\n",
+       "      <th>n_valid_education</th>\n",
+       "      <th>n_valid_employment</th>\n",
+       "      <th>biography_length</th>\n",
+       "      <th>biography_n_sentences</th>\n",
+       "      <th>biography_n_words</th>\n",
+       "      <th>date_diff</th>\n",
+       "      <th>ref_year</th>\n",
+       "      <th>date_stale</th>\n",
+       "    </tr>\n",
+       "  </thead>\n",
+       "  <tbody>\n",
+       "    <tr>\n",
+       "      <th>0</th>\n",
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+       "      <td>&lt;NA&gt;</td>\n",
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+       "      <td>NaN</td>\n",
+       "      <td>&lt;NA&gt;</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>0.009618</td>\n",
+       "      <td>2018</td>\n",
+       "      <td>1153.980551</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>1</th>\n",
+       "      <td>True</td>\n",
+       "      <td>True</td>\n",
+       "      <td>0</td>\n",
+       "      <td>0</td>\n",
+       "      <td>0</td>\n",
+       "      <td>0</td>\n",
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+       "      <td>False</td>\n",
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+       "      <td>&lt;NA&gt;</td>\n",
+       "      <td>...</td>\n",
+       "      <td>1</td>\n",
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+       "      <td>NaN</td>\n",
+       "      <td>1.0</td>\n",
+       "      <td>&lt;NA&gt;</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>715.078025</td>\n",
+       "      <td>2018</td>\n",
+       "      <td>406.980815</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>2</th>\n",
+       "      <td>True</td>\n",
+       "      <td>True</td>\n",
+       "      <td>0</td>\n",
+       "      <td>0</td>\n",
+       "      <td>0</td>\n",
+       "      <td>0</td>\n",
+       "      <td>0</td>\n",
+       "      <td>False</td>\n",
+       "      <td>&lt;NA&gt;</td>\n",
+       "      <td>&lt;NA&gt;</td>\n",
+       "      <td>...</td>\n",
+       "      <td>&lt;NA&gt;</td>\n",
+       "      <td>&lt;NA&gt;</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>&lt;NA&gt;</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>48.001631</td>\n",
+       "      <td>2019</td>\n",
+       "      <td>456.736688</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>3</th>\n",
+       "      <td>True</td>\n",
+       "      <td>True</td>\n",
+       "      <td>0</td>\n",
+       "      <td>0</td>\n",
+       "      <td>0</td>\n",
+       "      <td>0</td>\n",
+       "      <td>0</td>\n",
+       "      <td>False</td>\n",
+       "      <td>&lt;NA&gt;</td>\n",
+       "      <td>&lt;NA&gt;</td>\n",
+       "      <td>...</td>\n",
+       "      <td>1</td>\n",
+       "      <td>&lt;NA&gt;</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>0.0</td>\n",
+       "      <td>&lt;NA&gt;</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>1863.042464</td>\n",
+       "      <td>2015</td>\n",
+       "      <td>217.817512</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>4</th>\n",
+       "      <td>True</td>\n",
+       "      <td>True</td>\n",
+       "      <td>0</td>\n",
+       "      <td>0</td>\n",
+       "      <td>0</td>\n",
+       "      <td>0</td>\n",
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+       "      <td>False</td>\n",
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+       "      <td>&lt;NA&gt;</td>\n",
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+       "      <td>827.372135</td>\n",
+       "      <td>2014</td>\n",
+       "      <td>1779.456397</td>\n",
+       "    </tr>\n",
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+       "      <th>...</th>\n",
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+       "      <th>10989644</th>\n",
+       "      <td>True</td>\n",
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+       "      <td>False</td>\n",
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+       "      <td>&lt;NA&gt;</td>\n",
+       "      <td>...</td>\n",
+       "      <td>1</td>\n",
+       "      <td>&lt;NA&gt;</td>\n",
+       "      <td>1.0</td>\n",
+       "      <td>1.0</td>\n",
+       "      <td>118</td>\n",
+       "      <td>2.0</td>\n",
+       "      <td>23.0</td>\n",
+       "      <td>0.051116</td>\n",
+       "      <td>2020</td>\n",
+       "      <td>139.242812</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>10989645</th>\n",
+       "      <td>True</td>\n",
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+       "      <td>NaN</td>\n",
+       "      <td>2131.978000</td>\n",
+       "      <td>2015</td>\n",
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+       "      <td>NaN</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>0.000597</td>\n",
+       "      <td>2020</td>\n",
+       "      <td>139.226289</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>10989647</th>\n",
+       "      <td>True</td>\n",
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+       "      <td>False</td>\n",
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+       "      <td>&lt;NA&gt;</td>\n",
+       "      <td>...</td>\n",
+       "      <td>1</td>\n",
+       "      <td>&lt;NA&gt;</td>\n",
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+       "      <td>&lt;NA&gt;</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>1433.222830</td>\n",
+       "      <td>2016</td>\n",
+       "      <td>150.839463</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>10989648</th>\n",
+       "      <td>True</td>\n",
+       "      <td>True</td>\n",
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+       "      <td>&lt;NA&gt;</td>\n",
+       "      <td>&lt;NA&gt;</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>&lt;NA&gt;</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>1591.542558</td>\n",
+       "      <td>2016</td>\n",
+       "      <td>152.263413</td>\n",
+       "    </tr>\n",
+       "  </tbody>\n",
+       "</table>\n",
+       "<p>10989649 rows × 23 columns</p>\n",
+       "</div>"
+      ],
+      "text/plain": [
+       "          verified_email  verified_primary_email  n_works  n_doi  n_arxiv  \\\n",
