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Chap 2 - Enlever la création d'un graphique
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src/02-selection.ipynb

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},
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"source": [
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"### Exercice - Une sélection de données\n",
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"Calculez la moyenne des **longueurs d'arrière-pieds** et\n",
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"Obtenez la moyenne des **longueurs d'arrière-pieds** et\n",
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"des **poids** de chaque **espèce** de `'NL'` à `'PB'` :\n",
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"\n",
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"1. Commencez par sélectionner uniquement les colonnes requises.\n",
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},
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"source": [
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"### Exercise - Selecting data\n",
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"Calculate the average **hindfoot lengths** and\n",
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"Get the average **hindfoot lengths** and\n",
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"**weights** of each **species** from `'NL'` to `'PB'`:\n",
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"\n",
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"1. Start by selecting only the required columns.\n",
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"avg_by_site_sex.tail()"
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]
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},
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{
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"cell_type": "code",
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"execution_count": null,
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"id": "a9657ac7-81af-4cd0-bed3-621834048043",
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"metadata": {
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"lang": "fr",
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"tags": [
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"soln"
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]
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},
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"outputs": [],
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"source": [
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"# Transformer les catégories de sexe en noms de colonne\n",
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"table_site_sexe = moy_par_site_sexe.unstack()\n",
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"\n",
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"# L'entête contient deux niveaux. Pour enlever le premier niveau :\n",
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"table_site_sexe.columns = table_site_sexe.columns.droplevel()\n",
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"table_site_sexe.tail()"
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]
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},
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{
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"cell_type": "code",
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"execution_count": null,
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"id": "8571c63a-6c73-43eb-89ed-e772e1e9fd1e",
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"metadata": {
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"lang": "fr",
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"tags": [
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"exer"
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]
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},
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"outputs": [],
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"source": [
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"# Transformer les catégories de sexe en noms de colonne\n",
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"table_site_sexe = moy_par_site_sexe.unstack()\n",
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"\n",
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"# L'entête contient deux niveaux. Pour enlever le premier niveau :\n",
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"# table_site_sexe.columns = table_site_sexe.columns.droplevel()\n",
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"table_site_sexe.tail()"
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]
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},
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{
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"cell_type": "code",
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"execution_count": null,
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"id": "f9deccad-37a1-4489-b5d9-e3f8284dda00",
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"metadata": {
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"lang": "en",
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"tags": [
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"soln"
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]
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},
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"outputs": [],
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"source": [
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"# Transform categorical values into columns\n",
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"table_site_sex = avg_by_site_sex.unstack()\n",
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"\n",
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"# The legend header contains two levels. To remove the first level:\n",
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"table_site_sex.columns = table_site_sex.columns.droplevel()\n",
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"table_site_sex.tail()"
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]
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},
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{
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"cell_type": "code",
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"execution_count": null,
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"id": "fc477d1c-0cdb-4312-b505-6afbaa5209f4",
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"metadata": {
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"lang": "en",
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"tags": [
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"exer"
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]
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},
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"outputs": [],
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"source": [
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"# Transform categorical values into columns\n",
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"table_site_sex = avg_by_site_sex.unstack()\n",
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"\n",
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"# The legend header contains two levels. To remove the first level:\n",
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"# table_site_sex.columns = table_site_sex.columns.droplevel()\n",
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"table_site_sex.tail()"
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]
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},
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{
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"cell_type": "code",
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"execution_count": null,
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"id": "dc01d427-8519-4602-8522-e9d363953836",
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"metadata": {
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"lang": "fr"
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},
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"outputs": [],
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"source": [
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"# Créer le bar plot\n",
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"table_site_sexe.plot(kind='bar')"
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]
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},
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{
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"cell_type": "code",
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"execution_count": null,
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"id": "f9139ad6-7662-46bf-98d5-b3c5bfadd9a7",
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"metadata": {
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"lang": "en"
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},
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"outputs": [],
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"source": [
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"# And we can make a bar plot from this:\n",
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"table_site_sex.plot(kind='bar')"
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]
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},
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{
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"cell_type": "markdown",
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"id": "a2584e88-879e-4a8f-bcdc-b6bd0cba34a2",

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