{
"cells": [
{
"cell_type": "markdown",
"metadata": {},
"source": [
"# <span style=\"color:orange\">Clustering sur les données du Baromètre lorrain de la Science Ouverte</span>"
]
},
{
"cell_type": "markdown",
"metadata": {},
"source": [
"Le clustering, ou partitionnement des données, est une méthode d'analyse permettant de rassembler des données dans des \"paquets\", afin d'identifier des relations, des tendances. Ici, l'objectif est de voir s'il existe une corrélation entre le nombre de publications et leur taux d'accès ouvert, ou encore une corrélation entre accès ouvert et discipline.\n",
"\n",
"**Il faut remplacer \"lorraine\" par le nom de l'établissement directement dans le code ci-dessous. Vous pouvez faire ctrl+f pour modifier toutes les occurrences d'un coup.**\n",
"\n",
"En cas d'erreur \"module seaborn inexistant\", saisir la commande suivante : %pip install seaborn"
]
},
{
"cell_type": "code",
"execution_count": 1,
"metadata": {},
"outputs": [],
"source": [
"# Importer les librairies nécessaires\n",
"%matplotlib inline\n",
"import matplotlib.pyplot as plt\n",
"import pandas as pd"
]
},
{
"cell_type": "code",
"execution_count": 2,
"metadata": {},
"outputs": [],
"source": [
"import seaborn as sns"
]
},
{
"cell_type": "markdown",
"metadata": {},
"source": [
"Importer le jeu de données avec lequel on souhaite travailler (changer la partie \"lorraine\" en fonction de l'établissement) :"
]
},
{
"cell_type": "code",
"execution_count": 3,
"metadata": {},
"outputs": [],
"source": [
"publis_lorraine_df = pd.read_csv(\"Data/outputs/publis_lorraine_completes.csv\")"
]
},
{
"cell_type": "markdown",
"metadata": {},
"source": [
"Restreindre à l'année souhaitée (modifier l'année pour les mises à jour) :"
]
},
{
"cell_type": "code",
"execution_count": 4,
"metadata": {},
"outputs": [],
"source": [
"publications_2019 = publis_lorraine_df.loc[publis_lorraine_df['published_year'] == 2019.0,:]"
]
},
{
"cell_type": "markdown",
"metadata": {},
"source": [
"Créer une DataFrame avec deux informations : le nombre de publications dans l'année en fonction de la discipline, et le nombre de publications en accès ouvert dans ces mêmes disciplines."
]
},
{
"cell_type": "code",
"execution_count": 5,
"metadata": {},
"outputs": [],
"source": [
"publications_par_domaine = publications_2019['scientific_field'].value_counts().sort_index()\n",
"publications_par_domaine = publications_par_domaine.to_frame()"
]
},
{
"cell_type": "code",
"execution_count": 6,
"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>scientific_field</th>\n",
" </tr>\n",
" </thead>\n",
" <tbody>\n",
" <tr>\n",
" <td>Biology (fond.)</td>\n",
" <td>333</td>\n",
" </tr>\n",
" <tr>\n",
" <td>Chemistry</td>\n",
" <td>162</td>\n",
" </tr>\n",
" <tr>\n",
" <td>Computer and \\n information sciences</td>\n",
" <td>274</td>\n",
" </tr>\n",
" <tr>\n",
" <td>Earth, Ecology, \\nEnergy and applied biology</td>\n",
" <td>241</td>\n",
" </tr>\n",
" <tr>\n",
" <td>Engineering</td>\n",
" <td>98</td>\n",
" </tr>\n",
" <tr>\n",
" <td>Humanities</td>\n",
" <td>76</td>\n",
" </tr>\n",
" <tr>\n",
" <td>Mathematics</td>\n",
" <td>130</td>\n",
" </tr>\n",
" <tr>\n",
" <td>Medical research</td>\n",
" <td>455</td>\n",
" </tr>\n",
" <tr>\n",
" <td>Physical sciences, Astronomy</td>\n",
" <td>376</td>\n",
" </tr>\n",
" <tr>\n",
" <td>Social sciences</td>\n",
" <td>82</td>\n",
" </tr>\n",
" <tr>\n",
" <td>unknown</td>\n",
" <td>1</td>\n",
" </tr>\n",
" </tbody>\n",
"</table>\n",
"</div>"