+       "0                  False                   False        0      0        0   \n",
+       "1                   True                    True        0      0        0   \n",
+       "2                   True                    True        0      0        0   \n",
+       "3                   True                    True        0      0        0   \n",
+       "4                   True                    True        0      0        0   \n",
+       "...                  ...                     ...      ...    ...      ...   \n",
+       "10989644            True                    True        0      0        0   \n",
+       "10989645            True                    True        7      7        0   \n",
+       "10989646            True                    True        0      0        0   \n",
+       "10989647            True                    True        0      0        0   \n",
+       "10989648            True                    True        0      0        0   \n",
+       "\n",
+       "          n_pmc  n_other_pids  label  n_emails  n_urls  ...  n_employment  \\\n",
+       "0             0             0  False      <NA>    <NA>  ...          <NA>   \n",
+       "1             0             0  False      <NA>    <NA>  ...             1   \n",
+       "2             0             0  False      <NA>    <NA>  ...          <NA>   \n",
+       "3             0             0  False      <NA>    <NA>  ...             1   \n",
+       "4             0             0  False      <NA>    <NA>  ...             2   \n",
+       "...         ...           ...    ...       ...     ...  ...           ...   \n",
+       "10989644      0             0  False      <NA>    <NA>  ...             1   \n",
+       "10989645      1             0   True      <NA>    <NA>  ...             2   \n",
+       "10989646      0             0  False      <NA>    <NA>  ...          <NA>   \n",
+       "10989647      0             0  False      <NA>    <NA>  ...             1   \n",
+       "10989648      0             0  False      <NA>    <NA>  ...          <NA>   \n",
+       "\n",
+       "          n_ext_work_source  n_valid_education  n_valid_employment  \\\n",
+       "0                      <NA>                NaN                 NaN   \n",
+       "1                      <NA>                NaN                 1.0   \n",
+       "2                      <NA>                NaN                 NaN   \n",
+       "3                      <NA>                NaN                 0.0   \n",
+       "4                      <NA>                NaN                 1.0   \n",
+       "...                     ...                ...                 ...   \n",
+       "10989644               <NA>                1.0                 1.0   \n",
+       "10989645                  2                2.0                 0.0   \n",
+       "10989646               <NA>                NaN                 NaN   \n",
+       "10989647               <NA>                2.0                 1.0   \n",
+       "10989648               <NA>                NaN                 NaN   \n",
+       "\n",
+       "          biography_length  biography_n_sentences  biography_n_words  \\\n",
+       "0                     <NA>                    NaN                NaN   \n",
+       "1                     <NA>                    NaN                NaN   \n",
+       "2                     <NA>                    NaN                NaN   \n",
+       "3                     <NA>                    NaN                NaN   \n",
+       "4                     <NA>                    NaN                NaN   \n",
+       "...                    ...                    ...                ...   \n",
+       "10989644               118                    2.0               23.0   \n",
+       "10989645              <NA>                    NaN                NaN   \n",
+       "10989646              <NA>                    NaN                NaN   \n",
+       "10989647              <NA>                    NaN                NaN   \n",
+       "10989648              <NA>                    NaN                NaN   \n",
+       "\n",
+       "            date_diff  ref_year   date_stale  \n",
+       "0            0.009618      2018  1153.980551  \n",
+       "1          715.078025      2018   406.980815  \n",
+       "2           48.001631      2019   456.736688  \n",
+       "3         1863.042464      2015   217.817512  \n",
+       "4          827.372135      2014  1779.456397  \n",
+       "...               ...       ...          ...  \n",
+       "10989644     0.051116      2020   139.242812  \n",
+       "10989645  2131.978000      2015   158.560081  \n",
+       "10989646     0.000597      2020   139.226289  \n",
+       "10989647  1433.222830      2016   150.839463  \n",
+       "10989648  1591.542558      2016   152.263413  \n",
+       "\n",
+       "[10989649 rows x 23 columns]"
+      ]
+     },
+     "execution_count": 3,
+     "metadata": {},
+     "output_type": "execute_result"
+    }
+   ],
+   "source": [
+    "df"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 4,
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "df.fillna(0, inplace=True)"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 5,
+   "metadata": {},
+   "outputs": [
+    {
+     "data": {
+      "text/html": [
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+       "<style scoped>\n",
+       "    .dataframe tbody tr th:only-of-type {\n",
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+       "\n",
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+       "</style>\n",
+       "<table border=\"1\" class=\"dataframe\">\n",
+       "  <thead>\n",
+       "    <tr style=\"text-align: right;\">\n",
+       "      <th></th>\n",
+       "      <th>verified_email</th>\n",
+       "      <th>verified_primary_email</th>\n",
+       "      <th>n_works</th>\n",
+       "      <th>n_doi</th>\n",
+       "      <th>n_arxiv</th>\n",
+       "      <th>n_pmc</th>\n",
+       "      <th>n_other_pids</th>\n",
+       "      <th>label</th>\n",
+       "      <th>n_emails</th>\n",
+       "      <th>n_urls</th>\n",
+       "      <th>...</th>\n",
