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main
utku_inst_name_exploration
utku_keyword_suggestion
test
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ZSI_Reconnect_China/WOS/.ipynb_checkpoints/wos_concat-checkpoint.ipynb

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2 years ago
{
"cells": [
{
"cell_type": "code",
"execution_count": 70,
"metadata": {},
"outputs": [],
"source": [
"import numpy as np\n",
"import pandas as pd\n",
"from tqdm import tqdm\n",
"import os\n",
"import shutil"
]
},
{
"cell_type": "code",
"execution_count": 71,
"metadata": {},
"outputs": [],
"source": [
"workdir_path=r\"wos_extract\"\n",
"outfile='wos_extract_complete.csv'\n",
"# with_header=True\n",
"# for root, dirs, files in os.walk(workdir_path):\n",
"# for filename in files:\n",
"# if filename.startswith(\"wosexport\"):\n",
"# path=os.path.join(root, filename)\n",
"# print(path)\n",
"# chunk = pd.read_excel(path)\n",
"# chunk.to_csv(outfile, mode=\"a\", index=False, header=with_header, sep=\"\\t\")\n",
"# with_header = False"
]
},
{
"cell_type": "code",
"execution_count": 72,
"metadata": {},
"outputs": [],
"source": [
"record_col=\"UT (Unique WOS ID)\""
]
},
{
"cell_type": "code",
"execution_count": 73,
"metadata": {},
"outputs": [],
"source": [
"wos = pd.read_csv(outfile, sep=\"\\t\",low_memory=False)\n",
"metrix = pd.read_excel(\"sm_journal_classification.xlsx\", sheet_name=\"Journal_Classification\")\n",
"\n",
"\n",
"metrix = metrix.set_index([c for c in metrix.columns if \"issn\" not in c]).stack().reset_index()\n",
"metrix = metrix.rename(columns={'level_6':\"issn_type\", 0:\"issn\"})\n",
"metrix[\"issn\"]=metrix[\"issn\"].str.replace(\"-\",\"\").str.lower().str.strip()\n",
"\n",
"wos[\"issn\"] = wos[\"ISSN\"].str.replace(\"-\",\"\").str.lower().str.strip()\n",
"wos[\"eissn\"] = wos[\"eISSN\"].str.replace(\"-\",\"\").str.lower().str.strip()\n",
"wos = wos.set_index([c for c in wos.columns if \"issn\" not in c]).stack().reset_index()\n",
"wos = wos.rename(columns={'level_72':\"issn_var\", 0:\"issn\"})\n",
"\n",
"wos_merge = wos.merge(metrix, on=\"issn\", how=\"left\")\n",
"wos = wos_merge.sort_values(by=\"issn_var\",ascending=False).drop_duplicates(subset=record_col)"
]
},
{
"cell_type": "code",
"execution_count": 74,
"metadata": {},
"outputs": [
{
"data": {
"text/plain": [
"0 Publication Type\n",
"1 Authors\n",
"2 Book Authors\n",
"3 Book Editors\n",
"4 Book Group Authors\n",
" ... \n",
"76 SubField_English\n",
"77 2.00 SEQ\n",
"78 Source_title\n",
"79 srcid\n",
"80 issn_type\n",
"Length: 81, dtype: object"
]
},
"execution_count": 74,
"metadata": {},
"output_type": "execute_result"
}
],
"source": [
"pd.Series(wos.columns)"
]
},
{
"cell_type": "code",
"execution_count": 75,
"metadata": {},
"outputs": [
{
"data": {
"text/plain": [
"0 Salucci, Marco/S-8654-2016; Arrebola, Manuel/L...\n",
"9714 Huang, Yu/AAY-5464-2020\n",
"9697 Kakavand, Mohammad Reza Azadi/X-9556-2019; Fen...\n",
"9699 Dong, Sheng/AAE-3619-2021; Soares, Carlos Gued...\n",
"9701 Han, Guoqi/T-7365-2019; Nan, Yang/HKD-9687-202...\n",
" ... \n",
"3066 ; Liotta, Antonio/G-9532-2014\n",
"5097 , 卢帅/AAK-2185-2020; Popp, József/AFN-1250-2022\n",
"11369 NaN\n",
"11368 Rossiter, D G/D-3842-2009\n",
"11362 Jin, Shuanggen/B-8094-2008\n",
"Name: Researcher Ids, Length: 9889, dtype: object"
]
},
"execution_count": 75,
"metadata": {},
"output_type": "execute_result"
}
],
"source": [
"wos[\"Researcher Ids\"]"
]
},
{
"cell_type": "code",
"execution_count": 76,
"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>Publication Type</th>\n",
" <th>Authors</th>\n",
" <th>Book Authors</th>\n",
" <th>Book Editors</th>\n",
" <th>Book Group Authors</th>\n",
" <th>Author Full Names</th>\n",
" <th>Book Author Full Names</th>\n",
" <th>Group Authors</th>\n",
" <th>Article Title</th>\n",
" <th>Source Title</th>\n",
" <th>...</th>\n",
" <th>Web of Science Record</th>\n",
" <th>issn_var</th>\n",
" <th>issn</th>\n",
" <th>Domain_English</th>\n",
" <th>Field_English</th>\n",
" <th>SubField_English</th>\n",
" <th>2.00 SEQ</th>\n",
" <th>Source_title</th>\n",
" <th>srcid</th>\n",
" <th>issn_type</th>\n",
" </tr>\n",
" </thead>\n",
" <tbody>\n",
" <tr>\n",
" <th>16979</th>\n",
" <td>J</td>\n",
" <td>Zhang, MS; Huang, J; Cao, Y; Xiong, CH; Mohamm...</td>\n",
" <td>NaN</td>\n",
" <td>NaN</td>\n",
" <td>NaN</td>\n",
" <td>Zhang, Mengshi; Huang, Jian; Cao, Yu; Xiong, C...</td>\n",
" <td>NaN</td>\n",
" <td>NaN</td>\n",
" <td>Echo State Network-Enhanced Super-Twisting Con...</td>\n",
" <td>IEEE-ASME TRANSACTIONS ON MECHATRONICS</td>\n",
" <td>...</td>\n",
" <td>0</td>\n",
" <td>issn</td>\n",
" <td>10834435</td>\n",
" <td>Applied Sciences</td>\n",
" <td>Engineering</td>\n",
" <td>Industrial Engineering &amp; Automation</td>\n",
" <td>27</td>\n",
" <td>IEEE/ASME Transactions on Mechatronics</td>\n",
" <td>19113.0</td>\n",
" <td>issn1</td>\n",
" </tr>\n",
" <tr>\n",
" <th>1880</th>\n",
" <td>J</td>\n",
" <td>Zhang, MS; Huang, J; Cao, Y; Xiong, CH; Mohamm...</td>\n",
" <td>NaN</td>\n",
" <td>NaN</td>\n",
" <td>NaN</td>\n",
" <td>Zhang, Mengshi; Huang, Jian; Cao, Yu; Xiong, C...</td>\n",
" <td>NaN</td>\n",
" <td>NaN</td>\n",
" <td>Echo State Network-Enhanced Super-Twisting Con...</td>\n",
" <td>IEEE-ASME TRANSACTIONS ON MECHATRONICS</td>\n",
" <td>...</td>\n",
" <td>0</td>\n",
" <td>issn</td>\n",
" <td>10834435</td>\n",
" <td>Applied Sciences</td>\n",
" <td>Engineering</td>\n",
" <td>Industrial Engineering &amp; Automation</td>\n",
" <td>27</td>\n",
" <td>IEEE/ASME Transactions on Mechatronics</td>\n",
" <td>19113.0</td>\n",
" <td>issn1</td>\n",
" </tr>\n",
" </tbody>\n",
"</table>\n",
"<p>2 rows × 81 columns</p>\n",
"</div>"
],
"text/plain": [
" Publication Type Authors \n",
"16979 J Zhang, MS; Huang, J; Cao, Y; Xiong, CH; Mohamm... \\\n",
"1880 J Zhang, MS; Huang, J; Cao, Y; Xiong, CH; Mohamm... \n",
"\n",
" Book Authors Book Editors Book Group Authors \n",
"16979 NaN NaN NaN \\\n",
"1880 NaN NaN NaN \n",
"\n",
" Author Full Names \n",
"16979 Zhang, Mengshi; Huang, Jian; Cao, Yu; Xiong, C... \\\n",
"1880 Zhang, Mengshi; Huang, Jian; Cao, Yu; Xiong, C... \n",
"\n",
" Book Author Full Names Group Authors \n",
"16979 NaN NaN \\\n",
"1880 NaN NaN \n",
"\n",
" Article Title \n",
"16979 Echo State Network-Enhanced Super-Twisting Con... \\\n",
"1880 Echo State Network-Enhanced Super-Twisting Con... \n",
"\n",
" Source Title ... Web of Science Record \n",
"16979 IEEE-ASME TRANSACTIONS ON MECHATRONICS ... 0 \\\n",
"1880 IEEE-ASME TRANSACTIONS ON MECHATRONICS ... 0 \n",
"\n",
" issn_var issn Domain_English Field_English \n",
"16979 issn 10834435 Applied Sciences Engineering \\\n",
"1880 issn 10834435 Applied Sciences Engineering \n",
"\n",
" SubField_English 2.00 SEQ \n",
"16979 Industrial Engineering & Automation 27 \\\n",
"1880 Industrial Engineering & Automation 27 \n",
"\n",
" Source_title srcid issn_type \n",
"16979 IEEE/ASME Transactions on Mechatronics 19113.0 issn1 \n",
"1880 IEEE/ASME Transactions on Mechatronics 19113.0 issn1 \n",
"\n",
"[2 rows x 81 columns]"
]
},
"execution_count": 76,
"metadata": {},
"output_type": "execute_result"
}
],
"source": [
"wos[(~wos[\"DOI\"].isna())&(wos[\"DOI\"].duplicated(False))]"
]
},
{
"cell_type": "code",
"execution_count": 77,
"metadata": {},
"outputs": [],
"source": [
"from flashgeotext.geotext import GeoText\n",
"\n",
"geotext = GeoText()\n",
"\n",
"def extract_location(input_text, key='countries'):\n",
" anomalies = {\"Malta\":\"Malta\",\n",
" \"Mongolia\":\"Mongolia\",\n",
" \"Quatar\":\"Qatar\",\n",
" \"Qatar\":\"Qatar\",\n",
" \"Ethiop\":\"Ethiopia\",\n",
" \"Nigeria\":\"Nigeria\",\n",
" \"BELAR\":\"Belarus\",\n",
" \"Venezuela\":\"Venezuela\",\n",
" \"Cyprus\":\"Cyprus\",\n",
" \"Ecuador\":\"Ecuador\",\n",
" \"U Arab\":\"United Arab Emirates\",\n",
" \"Syria\":\"Syria\",\n",
" \"Uganda\":\"Uganda\",\n",
" \"Yemen\":\"Yemen\",\n",
" \"Mali\":\"Mali\",\n",
" \"Senegal\":\"Senegal\",\n",
" \"Vatican\":\"Vatican\",\n",
" \"Uruguay\":\"Uruguay\",\n",
" \"Panama\":\"Panama\",\n",
" \"Fiji\":\"Fiji\",\n",
" \"Faroe\":\"Faroe Islands\",\n",
" \"Macedonia\":\"Macedonia\",\n",
" 'Mozambique':'Mozambique',\n",
" \"Kuwait\":\"Kuwait\",\n",
" \"Libya\":\"Libya\",\n",
" \"Turkiy\":\"Turkey\",\n",
" \"Liberia\":\"Liberia\",\n",
" \"Namibia\":\"Namibia\",\n",
" \"Ivoire\":\"Ivory Coast\",\n",
" \"Guatemala\":\"Gutemala\",\n",
" \"Paraguay\":\"Paraguay\",\n",
" \"Honduras\":\"Honduras\",\n",
" \"Nicaragua\":\"Nicaragua\",\n",
" \"Trinidad\":\"Trinidad & Tobago\",\n",
" \"Liechtenstein\":\"Liechtenstein\",\n",
" \"Greenland\":\"Denmark\"}\n",
"\n",
" extracted = geotext.extract(input_text=input_text)\n",
" found = extracted[key].keys()\n",
" if len(sorted(found))>0:\n",
" return sorted(found)[0]\n",
" elif key=='countries':\n",
" for i in ['Scotland','Wales','England']:\n",
" if i in input_text:\n",
" return 'United Kingdom'\n",
" for j in anomalies.keys():\n",
" if j in input_text:\n",
" return anomalies.get(j)\n",
" else:\n",
" return None\n",
"\n",
"with open('../eu_members.txt',\"r\") as f:\n",
" eu_countries=f.readline().split(\",\")\n",
" eu_countries=[i.strip() for i in eu_countries]\n",
"\n",
"def country_type(country):\n",
" if country in eu_countries:\n",
" return \"EU\"\n",
" elif country==\"China\":\n",
" return \"China\"\n",
" else:\n",
" return \"Other\"\n"
]
},
{
"cell_type": "code",
"execution_count": 78,
"metadata": {},
"outputs": [],
"source": [
"locations = wos.groupby(record_col)[\"Addresses\"].apply(lambda x: x.str.split('[')).explode().reset_index().drop(columns=\"level_1\")\n",
"locations = locations[locations[\"Addresses\"]!=\"\"].copy()\n",
"locations[\"Address\"] = locations[\"Addresses\"].apply(lambda x:x.split(\"]\")[-1])\n",
"locations[\"Authors_of_address\"] = locations[\"Addresses\"].apply(lambda x:x.split(\"]\")[0])\n",
"locations[\"Country\"]=locations['Address'].apply(lambda x: extract_location(input_text=x, key='countries'))\n",
"locations[\"City\"]=locations['Address'].apply(lambda x: extract_location(input_text=x, key='cities'))\n",
"locations[\"Country_Type\"] = locations[\"Country\"].apply(lambda x: country_type(x))"
]
},
{
"cell_type": "code",
"execution_count": 119,
"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>UT (Unique WOS ID)</th>\n",
" <th>Address</th>\n",
" <th>Country</th>\n",
" <th>City</th>\n",
" <th>Country_Type</th>\n",
" <th>Institution</th>\n",
" </tr>\n",
" </thead>\n",
" <tbody>\n",
" <tr>\n",
" <th>1</th>\n",
" <td>WOS:000209536100003</td>\n",
" <td>BGI HK Ltd, GigaSci, Tai Po, Hong Kong, Peopl...</td>\n",
" <td>China</td>\n",
" <td>Hong Kong</td>\n",
" <td>China</td>\n",
" <td>BGI HK Ltd</td>\n",
" </tr>\n",
" <tr>\n",
" <th>2</th>\n",
" <td>WOS:000209536100003</td>\n",
" <td>Nat Hist Museum, London SW7 5BD, England;</td>\n",
" <td>United Kingdom</td>\n",
" <td>London</td>\n",
" <td>Other</td>\n",
" <td>Nat Hist Museum</td>\n",
" </tr>\n",
" <tr>\n",
" <th>3</th>\n",
" <td>WOS:000209536100003</td>\n",
" <td>Pensoft Publishers, Sofia, Bulgaria;</td>\n",
" <td>Bulgaria</td>\n",
" <td>Sofia</td>\n",
" <td>EU</td>\n",
" <td>Pensoft Publishers</td>\n",
" </tr>\n",
" <tr>\n",
" <th>4</th>\n",
" <td>WOS:000209536100003</td>\n",
" <td>Nat Hist Museum, Natl Museum, Sofia, Bulgaria;</td>\n",
" <td>Bulgaria</td>\n",
" <td>Sofia</td>\n",
" <td>EU</td>\n",
" <td>Nat Hist Museum</td>\n",
" </tr>\n",
" <tr>\n",
" <th>5</th>\n",
" <td>WOS:000209536100003</td>\n",
" <td>Bulgarian Acad Sci, Inst Biodivers &amp; Ecosyst ...</td>\n",
" <td>Bulgaria</td>\n",
" <td>Rees</td>\n",
" <td>EU</td>\n",
" <td>Bulgarian Acad Sci</td>\n",
" </tr>\n",
" </tbody>\n",
"</table>\n",
"</div>"
],
"text/plain": [
" UT (Unique WOS ID) Address \n",
"1 WOS:000209536100003 BGI HK Ltd, GigaSci, Tai Po, Hong Kong, Peopl... \\\n",
"2 WOS:000209536100003 Nat Hist Museum, London SW7 5BD, England; \n",
"3 WOS:000209536100003 Pensoft Publishers, Sofia, Bulgaria; \n",
"4 WOS:000209536100003 Nat Hist Museum, Natl Museum, Sofia, Bulgaria; \n",
"5 WOS:000209536100003 Bulgarian Acad Sci, Inst Biodivers & Ecosyst ... \n",
"\n",
" Country City Country_Type Institution \n",
"1 China Hong Kong China BGI HK Ltd \n",
"2 United Kingdom London Other Nat Hist Museum \n",
"3 Bulgaria Sofia EU Pensoft Publishers \n",
"4 Bulgaria Sofia EU Nat Hist Museum \n",
"5 Bulgaria Rees EU Bulgarian Acad Sci "
]
},
"execution_count": 119,
"metadata": {},
"output_type": "execute_result"
}
],
"source": [
"univ_locations = locations[[record_col,\"Address\",\"Country\",\"City\",\"Country_Type\"]].copy()\n",
"univ_locations[\"Institution\"] = univ_locations[\"Address\"].apply(lambda x: x.split(\",\")[0])\n",
"univ_locations.head()"
]
},
{
"cell_type": "code",
"execution_count": 79,
"metadata": {},
"outputs": [
{
"data": {
"text/plain": [
"Country\n",
"China 21063\n",
"United States 5913\n",
"Germany 4179\n",
"Italy 3195\n",
"France 2767\n",
" ... \n",