],
"text/plain": [
" scientific_field\n",
"Biology (fond.) 333\n",
"Chemistry 162\n",
"Computer and \\n information sciences 274\n",
"Earth, Ecology, \\nEnergy and applied biology 241\n",
"Engineering 98\n",
"Humanities 76\n",
"Mathematics 130\n",
"Medical research 455\n",
"Physical sciences, Astronomy 376\n",
"Social sciences 82\n",
"unknown 1"
]
},
"execution_count": 6,
"metadata": {},
"output_type": "execute_result"
}
],
"source": [
"publications_en_oa = publications_2019.loc[publications_2019['is_oa']==True,:]\n",
"publications_en_oa = publications_en_oa['scientific_field'].value_counts().sort_index()\n",
"publications_en_oa = publications_en_oa.to_frame()\n",
"publications_en_oa"
]
},
{
"cell_type": "code",
"execution_count": 7,
"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>Nombre total de publications</th>\n",
" <th>Nb de publications en accès ouvert</th>\n",
" <th>Disciplines</th>\n",
" <th>Pourcentage d'accès ouvert</th>\n",
" </tr>\n",
" <tr>\n",
" <th>Disciplines</th>\n",
" <th></th>\n",
" <th></th>\n",
" <th></th>\n",
" <th></th>\n",
" </tr>\n",
" </thead>\n",
" <tbody>\n",
" <tr>\n",
" <td>Biology (fond.)</td>\n",
" <td>566</td>\n",
" <td>333</td>\n",
" <td>Biology (fond.)</td>\n",
" <td>58.8</td>\n",
" </tr>\n",
" <tr>\n",
" <td>Chemistry</td>\n",
" <td>375</td>\n",
" <td>162</td>\n",
" <td>Chemistry</td>\n",
" <td>43.2</td>\n",
" </tr>\n",
" <tr>\n",
" <td>Computer and \\n information sciences</td>\n",
" <td>491</td>\n",
" <td>274</td>\n",
" <td>Computer and \\n information sciences</td>\n",
" <td>55.8</td>\n",
" </tr>\n",
" <tr>\n",
" <td>Earth, Ecology, \\nEnergy and applied biology</td>\n",
" <td>447</td>\n",
" <td>241</td>\n",
" <td>Earth, Ecology, \\nEnergy and applied biology</td>\n",
" <td>53.9</td>\n",
" </tr>\n",
" <tr>\n",
" <td>Engineering</td>\n",
" <td>215</td>\n",
" <td>98</td>\n",
" <td>Engineering</td>\n",
" <td>45.6</td>\n",
" </tr>\n",
" <tr>\n",
" <td>Humanities</td>\n",
" <td>140</td>\n",
" <td>76</td>\n",
" <td>Humanities</td>\n",
" <td>54.3</td>\n",
" </tr>\n",
" <tr>\n",
" <td>Mathematics</td>\n",
" <td>176</td>\n",
" <td>130</td>\n",
" <td>Mathematics</td>\n",
" <td>73.9</td>\n",
" </tr>\n",
" <tr>\n",
" <td>Medical research</td>\n",
" <td>985</td>\n",
" <td>455</td>\n",
" <td>Medical research</td>\n",
" <td>46.2</td>\n",
" </tr>\n",
" <tr>\n",
" <td>Physical sciences, Astronomy</td>\n",
" <td>661</td>\n",
" <td>376</td>\n",
" <td>Physical sciences, Astronomy</td>\n",
" <td>56.9</td>\n",
" </tr>\n",
" <tr>\n",
" <td>Social sciences</td>\n",
" <td>153</td>\n",
" <td>82</td>\n",
" <td>Social sciences</td>\n",
" <td>53.6</td>\n",
" </tr>\n",
" </tbody>\n",
"</table>\n",
"</div>"
],
"text/plain": [
" Nombre total de publications \\\n",
"Disciplines \n",
"Biology (fond.) 566 \n",
"Chemistry 375 \n",
"Computer and \\n information sciences 491 \n",
"Earth, Ecology, \\nEnergy and applied biology 447 \n",
"Engineering 215 \n",
"Humanities 140 \n",
"Mathematics 176 \n",
"Medical research 985 \n",
"Physical sciences, Astronomy 661 \n",
"Social sciences 153 \n",
"\n",
" Nb de publications en accès ouvert \\\n",
"Disciplines \n",
"Biology (fond.) 333 \n",
"Chemistry 162 \n",
"Computer and \\n information sciences 274 \n",
"Earth, Ecology, \\nEnergy and applied biology 241 \n",
"Engineering 98 \n",
"Humanities 76 \n",
"Mathematics 130 \n",
"Medical research 455 \n",
"Physical sciences, Astronomy 376 \n",
"Social sciences 82 \n",
"\n",
" Disciplines \\\n",
"Disciplines \n",