+       "      <th>n_employment</th>\n",
+       "      <th>n_ext_work_source</th>\n",
+       "      <th>n_valid_education</th>\n",
+       "      <th>n_valid_employment</th>\n",
+       "      <th>biography_length</th>\n",
+       "      <th>biography_n_sentences</th>\n",
+       "      <th>biography_n_words</th>\n",
+       "      <th>date_diff</th>\n",
+       "      <th>ref_year</th>\n",
+       "      <th>date_stale</th>\n",
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+       "      <td>2018</td>\n",
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+       "      <td>48.001631</td>\n",
+       "      <td>2019</td>\n",
+       "      <td>456.736688</td>\n",
+       "    </tr>\n",
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+       "      <th>3</th>\n",
+       "      <td>True</td>\n",
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+       "      <td>2015</td>\n",
+       "      <td>217.817512</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>4</th>\n",
+       "      <td>True</td>\n",
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+       "      <td>118</td>\n",
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+       "      <td>23.0</td>\n",
+       "      <td>0.051116</td>\n",
+       "      <td>2020</td>\n",
+       "      <td>139.242812</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>10989645</th>\n",
+       "      <td>True</td>\n",
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+       "      <td>0.000597</td>\n",
+       "      <td>2020</td>\n",
+       "      <td>139.226289</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>10989647</th>\n",
+       "      <td>True</td>\n",
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+       "      <td>0.0</td>\n",
+       "      <td>1433.222830</td>\n",
+       "      <td>2016</td>\n",
+       "      <td>150.839463</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>10989648</th>\n",
+       "      <td>True</td>\n",
+       "      <td>True</td>\n",
+       "      <td>0</td>\n",
+       "      <td>0</td>\n",
+       "      <td>0</td>\n",
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+       "      <td>False</td>\n",
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+       "      <td>0.0</td>\n",
+       "      <td>0.0</td>\n",
+       "      <td>1591.542558</td>\n",
+       "      <td>2016</td>\n",
+       "      <td>152.263413</td>\n",
+       "    </tr>\n",
+       "  </tbody>\n",
+       "</table>\n",
+       "<p>10989649 rows × 23 columns</p>\n",
+       "</div>"
+      ],
+      "text/plain": [
+       "          verified_email  verified_primary_email  n_works  n_doi  n_arxiv  \\\n",
+       "0                  False                   False        0      0        0   \n",
+       "1                   True                    True        0      0        0   \n",
+       "2                   True                    True        0      0        0   \n",
+       "3                   True                    True        0      0        0   \n",
+       "4                   True                    True        0      0        0   \n",
+       "...                  ...                     ...      ...    ...      ...   \n",
+       "10989644            True                    True        0      0        0   \n",
+       "10989645            True                    True        7      7        0   \n",
+       "10989646            True                    True        0      0        0   \n",
+       "10989647            True                    True        0      0        0   \n",
+       "10989648            True                    True        0      0        0   \n",
+       "\n",
+       "          n_pmc  n_other_pids  label  n_emails  n_urls  ...  n_employment  \\\n",
+       "0             0             0  False         0       0  ...             0   \n",
+       "1             0             0  False         0       0  ...             1   \n",
+       "2             0             0  False         0       0  ...             0   \n",
+       "3             0             0  False         0       0  ...             1   \n",
+       "4             0             0  False         0       0  ...             2   \n",
+       "...         ...           ...    ...       ...     ...  ...           ...   \n",
+       "10989644      0             0  False         0       0  ...             1   \n",
+       "10989645      1             0   True         0       0  ...             2   \n",
+       "10989646      0             0  False         0       0  ...             0   \n",
+       "10989647      0             0  False         0       0  ...             1   \n",
+       "10989648      0             0  False         0       0  ...             0   \n",
+       "\n",
+       "          n_ext_work_source  n_valid_education  n_valid_employment  \\\n",
+       "0                         0                0.0                 0.0   \n",
+       "1                         0                0.0                 1.0   \n",
+       "2                         0                0.0                 0.0   \n",
+       "3                         0                0.0                 0.0   \n",
+       "4                         0                0.0                 1.0   \n",
+       "...                     ...                ...                 ...   \n",
+       "10989644                  0                1.0                 1.0   \n",
+       "10989645                  2                2.0                 0.0   \n",
+       "10989646                  0                0.0                 0.0   \n",
+       "10989647                  0                2.0                 1.0   \n",
+       "10989648                  0                0.0                 0.0   \n",
+       "\n",
+       "          biography_length  biography_n_sentences  biography_n_words  \\\n",
+       "0                        0                    0.0                0.0   \n",
+       "1                        0                    0.0                0.0   \n",
+       "2                        0                    0.0                0.0   \n",
+       "3                        0                    0.0                0.0   \n",