"Faroe Islands 1\n",
"Honduras 1\n",
"Vatican 1\n",
"Macedonia 1\n",
"Jamaica 1\n",
"Name: count, Length: 137, dtype: int64"
]
},
"execution_count": 79,
"metadata": {},
"output_type": "execute_result"
}
],
"source": [
"locations[\"Country\"].value_counts()"
]
},
{
"cell_type": "code",
"execution_count": 80,
"metadata": {},
"outputs": [
{
"data": {
"text/plain": [
"Country_Type\n",
"EU 21228\n",
"China 21063\n",
"Other 20404\n",
"Name: count, dtype: int64"
]
},
"execution_count": 80,
"metadata": {},
"output_type": "execute_result"
}
],
"source": [
"locations[\"Country_Type\"].value_counts()"
]
},
{
"cell_type": "code",
"execution_count": 81,
"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>UT (Unique WOS ID)</th>\n",
" <th>Country</th>\n",
" <th>Country_Type</th>\n",
" <th>Author_name</th>\n",
" <th>author_str_id</th>\n",
" </tr>\n",
" </thead>\n",
" <tbody>\n",
" <tr>\n",
" <th>0</th>\n",
" <td>WOS:000209536100003</td>\n",
" <td>Bulgaria</td>\n",
" <td>EU</td>\n",
" <td>Stoev, Pavel</td>\n",
" <td>stoevpavel</td>\n",
" </tr>\n",
" <tr>\n",
" <th>1</th>\n",
" <td>WOS:000209536100003</td>\n",
" <td>Bulgaria</td>\n",
" <td>EU</td>\n",
" <td>Penev, Lyubomir</td>\n",
" <td>penevlyubomir</td>\n",
" </tr>\n",
" <tr>\n",
" <th>2</th>\n",
" <td>WOS:000209536100003</td>\n",
" <td>Bulgaria</td>\n",
" <td>EU</td>\n",
" <td>Stoev, Pavel</td>\n",
" <td>stoevpavel</td>\n",
" </tr>\n",
" <tr>\n",
" <th>3</th>\n",
" <td>WOS:000209536100003</td>\n",
" <td>Bulgaria</td>\n",
" <td>EU</td>\n",
" <td>Penev, Lyubomir</td>\n",
" <td>penevlyubomir</td>\n",
" </tr>\n",
" <tr>\n",
" <th>4</th>\n",
" <td>WOS:000209536100003</td>\n",
" <td>China</td>\n",
" <td>China</td>\n",
" <td>Edmunds, Scott C.</td>\n",
" <td>edmundsscottc</td>\n",
" </tr>\n",
" <tr>\n",
" <th>...</th>\n",
" <td>...</td>\n",
" <td>...</td>\n",
" <td>...</td>\n",
" <td>...</td>\n",
" <td>...</td>\n",
" </tr>\n",
" <tr>\n",
" <th>173441</th>\n",
" <td>WOS:000947693400001</td>\n",
" <td>China</td>\n",
" <td>China</td>\n",
" <td>Peng, Sihua</td>\n",
" <td>pengsihua</td>\n",
" </tr>\n",
" <tr>\n",
" <th>173442</th>\n",
" <td>WOS:000947693400001</td>\n",
" <td>China</td>\n",
" <td>China</td>\n",
" <td>Shen, Zhehan</td>\n",
" <td>shenzhehan</td>\n",
" </tr>\n",
" <tr>\n",
" <th>173443</th>\n",
" <td>WOS:000947693400001</td>\n",
" <td>China</td>\n",
" <td>China</td>\n",
" <td>Shen, Zhehan</td>\n",
" <td>shenzhehan</td>\n",
" </tr>\n",
" <tr>\n",
" <th>173444</th>\n",
" <td>WOS:000947693400001</td>\n",
" <td>China</td>\n",
" <td>China</td>\n",
" <td>Liu, Taigang</td>\n",
" <td>liutaigang</td>\n",
" </tr>\n",
" <tr>\n",
" <th>173445</th>\n",
" <td>WOS:000947693400001</td>\n",
" <td>Spain</td>\n",
" <td>EU</td>\n",
" <td>Jiang, Linhua</td>\n",
" <td>jianglinhua</td>\n",
" </tr>\n",
" </tbody>\n",
"</table>\n",
"<p>173446 rows × 5 columns</p>\n",
"</div>"
],
"text/plain": [
" UT (Unique WOS ID) Country Country_Type Author_name \n",
"0 WOS:000209536100003 Bulgaria EU Stoev, Pavel \\\n",
"1 WOS:000209536100003 Bulgaria EU Penev, Lyubomir \n",
"2 WOS:000209536100003 Bulgaria EU Stoev, Pavel \n",
"3 WOS:000209536100003 Bulgaria EU Penev, Lyubomir \n",
"4 WOS:000209536100003 China China Edmunds, Scott C. \n",
"... ... ... ... ... \n",
"173441 WOS:000947693400001 China China Peng, Sihua \n",
"173442 WOS:000947693400001 China China Shen, Zhehan \n",
"173443 WOS:000947693400001 China China Shen, Zhehan \n",
"173444 WOS:000947693400001 China China Liu, Taigang \n",
"173445 WOS:000947693400001 Spain EU Jiang, Linhua \n",
"\n",
" author_str_id \n",
"0 stoevpavel \n",
"1 penevlyubomir \n",
"2 stoevpavel \n",
"3 penevlyubomir \n",
"4 edmundsscottc \n",
"... ... \n",
"173441 pengsihua \n",
"173442 shenzhehan \n",
"173443 shenzhehan \n",
"173444 liutaigang \n",
"173445 jianglinhua \n",
"\n",
"[173446 rows x 5 columns]"
]
},
"execution_count": 81,
"metadata": {},
"output_type": "execute_result"
}
],
"source": [
"author_locations = locations.groupby([record_col,\"Country\",\"Country_Type\"])[\"Authors_of_address\"].apply(lambda x: x.str.split(';')).explode().reset_index().drop(columns=\"level_3\")\n",
"author_locations[\"Author_name\"] = author_locations[\"Authors_of_address\"].str.strip()\n",
"author_locations = author_locations.drop(columns=\"Authors_of_address\")\n",
"author_locations[\"author_str_id\"] = author_locations[\"Author_name\"].apply(lambda x:''.join(filter(str.isalnum, x.lower())))\n",
"author_locations"
]
},
{
"cell_type": "code",
"execution_count": 82,
"metadata": {},
"outputs": [
{
"data": {
"text/plain": [
"8925"
]
},
"execution_count": 82,
"metadata": {},
"output_type": "execute_result"
}
],
"source": [
"author_primary_region = author_locations.sort_values(by=\"Country_Type\").drop_duplicates(subset=[record_col,\"author_str_id\"])\n",
"# author_primary_region\n",
"\n",
"china=author_primary_region[author_primary_region[\"Country_Type\"]==\"China\"][record_col].unique()\n",
"eu=author_primary_region[author_primary_region[\"Country_Type\"]==\"EU\"][record_col].unique()\n",
"\n",
"len(wos[((wos[record_col].isin(china))\n",
" &\n",
" (wos[record_col].isin(eu)))])"
]
},
{
"cell_type": "code",
"execution_count": 83,
"metadata": {},
"outputs": [
{
"data": {
"text/plain": [
"9889"
]
},
"execution_count": 83,
"metadata": {},
"output_type": "execute_result"
}
],
"source": [
"len(wos)"
]
},
{
"cell_type": "code",
"execution_count": 84,
"metadata": {},
"outputs": [],
"source": [
"affiliations = wos.groupby(record_col)[\"Affiliations\"].apply(lambda x: x.str.split(';')).explode().reset_index().drop(columns=\"level_1\")\n",
"# affiliations[affiliations[\"Affiliations\"].str.lower().str.contains(\"chinese academy\", na=False, regex=True)][\"Affiliations\"].value_counts()\n",
"affiliations[\"Affiliations\"] = affiliations[\"Affiliations\"].str.strip().str.upper().fillna(\"UNKNOWN\")\n",
"affiliations = affiliations.drop_duplicates()"
]
},
{
"cell_type": "code",
"execution_count": 112,
"metadata": {},
"outputs": [
{
"name": "stdout",
"output_type": "stream",
"text": [
"69747 64845\n"
]
}
],
"source": [
"aff_ = wos.groupby(record_col)[\"Affiliations\"].apply(lambda x: x.str.split(';')).explode().reset_index().drop(columns=\"level_1\")\n",
"loc_ = wos.groupby(record_col)[\"Addresses\"].apply(lambda x: x.str.split('[')).explode().reset_index().drop(columns=\"level_1\")\n",
"print(len(aff_),len(loc_))"
]
},
{
"cell_type": "code",
"execution_count": 85,
"metadata": {},
"outputs": [
{
"data": {
"text/plain": [
"[['IDAHO'],\n",
" ['ICREA'],\n",
" ['CEA'],\n",
" ['AGROPARISTECH'],\n",
" ['LENOVO'],\n",
" ['RIKEN'],\n",
" ['MICROSOFT'],\n",
" ['GLAXOSMITHKLINE'],\n",
" ['UNICANCER'],\n",
" ['INRIA'],\n",
" ['CIBERESP'],\n",
" ['SINOPEC'],\n",
" ['PHILIPS'],\n",
" ['CIRAD'],\n",
" ['VITO'],\n",
" ['IMEC'],\n",
" ['ILLUMINA'],\n",
" ['EURECOM'],\n",
" ['BAIDU'],\n",
" ['CIBEREHD'],\n",
" ['UNKNOWN'],\n",
" ['BAYCREST'],\n",
" ['NOVARTIS'],\n",
" ['ITER'],\n",
" ['PELIN'],\n",
" ['INRAE'],\n",
" ['ASTRAZENECA'],\n",
" ['ERICSSON'],\n",
" ['IDIBAPS'],\n",
" ['CGIAR'],\n",
" ['UNILEVER'],\n",
" ['GENENTECH'],\n",
" ['TENCENT'],\n",
" ['NICTA'],\n",
" ['QUALCOMM'],\n",
" ['INESC-ID'],\n",
" ['CIBERES'],\n",
" ['ALCATEL-LUCENT'],\n",
" ['TEAGASC'],\n",
" ['ABB'],\n",
" ['HEWLETT-PACKARD'],\n",
" ['AT&T'],\n",
" ['RIGSHOSPITALET'],\n",
" ['FORTISS'],\n",
" ['AMAZON.COM'],\n",
" ['BASF'],\n",
" ['BOSCH'],\n",
" ['CIBERSAM'],\n",
" ['EURATOM'],\n",
" ['UNINETTUNO'],\n",
" ['E-ON'],\n",
" ['DELPHI'],\n",
" ['BIOGEN'],\n",
" ['SAMSUNG'],\n",
" ['INTERDIGITAL'],\n",
" ['SYNGENTA'],\n",
" ['CIBERONC'],\n",
" ['IRTA'],\n",
" ['MICA'],\n",
" ['MEDTRONIC'],\n",
" ['IFREMER'],\n",
" ['DELTARES'],\n",
" ['PROFIL'],\n",
" ['SANOFI-AVENTIS'],\n",
" ['REGENERON'],\n",
" ['YUTONG'],\n",
" ['CIBERBBN'],\n",
" ['KAKAO'],\n",
" ['DNV'],\n",
" ['SCHLUMBERGER'],\n",
" ['ITALFARMACO'],\n",
" ['CYBERNETICA'],\n",
" ['ZTE'],\n",
" ['NAVER'],\n",
" ['VOLVO'],\n",
" ['CHANGHONG'],\n",
" ['CINTECX'],\n",
" ['VINUNIVERSITY'],\n",
" ['SERVIER'],\n",
" ['CIBERCV'],\n",
" ['IMELDAZIEKENHUIS'],\n",
" ['DIAKONESSENHUIS'],\n",
" ['ADVENTHEALTH'],\n",
" ['ALLIANCE'],\n",
" ['AUDENCIA'],\n",
" ['SINTEF'],\n",
" ['SAP'],\n",
" ['ELEKTA'],\n",
" ['ELSEVIER'],\n",
" ['CIBEROBN'],\n",
" ['PFIZER'],\n",
" ['ABBVIE'],\n",
" ['NAVARRABIOMED'],\n",
" ['BYD'],\n",
" ['INSPUR'],\n",
" ['CIBERNED'],\n",
" ['SHANDONG', 'UNIVERSITY'],\n",
" ['HEBEI', 'UNIVERSITY'],\n",
" ['BOGAZICI', 'UNIVERSITY'],\n",
" ['DOGUS', 'UNIVERSITY'],\n",
" ['GAZIANTEP', 'UNIVERSITY'],\n",
" ['ANKARA', 'UNIVERSITY'],\n",
" ['DUMLUPINAR', 'UNIVERSITY'],\n",
" ['GAZI', 'UNIVERSITY'],\n",
" ['BOSTON', 'UNIVERSITY'],\n",
" ['BRANDEIS', 'UNIVERSITY'],\n",
" ['CARLETON', 'UNIVERSITY'],\n",
" ['NANJING', 'UNIVERSITY'],\n",
" ['COLUMBIA', 'UNIVERSITY'],\n",
" ['HELMHOLTZ', 'ASSOCIATION'],\n",
" ['DUKE', 'UNIVERSITY'],\n",
" ['HAMPTON', 'UNIVERSITY'],\n",
" ['HARVARD', 'UNIVERSITY'],\n",
" ['KOBE', 'UNIVERSITY'],\n",
" ['KYOTO', 'UNIVERSITY'],\n",
" ['LANCASTER', 'UNIVERSITY'],\n",
" ['SORBONNE', 'UNIVERSITE'],\n",
" ['LUND', 'UNIVERSITY'],\n",
" ['AIX-MARSEILLE', 'UNIVERSITE'],\n",
" ['MCGILL', 'UNIVERSITY'],\n",
" ['NAGOYA', 'UNIVERSITY'],\n",
" ['OKAYAMA', 'UNIVERSITY'],\n",
" ['OSAKA', 'UNIVERSITY'],\n",
" ['RITSUMEIKAN', 'UNIVERSITY'],\n",
" ['SHINSHU', 'UNIVERSITY'],\n",
" ['UNIVERSITAT', 'SIEGEN'],\n",
" ['STANFORD', 'UNIVERSITY'],\n",
" ['STOCKHOLM', 'UNIVERSITY'],\n",
" ['TUFTS', 'UNIVERSITY'],\n",
" ['UPPSALA', 'UNIVERSITY'],\n",
" ['WASEDA', 'UNIVERSITY'],\n",
" ['YALE', 'UNIVERSITY'],\n",
" ['HIROSHIMA', 'UNIVERSITY'],\n",
" ['MANHATTAN', 'COLLEGE'],\n",
" ['JAGIELLONIAN', 'UNIVERSITY'],\n",
" ['FUDAN', 'UNIVERSITY'],\n",
" ['YANTAI', 'UNIVERSITY'],\n",
" ['UNIVERSITY', 'OSNABRUCK'],\n",
" ['PEKING', 'UNIVERSITY'],\n",
" ['TSINGHUA', 'UNIVERSITY'],\n",
" ['SYRACUSE', 'UNIVERSITY'],\n",
" ['ZHEJIANG', 'UNIVERSITY'],\n",
" ['MCMASTER', 'UNIVERSITY'],\n",
" ['ETH', 'ZURICH'],\n",
" ['TUSCIA', 'UNIVERSITY'],\n",
" ['LISHUI', 'UNIVERSITY'],\n",
" ['LEGEND', 'HOLDINGS'],\n",
" ['WUHAN', 'UNIVERSITY'],\n",
" ['GHENT', 'UNIVERSITY'],\n",
" ['SHANGHAI', 'UNIVERSITY'],\n",
" ['JILIN', 'UNIVERSITY'],\n",
" ['ULSTER', 'UNIVERSITY'],\n",
" ['JIANGNAN', 'UNIVERSITY'],\n",
" ['KU', 'LEUVEN'],\n",
" ['HOCHSCHULE', 'AALEN'],\n",
" ['SHAOYANG', 'UNIVERSITY'],\n",
" ['HUNAN', 'UNIVERSITY'],\n",
" ['KYUSHU', 'UNIVERSITY'],\n",
" ['TONGJI', 'UNIVERSITY'],\n",
" ['TAMPERE', 'UNIVERSITY'],\n",
" ['AALTO', 'UNIVERSITY'],\n",
" ['OBUDA', 'UNIVERSITY'],\n",
" ['PANJAB', 'UNIVERSITY'],\n",
" ['KOREA', 'UNIVERSITY'],\n",
" ['VILNIUS', 'UNIVERSITY'],\n",
" ['CHULALONGKORN', 'UNIVERSITY'],\n",
" ['CUKUROVA', 'UNIVERSITY'],\n",
" ['BRUNEL', 'UNIVERSITY'],\n",
" ['BAYLOR', 'UNIVERSITY'],\n",
" ['BROWN', 'UNIVERSITY'],\n",
" ['CORNELL', 'UNIVERSITY'],\n",
" ['FAIRFIELD', 'UNIVERSITY'],\n",
" ['NORTHEASTERN', 'UNIVERSITY'],\n",
" ['NORTHWESTERN', 'UNIVERSITY'],\n",
" ['PRINCETON', 'UNIVERSITY'],\n",
" ['PURDUE', 'UNIVERSITY'],\n",
" ['RICE', 'UNIVERSITY'],\n",
" ['ROCKEFELLER', 'UNIVERSITY'],\n",
" ['VANDERBILT', 'UNIVERSITY'],\n",
" ['CAIRO', 'UNIVERSITY'],\n",
" ['FAYOUM', 'UNIVERSITY'],\n",
" ['HELWAN', 'UNIVERSITY'],\n",
" ['SHIRAZ', 'UNIVERSITY'],\n",
" ['GAZIOSMANPASA', 'UNIVERSITY'],\n",
" ['ADIYAMAN', 'UNIVERSITY'],\n",
" ['MERSIN', 'UNIVERSITY'],\n",
" ['OZYEGIN', 'UNIVERSITY'],\n",
" ['KAFKAS', 'UNIVERSITY'],\n",
" ['EGE', 'UNIVERSITY'],\n",
" ['HOHAI', 'UNIVERSITY'],\n",
" ['JIANGSU', 'UNIVERSITY'],\n",
" ['LANZHOU', 'UNIVERSITY'],\n",
" ['UNIVERSITE', 'PSL'],\n",
" ['UNIVERSITY', 'HOHENHEIM'],\n",
" ['TILBURG', 'UNIVERSITY'],\n",
" ['BEIHANG', 'UNIVERSITY'],\n",
" ['NORTHUMBRIA', 'UNIVERSITY'],\n",
" ['CHONGQING', 'UNIVERSITY'],\n",
" ['AALBORG', 'UNIVERSITY'],\n",
" ['HASSELT', 'UNIVERSITY'],\n",
" ['HAINAN', 'UNIVERSITY'],\n",
" ['GIFU', 'UNIVERSITY'],\n",
" ['HANYANG', 'UNIVERSITY'],\n",
" ['KANAGAWA', 'UNIVERSITY'],\n",
" ['NIIGATA', 'UNIVERSITY'],\n",
" ['SOONGSIL', 'UNIVERSITY'],\n",
" ['TOHO', 'UNIVERSITY'],\n",
" ['TOHOKU', 'UNIVERSITY'],\n",
" ['YAMAGATA', 'UNIVERSITY'],\n",
" ['YONSEI', 'UNIVERSITY'],\n",
" ['LINYI', 'UNIVERSITY'],\n",
" ['IMT', 'ATLANTIQUE'],\n",
" ['CHIBA', 'UNIVERSITY'],\n",
" ['DOSHISHA', 'UNIVERSITY'],\n",
" ['YANAN', 'UNIVERSITY'],\n",
" ['CENTRALE', 'LILLE'],\n",
" ['JINAN', 'UNIVERSITY'],\n",
" ['MONASH', 'UNIVERSITY'],\n",
" ['YUNNAN', 'UNIVERSITY'],\n",
" ['HENAN', 'UNIVERSITY'],\n",
" ['XIDIAN', 'UNIVERSITY'],\n",
" ['MIDDLESEX', 'UNIVERSITY'],\n",
" ['GEOSCIENCE', 'AUSTRALIA'],\n",
" ['YANSHAN', 'UNIVERSITY'],\n",
" ['OITA', 'UNIVERSITY'],\n",
" ['IBARAKI', 'UNIVERSITY'],\n",
" ['LEIDEN', 'UNIVERSITY'],\n",
" ['MITRE', 'CORPORATION'],\n",
" ['GOOGLE', 'INCORPORATED'],\n",
" ['SHENZHEN', 'UNIVERSITY'],\n",
" ['UNIVERSITY', 'BALAMAND'],\n",
" ['JANSSEN', 'PHARMACEUTICALS'],\n",
" ['LIVERPOOL', 'HOSPITAL'],\n",
