Update memo and start statistical studies
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"name": "python",
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"nbconvert_exporter": "python",
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"pygments_lexer": "ipython3",
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"version": "3.7.1"
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"version": "3.7.3"
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}
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},
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"nbformat": 4,
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"name": "python",
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"nbconvert_exporter": "python",
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"pygments_lexer": "ipython3",
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"version": "3.7.2"
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"version": "3.7.3"
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}
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"nbformat": 4,
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PreStSauveur/Programmation/7-Etudes Statistiques.ipynb
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PreStSauveur/Programmation/7-Etudes Statistiques.ipynb
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{
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"cells": [
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{
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"cell_type": "markdown",
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"metadata": {},
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"source": [
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"# Etudes statistiques\n",
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"\n",
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"Dans ce TP, vous allez réaliser 3 études statistiques basées sur des données issues de l'INSEE ([L’Institut national de la statistique et des études économiques](https://www.insee.fr/fr/accueil))\n",
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"\n",
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"- [Températures moyennes entre 1900 et 2017](#Temperature)\n",
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"- [Population totale par sexe et âge au 1er janvier 2019, France](#Population)\n",
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"- [Émissions de gaz à effet de serre dans l'UE ](#Gaz--%C3%A0-effet-de-serre)"
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]
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},
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{
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"cell_type": "markdown",
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"metadata": {},
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"source": [
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"## Temperature\n",
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"\n",
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"Voici les données des températures moyenne en France de 1900 à 2017 ([source](https://www.insee.fr/fr/statistiques/3676581?sommaire=3696937))"
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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": 3,
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"metadata": {},
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"outputs": [],
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"source": [
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"temperature = [\n",
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"12.14413, 11.11613, 11.18313, 11.48013, 11.93013, 11.22013, 11.75313, 11.44013,\n",
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"11.35113, 10.82313, 11.37413, 12.32013, 11.37913, 11.89413, 11.48813, 11.43513,\n",
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"11.59413, 10.57213, 11.64313, 11.09013, 11.83913, 12.42113, 11.11913, 11.71713,\n",
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"11.43513, 11.16313, 12.10113, 11.67313, 12.27613, 11.56013, 12.16513, 11.19613,\n",
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"11.54013, 11.59013, 12.20913, 11.72313, 11.77113, 12.28713, 11.73213, 11.51313,\n",
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"10.85413, 10.87613, 11.43513, 12.52613, 11.41213, 12.37413, 11.47213, 12.59313,\n",
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"12.11813, 12.62013, 12.03913, 11.69713, 11.85613, 11.85013, 11.34113, 11.84213,\n",
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"10.58113, 11.84313, 11.77313, 12.59413, 11.79813, 12.58413, 11.03513, 10.68313,\n",
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"11.71513, 11.29313, 12.02013, 11.92813, 11.59013, 11.57513, 11.66613, 11.57613,\n",
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"11.34313, 11.62213, 11.89313, 11.77913, 12.08513, 11.88713, 11.38613, 11.59513,\n",
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"11.16713, 11.91113, 12.63613, 12.36213, 11.61013, 11.34313, 11.64413, 11.65413,\n",
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"12.46513, 12.95013, 12.99913, 11.99113, 12.31813, 12.04713, 13.29813, 12.83713,\n",
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"11.85613, 13.12113, 12.53113, 12.99513, 13.12313, 12.76313, 13.14513, 13.48113,\n",
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"12.59113, 12.58813, 13.23913, 12.91113, 12.54513, 12.96413, 11.86613, 13.60113,\n",
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"12.79113, 12.38113, 13.72713, 13.512, 13, 13.4\n",
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"]"
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]
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},
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{
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"cell_type": "markdown",
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"metadata": {},
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"source": [
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"Pour toutes les questions suivantes, les réponses doivent être données par votre programme.\n",
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"\n",
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"1. Décrire la série statistique (population, individus, caractère)\n",
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"2. Quelle a été la température moyenne en 1900, 1918, 1945, 1990 et en 2000?\n",
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"3. Calculer les 5 indicateurs et donner une interprétation de chacun de ces indicateurs.\n",
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"4. Tracer la courbe d'évolution des températures.\n",
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"\n",
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"Vous pouvez utiliser la commande suivante pour générer les années."