+       "4                        0                    0.0                0.0   \n",
+       "...                    ...                    ...                ...   \n",
+       "10989644               118                    2.0               23.0   \n",
+       "10989645                 0                    0.0                0.0   \n",
+       "10989646                 0                    0.0                0.0   \n",
+       "10989647                 0                    0.0                0.0   \n",
+       "10989648                 0                    0.0                0.0   \n",
+       "\n",
+       "            date_diff  ref_year   date_stale  \n",
+       "0            0.009618      2018  1153.980551  \n",
+       "1          715.078025      2018   406.980815  \n",
+       "2           48.001631      2019   456.736688  \n",
+       "3         1863.042464      2015   217.817512  \n",
+       "4          827.372135      2014  1779.456397  \n",
+       "...               ...       ...          ...  \n",
+       "10989644     0.051116      2020   139.242812  \n",
+       "10989645  2131.978000      2015   158.560081  \n",
+       "10989646     0.000597      2020   139.226289  \n",
+       "10989647  1433.222830      2016   150.839463  \n",
+       "10989648  1591.542558      2016   152.263413  \n",
+       "\n",
+       "[10989649 rows x 23 columns]"
+      ]
+     },
+     "execution_count": 5,
+     "metadata": {},
+     "output_type": "execute_result"
+    }
+   ],
+   "source": [
+    "df"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 6,
+   "metadata": {},
+   "outputs": [
+    {
+     "data": {
+      "text/plain": [
+       "(2075872, 23)"
+      ]
+     },
+     "execution_count": 6,
+     "metadata": {},
+     "output_type": "execute_result"
+    }
+   ],
+   "source": [
+    "df[df.label == 1].shape"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 7,
+   "metadata": {},
+   "outputs": [
+    {
+     "data": {
+      "text/plain": [
+       "(8913777, 23)"
+      ]
+     },
+     "execution_count": 7,
+     "metadata": {},
+     "output_type": "execute_result"
+    }
+   ],
+   "source": [
+    "df[df.label == 0].shape"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 8,
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "# split into train/test sets\n",
+    "x = df.loc[:, df.columns != 'label']\n",
+    "y = df['label']\n",
+    "train_x, test_x, train_y, test_y = train_test_split(x, y, train_size=100000, test_size=1000000, random_state=2, stratify=y)"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 9,
+   "metadata": {},
+   "outputs": [
+    {
+     "data": {
+      "text/plain": [
+       "(18889, 22)"
+      ]
+     },
+     "execution_count": 9,
+     "metadata": {},
+     "output_type": "execute_result"
+    }
+   ],
+   "source": [
+    "train_x[train_y==1].shape"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 10,
+   "metadata": {},
+   "outputs": [
+    {
+     "data": {
+      "text/plain": [
+       "(188893, 22)"
+      ]
+     },
+     "execution_count": 10,
+     "metadata": {},
+     "output_type": "execute_result"
+    }
+   ],
+   "source": [
+    "test_x[test_y==1].shape"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 11,
+   "metadata": {},
+   "outputs": [
+    {
+     "data": {
+      "text/plain": [
+       "OneClassSVM()"
+      ]
+     },
+     "execution_count": 11,
+     "metadata": {},
+     "output_type": "execute_result"
+    }
+   ],
+   "source": [
+    "# define outlier detection model\n",
+    "model = OneClassSVM(gamma='scale', nu=0.5)\n",
+    "\n",
+    "# fit on majority class\n",
+    "train_x = train_x[train_y==1]\n",
+    "model.fit(train_x)"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 12,
+   "metadata": {},
+   "outputs": [
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      "F1 Score: 0.872\n"
+     ]
+    }
+   ],
+   "source": [
+    "# detect outliers in the test set\n",
+    "y_hat = model.predict(test_x)\n",
+    "\n",
+    "# mark inliers 1, outliers -1\n",
+    "test_y[test_y == 0] = -1\n",
+    "test_y[test_y == 1] = 1\n",
+    "\n",
+    "# calculate score\n",
+    "score = f1_score(test_y, y_hat, pos_label=-1)\n",
+    "print('F1 Score: %.3f' % score)"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 13,
+   "metadata": {},
+   "outputs": [
+    {
+     "name": "stderr",
+     "output_type": "stream",
+     "text": [
+      "/Users/andrea/.virtualenvs/data-science/lib/python3.8/site-packages/pandas/core/indexing.py:1597: SettingWithCopyWarning: \n",
+      "A value is trying to be set on a copy of a slice from a DataFrame.\n",
+      "Try using .loc[row_indexer,col_indexer] = value instead\n",
+      "\n",
+      "See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n",
+      "  self.obj[key] = value\n",
+      "/Users/andrea/.virtualenvs/data-science/lib/python3.8/site-packages/pandas/core/indexing.py:1676: SettingWithCopyWarning: \n",
+      "A value is trying to be set on a copy of a slice from a DataFrame.\n",
+      "Try using .loc[row_indexer,col_indexer] = value instead\n",
+      "\n",
+      "See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n",
+      "  self._setitem_single_column(ilocs[0], value, pi)\n"
+     ]
+    }
+   ],
+   "source": [
+    "test_x.loc[:, 'label'] = test_y.values"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 14,
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "test_x.loc[:, 'prediction'] = y_hat"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 15,
+   "metadata": {},
+   "outputs": [
+    {
+     "data": {
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+       "      <td>-1.0</td>\n",
+       "      <td>1</td>\n",
+       "    </tr>\n",
+       "  </tbody>\n",
+       "</table>\n",
+       "<p>205377 rows × 24 columns</p>\n",
+       "</div>"
+      ],
+      "text/plain": [
+       "         verified_email  verified_primary_email  n_works  n_doi  n_arxiv  \\\n",
+       "8422958            True                    True        7      3        0   \n",
+       "30426              True                    True        5      5        0   \n",
+       "1941223            True                    True        0      0        0   \n",