" ['IRCCS', 'FATEBENEFRATELLI'],\n",
" ['OCHANOMIZU', 'UNIVERSITY'],\n",
" ['UNIVERSITI', 'MALAYA'],\n",
" ['FUZHOU', 'UNIVERSITY'],\n",
" ['MARMARA', 'UNIVERSITY'],\n",
" ['STELLENBOSCH', 'UNIVERSITY'],\n",
" ['TIANJIN', 'UNIVERSITY'],\n",
" ['SHANXI', 'UNIVERSITY'],\n",
" ['PHILIPS', 'RESEARCH'],\n",
" ['GUANGZHOU', 'UNIVERSITY'],\n",
" ['NINGBO', 'UNIVERSITY'],\n",
" ['HOSEI', 'UNIVERSITY'],\n",
" ['SUWON', 'UNIVERSITY'],\n",
" ['HUAWEI', 'TECHNOLOGIES'],\n",
" ['INSTITUT', 'AGRO'],\n",
" ['MONTPELLIER', 'SUPAGRO'],\n",
" ['UNIVERSITE', 'PAUL-VALERY'],\n",
" ['HOKKAIDO', 'UNIVERSITY'],\n",
" ['FAHRENHEIT', 'UNIVERSITIES'],\n",
" ['NANTES', 'UNIVERSITE'],\n",
" ['XIANGTAN', 'UNIVERSITY'],\n",
" ['NOKIA', 'CORPORATION'],\n",
" ['NOKIA', 'FINLAND'],\n",
" ['INESC', 'TEC'],\n",
" ['FRAUNHOFER', 'GESELLSCHAFT'],\n",
" ['ZHENGZHOU', 'UNIVERSITY'],\n",
" ['AARHUS', 'UNIVERSITY'],\n",
" ['JACOBS', 'UNIVERSITY'],\n",
" ['MAYNOOTH', 'UNIVERSITY'],\n",
" ['CARDIFF', 'UNIVERSITY'],\n",
" ['DREXEL', 'UNIVERSITY'],\n",
" ['DONGHUA', 'UNIVERSITY'],\n",
" ['PICARDIE', 'UNIVERSITES'],\n",
" ['ATHABASCA', 'UNIVERSITY'],\n",
" ['NANKAI', 'UNIVERSITY'],\n",
" ['MINIA', 'UNIVERSITY'],\n",
" ['HOSPITAL', 'VALME'],\n",
" ['LEIPZIG', 'UNIVERSITY'],\n",
" ['KIRBY', 'INSTITUTE'],\n",
" ['NEPEAN', 'HOSPITAL'],\n",
" ['TAIF', 'UNIVERSITY'],\n",
" ['LAURENTIAN', 'UNIVERSITY'],\n",
" ['SICHUAN', 'UNIVERSITY'],\n",
" ['IE', 'UNIVERSITY'],\n",
" ['SMITHSONIAN', 'INSTITUTION'],\n",
" ['CRANFIELD', 'UNIVERSITY'],\n",
" ['GUANGXI', 'UNIVERSITY'],\n",
" ['THIRUVALLUVAR', 'UNIVERSITY'],\n",
" ['ALAGAPPA', 'UNIVERSITY'],\n",
" ['MID-SWEDEN', 'UNIVERSITY'],\n",
" ['MAASTRICHT', 'UNIVERSITY'],\n",
" ['BMW', 'AG'],\n",
" ['RUSH', 'UNIVERSITY'],\n",
" ['BROAD', 'INSTITUTE'],\n",
" ['DAEGU', 'UNIVERSITY'],\n",
" ['KAROLINSKA', 'INSTITUTET'],\n",
" ['DEAKIN', 'UNIVERSITY'],\n",
" ['ULM', 'UNIVERSITY'],\n",
" ['OAKLAND', 'UNIVERSITY'],\n",
" ['INSTITUTO', 'BUTANTAN'],\n",
" ['UNIVERSITE', 'GUSTAVE-EIFFEL'],\n",
" ['BOURNEMOUTH', 'UNIVERSITY'],\n",
" ['BRISTOL-MYERS', 'SQUIBB'],\n",
" ['XIAMEN', 'UNIVERSITY'],\n",
" ['UNIVERSITE', \"D'ARTOIS\"],\n",
" ['DALARNA', 'UNIVERSITY'],\n",
" ['BOEHRINGER', 'INGELHEIM'],\n",
" ['UTRECHT', 'UNIVERSITY'],\n",
" ['BAYER', 'AG'],\n",
" ['ROCHE', 'HOLDING'],\n",
" ['JAHANGIRNAGAR', 'UNIVERSITY'],\n",
" ['ANHUI', 'UNIVERSITY'],\n",
" ['PHILIPS', 'HEALTHCARE'],\n",
" ['QATAR', 'UNIVERSITY'],\n",
" ['TBS', 'EDUCATION'],\n",
" ['EMORY', 'UNIVERSITY'],\n",
" ['BAUHAUS-UNIVERSITAT', 'WEIMAR'],\n",
" ['LINKOPING', 'UNIVERSITY'],\n",
" ['HONGHE', 'UNIVERSITY'],\n",
" ['MAYO', 'CLINIC'],\n",
" ['SANMING', 'UNIVERSITY'],\n",
" ['SUNGKYUL', 'UNIVERSITY'],\n",
" ['INTEL', 'CORPORATION'],\n",
" ['TANTA', 'UNIVERSITY'],\n",
" ['UNIVERSITY', 'RUHUNA'],\n",
" ['HACETTEPE', 'UNIVERSITY'],\n",
" ['MACQUARIE', 'UNIVERSITY'],\n",
" ['SWANSEA', 'UNIVERSITY'],\n",
" ['BAHCESEHIR', 'UNIVERSITY'],\n",
" ['DURHAM', 'UNIVERSITY'],\n",
" ['SHANTOU', 'UNIVERSITY'],\n",
" ['BHARATHIAR', 'UNIVERSITY'],\n",
" ['UNIVERSITE', 'BORDEAUX-MONTAIGNE'],\n",
" ['TATA', 'SONS'],\n",
" ['HALMSTAD', 'UNIVERSITY'],\n",
" ['CHU', 'STRASBOURG'],\n",
" ['KANAZAWA', 'UNIVERSITY'],\n",
" ['CHU', 'BREST'],\n",
" ['HOSPITAL', 'ALEMAN'],\n",
" ['SALZBURG', 'UNIVERSITY'],\n",
" ['KARLSTAD', 'UNIVERSITY'],\n",
" ['COVENTRY', 'UNIVERSITY'],\n",
" ['HESAM', 'UNIVERSITE'],\n",
" ['MALARDALEN', 'UNIVERSITY'],\n",
" ['GILEAD', 'SCIENCES'],\n",
" ['LOUGHBOROUGH', 'UNIVERSITY'],\n",
" ['NAGASAKI', 'UNIVERSITY'],\n",
" ['XIHUA', 'UNIVERSITY'],\n",
" ['NYU', 'SHANGHAI'],\n",
" ['GUIZHOU', 'UNIVERSITY'],\n",
" ['CURTIN', 'UNIVERSITY'],\n",
" ['YANGZHOU', 'UNIVERSITY'],\n",
" ['TEMPLE', 'UNIVERSITY'],\n",
" ['SAARLAND', 'UNIVERSITY'],\n",
" ['PENNSYLVANIA', 'MEDICINE'],\n",
" ['LELOIR', 'INSTITUTE'],\n",
" ['DARTMOUTH', 'COLLEGE'],\n",
" ['NESTLE', 'SA'],\n",
" ['AMHERST', 'COLLEGE'],\n",
" ['BEIJING', 'HOSPITAL'],\n",
" ['MIE', 'UNIVERSITY'],\n",
" ['HEFEI', 'UNIVERSITY'],\n",
" ['QINGDAO', 'UNIVERSITY'],\n",
" ['BOSE', 'INSTITUTE'],\n",
" ['SEJONG', 'UNIVERSITY'],\n",
" ['GAUHATI', 'UNIVERSITY'],\n",
" ['INHA', 'UNIVERSITY'],\n",
" ['KONKUK', 'UNIVERSITY'],\n",
" ['CREIGHTON', 'UNIVERSITY'],\n",
" ['EFFAT', 'UNIVERSITY'],\n",
" ['FACEBOOK', 'INC'],\n",
" ['UNIVERSITE', 'PARIS-DAUPHINE'],\n",
" ['TEIKYO', 'UNIVERSITY'],\n",
" ['KONYANG', 'UNIVERSITY'],\n",
" ['KEIO', 'UNIVERSITY'],\n",
" ['PLOVDIV', 'UNIVERSITY'],\n",
" [\"CHANG'AN\", 'UNIVERSITY'],\n",
" ['BANGOR', 'UNIVERSITY'],\n",
" ['HUAQIAO', 'UNIVERSITY'],\n",
" ['NANCHANG', 'UNIVERSITY'],\n",
" ['PACE', 'UNIVERSITY'],\n",
" ['BINZHOU', 'UNIVERSITY'],\n",
" ['UMEA', 'UNIVERSITY'],\n",
" ['MINES', 'PARISTECH'],\n",
" ['LINGNAN', 'UNIVERSITY'],\n",
" ['GEORGETOWN', 'UNIVERSITY'],\n",
" ['MALMO', 'UNIVERSITY'],\n",
" ['VATICAN', 'OBSERVATORY'],\n",
" ['OHIO', 'UNIVERSITY'],\n",
" ['HAVERFORD', 'COLLEGE'],\n",
" ['XUCHANG', 'UNIVERSITY'],\n",
" ['YAMAGUCHI', 'UNIVERSITY'],\n",
" ['ALEXANDRIA', 'UNIVERSITY'],\n",
" ['GIRESUN', 'UNIVERSITY'],\n",
" ['HUAFAN', 'UNIVERSITY'],\n",
" ['ERASMUS', 'MC'],\n",
" ['YEUNGNAM', 'UNIVERSITY'],\n",
" ['UNIVERSIDADE', 'FORTALEZA'],\n",
" ['ITMO', 'UNIVERSITY'],\n",
" ['ALIBABA', 'GROUP'],\n",
" ['TINBERGEN', 'INSTITUTE'],\n",
" ['AUBURN', 'UNIVERSITY'],\n",
" ['DALHOUSIE', 'UNIVERSITY'],\n",
" ['KOGAKUIN', 'UNIVERSITY'],\n",
" ['NANTONG', 'UNIVERSITY'],\n",
" ['GENERAL', 'ELECTRIC'],\n",
" ['INNOPOLIS', 'UNIVERSITY'],\n",
" ['SUEZ', 'UNIVERSITY'],\n",
" ['SHOOLINI', 'UNIVERSITY'],\n",
" ['BEYKENT', 'UNIVERSITY'],\n",
" ['BINGOL', 'UNIVERSITY'],\n",
" ['SINOP', 'UNIVERSITY'],\n",
" ['VICTORIA', 'UNIVERSITY'],\n",
" ['BOHAI', 'UNIVERSITY'],\n",
" ['AGROCAMPUS', 'OUEST'],\n",
" ['CHU', 'RENNES'],\n",
" ['CHU', 'LYON'],\n",
" ['CHU', 'LILLE'],\n",
" ['SHANGHAITECH', 'UNIVERSITY'],\n",
" ['LINNAEUS', 'UNIVERSITY'],\n",
" ['VIT', 'VELLORE'],\n",
" ['KARNATAK', 'UNIVERSITY'],\n",
" ['NEC', 'CORPORATION'],\n",
" ['SHAOXING', 'UNIVERSITY'],\n",
" ['ISTANBUL', 'UNIVERSITY'],\n",
" ['CHOSUN', 'UNIVERSITY'],\n",
" ['TUNGHAI', 'UNIVERSITY'],\n",
" ['THUYLOI', 'UNIVERSITY'],\n",
" ['ATTITUS', 'EDUCACAO'],\n",
" ['LIAONING', 'UNIVERSITY'],\n",
" ['FUJITSU', 'LTD'],\n",
" ['FOSHAN', 'UNIVERSITY'],\n",
" ['MONMOUTH', 'UNIVERSITY'],\n",
" ['GUSTAVE', 'ROUSSY'],\n",
" ['ROTHAMSTED', 'RESEARCH'],\n",
" ['WUYI', 'UNIVERSITY'],\n",
" ['JEFFERSON', 'UNIVERSITY'],\n",
" ['HUBEI', 'UNIVERSITY'],\n",
" ['SIEMENS', 'AG'],\n",
" ['UNIVERSITY', 'MORATUWA'],\n",
" ['UNIVERSIDADE', 'PAULISTA'],\n",
" ['GACHON', 'UNIVERSITY'],\n",
" ['LEHIGH', 'UNIVERSITY'],\n",
" ['VALPARAISO', 'UNIVERSITY'],\n",
" ['RIJNSTATE', 'HOSPITAL'],\n",
" ['CANISIUS-WILHELMINA', 'HOSPITAL'],\n",
" ['BROCK', 'UNIVERSITY'],\n",
" ['SIEMENS', 'GERMANY'],\n",
" ['UNIVERSITAT', 'KASSEL'],\n",
" ['HIROSAKI', 'UNIVERSITY'],\n",
" ['WEIFANG', 'UNIVERSITY'],\n",
" ['XINJIANG', 'UNIVERSITY'],\n",
" ['TOSHIBA', 'CORPORATION'],\n",
" ['SAKARYA', 'UNIVERSITY'],\n",
" ['SHAHREKORD', 'UNIVERSITY'],\n",
" ['RHODES', 'UNIVERSITY'],\n",
" ['LUSOFONA', 'UNIVERSITY'],\n",
" ['TAIZ', 'UNIVERSITY'],\n",
" ['JIUJIANG', 'UNIVERSITY'],\n",
" ['SHENZHEN', 'POLYTECHNIC'],\n",
" ['KLINIKUM', 'BAYREUTH'],\n",
" ['NVIDIA', 'CORPORATION'],\n",
" ['SECTRA', 'AB'],\n",
" ['ORANGE', 'SA'],\n",
" ['ASWAN', 'UNIVERSITY'],\n",
" ['CHINA', 'MOBILE'],\n",
" ['SHAOGUAN', 'UNIVERSITY'],\n",
" ['MEIJO', 'UNIVERSITY'],\n",
" ['MINJIANG', 'UNIVERSITY'],\n",
" ['ZHEJIANG', 'LABORATORY'],\n",
" ['ENSTA', 'BRETAGNE'],\n",
" ['INSTITUT', 'CURIE'],\n",
" ['DEPAUL', 'UNIVERSITY'],\n",
" ['TOWSON', 'UNIVERSITY'],\n",
" ['ESIEE', 'PARIS'],\n",
" [\"L'OREAL\", 'GROUP'],\n",
" ['SOONCHUNHYANG', 'UNIVERSITY'],\n",
" ['TIANGONG', 'UNIVERSITY'],\n",
" ['LORESTAN', 'UNIVERSITY'],\n",
" ['CLARK', 'UNIVERSITY'],\n",
" ['MARQUETTE', 'UNIVERSITY'],\n",
" ['FORSCHUNGSZENTRUM', 'BORSTEL'],\n",
" ['CATHARINA', 'HOSPITAL'],\n",
" ['ROSKILDE', 'UNIVERSITY'],\n",
" ['SWERIM', 'AB'],\n",
" ['ZAGAZIG', 'UNIVERSITY'],\n",
" ['CHUZHOU', 'UNIVERSITY'],\n",
" ['SHIHEZI', 'UNIVERSITY'],\n",
" ['UNIVERSITY', 'KASHAN'],\n",
" ['SHENYANG', 'UNIVERSITY'],\n",
" ['YULIN', 'UNIVERSITY'],\n",
" ['HAREFIELD', 'HOSPITAL'],\n",
" ['UNIVERSIDADE', 'ABERTA'],\n",
" ['SKIDMORE', 'COLLEGE'],\n",
" ['LOCKHEED', 'MARTIN'],\n",
" ['LINCOLN', 'LABORATORY'],\n",
" ['CLAREMONT', 'COLLEGES'],\n",
" ['POMONA', 'COLLEGE'],\n",
" ['BARTIN', 'UNIVERSITY'],\n",
" ['LAVAL', 'UNIVERSITY'],\n",
" ['HOFSTRA', 'UNIVERSITY'],\n",
" ['POLYTECHNIQUE', 'MONTREAL'],\n",
" ['WESTLAKE', 'UNIVERSITY'],\n",
" ['UNIVERSIDAD', 'VERACRUZANA'],\n",
" ['AGROSUP', 'DIJON'],\n",
" ['URMIA', 'UNIVERSITY'],\n",
" ['NAZARBAYEV', 'UNIVERSITY'],\n",
" ['UNIVERSITE', \"D'ANGERS\"],\n",
" ['LAMAR', 'UNIVERSITY'],\n",
" ['MCLEAN', 'HOSPITAL'],\n",
" ['HUMANITAS', 'UNIVERSITY'],\n",
" ['ISTINYE', 'UNIVERSITY'],\n",
" ['MRC', 'HARWELL'],\n",
" ['TRIBHUVAN', 'UNIVERSITY'],\n",
" ['DALIAN', 'UNIVERSITY'],\n",
" ['HOPITAL', \"D'ENFANTS\"],\n",
" ['AKDENIZ', 'UNIVERSITY'],\n",
" ['NITEC', 'UNIVERSITY'],\n",
" ['NEWYORK-PRESBYTERIAN', 'HOSPITAL'],\n",
" ['MENOFIA', 'UNIVERSITY'],\n",
" ['AVIGNON', 'UNIVERSITE'],\n",
" ['KAISER', 'PERMANENTE'],\n",
" ['VINH', 'UNIVERSITY'],\n",
" ['FORDHAM', 'UNIVERSITY'],\n",
" ['CLEMSON', 'UNIVERSITY'],\n",
" ['NILE', 'UNIVERSITY'],\n",
" ['DIAKONHJEMMET', 'HOSPITAL'],\n",
" ['SHIZUOKA', 'UNIVERSITY'],\n",
" ['SAMSUNG', 'ELECTRONICS'],\n",
" ['MICRON', 'TECHNOLOGY'],\n",
" ['TU', 'CLAUSTHAL'],\n",
" ['DAMIETTA', 'UNIVERSITY'],\n",
" ['REYKJAVIK', 'UNIVERSITY'],\n",
" ['FPT', 'UNIVERSITY'],\n",
" ['HARTFORD', 'HOSPITAL'],\n",
" ['CENTRE', 'MURAZ'],\n",
" ['UNIVERSITAT', \"D'ALACANT\"],\n",
" ['KHULNA', 'UNIVERSITY'],\n",
" ['OREBRO', 'UNIVERSITY'],\n",
" ['MAHIDOL', 'UNIVERSITY'],\n",
" ['CHU', 'BORDEAUX'],\n",
" [\"ADDENBROOKE'S\", 'HOSPITAL'],\n",
" ['APPLE', 'INC'],\n",
" ['AGILENT', 'TECHNOLOGIES'],\n",
" ['JADAVPUR', 'UNIVERSITY'],\n",
" ['WALTON', 'CENTRE'],\n",
" ['ZAYED', 'UNIVERSITY'],\n",
" ['QASSIM', 'UNIVERSITY'],\n",
" ['MAJMAAH', 'UNIVERSITY'],\n",
" ['MEKELLE', 'UNIVERSITY'],\n",
" ['BRANDON', 'UNIVERSITY'],\n",
" ['CHENGDU', 'UNIVERSITY'],\n",
" ['EHIME', 'UNIVERSITY'],\n",
" ['AZERBAIJAN', 'UNIVERSITY'],\n",
" ['SONY', 'CORPORATION'],\n",
" ['MASSEY', 'UNIVERSITY'],\n",
" ['JACKSONVILLE', 'UNIVERSITY'],\n",
" ['SIRNAK', 'UNIVERSITY'],\n",
" ['KOCHI', 'UNIVERSITY'],\n",
" [\"TAYLOR'S\", 'UNIVERSITY'],\n",
" ['EARLHAM', 'INSTITUTE'],\n",
" ['ABERYSTWYTH', 'UNIVERSITY'],\n",
" ['WENZHOU', 'UNIVERSITY'],\n",
" ['SUNY', 'OPTOMETRY'],\n",
" ['MULTIMEDIA', 'UNIVERSITY'],\n",
" ['UNIVERSITA', 'LUMSA'],\n",
" ['JONKOPING', 'UNIVERSITY'],\n",
" ['ACIBADEM', 'UNIVERSITY'],\n",
" ['TRINA', 'SOLAR'],\n",
" ['SOLVAY', 'SA'],\n",
" ['CHANGSHA', 'UNIVERSITY'],\n",
" ['ACREO', 'AB'],\n",
" ['TALLINN', 'UNIVERSITY'],\n",
" ['KOZMINSKI', 'UNIVERSITY'],\n",
" ['STAFFORDSHIRE', 'UNIVERSITY'],\n",
" ['HARRAN', 'UNIVERSITY'],\n",
" ['ITHEMBA', 'LABS'],\n",
" ['TOTTORI', 'UNIVERSITY'],\n",
" ['UNIVERSITE', 'PARIS-VIII'],\n",
" ['SHOWA', 'UNIVERSITY'],\n",
" ['TOKAI', 'UNIVERSITY'],\n",
" ['ASML', 'HOLDING'],\n",
" ['COLGATE', 'UNIVERSITY'],\n",
" ['PAZHOU', 'LAB'],\n",
" ['JIMEI', 'UNIVERSITY'],\n",
" ['ROEHAMPTON', 'UNIVERSITY'],\n",
" ['KINGSTON', 'UNIVERSITY'],\n",
" ['HUZHOU', 'UNIVERSITY'],\n",
" ['COPPERBELT', 'UNIVERSITY'],\n",
" ['UNIVERSIDAD', 'ICESI'],\n",
" ['SEGI', 'UNIVERSITY'],\n",
" ['MAHSA', 'UNIVERSITY'],\n",
" ['SZEGED', 'UNIVERSITY'],\n",
" ['WENZHOU-KEAN', 'UNIVERSITY'],\n",
" ['IRCCS', 'NEUROMED'],\n",
" ['IUSS', 'PAVIA'],\n",
" ['MINES', 'SAINT-ETIENNE'],\n",
" ['BENGBU', 'UNIVERSITY'],\n",
" ['CHANGZHI', 'UNIVERSITY'],\n",
" ['LAKEHEAD', 'UNIVERSITY'],\n",
" ['MANSOURA', 'UNIVERSITY'],\n",
" ['AL-MUTHANNA', 'UNIVERSITY'],\n",
" ['WAKAYAMA', 'UNIVERSITY'],\n",
" ['HUAIHUA', 'UNIVERSITY'],\n",
" ['NAJRAN', 'UNIVERSITY'],\n",
" ['RAYTHEON', 'TECHNOLOGIES'],\n",
" ['SANJIANG', 'UNIVERSITY'],\n",
" ['WSB', 'UNIVERSITY'],\n",
" ['YANGTZE', 'UNIVERSITY'],\n",
" ['KEIMYUNG', 'UNIVERSITY'],\n",
" ['VODAFONE', 'GROUP'],\n",
" ['CARLETON', 'COLLEGE'],\n",
" ['TOPCON', 'CORPORATION'],\n",
" ['NINGXIA', 'UNIVERSITY'],\n",
" ['PARUL', 'UNIVERSITY'],\n",
" ['CIC', 'ENERGIGUNE'],\n",
" ['BIRZEIT', 'UNIVERSITY'],\n",
" ['YESHIVA', 'UNIVERSITY'],\n",
" ['DUQUESNE', 'UNIVERSITY'],\n",
" ['RIKKYO', 'UNIVERSITY'],\n",
" ['SEMNAN', 'UNIVERSITY'],\n",
" ['TAIBAH', 'UNIVERSITY'],\n",
" ['HAZARA', 'UNIVERSITY'],\n",
" ['CANKAYA', 'UNIVERSITY'],\n",
" ['BAYER', 'CROPSCIENCE'],\n",
" ['AHMEDABAD', 'UNIVERSITY'],\n",
" ['MURDOCH', 'UNIVERSITY'],\n",
" ['BOCCONI', 'UNIVERSITY'],\n",
" ['JAZAN', 'UNIVERSITY'],\n",
" ['ULVAC', 'INC.'],\n",
" ['ULVAC-PHI', 'INCORPORATED'],\n",
" ['AGC', 'INC'],\n",
" ['SEIKEI', 'UNIVERSITY'],\n",
" ['CANON', 'INCORPORATED'],\n",
" ['KAO', 'CORPORATION'],\n",
" ['CHAPMAN', 'UNIVERSITY'],\n",
" ['ANNA', 'UNIVERSITY'],\n",