"Biology (fond.) Biology (fond.) \n",
"Chemistry Chemistry \n",
"Computer and \\n information sciences Computer and \\n information sciences \n",
"Earth, Ecology, \\nEnergy and applied biology Earth, Ecology, \\nEnergy and applied biology \n",
"Engineering Engineering \n",
"Humanities Humanities \n",
"Mathematics Mathematics \n",
"Medical research Medical research \n",
"Physical sciences, Astronomy Physical sciences, Astronomy \n",
"Social sciences Social sciences \n",
"\n",
" Pourcentage d'accès ouvert \n",
"Disciplines \n",
"Biology (fond.) 58.8 \n",
"Chemistry 43.2 \n",
"Computer and \\n information sciences 55.8 \n",
"Earth, Ecology, \\nEnergy and applied biology 53.9 \n",
"Engineering 45.6 \n",
"Humanities 54.3 \n",
"Mathematics 73.9 \n",
"Medical research 46.2 \n",
"Physical sciences, Astronomy 56.9 \n",
"Social sciences 53.6 "
]
},
"execution_count": 7,
"metadata": {},
"output_type": "execute_result"
}
],
"source": [
"publis_triees = pd.merge(publications_par_domaine, publications_en_oa, left_index = True, right_index = True)\n",
"publis_triees = publis_triees.rename(columns = {'scientific_field_x': 'Nombre total de publications', 'scientific_field_y': 'Nb de publications en accès ouvert'})\n",
"publis_triees = publis_triees.rename_axis('Disciplines')\n",
"# Ajout d'une colonne pour l'affichage des disciplines dans le graphique\n",
"publis_triees[\"Disciplines\"] = publications_en_oa.index\n",
"# Ajout d'une colonne avec le calcul des pourcentages d'accès ouvert\n",
"publis_triees[\"Pourcentage d'accès ouvert\"] = ((publis_triees[\"Nb de publications en accès ouvert\"] * 100) / publis_triees[\"Nombre total de publications\"])\n",
"# N'afficher que la première décimale pour la colonne des pourcentages\n",
"pd.set_option('precision', 1)\n",
"# Supprimer les lignes où la discipline est inconnue\n",
"indexNames = publis_triees[publis_triees['Disciplines'] == 'unknown' ].index\n",
"publis_triees.drop(indexNames , inplace=True)\n",
"publis_triees"
]
},
{
"cell_type": "code",
"execution_count": 8,
"metadata": {},
"outputs": [
{
"data": {
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\n",
"text/plain": [
"<Figure size 360x360 with 1 Axes>"
]
},
"metadata": {},
"output_type": "display_data"
}
],
"source": [
"sns.set_style(\"whitegrid\")\n",
"\n",
"facet = sns.lmplot(data=publis_triees, x='Nombre total de publications', y=\"Pourcentage d'accès ouvert\", hue='Disciplines',\n",
" fit_reg=False, legend=False, legend_out=False, palette=['red','aqua', 'blue', 'gold', 'green',\n",
" 'darkgray', 'darkviolet', 'teal', 'deeppink', 'black', 'white'],\n",
" scatter_kws={\"s\": 80})\n",
"\n",
"plt.title(\"Taux d'accès ouvert 2019 par rapport au nombre de publications, par discipline\", fontsize = 15, x = 1, y = 2,\n",
" fontweight = 'bold', alpha = 0.8)\n",
"\n",
"plt.legend(title='Disciplines', loc='best', labels=['Biologie (fond.)', 'Chimie', \n",
" 'Informatique',\n",
" 'Sciences de la Terre, Ecologie, \\nEnergie et biologie appliquée',\n",
" \"Sciences de l'Ingénieur\",\n",
" 'Humanités',\n",
" 'Mathématiques',\n",
" 'Sciences médicales',\n",
" 'Sciences physiques, astronomie',\n",
" 'Sciences sociales'], bbox_to_anchor=(1.1, 0.7))\n",
"\n",
"plt.savefig('Data/outputs/2019_rapport_oa_nb_publications.png', dpi=100, bbox_inches='tight', pad_inches=0.9)"
]
},
{
"cell_type": "markdown",
"metadata": {},
"source": [
"Répéter l'opération pour le graphique par éditeurs. Modifier l'année pour les mises à jour."