+       "9232681            True                    True        1      1        0   \n",
+       "7646644           False                   False        0      0        0   \n",
+       "...                 ...                     ...      ...    ...      ...   \n",
+       "4769520            True                    True        0      0        0   \n",
+       "2817268            True                    True        9      7        0   \n",
+       "4840353            True                    True        0      0        0   \n",
+       "9717615            True                    True        0      0        0   \n",
+       "2290714           False                   False        0      0        0   \n",
+       "\n",
+       "         n_pmc  n_other_pids  n_emails  n_urls  n_ids  ...  n_valid_education  \\\n",
+       "8422958      0             6         0       0      1  ...                2.0   \n",
+       "30426        0             0         0       0      0  ...                1.0   \n",
+       "1941223      0             0         0       0      0  ...                0.0   \n",
+       "9232681      0             0         0       0      0  ...                0.0   \n",
+       "7646644      0             0         0       0      0  ...                0.0   \n",
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+       "9717615      0             0         0       0      1  ...                0.0   \n",
+       "2290714      0             0         0       0      0  ...                0.0   \n",
+       "\n",
+       "         n_valid_employment  biography_length  biography_n_sentences  \\\n",
+       "8422958                 1.0                 0                    0.0   \n",
+       "30426                   3.0                 0                    0.0   \n",
+       "1941223                 0.0                 0                    0.0   \n",
+       "9232681                 0.0                 0                    0.0   \n",
+       "7646644                 0.0                 0                    0.0   \n",
+       "...                     ...               ...                    ...   \n",
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+       "2817268                 0.0                 0                    0.0   \n",
+       "4840353                 0.0                 0                    0.0   \n",
+       "9717615                 0.0                 0                    0.0   \n",
+       "2290714                 0.0                 0                    0.0   \n",
+       "\n",
+       "         biography_n_words    date_diff  ref_year   date_stale  label  \\\n",
+       "8422958                0.0  1149.760128      2016   498.053074   -1.0   \n",
+       "30426                  0.0  2446.815456      2014   112.064679    1.0   \n",
+       "1941223                0.0   811.573040      2017   486.567693   -1.0   \n",
+       "9232681                0.0   888.520157      2017   359.397781   -1.0   \n",
+       "7646644                0.0     0.000030      2017  1443.731837    1.0   \n",
+       "...                    ...          ...       ...          ...    ...   \n",
+       "4769520                0.0   781.732331      2019    46.115046   -1.0   \n",
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+       "4840353                0.0   659.864595      2017   634.846007    1.0   \n",
+       "9717615                0.0  1971.810335      2015    38.063916   -1.0   \n",
+       "2290714                0.0   947.216224      2018   104.732935   -1.0   \n",
+       "\n",
+       "         prediction  \n",
+       "8422958           1  \n",
+       "30426            -1  \n",
+       "1941223           1  \n",
+       "9232681           1  \n",
+       "7646644          -1  \n",
+       "...             ...  \n",
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+       "2817268           1  \n",
+       "4840353          -1  \n",
+       "9717615           1  \n",
+       "2290714           1  \n",
+       "\n",
+       "[205377 rows x 24 columns]"
+      ]
+     },
+     "execution_count": 15,
+     "metadata": {},
+     "output_type": "execute_result"
+    }
+   ],
+   "source": [
+    "test_x[test_x.label != test_x.prediction]"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 27,
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "fake_df = pd.read_csv('../data/processed/fake_heap_index.csv', index_col='index')"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 30,
+   "metadata": {},
+   "outputs": [
+    {
+     "data": {
+      "text/html": [
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+       "Empty DataFrame\n",
+       "Columns: [verified_email, verified_primary_email, n_works, n_doi, n_arxiv, n_pmc, n_other_pids, n_emails, n_urls, n_ids, n_keywords, n_education, n_employment, n_ext_work_source, n_valid_education, n_valid_employment, biography_length, biography_n_sentences, biography_n_words, date_diff, ref_year, date_stale, label, prediction]\n",
+       "Index: []\n",
+       "\n",
+       "[0 rows x 24 columns]"
+      ]
+     },
+     "execution_count": 30,
+     "metadata": {},
+     "output_type": "execute_result"
+    }
+   ],
+   "source": [
+    "test_x[(test_x.label != test_x.prediction) & (test_x.index.isin(fake_df.index))]"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 31,
+   "metadata": {},
+   "outputs": [
+    {
+     "data": {
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+       "      <td>0</td>\n",
+       "      <td>...</td>\n",
+       "      <td>0.0</td>\n",
+       "      <td>0.0</td>\n",
+       "      <td>445</td>\n",
+       "      <td>4.0</td>\n",
+       "      <td>85.0</td>\n",
+       "      <td>0.003391</td>\n",
+       "      <td>2020</td>\n",
+       "      <td>140.230023</td>\n",
+       "      <td>-1.0</td>\n",
+       "      <td>-1</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>3659063</th>\n",
+       "      <td>True</td>\n",
+       "      <td>True</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>1</td>\n",
+       "      <td>0</td>\n",
+       "      <td>...</td>\n",
+       "      <td>0.0</td>\n",
+       "      <td>0.0</td>\n",