" ['CHANGZHOU', 'UNIVERSITY'],\n",
" ['FUNDACIO', 'PUIGVERT'],\n",
" ['KOC', 'UNIVERSITY'],\n",
" ['FUNDACAO', 'CHAMPALIMAUD'],\n",
" ['JIKEI', 'UNIVERSITY'],\n",
" ['METEO', 'FRANCE'],\n",
" ['SEMMELWEIS', 'UNIVERSITY'],\n",
" ['CENTENARY', 'INSTITUTE'],\n",
" ['ESSILOR', 'INTERNATIONAL'],\n",
" ['TELKOM', 'UNIVERSITY'],\n",
" ['JINING', 'UNIVERSITY'],\n",
" ['UNIVERSITAT', 'TRIER'],\n",
" ['KYONGGI', 'UNIVERSITY'],\n",
" ['LONGYAN', 'UNIVERSITY'],\n",
" ['CHU', 'POITIERS'],\n",
" ['PAPAGEORGIOU', 'HOSPITAL'],\n",
" ['THALES', 'GROUP'],\n",
" ['WILHELMINA', 'KINDERZIEKENHUIS'],\n",
" ['BENHA', 'UNIVERSITY'],\n",
" ['GENERAL', 'MOTORS'],\n",
" ['TAIZHOU', 'UNIVERSITY'],\n",
" ['YIBIN', 'UNIVERSITY'],\n",
" ['DAIMLER', 'AG'],\n",
" ['HEILONGJIANG', 'UNIVERSITY'],\n",
" ['KASETSART', 'UNIVERSITY'],\n",
" ['EVANGELISMOS', 'HOSPITAL'],\n",
" ['UNIVERSITAS', 'MULAWARMAN'],\n",
" ['TELECOM', 'ITALIA'],\n",
" ['GRIFFITH', 'UNIVERSITY'],\n",
" ['CHIMIE', 'PARISTECH'],\n",
" ['DAMANHOUR', 'UNIVERSITY'],\n",
" ['KARABUK', 'UNIVERSITY'],\n",
" ['ASTON', 'UNIVERSITY'],\n",
" ['AIRLANGGA', 'UNIVERSITY'],\n",
" ['AJMAN', 'UNIVERSITY'],\n",
" ['AERODYNE', 'RESEARCH'],\n",
" ['BIRUNI', 'UNIVERSITY'],\n",
" ['SELCUK', 'UNIVERSITY'],\n",
" ['CHU', 'REUNION'],\n",
" ['ASSIUT', 'UNIVERSITY'],\n",
" ['INONU', 'UNIVERSITY'],\n",
" ['UNIVERSITAS', 'PADJADJARAN'],\n",
" ['SHIGA', 'UNIVERSITY'],\n",
" ['KITASATO', 'UNIVERSITY'],\n",
" ['LISTER', 'HOSPITAL'],\n",
" ['RAZI', 'UNIVERSITY'],\n",
" ['MIMOS', 'BERHAD'],\n",
" ['CHANDIGARH', 'UNIVERSITY'],\n",
" ['CAMPBELL', 'UNIVERSITY'],\n",
" ['INSTITUT', 'BERGONIE'],\n",
" ['AUTODESK', 'INC.'],\n",
" ['DUZCE', 'UNIVERSITY'],\n",
" ['TWITTER', 'INC.'],\n",
" ['JULIUS', 'KUHN-INSTITUT'],\n",
" ['HUIZHOU', 'UNIVERSITY'],\n",
" ['WENZHOU', 'POLYTECHNIC'],\n",
" ['DIBRUGARH', 'UNIVERSITY'],\n",
" ['DEUTSCHE', 'BAHN'],\n",
" ['TERI', 'UNIVERSITY'],\n",
" ['TRAKYA', 'UNIVERSITY'],\n",
" ['SANGMYUNG', 'UNIVERSITY'],\n",
" ['COVENANT', 'UNIVERSITY'],\n",
" ['ATILIM', 'UNIVERSITY'],\n",
" ['ILAM', 'UNIVERSITY'],\n",
" ['UNIVERSITY', 'ZANJAN'],\n",
" ['SRI', 'INTERNATIONAL'],\n",
" [\"XI'AN\", 'UNIVERSITY'],\n",
" ['YASOUJ', 'UNIVERSITY'],\n",
" ['HUANGHUAI', 'UNIVERSITY'],\n",
" ['MIAMI', 'UNIVERSITY'],\n",
" ['SHARDA', 'UNIVERSITY'],\n",
" ['WILLAMETTE', 'UNIVERSITY'],\n",
" ['IQRA', 'UNIVERSITY'],\n",
" ['HOWARD', 'UNIVERSITY'],\n",
" ['KETTERING', 'UNIVERSITY'],\n",
" ['SYNOPSYS', 'INC'],\n",
" ['BOZOK', 'UNIVERSITY'],\n",
" ['ERCIYES', 'UNIVERSITY'],\n",
" ['PUNJABI', 'UNIVERSITY'],\n",
" ['PIUS-HOSPITAL', 'OLDENBURG'],\n",
" ['NORTHWELL', 'HEALTH'],\n",
" ['BARNES-JEWISH', 'HOSPITAL'],\n",
" ['NIRMA', 'UNIVERSITY'],\n",
" ['SUNWAY', 'UNIVERSITY'],\n",
" ['INJE', 'UNIVERSITY'],\n",
" ['LIAOCHENG', 'UNIVERSITY'],\n",
" ['YEDITEPE', 'UNIVERSITY'],\n",
" ['SRINAKHARINWIROT', 'UNIVERSITY'],\n",
" ['WOLLONGONG', 'HOSPITAL'],\n",
" ['BISPEBJERG', 'HOSPITAL'],\n",
" ['CHU', 'AMIENS'],\n",
" ['CHU', 'BESANCON'],\n",
" ['CHU', 'LIMOGES'],\n",
" ['HELIOS', 'KLINIKEN'],\n",
" ['ARCISPEDALE', \"SANT'ANNA\"],\n",
" [\"SANT'EUGENIO\", 'HOSPITAL'],\n",
" ['GELRE', 'HOSPITALS'],\n",
" ['SPAARNE', 'HOSPITAL'],\n",
" ['TYGERBERG', 'HOSPITAL'],\n",
" ['BASURTO', 'HOSPITAL'],\n",
" ['GALDAKAO', 'HOSPITAL'],\n",
" ['DANDERYDS', 'HOSPITAL'],\n",
" ['KOCAELI', 'UNIVERSITY'],\n",
" ['DUBAI', 'HOSPITAL'],\n",
" ['SOUTHMEAD', 'HOSPITAL'],\n",
" ['PAPWORTH', 'HOSPITAL'],\n",
" ['IPSWICH', 'HOSPITAL'],\n",
" ['GLENFIELD', 'HOSPITAL'],\n",
" ['WYTHENSHAWE', 'HOSPITAL'],\n",
" ['KEELE', 'UNIVERSITY'],\n",
" ['DERRIFORD', 'HOSPITAL'],\n",
" ['POOLE', 'HOSPITAL'],\n",
" ['MORRISTON', 'HOSPITAL'],\n",
" ['PINDERFIELDS', 'HOSPITAL'],\n",
" ['ADVENTHEALTH', 'ORLANDO'],\n",
" ['LG', 'ELECTRONICS'],\n",
" ['EUREKA', 'SCIENTIFIC'],\n",
" ['KRISTIANSTAD', 'UNIVERSITY'],\n",
" ['ZHAOTONG', 'UNIVERSITY'],\n",
" ['JIAXING', 'UNIVERSITY'],\n",
" ['BOND', 'UNIVERSITY'],\n",
" ['JIANGHAN', 'UNIVERSITY'],\n",
" ['HALLYM', 'UNIVERSITY'],\n",
" ['UTKAL', 'UNIVERSITY'],\n",
" ['UTSUNOMIYA', 'UNIVERSITY'],\n",
" ['KUWAIT', 'UNIVERSITY'],\n",
" ['MAEJO', 'UNIVERSITY'],\n",
" ['ATATURK', 'UNIVERSITY'],\n",
" ['JISHOU', 'UNIVERSITY'],\n",
" ['UNIVERSITY', \"HA'IL\"],\n",
" ['FIRAT', 'UNIVERSITY'],\n",
" ['ISLAMIC', 'UNIVERSITY'],\n",
" ['GUANGZHOU', 'LABORATORY'],\n",
" ['CHU', 'NICE'],\n",
" ['BABSON', 'COLLEGE'],\n",
" ['YARMOUK', 'UNIVERSITY'],\n",
" ['REICHMAN', 'UNIVERSITY'],\n",
" ['CONSERVATION', 'INTERNATIONAL'],\n",
" ['JUNTENDO', 'UNIVERSITY'],\n",
" ['ANKANG', 'UNIVERSITY'],\n",
" ['AL-MAARIF', 'UNIVERSITY'],\n",
" ['TECH-X', 'CORPORATION'],\n",
" ['LEBANESE', 'UNIVERSITY'],\n",
" ['EDINBORO', 'UNIVERSITY'],\n",
" ['TAIYUAN', 'UNIVERSITY'],\n",
" ['VIT', 'CHENNAI'],\n",
" ['ALMAAREFA', 'UNIVERSITY'],\n",
" ['NIHON', 'UNIVERSITY'],\n",
" ['TULANE', 'UNIVERSITY'],\n",
" ['SABANCI', 'UNIVERSITY'],\n",
" ['THAMMASAT', 'UNIVERSITY'],\n",
" ['UNIVERSITAS', 'UDAYANA'],\n",
" ['XIJING', 'UNIVERSITY'],\n",
" ['NORDIC', 'BIOSCIENCE'],\n",
" ['LUDONG', 'UNIVERSITY'],\n",
" ['JINGGANGSHAN', 'UNIVERSITY'],\n",
" ['BIOTALENTUM', 'LTD'],\n",
" ['ACADIA', 'UNIVERSITY'],\n",
" ['HOCHSCHULE', 'BOCHUM'],\n",
" ['WUXI', 'UNIVERSITY'],\n",
" ['TOYO', 'UNIVERSITY'],\n",
" ['CHEMNITZ', 'CLINIC'],\n",
" ['GALALA', 'UNIVERSITY'],\n",
" ['CRRC', 'CORPORATION'],\n",
" ['ANADOLU', 'UNIVERSITY'],\n",
" ['FUKUOKA', 'UNIVERSITY'],\n",
" ['PETROCHINA', 'COMPANY'],\n",
" ['NINGXIA', 'POLYTECHNIC'],\n",
" ['KHARAZMI', 'UNIVERSITY'],\n",
" ['XIANGNAN', 'UNIVERSITY'],\n",
" ['AL-AQSA', 'UNIVERSITY'],\n",
" ['WASIT', 'UNIVERSITY'],\n",
" ['REED', 'ELSEVIER'],\n",
" ['HELSINGBORGS', 'HOSPITAL'],\n",
" ['BRAC', 'UNIVERSITY'],\n",
" ['VETAGRO', 'SUP'],\n",
" ['DEZHOU', 'UNIVERSITY'],\n",
" ['RAFFLES', 'HOSPITAL'],\n",
" ['TARIM', 'UNIVERSITY'],\n",
" ['OBERLIN', 'COLLEGE'],\n",
" ['JACKSON', 'LABORATORY'],\n",
" ['DAYSTAR', 'UNIVERSITY'],\n",
" ['SAIGON', 'UNIVERSITY'],\n",
" ['UTTARANCHAL', 'UNIVERSITY'],\n",
" ['UNIVERSITY', 'ANTANANARIVO'],\n",
" ['IWATE', 'UNIVERSITY'],\n",
" ['LUCKNOW', 'UNIVERSITY'],\n",
" ['OCCIDENTAL', 'COLLEGE'],\n",
" ['WELLESLEY', 'COLLEGE'],\n",
" ['HEXI', 'UNIVERSITY'],\n",
" ['SOFTWAREPARK', 'HAGENBERG'],\n",
" ['NOVO', 'NORDISK'],\n",
" ['TOTAL', 'SA'],\n",
" ['RAJAVITHI', 'HOSPITAL'],\n",
" ['RANGSIT', 'UNIVERSITY'],\n",
" ['KAGOSHIMA', 'UNIVERSITY'],\n",
" ['AL-NAHRAIN', 'UNIVERSITY'],\n",
" ['UNIVERSITE', 'CONSTANTINE'],\n",
" ['DAVIDSON', 'COLLEGE'],\n",
" ['VILLANOVA', 'UNIVERSITY'],\n",
" ['CIHAN', 'UNIVERSITY-ERBIL'],\n",
" ['QIQIHAR', 'UNIVERSITY'],\n",
" ['KYUNGNAM', 'UNIVERSITY'],\n",
" ['SOPHIA', 'UNIVERSITY'],\n",
" ['EIJKMAN', 'INSTITUTE'],\n",
" ['JIMMA', 'UNIVERSITY'],\n",
" ['GLYNDWR', 'UNIVERSITY'],\n",
" ['IFO', 'INSTITUT'],\n",
" ['HECHI', 'UNIVERSITY'],\n",
" ['DHOFAR', 'UNIVERSITY'],\n",
" ['SOHAG', 'UNIVERSITY'],\n",
" ['METROHEALTH', 'SYSTEM'],\n",
" ['DIPONEGORO', 'UNIVERSITY'],\n",
" ['ZARQA', 'UNIVERSITY'],\n",
" ['SOGANG', 'UNIVERSITY'],\n",
" ['SAITAMA', 'UNIVERSITY'],\n",
" ['CUMHURIYET', 'UNIVERSITY'],\n",
" ['UNIVERSITY', 'OF', 'LUBECK'],\n",
" ['CAPITAL', 'MEDICAL', 'UNIVERSITY'],\n",
" ['UNIVERSITY', 'OF', 'LONDON'],\n",
" ['BIRKBECK', 'UNIVERSITY', 'LONDON'],\n",
" ['CHINA', 'MEDICAL', 'UNIVERSITY'],\n",
" ['UNIVERSITY', 'OF', 'POTSDAM'],\n",
" ['SHANDONG', 'JIANZHU', 'UNIVERSITY'],\n",
" ['UNIVERSITY', 'OF', 'HAMBURG'],\n",
" ['IMPERIAL', 'COLLEGE', 'LONDON'],\n",
" ['IDAHO', 'STATE', 'UNIVERSITY'],\n",
" ['UNIVERSITY', 'OF', 'CAGLIARI'],\n",
" ['UNIVERSITY', 'OF', 'FLORENCE'],\n",
" ['UNIVERSITY', 'OF', 'JINAN'],\n",
" ['UNIVERSITY', 'OF', 'ALBERTA'],\n",
" ['UDICE-FRENCH', 'RESEARCH', 'UNIVERSITIES'],\n",
" ['ISTANBUL', 'TECHNICAL', 'UNIVERSITY'],\n",
" ['UNIVERSITE', 'DE', 'SAVOIE'],\n",
" ['ARGONNE', 'NATIONAL', 'LABORATORY'],\n",
" ['UNIVERSITY', 'OF', 'ARIZONA'],\n",
" ['UNIVERSITY', 'OF', 'BELGRADE'],\n",
" ['UNIVERSITY', 'OF', 'BERGEN'],\n",
" ['UNIVERSITY', 'OF', 'BERN'],\n",
" ['UNIVERSITY', 'OF', 'BIRMINGHAM'],\n",
" ['UNIVERSITY', 'OF', 'BOLOGNA'],\n",
" ['UNIVERSITY', 'OF', 'BONN'],\n",
" ['BROOKHAVEN', 'NATIONAL', 'LABORATORY'],\n",
" ['UNIVERSITY', 'OF', 'CAMBRIDGE'],\n",
" ['UNIVERSITY', 'OF', 'CHICAGO'],\n",
" ['UNIVERSITY', 'OF', 'COPENHAGEN'],\n",
" ['NIELS', 'BOHR', 'INSTITUTE'],\n",
" ['UNIVERSITY', 'OF', 'CALABRIA'],\n",
" ['SOUTHERN', 'METHODIST', 'UNIVERSITY'],\n",
" ['DEUTSCHES', 'ELEKTRONEN-SYNCHROTRON', 'DESY'],\n",
" ['TECHNISCHE', 'UNIVERSITAT', 'DRESDEN'],\n",
" ['UNIVERSITY', 'OF', 'EDINBURGH'],\n",
" ['UNIVERSITY', 'OF', 'FREIBURG'],\n",
" ['UNIVERSITY', 'OF', 'GENEVA'],\n",
" ['UNIVERSITY', 'OF', 'GENOA'],\n",
" ['UNIVERSITY', 'OF', 'GLASGOW'],\n",
" ['UNIVERSITY', 'OF', 'GOTTINGEN'],\n",
" ['INDIANA', 'UNIVERSITY', 'SYSTEM'],\n",
" ['INDIANA', 'UNIVERSITY', 'BLOOMINGTON'],\n",
" ['UNIVERSITY', 'OF', 'INNSBRUCK'],\n",
" ['UNIVERSITY', 'OF', 'IOWA'],\n",
" ['IOWA', 'STATE', 'UNIVERSITY'],\n",
" ['UNIVERSITY', 'OF', 'SALENTO'],\n",
" ['UNIVERSITY', 'OF', 'LIVERPOOL'],\n",
" ['JOZEF', 'STEFAN', 'INSTITUTE'],\n",
" ['UNIVERSITY', 'OF', 'LJUBLJANA'],\n",
" ['UNIVERSITY', 'COLLEGE', 'LONDON'],\n",
" ['UNIVERSITE', 'PARIS', 'CITE'],\n",
" ['UNIVERSITY', 'OF', 'MANCHESTER'],\n",
" ['UNIVERSITY', 'OF', 'MELBOURNE'],\n",
" ['UNIVERSITY', 'OF', 'MICHIGAN'],\n",
" ['MICHIGAN', 'STATE', 'UNIVERSITY'],\n",
" ['UNIVERSITY', 'OF', 'MILAN'],\n",
" ['BELARUSIAN', 'STATE', 'UNIVERSITY'],\n",
" ['UNIVERSITE', 'DE', 'MONTREAL'],\n",
" ['UNIVERSITY', 'OF', 'MUNICH'],\n",
" ['MAX', 'PLANCK', 'SOCIETY'],\n",
" ['RADBOUD', 'UNIVERSITY', 'NIJMEGEN'],\n",
" ['UNIVERSITY', 'OF', 'AMSTERDAM'],\n",
" ['NORTHERN', 'ILLINOIS', 'UNIVERSITY'],\n",
" ['NEW', 'YORK', 'UNIVERSITY'],\n",
" ['OHIO', 'STATE', 'UNIVERSITY'],\n",
" ['PALACKY', 'UNIVERSITY', 'OLOMOUC'],\n",
" ['UNIVERSITY', 'OF', 'OREGON'],\n",
" ['UNIVERSITE', 'PARIS', 'SACLAY'],\n",
" ['UNIVERSITY', 'OF', 'OSLO'],\n",
" ['UNIVERSITY', 'OF', 'OXFORD'],\n",
" ['UNIVERSITY', 'OF', 'PAVIA'],\n",
" ['UNIVERSITY', 'OF', 'PENNSYLVANIA'],\n",
" ['UNIVERSITY', 'OF', 'PISA'],\n",
" ['UNIVERSITY', 'OF', 'PITTSBURGH'],\n",
" ['UNIVERSITY', 'OF', 'GRANADA'],\n",
" ['CHARLES', 'UNIVERSITY', 'PRAGUE'],\n",
" ['UNIVERSITY', 'OF', 'REGINA'],\n",
" ['SAPIENZA', 'UNIVERSITY', 'ROME'],\n",
" ['ROMA', 'TRE', 'UNIVERSITY'],\n",
" ['UNIVERSITY', 'OF', 'WASHINGTON'],\n",
" ['UNIVERSITY', 'OF', 'SHEFFIELD'],\n",
" ['SIMON', 'FRASER', 'UNIVERSITY'],\n",
" ['COMENIUS', 'UNIVERSITY', 'BRATISLAVA'],\n",
" ['UNIVERSITY', 'OF', 'JOHANNESBURG'],\n",
" ['UNIVERSITY', 'OF', 'WITWATERSRAND'],\n",
" ['OSKAR', 'KLEIN', 'CENTRE'],\n",
" ['UNIVERSITY', 'OF', 'SUSSEX'],\n",
" ['UNIVERSITY', 'OF', 'SYDNEY'],\n",
" ['TEL', 'AVIV', 'UNIVERSITY'],\n",
" ['UNIVERSITY', 'OF', 'TOKYO'],\n",
" ['TOKYO', 'METROPOLITAN', 'UNIVERSITY'],\n",
" ['UNIVERSITY', 'OF', 'TORONTO'],\n",
" ['UNIVERSITY', 'OF', 'TSUKUBA'],\n",
" ['UNIVERSIDAD', 'ANTONIO', 'NARINO'],\n",
" ['UNIVERSITY', 'OF', 'UDINE'],\n",
" ['UNIVERSITY', 'OF', 'VALENCIA'],\n",
" ['UNIVERSITY', 'OF', 'VICTORIA'],\n",
" ['UNIVERSITY', 'OF', 'WURZBURG'],\n",
" ['UNIVERSITY', 'OF', 'WUPPERTAL'],\n",
" ['YEREVAN', 'PHYSICS', 'INSTITUTE'],\n",
" ['UNIVERSIDADE', 'DE', 'LISBOA'],\n",
" ['NOVOSIBIRSK', 'STATE', 'UNIVERSITY'],\n",
" ['UNIVERSIDADE', 'DE', 'COIMBRA'],\n",
" ['PARTHENOPE', 'UNIVERSITY', 'NAPLES'],\n",
" ['LOUISIANA', 'TECHNICAL', 'UNIVERSITY'],\n",
" ['UNIVERSIDADE', 'DO', 'MINHO'],\n",
" ['ZHEJIANG', 'NORMAL', 'UNIVERSITY'],\n",
" ['UNIVERSITY', 'OF', 'WARWICK'],\n",
" ['UNIVERSIDADE', 'DO', 'PORTO'],\n",
" ['UNIVERSIDADE', 'ESTADUAL', 'PAULISTA'],\n",
" ['DUBLIN', 'CITY', 'UNIVERSITY'],\n",
" ['UNIVERSITY', 'OF', 'TWENTE'],\n",
" ['LOUISIANA', 'STATE', 'UNIVERSITY'],\n",
" ['UNIVERSITY', 'OF', 'SEVILLA'],\n",
" ['LUOYANG', 'NORMAL', 'UNIVERSITY'],\n",
" ['SHAANXI', 'NORMAL', 'UNIVERSITY'],\n",
" ['CHINA', 'JILIANG', 'UNIVERSITY'],\n",
" ['VRIJE', 'UNIVERSITEIT', 'BRUSSEL'],\n",
" ['UNIVERSITY', 'COLLEGE', 'DUBLIN'],\n",
" ['UNIVERSITY', 'OF', 'BARCELONA'],\n",
" ['UNIVERSITY', 'OF', 'ZURICH'],\n",
" ['VRIJE', 'UNIVERSITEIT', 'AMSTERDAM'],\n",
" ['UNIVERSITY', 'OF', 'BRISTOL'],\n",
" ['UNIVERSITY', 'OF', 'ROSTOCK'],\n",
" ['UNIVERSITY', 'OF', 'FERRARA'],\n",
" ['UNIVERSITY', 'OF', 'URBINO'],\n",
" ['UNIVERSITY', 'OF', 'MILANO-BICOCCA'],\n",
" ['UNIVERSITY', 'OF', 'BASILICATA'],\n",
" ['UNIVERSITAT', 'RAMON', 'LLULL'],\n",
" ['UNIVERSITY', 'COLLEGE', 'CORK'],\n",
" ['OREGON', 'STATE', 'UNIVERSITY'],\n",
" ['UNIVERSITE', 'DE', 'LILLE'],\n",
" ['FINNISH', 'ENVIRONMENT', 'INSTITUTE'],\n",
" ['ANHUI', 'AGRICULTURAL', 'UNIVERSITY'],\n",
" ['UNIVERSITE', 'CATHOLIQUE', 'LOUVAIN'],\n",
" ['UNIVERSITY', 'OF', 'OULU'],\n",
" ['QUEENS', 'UNIVERSITY', 'BELFAST'],\n",
" ['SHANGHAI', 'DIANJI', 'UNIVERSITY'],\n",
" ['FUJIAN', 'NORMAL', 'UNIVERSITY'],\n",
" ['TAMPERE', 'UNIVERSITY', 'HOSPITAL'],\n",