]
},
{
"cell_type": "code",
"execution_count": 9,
"metadata": {},
"outputs": [],
"source": [
"publications_par_editeur = publications_2019['publisher'].value_counts().sort_index()\n",
"publications_par_editeur = publications_par_editeur.to_frame()"
]
},
{
"cell_type": "code",
"execution_count": 10,
"metadata": {},
"outputs": [],
"source": [
"publications_en_oa_ed = publications_2019.loc[publications_2019['is_oa']==True,:]\n",
"publications_en_oa_ed = publications_en_oa_ed['publisher'].value_counts().sort_index()\n",
"publications_en_oa_ed = publications_en_oa_ed.to_frame()"
]
},
{
"cell_type": "code",
"execution_count": 13,
"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>Nombre total de publications</th>\n",
" <th>Nb de publications en accès ouvert</th>\n",
" <th>Editeurs</th>\n",
" <th>Pourcentage d'accès ouvert</th>\n",
" </tr>\n",
" <tr>\n",
" <th>Editeurs</th>\n",
" <th></th>\n",
" <th></th>\n",
" <th></th>\n",
" <th></th>\n",
" </tr>\n",
" </thead>\n",
" <tbody>\n",
" <tr>\n",
" <td>Elsevier BV</td>\n",
" <td>1227</td>\n",
" <td>468</td>\n",
" <td>Elsevier BV</td>\n",
" <td>38.1</td>\n",
" </tr>\n",
" <tr>\n",
" <td>Springer Science and Business Media LLC</td>\n",
" <td>470</td>\n",
" <td>272</td>\n",
" <td>Springer Science and Business Media LLC</td>\n",
" <td>57.9</td>\n",
" </tr>\n",
" <tr>\n",
" <td>Wiley</td>\n",
" <td>303</td>\n",
" <td>158</td>\n",
" <td>Wiley</td>\n",
" <td>52.1</td>\n",
" </tr>\n",
" <tr>\n",
" <td>Springer International Publishing</td>\n",
" <td>171</td>\n",
" <td>83</td>\n",
" <td>Springer International Publishing</td>\n",
" <td>48.5</td>\n",
" </tr>\n",
" <tr>\n",
" <td>IEEE</td>\n",
" <td>150</td>\n",
" <td>50</td>\n",
" <td>IEEE</td>\n",
" <td>33.3</td>\n",
" </tr>\n",
" <tr>\n",
" <td>MDPI AG</td>\n",
" <td>146</td>\n",
" <td>146</td>\n",
" <td>MDPI AG</td>\n",
" <td>100.0</td>\n",
" </tr>\n",
" <tr>\n",
" <td>Informa UK Limited</td>\n",
" <td>113</td>\n",
" <td>27</td>\n",
" <td>Informa UK Limited</td>\n",
" <td>23.9</td>\n",
" </tr>\n",
" <tr>\n",
" <td>IOP Publishing</td>\n",
" <td>105</td>\n",
" <td>82</td>\n",
" <td>IOP Publishing</td>\n",
" <td>78.1</td>\n",
" </tr>\n",
" <tr>\n",
" <td>American Chemical Society (ACS)</td>\n",
" <td>101</td>\n",
" <td>48</td>\n",
" <td>American Chemical Society (ACS)</td>\n",
" <td>47.5</td>\n",
" </tr>\n",
" <tr>\n",
" <td>Oxford University Press (OUP)</td>\n",
" <td>91</td>\n",
" <td>49</td>\n",
" <td>Oxford University Press (OUP)</td>\n",
" <td>53.8</td>\n",
" </tr>\n",
" </tbody>\n",
"</table>\n",
"</div>"
],
"text/plain": [
" Nombre total de publications \\\n",
"Editeurs \n",
"Elsevier BV 1227 \n",
"Springer Science and Business Media LLC 470 \n",
"Wiley 303 \n",
"Springer International Publishing 171 \n",
"IEEE 150 \n",
"MDPI AG 146 \n",
"Informa UK Limited 113 \n",
"IOP Publishing 105 \n",
"American Chemical Society (ACS) 101 \n",
"Oxford University Press (OUP) 91 \n",
"\n",
" Nb de publications en accès ouvert \\\n",
"Editeurs \n",
"Elsevier BV 468 \n",
"Springer Science and Business Media LLC 272 \n",
"Wiley 158 \n",
"Springer International Publishing 83 \n",
"IEEE 50 \n",
"MDPI AG 146 \n",
"Informa UK Limited 27 \n",
"IOP Publishing 82 \n",
"American Chemical Society (ACS) 48 \n",
"Oxford University Press (OUP) 49 \n",
"\n",
" Editeurs \\\n",
"Editeurs \n",
"Elsevier BV Elsevier BV \n",
"Springer Science and Business Media LLC Springer Science and Business Media LLC \n",