+       "      <td>445</td>\n",
+       "      <td>4.0</td>\n",
+       "      <td>85.0</td>\n",
+       "      <td>0.010618</td>\n",
+       "      <td>2020</td>\n",
+       "      <td>131.658167</td>\n",
+       "      <td>-1.0</td>\n",
+       "      <td>-1</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>6099073</th>\n",
+       "      <td>True</td>\n",
+       "      <td>True</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>1</td>\n",
+       "      <td>0</td>\n",
+       "      <td>...</td>\n",
+       "      <td>0.0</td>\n",
+       "      <td>0.0</td>\n",
+       "      <td>445</td>\n",
+       "      <td>4.0</td>\n",
+       "      <td>85.0</td>\n",
+       "      <td>0.025714</td>\n",
+       "      <td>2020</td>\n",
+       "      <td>142.184268</td>\n",
+       "      <td>-1.0</td>\n",
+       "      <td>-1</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>3953358</th>\n",
+       "      <td>True</td>\n",
+       "      <td>True</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>0</td>\n",
+       "      <td>...</td>\n",
+       "      <td>0.0</td>\n",
+       "      <td>0.0</td>\n",
+       "      <td>445</td>\n",
+       "      <td>4.0</td>\n",
+       "      <td>85.0</td>\n",
+       "      <td>0.005145</td>\n",
+       "      <td>2020</td>\n",
+       "      <td>185.115723</td>\n",
+       "      <td>-1.0</td>\n",
+       "      <td>-1</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>9724190</th>\n",
+       "      <td>True</td>\n",
+       "      <td>True</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>1</td>\n",
+       "      <td>0</td>\n",
+       "      <td>...</td>\n",
+       "      <td>0.0</td>\n",
+       "      <td>0.0</td>\n",
+       "      <td>543</td>\n",
+       "      <td>4.0</td>\n",
+       "      <td>107.0</td>\n",
+       "      <td>6.993352</td>\n",
+       "      <td>2020</td>\n",
+       "      <td>135.124112</td>\n",
+       "      <td>-1.0</td>\n",
+       "      <td>-1</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>1041978</th>\n",
+       "      <td>True</td>\n",
+       "      <td>True</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>1</td>\n",
+       "      <td>0</td>\n",
+       "      <td>...</td>\n",
+       "      <td>0.0</td>\n",
+       "      <td>0.0</td>\n",
+       "      <td>445</td>\n",
+       "      <td>4.0</td>\n",
+       "      <td>85.0</td>\n",
+       "      <td>0.006524</td>\n",
+       "      <td>2020</td>\n",
+       "      <td>167.270642</td>\n",
+       "      <td>-1.0</td>\n",
+       "      <td>-1</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>880090</th>\n",
+       "      <td>True</td>\n",
+       "      <td>True</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>1</td>\n",
+       "      <td>0</td>\n",
+       "      <td>...</td>\n",
+       "      <td>0.0</td>\n",
+       "      <td>0.0</td>\n",
+       "      <td>445</td>\n",
+       "      <td>4.0</td>\n",
+       "      <td>85.0</td>\n",
+       "      <td>0.001572</td>\n",
+       "      <td>2020</td>\n",
+       "      <td>143.298327</td>\n",
+       "      <td>-1.0</td>\n",
+       "      <td>-1</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>8492341</th>\n",
+       "      <td>True</td>\n",
+       "      <td>True</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>1</td>\n",
+       "      <td>0</td>\n",
+       "      <td>...</td>\n",
+       "      <td>0.0</td>\n",
+       "      <td>0.0</td>\n",
+       "      <td>445</td>\n",
+       "      <td>4.0</td>\n",
+       "      <td>85.0</td>\n",
+       "      <td>0.006172</td>\n",
+       "      <td>2020</td>\n",
+       "      <td>123.742413</td>\n",
+       "      <td>-1.0</td>\n",
+       "      <td>-1</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>8952735</th>\n",
+       "      <td>True</td>\n",
+       "      <td>True</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>1</td>\n",
+       "      <td>0</td>\n",
+       "      <td>...</td>\n",
+       "      <td>0.0</td>\n",
+       "      <td>0.0</td>\n",
+       "      <td>445</td>\n",
+       "      <td>4.0</td>\n",
+       "      <td>85.0</td>\n",
+       "      <td>0.004785</td>\n",
+       "      <td>2020</td>\n",
+       "      <td>188.359673</td>\n",
+       "      <td>-1.0</td>\n",
+       "      <td>-1</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>3274872</th>\n",
+       "      <td>True</td>\n",
+       "      <td>True</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>1</td>\n",
+       "      <td>0</td>\n",
+       "      <td>...</td>\n",
+       "      <td>0.0</td>\n",
+       "      <td>0.0</td>\n",
+       "      <td>445</td>\n",
+       "      <td>4.0</td>\n",
+       "      <td>85.0</td>\n",
+       "      <td>0.017478</td>\n",
+       "      <td>2020</td>\n",
+       "      <td>126.967926</td>\n",
+       "      <td>-1.0</td>\n",
+       "      <td>-1</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>989919</th>\n",
+       "      <td>True</td>\n",
+       "      <td>True</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>1</td>\n",
+       "      <td>0</td>\n",
+       "      <td>...</td>\n",
+       "      <td>0.0</td>\n",
+       "      <td>0.0</td>\n",
+       "      <td>561</td>\n",
+       "      <td>5.0</td>\n",
+       "      <td>110.0</td>\n",
+       "      <td>0.002649</td>\n",
+       "      <td>2020</td>\n",
+       "      <td>146.098129</td>\n",
+       "      <td>-1.0</td>\n",
+       "      <td>-1</td>\n",
+       "    </tr>\n",
+       "  </tbody>\n",
+       "</table>\n",
+       "<p>30 rows × 24 columns</p>\n",
+       "</div>"
+      ],
+      "text/plain": [
+       "          verified_email  verified_primary_email  n_works  n_doi  n_arxiv  \\\n",
+       "1319584             True                    True        0      0        0   \n",
+       "7579770             True                    True        0      0        0   \n",
+       "9173011             True                    True        0      0        0   \n",
+       "1209389             True                    True        0      0        0   \n",
+       "4173344             True                    True        0      0        0   \n",