" ['NORTHWESTERN', 'POLYTECHNICAL', 'UNIVERSITY'],\n",
" ['UNIVERSITE', 'PARIS-EST-CRETEIL-VAL-DE-MARNE', 'UPEC'],\n",
" ['KING', 'ABDULAZIZ', 'UNIVERSITY'],\n",
" ['UNIVERSITE', 'DE', 'STRASBOURG'],\n",
" ['BEIJING', 'NORMAL', 'UNIVERSITY'],\n",
" ['UNIVERSITY', 'OF', 'ANTWERP'],\n",
" ['UNIVERSITY', 'OF', 'MONS'],\n",
" ['UNIVERSITY', 'OF', 'SOFIA'],\n",
" ['UNIVERSITY', 'OF', 'SPLIT'],\n",
" ['RUDJER', 'BOSKOVIC', 'INSTITUTE'],\n",
" ['UNIVERSITY', 'OF', 'CYPRUS'],\n",
" ['UNIVERSITY', 'OF', 'HELSINKI'],\n",
" ['RWTH', 'AACHEN', 'UNIVERSITY'],\n",
" ...]"
]
},
"execution_count": 85,
"metadata": {},
"output_type": "execute_result"
}
],
"source": [
"unique_inst = sorted([i.split(\" \") for i in list(affiliations[\"Affiliations\"].unique())], key=len)\n",
"# unique_inst = [[''.join(filter(str.isalnum, i)) for i in i_list] for i_list in unique_inst]\n",
"unique_inst = [[i.strip(\",\").strip(\"(\").strip(\")\") for i in i_list] for i_list in unique_inst]\n",
"unique_inst"
]
},
{
"cell_type": "code",
"execution_count": 86,
"metadata": {},
"outputs": [],
"source": [
"def institution_chunk_norris(text):\n",
" for i in unique_inst:\n",
" text_split=text.split(\" \")\n",
" text_split=[i.strip(\",\").strip(\"(\").strip(\")\") for i in text_split]\n",
" overlap = all(token in text_split for token in i)\n",
" if overlap:\n",
" return (\" \".join(i))\n",
" return \"ERROR\""
]
},
{
"cell_type": "code",
"execution_count": 87,
"metadata": {},
"outputs": [],
"source": [
"affiliations[\"Affiliations_merged\"] = affiliations[\"Affiliations\"].apply(lambda x: institution_chunk_norris(x))"
]
},
{
"cell_type": "code",
"execution_count": 88,
"metadata": {},
"outputs": [
{
"data": {
"text/plain": [
"Affiliations\n",
"CHINESE ACADEMY OF SCIENCES 1188\n",
"UDICE-FRENCH RESEARCH UNIVERSITIES 647\n",
"CENTRE NATIONAL DE LA RECHERCHE SCIENTIFIQUE (CNRS) 640\n",
"HELMHOLTZ ASSOCIATION 427\n",
"UNIVERSITY OF CHINESE ACADEMY OF SCIENCES, CAS 411\n",
" ... \n",
"IMT NORD EUROPE 1\n",
"SANGMYUNG UNIVERSITY 1\n",
"INDIANA UNIVERSITY PURDUE UNIVERSITY FORT WAYNE 1\n",
"JAHANGIRNAGAR UNIVERSITY 1\n",
"SAINT JAMES'S UNIVERSITY HOSPITAL 1\n",
"Name: count, Length: 4884, dtype: int64"
]
},
"execution_count": 88,
"metadata": {},
"output_type": "execute_result"
}
],
"source": [
"affiliations[\"Affiliations\"].value_counts()"
]
},
{
"cell_type": "code",
"execution_count": 89,
"metadata": {},
"outputs": [
{
"data": {
"text/plain": [
"Affiliations_merged\n",
"CHINESE ACADEMY OF SCIENCES 1725\n",
"NANJING UNIVERSITY 737\n",
"SHANGHAI UNIVERSITY 667\n",
"UDICE-FRENCH RESEARCH UNIVERSITIES 647\n",
"CENTRE NATIONAL DE LA RECHERCHE SCIENTIFIQUE CNRS 640\n",
" ... \n",
"ULVAC INC. 1\n",
"NATIONAL METROLOGY INSTITUTE OF JAPAN 1\n",
"SHEFFIELD HALLAM UNIVERSITY 1\n",
"GLOBAL INSTITUTE FOR WATER SECURITY 1\n",
"SAINT JAMES'S UNIVERSITY HOSPITAL 1\n",
"Name: count, Length: 4241, dtype: int64"
]
},
"execution_count": 89,
"metadata": {},
"output_type": "execute_result"
}
],
"source": [
"affiliations[\"Affiliations_merged\"].value_counts()"
]
},
{
"cell_type": "code",
"execution_count": 90,
"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>UT (Unique WOS ID)</th>\n",
" <th>Affiliations</th>\n",
" <th>Affiliations_merged</th>\n",
" </tr>\n",
" </thead>\n",
" <tbody>\n",
" </tbody>\n",
"</table>\n",
"</div>"
],
"text/plain": [
"Empty DataFrame\n",
"Columns: [UT (Unique WOS ID), Affiliations, Affiliations_merged]\n",
"Index: []"
]
},
"execution_count": 90,
"metadata": {},
"output_type": "execute_result"
}
],
"source": [
"affiliations[affiliations[\"Affiliations_merged\"]==\"ERROR\"]"
]
},
{
"cell_type": "code",
"execution_count": 123,
"metadata": {},
"outputs": [],
"source": [
"from nltk.metrics import edit_distance\n",
"#results = df.apply(lambda x: edit_distance(x[\"column1\"], x[\"column2\"]), axis=1)"
]
},
{
"cell_type": "code",
"execution_count": 125,
"metadata": {},
"outputs": [
{
"data": {
"text/html": [
"<div>\n",
"<style scoped>\n",
" .dataframe tbody tr th:only-of-type {\n",
" vertical-align: middle;\n",
" }\n",
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" .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>UT (Unique WOS ID)</th>\n",
" <th>Affiliations</th>\n",
" <th>Affiliations_merged</th>\n",
" <th>Address</th>\n",
" <th>Country</th>\n",
" <th>City</th>\n",
" <th>Country_Type</th>\n",
" <th>Institution</th>\n",
" </tr>\n",
" </thead>\n",
" <tbody>\n",
" <tr>\n",
" <th>0</th>\n",
" <td>WOS:000209536100003</td>\n",
" <td>NATURAL HISTORY MUSEUM LONDON</td>\n",
" <td>NATURAL HISTORY MUSEUM LONDON</td>\n",
" <td>BGI HK Ltd, GigaSci, Tai Po, Hong Kong, Peopl...</td>\n",
" <td>China</td>\n",
" <td>Hong Kong</td>\n",
" <td>China</td>\n",
" <td>BGI HK Ltd</td>\n",
" </tr>\n",
" <tr>\n",
" <th>1</th>\n",
" <td>WOS:000209536100003</td>\n",
" <td>NATURAL HISTORY MUSEUM LONDON</td>\n",
" <td>NATURAL HISTORY MUSEUM LONDON</td>\n",
" <td>Nat Hist Museum, London SW7 5BD, England;</td>\n",
" <td>United Kingdom</td>\n",
" <td>London</td>\n",
" <td>Other</td>\n",
" <td>Nat Hist Museum</td>\n",
" </tr>\n",
" <tr>\n",
" <th>2</th>\n",
" <td>WOS:000209536100003</td>\n",
" <td>NATURAL HISTORY MUSEUM LONDON</td>\n",
" <td>NATURAL HISTORY MUSEUM LONDON</td>\n",
" <td>Pensoft Publishers, Sofia, Bulgaria;</td>\n",
" <td>Bulgaria</td>\n",
" <td>Sofia</td>\n",
" <td>EU</td>\n",
" <td>Pensoft Publishers</td>\n",
" </tr>\n",
" <tr>\n",
" <th>3</th>\n",
" <td>WOS:000209536100003</td>\n",
" <td>NATURAL HISTORY MUSEUM LONDON</td>\n",
" <td>NATURAL HISTORY MUSEUM LONDON</td>\n",
" <td>Nat Hist Museum, Natl Museum, Sofia, Bulgaria;</td>\n",
" <td>Bulgaria</td>\n",
" <td>Sofia</td>\n",
" <td>EU</td>\n",
" <td>Nat Hist Museum</td>\n",
" </tr>\n",
" <tr>\n",
" <th>4</th>\n",
" <td>WOS:000209536100003</td>\n",
" <td>NATURAL HISTORY MUSEUM LONDON</td>\n",
" <td>NATURAL HISTORY MUSEUM LONDON</td>\n",
" <td>Bulgarian Acad Sci, Inst Biodivers &amp; Ecosyst ...</td>\n",
" <td>Bulgaria</td>\n",
" <td>Rees</td>\n",
" <td>EU</td>\n",
" <td>Bulgarian Acad Sci</td>\n",
" </tr>\n",
" </tbody>\n",
"</table>\n",
"</div>"
],
"text/plain": [
" UT (Unique WOS ID) Affiliations \n",
"0 WOS:000209536100003 NATURAL HISTORY MUSEUM LONDON \\\n",
"1 WOS:000209536100003 NATURAL HISTORY MUSEUM LONDON \n",
"2 WOS:000209536100003 NATURAL HISTORY MUSEUM LONDON \n",
"3 WOS:000209536100003 NATURAL HISTORY MUSEUM LONDON \n",
"4 WOS:000209536100003 NATURAL HISTORY MUSEUM LONDON \n",
"\n",
" Affiliations_merged \n",
"0 NATURAL HISTORY MUSEUM LONDON \\\n",
"1 NATURAL HISTORY MUSEUM LONDON \n",
"2 NATURAL HISTORY MUSEUM LONDON \n",
"3 NATURAL HISTORY MUSEUM LONDON \n",
"4 NATURAL HISTORY MUSEUM LONDON \n",
"\n",
" Address Country \n",
"0 BGI HK Ltd, GigaSci, Tai Po, Hong Kong, Peopl... China \\\n",
"1 Nat Hist Museum, London SW7 5BD, England; United Kingdom \n",
"2 Pensoft Publishers, Sofia, Bulgaria; Bulgaria \n",
"3 Nat Hist Museum, Natl Museum, Sofia, Bulgaria; Bulgaria \n",
"4 Bulgarian Acad Sci, Inst Biodivers & Ecosyst ... Bulgaria \n",
"\n",
" City Country_Type Institution \n",
"0 Hong Kong China BGI HK Ltd \n",
"1 London Other Nat Hist Museum \n",
"2 Sofia EU Pensoft Publishers \n",
"3 Sofia EU Nat Hist Museum \n",
"4 Rees EU Bulgarian Acad Sci "
]
},
"execution_count": 125,
"metadata": {},
"output_type": "execute_result"
}
],
"source": [
"affiliations = affiliations.merge(univ_locations, on=record_col)"
]
},
{
"cell_type": "code",
"execution_count": 128,
"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>UT (Unique WOS ID)</th>\n",
" <th>Affiliations</th>\n",
" <th>Affiliations_merged</th>\n",
" <th>Address</th>\n",
" <th>Country</th>\n",
" <th>City</th>\n",
" <th>Country_Type</th>\n",
" <th>Institution</th>\n",
" <th>levehnstein</th>\n",
" </tr>\n",
" </thead>\n",
" <tbody>\n",
" <tr>\n",
" <th>0</th>\n",
" <td>WOS:000209536100003</td>\n",
" <td>NATURAL HISTORY MUSEUM LONDON</td>\n",
" <td>NATURAL HISTORY MUSEUM LONDON</td>\n",
" <td>BGI HK Ltd, GigaSci, Tai Po, Hong Kong, Peopl...</td>\n",
" <td>China</td>\n",
" <td>Hong Kong</td>\n",
" <td>China</td>\n",
" <td>BGI HK LTD</td>\n",
" <td>24</td>\n",
" </tr>\n",
" <tr>\n",
" <th>1</th>\n",
" <td>WOS:000209536100003</td>\n",
" <td>NATURAL HISTORY MUSEUM LONDON</td>\n",
" <td>NATURAL HISTORY MUSEUM LONDON</td>\n",
" <td>Nat Hist Museum, London SW7 5BD, England;</td>\n",
" <td>United Kingdom</td>\n",
" <td>London</td>\n",
" <td>Other</td>\n",
" <td>NAT HIST MUSEUM</td>\n",
" <td>14</td>\n",
" </tr>\n",
" <tr>\n",
" <th>2</th>\n",
" <td>WOS:000209536100003</td>\n",
" <td>NATURAL HISTORY MUSEUM LONDON</td>\n",
" <td>NATURAL HISTORY MUSEUM LONDON</td>\n",
" <td>Pensoft Publishers, Sofia, Bulgaria;</td>\n",
" <td>Bulgaria</td>\n",
" <td>Sofia</td>\n",
" <td>EU</td>\n",
" <td>PENSOFT PUBLISHERS</td>\n",
" <td>25</td>\n",
" </tr>\n",
" <tr>\n",
" <th>3</th>\n",
" <td>WOS:000209536100003</td>\n",
" <td>NATURAL HISTORY MUSEUM LONDON</td>\n",
" <td>NATURAL HISTORY MUSEUM LONDON</td>\n",
" <td>Nat Hist Museum, Natl Museum, Sofia, Bulgaria;</td>\n",
" <td>Bulgaria</td>\n",
" <td>Sofia</td>\n",
" <td>EU</td>\n",
" <td>NAT HIST MUSEUM</td>\n",
" <td>14</td>\n",
" </tr>\n",
" <tr>\n",
" <th>4</th>\n",
" <td>WOS:000209536100003</td>\n",
" <td>NATURAL HISTORY MUSEUM LONDON</td>\n",
" <td>NATURAL HISTORY MUSEUM LONDON</td>\n",
" <td>Bulgarian Acad Sci, Inst Biodivers &amp; Ecosyst ...</td>\n",
" <td>Bulgaria</td>\n",
" <td>Rees</td>\n",
" <td>EU</td>\n",
" <td>BULGARIAN ACAD SCI</td>\n",
" <td>25</td>\n",
" </tr>\n",
" </tbody>\n",
"</table>\n",
"</div>"
],
"text/plain": [
" UT (Unique WOS ID) Affiliations \n",
"0 WOS:000209536100003 NATURAL HISTORY MUSEUM LONDON \\\n",
"1 WOS:000209536100003 NATURAL HISTORY MUSEUM LONDON \n",
"2 WOS:000209536100003 NATURAL HISTORY MUSEUM LONDON \n",
"3 WOS:000209536100003 NATURAL HISTORY MUSEUM LONDON \n",
"4 WOS:000209536100003 NATURAL HISTORY MUSEUM LONDON \n",
"\n",
" Affiliations_merged \n",
"0 NATURAL HISTORY MUSEUM LONDON \\\n",
"1 NATURAL HISTORY MUSEUM LONDON \n",
"2 NATURAL HISTORY MUSEUM LONDON \n",
"3 NATURAL HISTORY MUSEUM LONDON \n",
"4 NATURAL HISTORY MUSEUM LONDON \n",
"\n",
" Address Country \n",
"0 BGI HK Ltd, GigaSci, Tai Po, Hong Kong, Peopl... China \\\n",
"1 Nat Hist Museum, London SW7 5BD, England; United Kingdom \n",
"2 Pensoft Publishers, Sofia, Bulgaria; Bulgaria \n",
"3 Nat Hist Museum, Natl Museum, Sofia, Bulgaria; Bulgaria \n",
"4 Bulgarian Acad Sci, Inst Biodivers & Ecosyst ... Bulgaria \n",
"\n",
" City Country_Type Institution levehnstein \n",
"0 Hong Kong China BGI HK LTD 24 \n",
"1 London Other NAT HIST MUSEUM 14 \n",
"2 Sofia EU PENSOFT PUBLISHERS 25 \n",
"3 Sofia EU NAT HIST MUSEUM 14 \n",
"4 Rees EU BULGARIAN ACAD SCI 25 "
]
},
"execution_count": 128,
"metadata": {},
"output_type": "execute_result"
}
],
"source": [
"affiliations[\"Affiliations\"] = affiliations[\"Affiliations\"].str.upper().str.strip()\n",
"affiliations[\"Institution\"] = affiliations[\"Institution\"].str.upper().str.strip()\n",
"\n",
"affiliations[\"levehnstein\"] = affiliations.apply(\n",
" lambda x: edit_distance(x[\"Affiliations\"], x[\"Institution\"]), axis=1)\n",
"affiliations.head()"
]
},
{
"cell_type": "code",
"execution_count": 133,
"metadata": {},
"outputs": [
{
"data": {
"text/html": [
"<div>\n",
"<style scoped>\n",
" .dataframe tbody tr th:only-of-type {\n",
" vertical-align: middle;\n",
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"\n",
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" 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>UT (Unique WOS ID)</th>\n",
" <th>Affiliations</th>\n",
" <th>Affiliations_merged</th>\n",
" <th>Address</th>\n",
" <th>Country</th>\n",
" <th>City</th>\n",
" <th>Country_Type</th>\n",
" <th>Institution</th>\n",
" <th>levehnstein</th>\n",
" </tr>\n",
" </thead>\n",
" <tbody>\n",
" <tr>\n",
" <th>2430154</th>\n",
" <td>WOS:000947693400001</td>\n",
" <td>UNIVERSITAT POLITECNICA DE VALENCIA</td>\n",
" <td>UNIVERSITAT POLITECNICA DE VALENCIA</td>\n",
" <td>Univ Politecn Valencia, European Inst Innovat...</td>\n",
" <td>Spain</td>\n",
" <td>Valencia</td>\n",
" <td>EU</td>\n",
" <td>UNIV POLITECN VALENCIA</td>\n",
" <td>13</td>\n",
" </tr>\n",
" <tr>\n",
" <th>2430132</th>\n",
" <td>WOS:000947693400001</td>\n",
" <td>SHANGHAITECH UNIVERSITY</td>\n",
" <td>SHANGHAITECH UNIVERSITY</td>\n",
" <td>ShanghaiTech Univ, Shanghai Inst Adv Immunoch...</td>\n",
" <td>China</td>\n",
" <td>Shanghai</td>\n",
" <td>China</td>\n",
" <td>SHANGHAITECH UNIV</td>\n",
" <td>6</td>\n",
" </tr>\n",
" <tr>\n",
" <th>2430139</th>\n",
" <td>WOS:000947693400001</td>\n",
" <td>SHANGHAI OCEAN UNIVERSITY</td>\n",
" <td>SHANGHAI UNIVERSITY</td>\n",
" <td>Shanghai Ocean Univ, Coll Fisheries &amp; Life Sc...</td>\n",
" <td>China</td>\n",
" <td>Shanghai</td>\n",
" <td>China</td>\n",
" <td>SHANGHAI OCEAN UNIV</td>\n",
" <td>6</td>\n",
" </tr>\n",
" <tr>\n",
" <th>2430146</th>\n",
" <td>WOS:000947693400001</td>\n",