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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": 4,
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"metadata": {},
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"outputs": [],
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"source": [
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"annee = list(range(1900, 2018))"
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]
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},
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{
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"cell_type": "markdown",
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"metadata": {},
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"source": [
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"# Population\n",
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"\n",
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"Voici l'estimation de la population totale par sexe et âge au 1er janvier 2019. Chaque élément de la liste correspond à une tranche d'age.\n",
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"\n",
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"- le premier élément correspond au nombre de personnes ayant 0 an (nés en 2018)\n",
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"- le deuxime élément correspond au nombre de personnes ayant 1 an (nés en 2019)\n",
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"- le dernier élément correspon au nombre de personnes ayant plus de 100ans (nés avant 1918)"
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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": 1,
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"metadata": {},
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"outputs": [],
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"source": [
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"femmes = [\n",
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"347749, 355472, 363162, 372402, 387042, 389920, 396835, 403349, 412555, 408232,\n",
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"410703, 408166, 415280, 405218, 403761, 402532, 403441, 409037, 412560, 390002,\n",
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"384532, 370258, 374177, 367951, 358614, 357966, 376224, 385366, 397080, 405038,\n",
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"409842, 413955, 422167, 420790, 417815, 414133, 438390, 442482, 448307, 424441,\n",
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"414208, 413671, 404350, 413722, 435157, 460384, 469527, 466462, 457896, 452879,\n",
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"450472, 447421, 457665, 459310, 464153, 460412, 445047, 444896, 444709, 442263,\n",
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"433635, 430912, 427893, 424094, 421875, 413428, 418007, 408050, 422019, 413673,\n",
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"409072, 400876, 378561, 286325, 279055, 269401, 249057, 221914, 231318, 239598,\n",
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"232663, 226088, 222853, 213902, 210980, 195596, 192550, 175872, 164803, 139226,\n",
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"124322, 105456, 91072, 76447, 61235, 48398, 37882, 27754, 19813, 8273, 12670\n",
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"]\n",
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"hommes = [\n",
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"364155, 370453, 378518, 387906, 399232, 407611, 417471, 418623,\n",
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"429919, 427917, 430934, 426744, 433073, 424141, 422877, 422127,\n",
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"423901, 431086, 433377, 410714, 398993, 384384, 381869, 371731,\n",
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"357849, 356195, 373660, 377772, 384835, 385034, 390899, 392786,\n",
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"397979, 398786, 396435, 391214, 416777, 421707, 427643, 405581,\n",
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"399149, 404816, 390441, 404346, 426173, 448213, 459886, 457822,\n",
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"448697, 441572, 434971, 432749, 441979, 442828, 444960, 438142,\n",
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"422099, 421161, 416331, 410415, 400042, 395817, 390345, 382395,\n",
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"381146, 371165, 374781, 364694, 374817, 364312, 361485, 350179,\n",
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"327085, 242793, 234112, 224687, 204674, 177799, 179151, 182015,\n",
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"171854, 160969, 153145, 139041, 131872, 116712, 108339, 95104,\n",
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"83373, 66602, 55382, 44797, 34519, 27317, 20525, 14477,\n",
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"10101, 7239, 4977, 2058, 2976,\n",
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"]"
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]
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},
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{
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"cell_type": "markdown",
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"metadata": {},
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"source": [
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"1. Décrire les séries statistiques (population, individues, caractères)\n",
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"\n",
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"2. Combien y a-t-il d'homme en tout? De femmes? De personnes?\n",
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"\n",
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"3. Sur un même graphique tracer la répartition en fonction de l'age de la population féminine et masculine.\n",
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"\n",
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"4. Pour comparer la **répartition** de la population les **quantités** ne sont pas adapté, on préfèrera la **fréquence** (effectif divisé par l'effectif total). Créer 2 autres listes pour calculer la fréquence de chaque classe d'age pour les hommes et les femmes. Tracer à nouveau la répartition selon les ages.\n",
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"\n",
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"5. Calculer les 5 indicateurs pour les 2 séries. Interpréter."
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]
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},
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{
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"cell_type": "markdown",
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"metadata": {},
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"source": [
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"## Gaz à effet de serre\n"
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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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"metadata": {},
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"outputs": [],
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"source": [
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"emmissions_1990 = {\n",
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"\n",
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"}\n",
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"emmissions_2000 = {\n",
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" \n",
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"}"
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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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"metadata": {},
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"outputs": [],
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"source": []
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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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"metadata": {},
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"outputs": [],
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"source": []
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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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"metadata": {},
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"outputs": [],
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"source": []
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}
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],
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"metadata": {
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"kernelspec": {
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"display_name": "Python 3",
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"language": "python",
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"name": "python3"
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},
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"language_info": {
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"codemirror_mode": {
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"name": "ipython",
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"version": 3
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},
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"file_extension": ".py",
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"mimetype": "text/x-python",
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"name": "python",
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"nbconvert_exporter": "python",
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"pygments_lexer": "ipython3",
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"version": "3.7.3"
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}
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},
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"nbformat": 4,
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"nbformat_minor": 2
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}
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