+       "10985986            True                    True        0      0        0   \n",
+       "6208696             True                    True        0      0        0   \n",
+       "801178              True                    True        0      0        0   \n",
+       "4392500             True                    True        0      0        0   \n",
+       "7963350             True                    True        0      0        0   \n",
+       "5659388             True                    True        0      0        0   \n",
+       "2749172             True                    True        0      0        0   \n",
+       "4230883             True                    True        0      0        0   \n",
+       "6370669             True                    True        0      0        0   \n",
+       "5109458             True                    True        0      0        0   \n",
+       "7689620             True                    True        0      0        0   \n",
+       "9831120             True                    True        0      0        0   \n",
+       "6263478             True                    True        0      0        0   \n",
+       "10581997            True                    True        0      0        0   \n",
+       "3243302             True                    True        0      0        0   \n",
+       "3659063             True                    True        0      0        0   \n",
+       "6099073             True                    True        0      0        0   \n",
+       "3953358             True                    True        0      0        0   \n",
+       "9724190             True                    True        0      0        0   \n",
+       "1041978             True                    True        0      0        0   \n",
+       "880090              True                    True        0      0        0   \n",
+       "8492341             True                    True        0      0        0   \n",
+       "8952735             True                    True        0      0        0   \n",
+       "3274872             True                    True        0      0        0   \n",
+       "989919              True                    True        0      0        0   \n",
+       "\n",
+       "          n_pmc  n_other_pids  n_emails  n_urls  n_ids  ...  \\\n",
+       "1319584       0             0         0       1      0  ...   \n",
+       "7579770       0             0         0       1      0  ...   \n",
+       "9173011       0             0         0       1      0  ...   \n",
+       "1209389       0             0         0       1      0  ...   \n",
+       "4173344       0             0         0       1      0  ...   \n",
+       "10985986      0             0         0       1      0  ...   \n",
+       "6208696       0             0         0       1      0  ...   \n",
+       "801178        0             0         0       1      0  ...   \n",
+       "4392500       0             0         0       1      0  ...   \n",
+       "7963350       0             0         0       1      0  ...   \n",
+       "5659388       0             0         0       1      0  ...   \n",
+       "2749172       0             0         0       1      0  ...   \n",
+       "4230883       0             0         0       1      0  ...   \n",
+       "6370669       0             0         0       1      0  ...   \n",
+       "5109458       0             0         0       1      0  ...   \n",
+       "7689620       0             0         0       1      0  ...   \n",
+       "9831120       0             0         0       1      0  ...   \n",
+       "6263478       0             0         0       1      0  ...   \n",
+       "10581997      0             0         0       1      0  ...   \n",
+       "3243302       0             0         0       1      0  ...   \n",
+       "3659063       0             0         0       1      0  ...   \n",
+       "6099073       0             0         0       1      0  ...   \n",
+       "3953358       0             0         0       0      0  ...   \n",
+       "9724190       0             0         0       1      0  ...   \n",
+       "1041978       0             0         0       1      0  ...   \n",
+       "880090        0             0         0       1      0  ...   \n",
+       "8492341       0             0         0       1      0  ...   \n",
+       "8952735       0             0         0       1      0  ...   \n",
+       "3274872       0             0         0       1      0  ...   \n",
+       "989919        0             0         0       1      0  ...   \n",
+       "\n",
+       "          n_valid_education  n_valid_employment  biography_length  \\\n",
+       "1319584                 0.0                 0.0               637   \n",
+       "7579770                 0.0                 0.0               445   \n",
+       "9173011                 0.0                 0.0               445   \n",
+       "1209389                 0.0                 0.0               445   \n",
+       "4173344                 0.0                 0.0               445   \n",
+       "10985986                0.0                 0.0               445   \n",
+       "6208696                 0.0                 0.0               445   \n",
+       "801178                  0.0                 0.0               445   \n",
+       "4392500                 0.0                 0.0               445   \n",
+       "7963350                 0.0                 0.0               445   \n",
+       "5659388                 0.0                 0.0               445   \n",
+       "2749172                 0.0                 0.0               540   \n",
+       "4230883                 0.0                 0.0               445   \n",
+       "6370669                 0.0                 0.0               445   \n",
+       "5109458                 0.0                 0.0               445   \n",
+       "7689620                 0.0                 0.0               445   \n",
+       "9831120                 0.0                 0.0               445   \n",
+       "6263478                 0.0                 0.0               552   \n",