" <td>SHANGHAI JIAO TONG UNIVERSITY</td>\n",
" <td>SHANGHAI UNIVERSITY</td>\n",
" <td>Shanghai Jiao Tong Univ, Ruijin Hosp, Sch Med...</td>\n",
" <td>China</td>\n",
" <td>Meda</td>\n",
" <td>China</td>\n",
" <td>SHANGHAI JIAO TONG UNIV</td>\n",
" <td>6</td>\n",
" </tr>\n",
" <tr>\n",
" <th>2430125</th>\n",
" <td>WOS:000947693400001</td>\n",
" <td>HUZHOU UNIVERSITY</td>\n",
" <td>HUZHOU UNIVERSITY</td>\n",
" <td>Huzhou Univ, Sch Informat Engn, Huzhou 313000...</td>\n",
" <td>China</td>\n",
" <td>Huzhou</td>\n",
" <td>China</td>\n",
" <td>HUZHOU UNIV</td>\n",
" <td>6</td>\n",
" </tr>\n",
" <tr>\n",
" <th>2430113</th>\n",
" <td>WOS:000946746700001</td>\n",
" <td>SUZHOU UNIVERSITY OF SCIENCE &amp; TECHNOLOGY</td>\n",
" <td>SUZHOU UNIVERSITY OF SCIENCE &amp; TECHNOLOGY</td>\n",
" <td>Suzhou Univ Sci &amp; Technol, Sch Elect &amp; Inform...</td>\n",
" <td>China</td>\n",
" <td>Suzhou</td>\n",
" <td>China</td>\n",
" <td>SUZHOU UNIV SCI &amp; TECHNOL</td>\n",
" <td>16</td>\n",
" </tr>\n",
" <tr>\n",
" <th>2430118</th>\n",
" <td>WOS:000946746700001</td>\n",
" <td>POLYTECHNIC UNIVERSITY OF MILAN</td>\n",
" <td>UNIVERSITY OF MILAN</td>\n",
" <td>Politecn Milan, Dept Mech Engn, Milan, Italy;</td>\n",
" <td>Italy</td>\n",
" <td>Milano</td>\n",
" <td>EU</td>\n",
" <td>POLITECN MILAN</td>\n",
" <td>18</td>\n",
" </tr>\n",
" <tr>\n",
" <th>2430123</th>\n",
" <td>WOS:000946746700001</td>\n",
" <td>HONG KONG POLYTECHNIC UNIVERSITY</td>\n",
" <td>HONG KONG POLYTECHNIC UNIVERSITY</td>\n",
" <td>Hong Kong Polytech Univ, Dept Comp, Hong Kong...</td>\n",
" <td>China</td>\n",
" <td>Hong Kong</td>\n",
" <td>China</td>\n",
" <td>HONG KONG POLYTECH UNIV</td>\n",
" <td>9</td>\n",
" </tr>\n",
" <tr>\n",
" <th>2430111</th>\n",
" <td>WOS:000945297300001</td>\n",
" <td>UNIVERSITY OF PANNONIA</td>\n",
" <td>UNIVERSITY OF PANNONIA</td>\n",
" <td>Univ Pannonia, Dept Elect Engn &amp; Informat Sys...</td>\n",
" <td>Hungary</td>\n",
" <td>Veszprém</td>\n",
" <td>EU</td>\n",
" <td>UNIV PANNONIA</td>\n",
" <td>9</td>\n",
" </tr>\n",
" <tr>\n",
" <th>2430107</th>\n",
" <td>WOS:000945297300001</td>\n",
" <td>SHENYANG UNIVERSITY OF TECHNOLOGY</td>\n",
" <td>SHENYANG UNIVERSITY</td>\n",
" <td>Shenyang Univ Technol, Sch Elect Engn, Dept B...</td>\n",
" <td>China</td>\n",
" <td>Shenyang</td>\n",
" <td>China</td>\n",
" <td>SHENYANG UNIV TECHNOL</td>\n",
" <td>12</td>\n",
" </tr>\n",
" </tbody>\n",
"</table>\n",
"</div>"
],
"text/plain": [
" UT (Unique WOS ID) Affiliations \n",
"2430154 WOS:000947693400001 UNIVERSITAT POLITECNICA DE VALENCIA \\\n",
"2430132 WOS:000947693400001 SHANGHAITECH UNIVERSITY \n",
"2430139 WOS:000947693400001 SHANGHAI OCEAN UNIVERSITY \n",
"2430146 WOS:000947693400001 SHANGHAI JIAO TONG UNIVERSITY \n",
"2430125 WOS:000947693400001 HUZHOU UNIVERSITY \n",
"2430113 WOS:000946746700001 SUZHOU UNIVERSITY OF SCIENCE & TECHNOLOGY \n",
"2430118 WOS:000946746700001 POLYTECHNIC UNIVERSITY OF MILAN \n",
"2430123 WOS:000946746700001 HONG KONG POLYTECHNIC UNIVERSITY \n",
"2430111 WOS:000945297300001 UNIVERSITY OF PANNONIA \n",
"2430107 WOS:000945297300001 SHENYANG UNIVERSITY OF TECHNOLOGY \n",
"\n",
" Affiliations_merged \n",
"2430154 UNIVERSITAT POLITECNICA DE VALENCIA \\\n",
"2430132 SHANGHAITECH UNIVERSITY \n",
"2430139 SHANGHAI UNIVERSITY \n",
"2430146 SHANGHAI UNIVERSITY \n",
"2430125 HUZHOU UNIVERSITY \n",
"2430113 SUZHOU UNIVERSITY OF SCIENCE & TECHNOLOGY \n",
"2430118 UNIVERSITY OF MILAN \n",
"2430123 HONG KONG POLYTECHNIC UNIVERSITY \n",
"2430111 UNIVERSITY OF PANNONIA \n",
"2430107 SHENYANG UNIVERSITY \n",
"\n",
" Address Country \n",
"2430154 Univ Politecn Valencia, European Inst Innovat... Spain \\\n",
"2430132 ShanghaiTech Univ, Shanghai Inst Adv Immunoch... China \n",
"2430139 Shanghai Ocean Univ, Coll Fisheries & Life Sc... China \n",
"2430146 Shanghai Jiao Tong Univ, Ruijin Hosp, Sch Med... China \n",
"2430125 Huzhou Univ, Sch Informat Engn, Huzhou 313000... China \n",
"2430113 Suzhou Univ Sci & Technol, Sch Elect & Inform... China \n",
"2430118 Politecn Milan, Dept Mech Engn, Milan, Italy; Italy \n",
"2430123 Hong Kong Polytech Univ, Dept Comp, Hong Kong... China \n",
"2430111 Univ Pannonia, Dept Elect Engn & Informat Sys... Hungary \n",
"2430107 Shenyang Univ Technol, Sch Elect Engn, Dept B... China \n",
"\n",
" City Country_Type Institution levehnstein \n",
"2430154 Valencia EU UNIV POLITECN VALENCIA 13 \n",
"2430132 Shanghai China SHANGHAITECH UNIV 6 \n",
"2430139 Shanghai China SHANGHAI OCEAN UNIV 6 \n",
"2430146 Meda China SHANGHAI JIAO TONG UNIV 6 \n",
"2430125 Huzhou China HUZHOU UNIV 6 \n",
"2430113 Suzhou China SUZHOU UNIV SCI & TECHNOL 16 \n",
"2430118 Milano EU POLITECN MILAN 18 \n",
"2430123 Hong Kong China HONG KONG POLYTECH UNIV 9 \n",
"2430111 Veszprém EU UNIV PANNONIA 9 \n",
"2430107 Shenyang China SHENYANG UNIV TECHNOL 12 "
]
},
"execution_count": 133,
"metadata": {},
"output_type": "execute_result"
}
],
"source": [
"affiliations = affiliations.sort_values(by=[record_col,\"Affiliations\",\"levehnstein\"], ascending=[False,False,True])\n",
"affiliations_merge = affiliations.drop_duplicates(subset=[record_col,\"Affiliations\"])\n",
"affiliations_merge.head(10)"
]
},
{
"cell_type": "code",
"execution_count": 91,
"metadata": {},
"outputs": [
{
"data": {
"text/plain": [
"WoS Categories\n",
" Engineering, Electrical & Electronic 1703\n",
"Computer Science, Artificial Intelligence 1366\n",
"Computer Science, Information Systems 973\n",
" Telecommunications 834\n",
" Imaging Science & Photographic Technology 762\n",
" ... \n",
" Crystallography 1\n",
"Mining & Mineral Processing 1\n",
" Art 1\n",
"Archaeology 1\n",
"Physics, Mathematical 1\n",
"Name: count, Length: 379, dtype: int64"
]
},
"execution_count": 91,
"metadata": {},
"output_type": "execute_result"
}
],
"source": [
"wos_cat = wos.groupby(record_col)[\"WoS Categories\"].apply(lambda x: x.str.split(';')).explode().reset_index().drop(columns=\"level_1\")\n",
"wos_cat[\"WoS Categories\"].value_counts()"
]
},
{
"cell_type": "code",
"execution_count": 92,
"metadata": {},
"outputs": [
{
"data": {
"text/plain": [
"Research Areas\n",
"Engineering 3740\n",
"Computer Science 3466\n",
"Telecommunications 888\n",
"Imaging Science & Photographic Technology 779\n",
"Remote Sensing 716\n",
" ... \n",
"Otorhinolaryngology 1\n",
"Medical Ethics 1\n",
"Anesthesiology 1\n",
"Biomedical Social Sciences 1\n",
"History & Philosophy of Science 1\n",
"Name: count, Length: 141, dtype: int64"
]
},
"execution_count": 92,
"metadata": {},
"output_type": "execute_result"
}
],
"source": [
"wos_areas = wos.groupby(record_col)[\"Research Areas\"].apply(lambda x: x.str.split(';')).explode().reset_index().drop(columns=\"level_1\")\n",
"wos_areas[\"Research Areas\"] = wos_areas[\"Research Areas\"].str.strip()\n",
"wos_areas[\"Research Areas\"].value_counts()"
]
},
{
"cell_type": "code",
"execution_count": 93,
"metadata": {},
"outputs": [
{
"data": {
"text/plain": [
"Research Areas\n",
"Engineering 3740\n",
"Computer Science 3466\n",
"Telecommunications 888\n",
"Imaging Science & Photographic Technology 779\n",
"Remote Sensing 716\n",
" ... \n",
"Otorhinolaryngology 1\n",
"Medical Ethics 1\n",
"Anesthesiology 1\n",
"Biomedical Social Sciences 1\n",
"History & Philosophy of Science 1\n",
"Name: count, Length: 141, dtype: int64"
]
},
"execution_count": 93,
"metadata": {},
"output_type": "execute_result"
}
],
"source": [
"wos_areas[\"Research Areas\"].value_counts()"
]
},
{
"cell_type": "code",
"execution_count": 94,
"metadata": {},
"outputs": [
{
"data": {
"text/plain": [
"['Domain_English', 'Field_English', 'SubField_English']"
]
},
"execution_count": 94,
"metadata": {},
"output_type": "execute_result"
}
],
"source": [
"[c for c in wos.columns if \"_English\" in c]"
]
},
{
"cell_type": "code",
"execution_count": 95,
"metadata": {},
"outputs": [],
"source": [
"import seaborn as sns\n",
"from matplotlib.ticker import MaxNLocator\n",
"import math"
]
},
{
"cell_type": "code",
"execution_count": 96,
"metadata": {},
"outputs": [],
"source": [
"wos = wos[((wos[\"Publication Year\"]<2023) & (~wos['Domain_English'].isna()))]\n",
"\n",
"metrix_levels = [c for c in wos.columns if \"_English\" in c]\n",
"for m in metrix_levels:\n",
" wos[m] = wos[m].replace({\"article-level classification\":\"Miscellaneous\"})\n"
]
},
{
"cell_type": "code",
"execution_count": 97,
"metadata": {},
"outputs": [
{
"data": {
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" <th>0</th>\n",
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" <td>Applied Sciences</td>\n",
" <td>Information &amp; Communication Technologies</td>\n",
" <td>Networking &amp; Telecommunications</td>\n",
" <td>37</td>\n",
" <td>IEEE Transactions on Antennas and Propagation</td>\n",
" <td>1.733700e+04</td>\n",
" <td>issn1</td>\n",
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" <tr>\n",
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" <td>issn</td>\n",
" <td>07339445</td>\n",
" <td>Applied Sciences</td>\n",
" <td>Engineering</td>\n",
" <td>Civil Engineering</td>\n",
" <td>23</td>\n",
" <td>Journal of Structural Engineering (United States)</td>\n",
" <td>1.630500e+04</td>\n",
" <td>issn1</td>\n",
" </tr>\n",
" <tr>\n",
" <th>9699</th>\n",
" <td>J</td>\n",
" <td>Zhao, YL; Dong, S; Jiang, FY; Soares, CG</td>\n",
" <td>NaN</td>\n",
" <td>NaN</td>\n",
" <td>NaN</td>\n",
" <td>Zhao, Yuliang; Dong, Sheng; Jiang, Fengyuan; G...</td>\n",
" <td>NaN</td>\n",
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" <td>System Reliability Analysis of an Offshore Jac...</td>\n",
" <td>JOURNAL OF OCEAN UNIVERSITY OF CHINA</td>\n",
" <td>...</td>\n",
" <td>0</td>\n",
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" <td>16725182</td>\n",
" <td>Applied Sciences</td>\n",
" <td>Agriculture, Fisheries &amp; Forestry</td>\n",
" <td>Fisheries</td>\n",
" <td>3</td>\n",
" <td>Journal of Ocean University of China</td>\n",
" <td>6.100153e+09</td>\n",
" <td>issn2</td>\n",
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" <tr>\n",
" <th>9701</th>\n",
" <td>J</td>\n",
" <td>Li, XH; Yang, DK; Yang, JS; Zheng, G; Han, GQ;...</td>\n",
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" <td>REMOTE SENSING OF ENVIRONMENT</td>\n",
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" <td>0</td>\n",
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" <td>Applied Sciences</td>\n",
" <td>Engineering</td>\n",
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" <td>issn1</td>\n",
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" <tr>\n",
" <th>3066</th>\n",
" <td>J</td>\n",
" <td>He, Q; Zha, C; Song, W; Hao, ZZ; Du, YL; Liott...</td>\n",
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" <td>issn1</td>\n",
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" <th>5097</th>\n",
" <td>J</td>\n",
" <td>Hasan, MM; Popp, J; Olah, J</td>\n",
" <td>NaN</td>\n",
" <td>NaN</td>\n",
" <td>NaN</td>\n",
" <td>Hasan, Md Morshadul; Popp, Jozsef; Olah, Judit</td>\n",
" <td>NaN</td>\n",
" <td>NaN</td>\n",
" <td>Current landscape and influence of big data on...</td>\n",
" <td>JOURNAL OF BIG DATA</td>\n",
" <td>...</td>\n",
" <td>0</td>\n",
" <td>eissn</td>\n",
" <td>21961115</td>\n",
" <td>Applied Sciences</td>\n",
" <td>Information &amp; Communication Technologies</td>\n",
" <td>Artificial Intelligence &amp; Image Processing</td>\n",
" <td>31</td>\n",
" <td>Journal of Big Data</td>\n",
" <td>2.110079e+10</td>\n",
" <td>issn1</td>\n",
" </tr>\n",
" <tr>\n",
" <th>11369</th>\n",
" <td>J</td>\n",
" <td>Li, Y; Cheng, G; Pang, YS; Kuai, M</td>\n",
" <td>NaN</td>\n",
" <td>NaN</td>\n",
" <td>NaN</td>\n",
" <td>Li, Yong; Cheng, Gang; Pang, Yusong; Kuai, Moshen</td>\n",
" <td>NaN</td>\n",
" <td>NaN</td>\n",
" <td>Planetary Gear Fault Diagnosis via Feature Ima...</td>\n",
" <td>SENSORS</td>\n",
" <td>...</td>\n",
" <td>0</td>\n",
" <td>eissn</td>\n",
" <td>14248220</td>\n",
" <td>Natural Sciences</td>\n",
" <td>Chemistry</td>\n",
" <td>Analytical Chemistry</td>\n",
" <td>149</td>\n",
" <td>Sensors (Switzerland)</td>\n",
" <td>1.301240e+05</td>\n",
" <td>issn1</td>\n",
" </tr>\n",
" <tr>\n",
" <th>11368</th>\n",
" <td>J</td>\n",
" <td>Zeng, R; Rossiter, DG; Zhang, JP; Cai, K; Gao,...</td>\n",
" <td>NaN</td>\n",
" <td>NaN</td>\n",
" <td>NaN</td>\n",
" <td>Zeng, Rong; Rossiter, David G.; Zhang, Jiapeng...</td>\n",
" <td>NaN</td>\n",
" <td>NaN</td>\n",
" <td>How Well Can Reflectance Spectroscopy Allocate...</td>\n",
" <td>AGRONOMY-BASEL</td>\n",
" <td>...</td>\n",
" <td>0</td>\n",
" <td>eissn</td>\n",
" <td>20734395</td>\n",
" <td>Natural Sciences</td>\n",
" <td>Biology</td>\n",
" <td>Plant Biology &amp; Botany</td>\n",
" <td>147</td>\n",
" <td>Agronomy</td>\n",
" <td>2.110045e+10</td>\n",
" <td>issn1</td>\n",
" </tr>\n",
" <tr>\n",
" <th>11362</th>\n",
" <td>J</td>\n",
" <td>Jia, Y; Jin, SG; Savi, P; Gao, Y; Tang, J; Che...</td>\n",
" <td>NaN</td>\n",