"Wiley Wiley \n",
"Springer International Publishing Springer International Publishing \n",
"IEEE IEEE \n",
"MDPI AG MDPI AG \n",
"Informa UK Limited Informa UK Limited \n",
"IOP Publishing IOP Publishing \n",
"American Chemical Society (ACS) American Chemical Society (ACS) \n",
"Oxford University Press (OUP) Oxford University Press (OUP) \n",
"\n",
" Pourcentage d'accès ouvert \n",
"Editeurs \n",
"Elsevier BV 38.1 \n",
"Springer Science and Business Media LLC 57.9 \n",
"Wiley 52.1 \n",
"Springer International Publishing 48.5 \n",
"IEEE 33.3 \n",
"MDPI AG 100.0 \n",
"Informa UK Limited 23.9 \n",
"IOP Publishing 78.1 \n",
"American Chemical Society (ACS) 47.5 \n",
"Oxford University Press (OUP) 53.8 "
]
},
"execution_count": 13,
"metadata": {},
"output_type": "execute_result"
}
],
"source": [
"publis_triees_ed = pd.merge(publications_par_editeur, publications_en_oa_ed, left_index = True, right_index = True)\n",
"publis_triees_ed = publis_triees_ed.rename(columns = {'publisher_x': 'Nombre total de publications', 'publisher_y': 'Nb de publications en accès ouvert'})\n",
"publis_triees_ed = publis_triees_ed.rename_axis('Editeurs')\n",
"publis_triees_ed[\"Editeurs\"] = publications_en_oa_ed.index\n",
"publis_triees_ed = publis_triees_ed.sort_values(by=['Nombre total de publications'], ascending=False)\n",
"# Limiter le nombre d'éditeurs affichés aux 10 premiers. Ce chiffre peut être modulé comme on le souhaite mais attention, le graphique doit rester lisible\n",
"publis_triees_ed = publis_triees_ed[0:10]\n",
"publis_triees_ed[\"Pourcentage d'accès ouvert\"] = ((publis_triees_ed[\"Nb de publications en accès ouvert\"] * 100) / publis_triees_ed[\"Nombre total de publications\"])\n",
"# N'afficher que la première décimale pour la colonne des pourcentages\n",
"pd.set_option('precision', 1)\n",
"publis_triees_ed"
]
},
{
"cell_type": "code",
"execution_count": 14,
"metadata": {},
"outputs": [
{
"data": {
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\n",
"text/plain": [
"<Figure size 360x360 with 1 Axes>"
]
},
"metadata": {},
"output_type": "display_data"
}
],
"source": [
"sns.set_style(\"darkgrid\")\n",
"\n",
"facet = sns.lmplot(data=publis_triees_ed, x='Nombre total de publications', y=\"Pourcentage d'accès ouvert\", hue='Editeurs',\n",
" fit_reg=False, legend=False, scatter_kws={\"s\": 50}, palette= 'Paired')\n",
"\n",
"plt.title(\"Taux d'accès ouvert 2019 par rapport au nombre de publications, par éditeur/plateforme\", fontsize = 15, x = 0.5, y = 1,\n",
" fontweight = 'bold', alpha = 0.8)\n",
"\n",
"for ax in facet.axes.ravel():\n",
" for t, x, y in publis_triees_ed[[\"Editeurs\",\"Nombre total de publications\",\"Pourcentage d'accès ouvert\"]].values.tolist():\n",
" ax.annotate(t, (x, y))\n",
"\n",
"plt.savefig('Data/outputs/2019_rapport_oa_nb_publications_editeurs.png', dpi=100, bbox_inches='tight', pad_inches=0.9)"
]
},
{
"cell_type": "code",
"execution_count": null,
"metadata": {},
"outputs": [],
"source": []
}
],
"metadata": {
"kernelspec": {
"display_name": "Python 3",
"language": "python",
"name": "python3"
},
"language_info": {
"codemirror_mode": {
"name": "ipython",
"version": 3
},
"file_extension": ".py",
"mimetype": "text/x-python",
"name": "python",
"nbconvert_exporter": "python",
"pygments_lexer": "ipython3",
"version": "3.7.4"
}
},
"nbformat": 4,
"nbformat_minor": 4
}