+       "10581997                0.0                 0.0               445   \n",
+       "3243302                 0.0                 0.0               445   \n",
+       "3659063                 0.0                 0.0               445   \n",
+       "6099073                 0.0                 0.0               445   \n",
+       "3953358                 0.0                 0.0               445   \n",
+       "9724190                 0.0                 0.0               543   \n",
+       "1041978                 0.0                 0.0               445   \n",
+       "880090                  0.0                 0.0               445   \n",
+       "8492341                 0.0                 0.0               445   \n",
+       "8952735                 0.0                 0.0               445   \n",
+       "3274872                 0.0                 0.0               445   \n",
+       "989919                  0.0                 0.0               561   \n",
+       "\n",
+       "          biography_n_sentences  biography_n_words  date_diff  ref_year  \\\n",
+       "1319584                     4.0              113.0   0.000852      2020   \n",
+       "7579770                     4.0               85.0   0.002694      2020   \n",
+       "9173011                     4.0               85.0   0.005271      2020   \n",
+       "1209389                     4.0               85.0   0.006071      2020   \n",
+       "4173344                     4.0               85.0   0.005405      2020   \n",
+       "10985986                    4.0               85.0   0.003662      2020   \n",
+       "6208696                     4.0               85.0   0.001287      2020   \n",
+       "801178                      4.0               85.0   0.008069      2020   \n",
+       "4392500                     4.0               85.0   0.004414      2020   \n",
+       "7963350                     4.0               85.0   0.003572      2020   \n",
+       "5659388                     4.0               85.0   0.011685      2020   \n",
+       "2749172                     4.0              103.0   0.001172      2020   \n",
+       "4230883                     4.0               85.0   0.001681      2020   \n",
+       "6370669                     4.0               85.0   0.006984      2020   \n",
+       "5109458                     4.0               85.0   0.004633      2020   \n",
+       "7689620                     4.0               85.0   0.003671      2020   \n",
+       "9831120                     4.0               85.0   0.004996      2020   \n",
+       "6263478                     4.0              107.0   0.005174      2020   \n",
+       "10581997                    4.0               85.0   0.020527      2020   \n",
+       "3243302                     4.0               85.0   0.003391      2020   \n",
+       "3659063                     4.0               85.0   0.010618      2020   \n",
+       "6099073                     4.0               85.0   0.025714      2020   \n",
+       "3953358                     4.0               85.0   0.005145      2020   \n",
+       "9724190                     4.0              107.0   6.993352      2020   \n",
+       "1041978                     4.0               85.0   0.006524      2020   \n",
+       "880090                      4.0               85.0   0.001572      2020   \n",
+       "8492341                     4.0               85.0   0.006172      2020   \n",
+       "8952735                     4.0               85.0   0.004785      2020   \n",
+       "3274872                     4.0               85.0   0.017478      2020   \n",
+       "989919                      5.0              110.0   0.002649      2020   \n",
+       "\n",
+       "          date_stale  label  prediction  \n",
+       "1319584   143.341818   -1.0          -1  \n",
+       "7579770   184.261009   -1.0          -1  \n",
+       "9173011   169.293431   -1.0          -1  \n",
+       "1209389   146.328318   -1.0          -1  \n",
+       "4173344   191.303842   -1.0          -1  \n",
+       "10985986  195.359312   -1.0          -1  \n",
+       "6208696   142.360796   -1.0          -1  \n",
+       "801178    131.828965   -1.0          -1  \n",
+       "4392500   206.150937   -1.0          -1  \n",
+       "7963350   190.312686   -1.0          -1  \n",
+       "5659388   140.250630   -1.0          -1  \n",
+       "2749172   142.989201   -1.0          -1  \n",
+       "4230883   153.354072   -1.0          -1  \n",
+       "6370669   178.167846   -1.0          -1  \n",
+       "5109458   140.166676   -1.0          -1  \n",
+       "7689620   203.189280   -1.0          -1  \n",
+       "9831120   167.149854   -1.0          -1  \n",
+       "6263478   140.365511   -1.0          -1  \n",
+       "10581997  129.861984   -1.0          -1  \n",
+       "3243302   140.230023   -1.0          -1  \n",
+       "3659063   131.658167   -1.0          -1  \n",
+       "6099073   142.184268   -1.0          -1  \n",
+       "3953358   185.115723   -1.0          -1  \n",
+       "9724190   135.124112   -1.0          -1  \n",
+       "1041978   167.270642   -1.0          -1  \n",
+       "880090    143.298327   -1.0          -1  \n",
+       "8492341   123.742413   -1.0          -1  \n",
+       "8952735   188.359673   -1.0          -1  \n",
+       "3274872   126.967926   -1.0          -1  \n",
+       "989919    146.098129   -1.0          -1  \n",
+       "\n",
+       "[30 rows x 24 columns]"
+      ]
+     },
+     "execution_count": 31,
+     "metadata": {},
+     "output_type": "execute_result"
+    }
+   ],
+   "source": [
+    "test_x[(test_x.index.isin(fake_df.index))]"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "metadata": {},
+   "outputs": [],
+   "source": []
+  }
+ ],
+ "metadata": {
+  "kernelspec": {
+   "display_name": "Python 3",
+   "language": "python",
+   "name": "python3"
+  },
+  "language_info": {
+   "codemirror_mode": {
+    "name": "ipython",
+    "version": 3
+   },
+   "file_extension": ".py",
+   "mimetype": "text/x-python",
+   "name": "python",
+   "nbconvert_exporter": "python",
+   "pygments_lexer": "ipython3",
+   "version": "3.8.3"
+  }
+ },
+ "nbformat": 4,
+ "nbformat_minor": 4
+}