" <td>NaN</td>\n",
" <td>NaN</td>\n",
" <td>Jia, Yan; Jin, Shuanggen; Savi, Patrizia; Gao,...</td>\n",
" <td>NaN</td>\n",
" <td>NaN</td>\n",
" <td>GNSS-R Soil Moisture Retrieval Based on a XGbo...</td>\n",
" <td>REMOTE SENSING</td>\n",
" <td>...</td>\n",
" <td>0</td>\n",
" <td>eissn</td>\n",
" <td>20724292</td>\n",
" <td>Applied Sciences</td>\n",
" <td>Engineering</td>\n",
" <td>Geological &amp; Geomatics Engineering</td>\n",
" <td>26</td>\n",
" <td>Remote Sensing</td>\n",
" <td>8.643000e+04</td>\n",
" <td>issn1</td>\n",
" </tr>\n",
" </tbody>\n",
"</table>\n",
"<p>8592 rows × 81 columns</p>\n",
"</div>"
],
"text/plain": [
" Publication Type Authors \n",
"0 J Salucci, M; Arrebola, M; Shan, T; Li, MK \\\n",
"9714 J Huang, Y; Fu, ZT; Franzke, CLE \n",
"9697 J Feng, DC; Cetiner, B; Kakavand, MRA; Taciroglu, E \n",
"9699 J Zhao, YL; Dong, S; Jiang, FY; Soares, CG \n",
"9701 J Li, XH; Yang, DK; Yang, JS; Zheng, G; Han, GQ;... \n",
"... ... ... \n",
"3066 J He, Q; Zha, C; Song, W; Hao, ZZ; Du, YL; Liott... \n",
"5097 J Hasan, MM; Popp, J; Olah, J \n",
"11369 J Li, Y; Cheng, G; Pang, YS; Kuai, M \n",
"11368 J Zeng, R; Rossiter, DG; Zhang, JP; Cai, K; Gao,... \n",
"11362 J Jia, Y; Jin, SG; Savi, P; Gao, Y; Tang, J; Che... \n",
"\n",
" Book Authors Book Editors Book Group Authors \n",
"0 NaN NaN NaN \\\n",
"9714 NaN NaN NaN \n",
"9697 NaN NaN NaN \n",
"9699 NaN NaN NaN \n",
"9701 NaN NaN NaN \n",
"... ... ... ... \n",
"3066 NaN NaN NaN \n",
"5097 NaN NaN NaN \n",
"11369 NaN NaN NaN \n",
"11368 NaN NaN NaN \n",
"11362 NaN NaN NaN \n",
"\n",
" Author Full Names \n",
"0 Salucci, Marco; Arrebola, Manuel; Shan, Tao; L... \\\n",
"9714 Huang, Yu; Fu, Zuntao; Franzke, Christian L. E. \n",
"9697 Feng, De-Cheng; Cetiner, Barbaros; Kakavand, M... \n",
"9699 Zhao, Yuliang; Dong, Sheng; Jiang, Fengyuan; G... \n",
"9701 Li, Xiaohui; Yang, Dongkai; Yang, Jingsong; Zh... \n",
"... ... \n",
"3066 He, Qi; Zha, Cheng; Song, Wei; Hao, Zengzhou; ... \n",
"5097 Hasan, Md Morshadul; Popp, Jozsef; Olah, Judit \n",
"11369 Li, Yong; Cheng, Gang; Pang, Yusong; Kuai, Moshen \n",
"11368 Zeng, Rong; Rossiter, David G.; Zhang, Jiapeng... \n",
"11362 Jia, Yan; Jin, Shuanggen; Savi, Patrizia; Gao,... \n",
"\n",
" Book Author Full Names Group Authors \n",
"0 NaN NaN \\\n",
"9714 NaN NaN \n",
"9697 NaN NaN \n",
"9699 NaN NaN \n",
"9701 NaN NaN \n",
"... ... ... \n",
"3066 NaN NaN \n",
"5097 NaN NaN \n",
"11369 NaN NaN \n",
"11368 NaN NaN \n",
"11362 NaN NaN \n",
"\n",
" Article Title \n",
"0 Artificial Intelligence: New Frontiers in Real... \\\n",
"9714 Detecting causality from time series in a mach... \n",
"9697 Data-Driven Approach to Predict the Plastic Hi... \n",
"9699 System Reliability Analysis of an Offshore Jac... \n",
"9701 Analysis of coastal wind speed retrieval from ... \n",
"... ... \n",
"3066 Improved Particle Swarm Optimization for Sea S... \n",
"5097 Current landscape and influence of big data on... \n",
"11369 Planetary Gear Fault Diagnosis via Feature Ima... \n",
"11368 How Well Can Reflectance Spectroscopy Allocate... \n",
"11362 GNSS-R Soil Moisture Retrieval Based on a XGbo... \n",
"\n",
" Source Title ... \n",
"0 IEEE TRANSACTIONS ON ANTENNAS AND PROPAGATION ... \\\n",
"9714 CHAOS ... \n",
"9697 JOURNAL OF STRUCTURAL ENGINEERING ... \n",
"9699 JOURNAL OF OCEAN UNIVERSITY OF CHINA ... \n",
"9701 REMOTE SENSING OF ENVIRONMENT ... \n",
"... ... ... \n",
"3066 ENERGIES ... \n",
"5097 JOURNAL OF BIG DATA ... \n",
"11369 SENSORS ... \n",
"11368 AGRONOMY-BASEL ... \n",
"11362 REMOTE SENSING ... \n",
"\n",
" Web of Science Record issn_var issn Domain_English \n",
"0 0 issn 0018926x Applied Sciences \\\n",
"9714 0 issn 10541500 Natural Sciences \n",
"9697 0 issn 07339445 Applied Sciences \n",
"9699 0 issn 16725182 Applied Sciences \n",
"9701 0 issn 00344257 Applied Sciences \n",
"... ... ... ... ... \n",
"3066 0 eissn 19961073 Applied Sciences \n",
"5097 0 eissn 21961115 Applied Sciences \n",
"11369 0 eissn 14248220 Natural Sciences \n",
"11368 0 eissn 20734395 Natural Sciences \n",
"11362 0 eissn 20724292 Applied Sciences \n",
"\n",
" Field_English \n",
"0 Information & Communication Technologies \\\n",
"9714 Physics & Astronomy \n",
"9697 Engineering \n",
"9699 Agriculture, Fisheries & Forestry \n",
"9701 Engineering \n",
"... ... \n",
"3066 Enabling & Strategic Technologies \n",
"5097 Information & Communication Technologies \n",
"11369 Chemistry \n",
"11368 Biology \n",
"11362 Engineering \n",
"\n",
" SubField_English 2.00 SEQ \n",
"0 Networking & Telecommunications 37 \\\n",
"9714 Fluids & Plasmas 170 \n",
"9697 Civil Engineering 23 \n",
"9699 Fisheries 3 \n",
"9701 Geological & Geomatics Engineering 26 \n",
"... ... ... \n",
"3066 Energy 14 \n",
"5097 Artificial Intelligence & Image Processing 31 \n",
"11369 Analytical Chemistry 149 \n",
"11368 Plant Biology & Botany 147 \n",
"11362 Geological & Geomatics Engineering 26 \n",
"\n",
" Source_title srcid \n",
"0 IEEE Transactions on Antennas and Propagation 1.733700e+04 \\\n",
"9714 Chaos 2.743000e+04 \n",
"9697 Journal of Structural Engineering (United States) 1.630500e+04 \n",
"9699 Journal of Ocean University of China 6.100153e+09 \n",
"9701 Remote Sensing of Environment 1.250300e+04 \n",
"... ... ... \n",
"3066 Energies 6.293200e+04 \n",
"5097 Journal of Big Data 2.110079e+10 \n",
"11369 Sensors (Switzerland) 1.301240e+05 \n",
"11368 Agronomy 2.110045e+10 \n",
"11362 Remote Sensing 8.643000e+04 \n",
"\n",
" issn_type \n",
"0 issn1 \n",
"9714 issn2 \n",
"9697 issn1 \n",
"9699 issn2 \n",
"9701 issn1 \n",
"... ... \n",
"3066 issn1 \n",
"5097 issn1 \n",
"11369 issn1 \n",
"11368 issn1 \n",
"11362 issn1 \n",
"\n",
"[8592 rows x 81 columns]"
]
},
"execution_count": 97,
"metadata": {},
"output_type": "execute_result"
}
],
"source": [
"wos"
]
},
{
"cell_type": "code",
"execution_count": 98,
"metadata": {},
"outputs": [
{
"data": {
"text/plain": [
"['Domain_English', 'Field_English', 'SubField_English']"
]
},
"execution_count": 98,
"metadata": {},
"output_type": "execute_result"
}
],
"source": [
"metrix_levels"
]
},
{
"cell_type": "code",
"execution_count": 134,
"metadata": {},
"outputs": [],
"source": [
"outdir=\"wos_processed_data\"\n",
"os.makedirs(outdir, exist_ok=True)\n",
"\n",
"wos.to_excel(f\"{outdir}/wos_processed.xlsx\", index=False)\n",
"\n",
"locations.drop(columns=\"Addresses\").to_excel(f\"{outdir}/wos_addresses.xlsx\", index=False)\n",
"\n",
"affiliations_merge.to_excel(f\"{outdir}/wos_affiliations.xlsx\", index=False)\n",
"\n",
"author_locations.to_excel(f\"{outdir}/wos_author_locations.xlsx\", index=False)\n",
"\n",
"univ_locations.to_excel(f\"{outdir}/wos_univ_locations.xlsx\", index=False)"
]
},
{
"cell_type": "markdown",
"metadata": {},
"source": [
"# Domain"
]
},
{
"cell_type": "code",
"execution_count": 31,
"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>Domain_English</th>\n",
" <th>UT (Unique WOS ID)</th>\n",
" </tr>\n",
" </thead>\n",
" <tbody>\n",
" <tr>\n",
" <th>0</th>\n",
" <td>Applied Sciences</td>\n",
" <td>5379</td>\n",
" </tr>\n",
" <tr>\n",
" <th>5</th>\n",
" <td>Natural Sciences</td>\n",
" <td>1649</td>\n",
" </tr>\n",
" <tr>\n",
" <th>3</th>\n",
" <td>Health Sciences</td>\n",
" <td>1106</td>\n",
" </tr>\n",
" <tr>\n",
" <th>2</th>\n",
" <td>Economic &amp; Social Sciences</td>\n",
" <td>289</td>\n",
" </tr>\n",
" <tr>\n",
" <th>4</th>\n",
" <td>Miscellaneous</td>\n",
" <td>156</td>\n",
" </tr>\n",
" <tr>\n",
" <th>1</th>\n",
" <td>Arts &amp; Humanities</td>\n",
" <td>13</td>\n",
" </tr>\n",
" </tbody>\n",
"</table>\n",
"</div>"
],
"text/plain": [
" Domain_English UT (Unique WOS ID)\n",
"0 Applied Sciences 5379\n",
"5 Natural Sciences 1649\n",
"3 Health Sciences 1106\n",
"2 Economic & Social Sciences 289\n",
"4 Miscellaneous 156\n",
"1 Arts & Humanities 13"
]
},
"execution_count": 31,
"metadata": {},
"output_type": "execute_result"
}
],
"source": [
"group = 'Domain_English'\n",
"data = wos.groupby(group, as_index=False)[record_col].nunique().sort_values(ascending=False, by=record_col)\n",
"data"
]
},
{
"cell_type": "code",
"execution_count": 32,
"metadata": {},
"outputs": [
{
"data": {
"text/plain": [
"<Axes: xlabel='UT (Unique WOS ID)', ylabel='Domain_English'>"
]
},
"execution_count": 32,
"metadata": {},
"output_type": "execute_result"
},
{
"data": {
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"text/plain": [
"<Figure size 640x480 with 1 Axes>"
]
},
"metadata": {},
"output_type": "display_data"
}
],
"source": [
"sns.barplot(data, x=record_col, y=group)"
]
},
{
"cell_type": "code",
"execution_count": 33,
"metadata": {},
"outputs": [],
"source": [
"# group = ['Publication Year','Domain_English']\n",
"# data = wos.groupby(group, as_index=False)[record_col].nunique().sort_values(ascending=False, by=group+[record_col])\n",
"# data"
]
},
{
"cell_type": "code",
"execution_count": 34,
"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>Publication Year</th>\n",
" <th>Domain_English</th>\n",
" <th>UT (Unique WOS ID)</th>\n",
" </tr>\n",
" </thead>\n",
" <tbody>\n",
" <tr>\n",
" <th>65</th>\n",
" <td>2022.0</td>\n",
" <td>Natural Sciences</td>\n",
" <td>524</td>\n",
" </tr>\n",
" <tr>\n",
" <th>64</th>\n",
" <td>2022.0</td>\n",
" <td>Miscellaneous</td>\n",
" <td>41</td>\n",
" </tr>\n",
" <tr>\n",
" <th>63</th>\n",
" <td>2022.0</td>\n",
" <td>Health Sciences</td>\n",
" <td>368</td>\n",
" </tr>\n",
" <tr>\n",
" <th>62</th>\n",
" <td>2022.0</td>\n",
" <td>Economic &amp; Social Sciences</td>\n",
" <td>106</td>\n",
" </tr>\n",
" <tr>\n",
" <th>61</th>\n",
" <td>2022.0</td>\n",
" <td>Arts &amp; Humanities</td>\n",
" <td>4</td>\n",
" </tr>\n",
" <tr>\n",
" <th>...</th>\n",
" <td>...</td>\n",
" <td>...</td>\n",
" <td>...</td>\n",
" </tr>\n",
" <tr>\n",
" <th>4</th>\n",
" <td>2012.0</td>\n",
" <td>Miscellaneous</td>\n",
" <td>3</td>\n",
" </tr>\n",
" <tr>\n",
" <th>3</th>\n",
" <td>2012.0</td>\n",
" <td>Health Sciences</td>\n",
" <td>2</td>\n",
" </tr>\n",
" <tr>\n",
" <th>2</th>\n",
" <td>2012.0</td>\n",
" <td>Economic &amp; Social Sciences</td>\n",
" <td>0</td>\n",
" </tr>\n",
" <tr>\n",
" <th>1</th>\n",
" <td>2012.0</td>\n",
" <td>Arts &amp; Humanities</td>\n",
" <td>0</td>\n",
" </tr>\n",
" <tr>\n",
" <th>0</th>\n",
" <td>2012.0</td>\n",
" <td>Applied Sciences</td>\n",
" <td>21</td>\n",
" </tr>\n",
" </tbody>\n",
"</table>\n",
"<p>66 rows × 3 columns</p>\n",
"</div>"
],
"text/plain": [
" Publication Year Domain_English UT (Unique WOS ID)\n",
"65 2022.0 Natural Sciences 524\n",
"64 2022.0 Miscellaneous 41\n",
"63 2022.0 Health Sciences 368\n",
"62 2022.0 Economic & Social Sciences 106\n",
"61 2022.0 Arts & Humanities 4\n",
".. ... ... ...\n",
"4 2012.0 Miscellaneous 3\n",
"3 2012.0 Health Sciences 2\n",
"2 2012.0 Economic & Social Sciences 0\n",
"1 2012.0 Arts & Humanities 0\n",
"0 2012.0 Applied Sciences 21\n",
"\n",
"[66 rows x 3 columns]"
]
},
"execution_count": 34,
"metadata": {},
"output_type": "execute_result"
}
],
"source": [
"group = ['Publication Year','Domain_English']\n",
"data = wos.groupby(group)[record_col].nunique().unstack(fill_value=0).stack().reset_index().rename(columns={0:record_col}).sort_values(ascending=False, by=group+[record_col])\n",
"data"
]
},
{
"cell_type": "code",
"execution_count": 35,
"metadata": {},
"outputs": [
{
"data": {
"text/plain": [
"<matplotlib.legend.Legend at 0x1909ff98d30>"
]
},
"execution_count": 35,
"metadata": {},
"output_type": "execute_result"
},
{
"data": {
"image/png": "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
"text/plain": [
"<Figure size 640x480 with 1 Axes>"
]
},
"metadata": {},
"output_type": "display_data"
}
],
"source": [
"g=sns.lineplot(data.sort_values(ascending=True, by=group[-1]),y=record_col,x=group[0], hue=group[-1])\n",
"g.set(xticks=list(range(2012,2022+1,2)))\n",
"g.legend(title=None)"
]
},
{
"cell_type": "markdown",
"metadata": {},
"source": [
"# Field"
]
},
{
"cell_type": "code",
"execution_count": 65,
"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>Publication Year</th>\n",
" <th>Domain_English</th>\n",
" <th>Field_English</th>\n",
" <th>UT (Unique WOS ID)</th>\n",
" </tr>\n",
" </thead>\n",
" <tbody>\n",
" <tr>\n",
" <th>176</th>\n",
" <td>2022.0</td>\n",
" <td>Natural Sciences</td>\n",
" <td>Physics &amp; Astronomy</td>\n",
" <td>205</td>\n",
" </tr>\n",
" <tr>\n",
" <th>175</th>\n",
" <td>2022.0</td>\n",
" <td>Natural Sciences</td>\n",
" <td>Mathematics &amp; Statistics</td>\n",
" <td>61</td>\n",
" </tr>\n",
" <tr>\n",
" <th>174</th>\n",
" <td>2022.0</td>\n",
" <td>Natural Sciences</td>\n",
" <td>Earth &amp; Environmental Sciences</td>\n",
" <td>134</td>\n",
" </tr>\n",
" <tr>\n",
" <th>173</th>\n",
" <td>2022.0</td>\n",
" <td>Natural Sciences</td>\n",
" <td>Chemistry</td>\n",
" <td>81</td>\n",
" </tr>\n",
" <tr>\n",
" <th>172</th>\n",
" <td>2022.0</td>\n",
" <td>Natural Sciences</td>\n",
" <td>Biology</td>\n",
" <td>43</td>\n",
" </tr>\n",
" <tr>\n",
" <th>...</th>\n",
" <td>...</td>\n",
" <td>...</td>\n",
" <td>...</td>\n",
" <td>...</td>\n",
" </tr>\n",
" <tr>\n",
" <th>4</th>\n",
" <td>2012.0</td>\n",
" <td>Miscellaneous</td>\n",
" <td>Miscellaneous</td>\n",
" <td>3</td>\n",
" </tr>\n",
" <tr>\n",
" <th>3</th>\n",
" <td>2012.0</td>\n",
" <td>Health Sciences</td>\n",
" <td>Clinical Medicine</td>\n",
" <td>2</td>\n",
" </tr>\n",
" <tr>\n",
" <th>2</th>\n",
" <td>2012.0</td>\n",
" <td>Applied Sciences</td>\n",
" <td>Information &amp; Communication Technologies</td>\n",
" <td>14</td>\n",
" </tr>\n",
" <tr>\n",
" <th>1</th>\n",
" <td>2012.0</td>\n",
" <td>Applied Sciences</td>\n",
" <td>Engineering</td>\n",
" <td>5</td>\n",
" </tr>\n",
" <tr>\n",
" <th>0</th>\n",
" <td>2012.0</td>\n",
" <td>Applied Sciences</td>\n",
" <td>Agriculture, Fisheries &amp; Forestry</td>\n",
" <td>2</td>\n",
" </tr>\n",
" </tbody>\n",
"</table>\n",
"<p>177 rows × 4 columns</p>\n",
"</div>"
],
"text/plain": [
" Publication Year Domain_English \n",
"176 2022.0 Natural Sciences \\\n",
"175 2022.0 Natural Sciences \n",
"174 2022.0 Natural Sciences \n",
"173 2022.0 Natural Sciences \n",
"172 2022.0 Natural Sciences \n",
".. ... ... \n",
"4 2012.0 Miscellaneous \n",
"3 2012.0 Health Sciences \n",
"2 2012.0 Applied Sciences \n",
"1 2012.0 Applied Sciences \n",
"0 2012.0 Applied Sciences \n",
"\n",
" Field_English UT (Unique WOS ID) \n",
"176 Physics & Astronomy 205 \n",
"175 Mathematics & Statistics 61 \n",
"174 Earth & Environmental Sciences 134 \n",
"173 Chemistry 81 \n",
"172 Biology 43 \n",
".. ... ... \n",
"4 Miscellaneous 3 \n",
"3 Clinical Medicine 2 \n",
"2 Information & Communication Technologies 14 \n",
"1 Engineering 5 \n",
"0 Agriculture, Fisheries & Forestry 2 \n",
"\n",
"[177 rows x 4 columns]"
]
},
"execution_count": 65,
"metadata": {},
"output_type": "execute_result"
}
],
"source": [
"group = ['Publication Year',\"Domain_English\",'Field_English']\n",
"data = wos.groupby(group, as_index=False)[record_col].nunique().sort_values(ascending=False, by=group+[record_col])\n",
"data"
]
},
{
"cell_type": "code",
"execution_count": null,
"metadata": {},
"outputs": [],
"source": []
},
{
"cell_type": "code",
"execution_count": 37,
"metadata": {},
"outputs": [],
"source": [
"# g = sns.FacetGrid(data, col=\"Domain_English\", col_wrap=3, height=5)\n",
"# g.map_dataframe(sns.lineplot,x=group[0],y=record_col,hue=group[-1])\n",
"# g.set_titles(col_template=\"{col_name}\")\n",
"# g.set(xticks=list(range(2012,2022+1,2)))\n",
"# # g.add_legend()"
]
},
{
"cell_type": "code",
"execution_count": 66,
"metadata": {},
"outputs": [
{
"data": {
"image/png": "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
"text/plain": [
"<Figure size 640x480 with 1 Axes>"
]
},
"metadata": {},
"output_type": "display_data"
},
{
"data": {
"image/png": "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
"text/plain": [
"<Figure size 640x480 with 1 Axes>"
]
},
"metadata": {},
"output_type": "display_data"
},
{
"data": {
"image/png": "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
"text/plain": [
"<Figure size 640x480 with 1 Axes>"
]
},
"metadata": {},
"output_type": "display_data"
},
{
"data": {
"image/png": "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
"text/plain": [
"<Figure size 640x480 with 1 Axes>"
]
},
"metadata": {},
"output_type": "display_data"
},
{
"data": {
"image/png": "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
"text/plain": [
"<Figure size 640x480 with 1 Axes>"
]
},
"metadata": {},
"output_type": "display_data"
},
{
"data": {
"image/png": "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
"text/plain": [
"<Figure size 640x480 with 1 Axes>"
]
},
"metadata": {},
"output_type": "display_data"
}
],
"source": [
"import matplotlib.pyplot as plt\n",
"for cat in sorted(data[group[-2]].unique()):\n",
" sub_data = data[data[group[-2]]==cat]\n",
" sub_data = sub_data.complete({group[0]:range(int(data[group[0]].min()), int(data[group[0]].max()) + 1)}\n",
" ,group[-1],fill_value=0)\n",
" g=sns.lineplot(sub_data.sort_values(ascending=True, by=group[-1]),y=record_col,x=group[0], hue=group[-1])\n",
" g.set(xticks=list(range(2012,2022+1,2)))\n",
" g.legend(title=None)\n",
" g.set_title(cat)\n",
" g.yaxis.set_major_locator(MaxNLocator(integer=True))\n",
" plt.show()"
]
},
{
"cell_type": "markdown",
"metadata": {},
"source": [
"# SubField"
]
},
{
"cell_type": "code",
"execution_count": 68,
"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>Publication Year</th>\n",
" <th>Domain_English</th>\n",
" <th>Field_English</th>\n",
" <th>SubField_English</th>\n",
" <th>UT (Unique WOS ID)</th>\n",
" </tr>\n",
" </thead>\n",
" <tbody>\n",
" <tr>\n",
" <th>774</th>\n",
" <td>2022.0</td>\n",
" <td>Natural Sciences</td>\n",
" <td>Physics &amp; Astronomy</td>\n",
" <td>Optics</td>\n",
" <td>56</td>\n",
" </tr>\n",
" <tr>\n",
" <th>773</th>\n",
" <td>2022.0</td>\n",
" <td>Natural Sciences</td>\n",
" <td>Physics &amp; Astronomy</td>\n",
" <td>Nuclear &amp; Particle Physics</td>\n",
" <td>28</td>\n",
" </tr>\n",
" <tr>\n",
" <th>772</th>\n",
" <td>2022.0</td>\n",
" <td>Natural Sciences</td>\n",
" <td>Physics &amp; Astronomy</td>\n",
" <td>Mathematical Physics</td>\n",
" <td>2</td>\n",
" </tr>\n",
" <tr>\n",
" <th>771</th>\n",
" <td>2022.0</td>\n",
" <td>Natural Sciences</td>\n",
" <td>Physics &amp; Astronomy</td>\n",
" <td>General Physics</td>\n",
" <td>14</td>\n",
" </tr>\n",
" <tr>\n",
" <th>770</th>\n",
" <td>2022.0</td>\n",
" <td>Natural Sciences</td>\n",
" <td>Physics &amp; Astronomy</td>\n",
" <td>Fluids &amp; Plasmas</td>\n",
" <td>21</td>\n",
" </tr>\n",
" <tr>\n",
" <th>...</th>\n",
" <td>...</td>\n",
" <td>...</td>\n",
" <td>...</td>\n",
" <td>...</td>\n",
" <td>...</td>\n",
" </tr>\n",
" <tr>\n",
" <th>4</th>\n",
" <td>2012.0</td>\n",
" <td>Applied Sciences</td>\n",
" <td>Information &amp; Communication Technologies</td>\n",
" <td>Artificial Intelligence &amp; Image Processing</td>\n",
" <td>10</td>\n",
" </tr>\n",
" <tr>\n",
" <th>3</th>\n",
" <td>2012.0</td>\n",
" <td>Applied Sciences</td>\n",
" <td>Engineering</td>\n",
" <td>Mechanical Engineering &amp; Transports</td>\n",
" <td>1</td>\n",
" </tr>\n",
" <tr>\n",
" <th>2</th>\n",
" <td>2012.0</td>\n",
" <td>Applied Sciences</td>\n",
" <td>Engineering</td>\n",
" <td>Industrial Engineering &amp; Automation</td>\n",
" <td>3</td>\n",
" </tr>\n",
" <tr>\n",
" <th>1</th>\n",
" <td>2012.0</td>\n",
" <td>Applied Sciences</td>\n",
" <td>Engineering</td>\n",
" <td>Geological &amp; Geomatics Engineering</td>\n",
" <td>1</td>\n",
" </tr>\n",
" <tr>\n",
" <th>0</th>\n",
" <td>2012.0</td>\n",
" <td>Applied Sciences</td>\n",
" <td>Agriculture, Fisheries &amp; Forestry</td>\n",
" <td>Food Science</td>\n",
" <td>2</td>\n",
" </tr>\n",
" </tbody>\n",
"</table>\n",
"<p>775 rows × 5 columns</p>\n",
"</div>"
],
"text/plain": [
" Publication Year Domain_English \n",
"774 2022.0 Natural Sciences \\\n",
"773 2022.0 Natural Sciences \n",
"772 2022.0 Natural Sciences \n",
"771 2022.0 Natural Sciences \n",
"770 2022.0 Natural Sciences \n",
".. ... ... \n",
"4 2012.0 Applied Sciences \n",
"3 2012.0 Applied Sciences \n",
"2 2012.0 Applied Sciences \n",
"1 2012.0 Applied Sciences \n",
"0 2012.0 Applied Sciences \n",
"\n",
" Field_English \n",
"774 Physics & Astronomy \\\n",
"773 Physics & Astronomy \n",
"772 Physics & Astronomy \n",
"771 Physics & Astronomy \n",
"770 Physics & Astronomy \n",
".. ... \n",
"4 Information & Communication Technologies \n",
"3 Engineering \n",
"2 Engineering \n",
"1 Engineering \n",
"0 Agriculture, Fisheries & Forestry \n",
"\n",
" SubField_English UT (Unique WOS ID) \n",
"774 Optics 56 \n",
"773 Nuclear & Particle Physics 28 \n",
"772 Mathematical Physics 2 \n",
"771 General Physics 14 \n",
"770 Fluids & Plasmas 21 \n",
".. ... ... \n",
"4 Artificial Intelligence & Image Processing 10 \n",
"3 Mechanical Engineering & Transports 1 \n",
"2 Industrial Engineering & Automation 3 \n",
"1 Geological & Geomatics Engineering 1 \n",
"0 Food Science 2 \n",
"\n",
"[775 rows x 5 columns]"
]
},
"execution_count": 68,
"metadata": {},
"output_type": "execute_result"
}
],
"source": [
"group = ['Publication Year',\"Domain_English\",'Field_English',\"SubField_English\"]\n",
"data = wos.groupby(group, as_index=False)[record_col].nunique().sort_values(ascending=False, by=group+[record_col])\n",
"data"
]
},
{
"cell_type": "code",
"execution_count": 69,
"metadata": {},
"outputs": [
{
"data": {
"image/png": "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
"text/plain": [
"<Figure size 640x480 with 1 Axes>"
]
},
"metadata": {},
"output_type": "display_data"
},
{
"data": {
"image/png": "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
"text/plain": [
"<Figure size 640x480 with 1 Axes>"
]
},
"metadata": {},
"output_type": "display_data"
},
{
"data": {
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"text/plain": [
"<Figure size 640x480 with 1 Axes>"
]
},
"metadata": {},
"output_type": "display_data"
},
{
"data": {
"image/png": "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
"text/plain": [
"<Figure size 640x480 with 1 Axes>"
]
},
"metadata": {},
"output_type": "display_data"
},
{
"data": {
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"text/plain": [
"<Figure size 640x480 with 1 Axes>"
]
},
"metadata": {},
"output_type": "display_data"
},
{
"data": {
"image/png": "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
"text/plain": [
"<Figure size 640x480 with 1 Axes>"
]
},
"metadata": {},
"output_type": "display_data"
},
{
"data": {
"image/png": "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
"text/plain": [
"<Figure size 640x480 with 1 Axes>"
]
},
"metadata": {},
"output_type": "display_data"
},
{
"data": {
"image/png": "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
"text/plain": [
"<Figure size 640x480 with 1 Axes>"
]
},
"metadata": {},
"output_type": "display_data"
},
{
"data": {
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"text/plain": [
"<Figure size 640x480 with 1 Axes>"
]
},
"metadata": {},
"output_type": "display_data"
},
{
"data": {
"image/png": "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
"text/plain": [
"<Figure size 640x480 with 1 Axes>"
]
},
"metadata": {},
"output_type": "display_data"
},
{
"data": {
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"text/plain": [
"<Figure size 640x480 with 1 Axes>"
]
},
"metadata": {},
"output_type": "display_data"
},
{
"data": {
"image/png": "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
"text/plain": [
"<Figure size 640x480 with 1 Axes>"
]
},
"metadata": {},
"output_type": "display_data"
},
{
"data": {
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"text/plain": [
"<Figure size 640x480 with 1 Axes>"
]
},
"metadata": {},
"output_type": "display_data"
},
{
"data": {
"image/png": "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
"text/plain": [
"<Figure size 640x480 with 1 Axes>"
]
},
"metadata": {},
"output_type": "display_data"
},
{
"data": {
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"text/plain": [
"<Figure size 640x480 with 1 Axes>"
]
},
"metadata": {},
"output_type": "display_data"
},
{
"data": {
"image/png": "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
"text/plain": [
"<Figure size 640x480 with 1 Axes>"
]
},
"metadata": {},
"output_type": "display_data"
},
{
"data": {
"image/png": "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
"text/plain": [
"<Figure size 640x480 with 1 Axes>"
]
},
"metadata": {},
"output_type": "display_data"
},
{
"data": {
"image/png": "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
"text/plain": [
"<Figure size 640x480 with 1 Axes>"
]
},
"metadata": {},
"output_type": "display_data"
},
{
"data": {
"image/png": "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
"text/plain": [
"<Figure size 640x480 with 1 Axes>"
]
},
"metadata": {},
"output_type": "display_data"
},
{
"data": {
"image/png": "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
"text/plain": [
"<Figure size 640x480 with 1 Axes>"
]
},
"metadata": {},
"output_type": "display_data"
}
],
"source": [
"import matplotlib.pyplot as plt\n",
"for cat in sorted(data[group[-2]].unique()):\n",
" sub_data = data[data[group[-2]]==cat]\n",
" sub_data = sub_data.complete({group[0]:range(int(data[group[0]].min()), int(data[group[0]].max()) + 1)}\n",
" ,group[-1],fill_value=0)\n",
" g=sns.lineplot(sub_data.sort_values(ascending=True, by=group[-1]),y=record_col,x=group[0], hue=group[-1])\n",
" g.set(xticks=list(range(2012,2022+1,2)))\n",
" g.legend(title=None,bbox_to_anchor=(1.05, 1), loc=2, borderaxespad=0., ncols=math.ceil(len(g.legend_.texts)/12))\n",
" g.set_title(cat)\n",
" plt.show()"
]
}
],
"metadata": {
"kernelspec": {
"display_name": "Python 3 (ipykernel)",
"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": "3.9.16"
}
},
"nbformat": 4,
"nbformat_minor": 1
}