diff --git a/module2/exo4/exercice.ipynb b/module2/exo4/exercice.ipynb index c982256411e9df1ca9b19bf15eae5702459397da..3c7a1d93c5f86fa62ffe109acf4e357682f9de80 100644 --- a/module2/exo4/exercice.ipynb +++ b/module2/exo4/exercice.ipynb @@ -185,8 +185,796 @@ "cell_type": "markdown", "metadata": {}, "source": [ - "Bon j'arrive pas à importer le fichier ça me soule" + "Bon j'arrive pas à importer le fichier ça me soule. J'essaie avec les conseils de ChatGTP." ] + }, + { + "cell_type": "code", + "execution_count": 31, + "metadata": {}, + "outputs": [ + { + "name": "stderr", + "output_type": "stream", + "text": [ + "Warning message in FUN(X[[i]], ...):\n", + "“input string 2 is invalid in this locale”Warning message in FUN(X[[i]], ...):\n", + "“input string 4 is invalid in this locale”Warning message in FUN(X[[i]], ...):\n", + "“input string 2 is invalid in this locale”Warning message in FUN(X[[i]], ...):\n", + "“input string 4 is invalid in this locale”Warning message in FUN(X[[i]], ...):\n", + "“input string 2 is invalid in this locale”Warning message in FUN(X[[i]], ...):\n", + "“input string 4 is invalid in this locale”Warning message in FUN(X[[i]], ...):\n", + "“input string 2 is invalid in this locale”Warning message in FUN(X[[i]], ...):\n", + "“input string 4 is invalid in this locale”Warning message in FUN(X[[i]], ...):\n", + "“input string 12 is invalid in this locale”Warning message in FUN(X[[i]], ...):\n", + "“input string 2 is invalid in this locale”Warning message in FUN(X[[i]], ...):\n", + "“input string 4 is invalid in this locale”Warning message in FUN(X[[i]], ...):\n", + "“input string 12 is invalid in this locale”Warning message in FUN(X[[i]], ...):\n", + "“input string 2 is invalid in this locale”Warning message in FUN(X[[i]], ...):\n", + "“input string 4 is invalid in this locale”Warning message in FUN(X[[i]], ...):\n", + "“input string 12 is invalid in this locale”Warning message in FUN(X[[i]], ...):\n", + "“input string 4 is invalid in this locale”Warning message in FUN(X[[i]], ...):\n", + "“input string 12 is invalid in this locale”Warning message in FUN(X[[i]], ...):\n", + "“input string 4 is invalid in this locale”Warning message in FUN(X[[i]], ...):\n", + "“input string 12 is invalid in this locale”Warning message in FUN(X[[i]], ...):\n", + "“input string 4 is invalid in this locale”Warning message in FUN(X[[i]], ...):\n", + "“input string 12 is invalid in this locale”Warning message in FUN(X[[i]], ...):\n", + "“input string 4 is invalid in this locale”Warning message in FUN(X[[i]], ...):\n", + "“input string 12 is invalid in this locale”Warning message in FUN(X[[i]], ...):\n", + "“input string 4 is invalid in this locale”Warning message in FUN(X[[i]], ...):\n", + "“input string 12 is invalid in this locale”Warning message in FUN(X[[i]], ...):\n", + "“input string 4 is invalid in this locale”Warning message in FUN(X[[i]], ...):\n", + "“input string 12 is invalid in this locale”Warning message in FUN(X[[i]], ...):\n", + "“input string 6 is invalid in this locale”Warning message in FUN(X[[i]], ...):\n", + "“input string 14 is invalid in this locale”Warning message in FUN(X[[i]], ...):\n", + "“input string 6 is invalid in this locale”Warning message in FUN(X[[i]], ...):\n", + "“input string 14 is invalid in this locale”Warning message in FUN(X[[i]], ...):\n", + "“input string 6 is invalid in this locale”Warning message in FUN(X[[i]], ...):\n", + "“input string 14 is invalid in this locale”Warning message in FUN(X[[i]], ...):\n", + "“input string 2 is invalid in this locale”Warning message in FUN(X[[i]], ...):\n", + "“input string 4 is invalid in this locale”Warning message in FUN(X[[i]], ...):\n", + "“input string 2 is invalid in this locale”Warning message in FUN(X[[i]], ...):\n", + "“input string 4 is invalid in this locale”Warning message in FUN(X[[i]], ...):\n", + "“input string 2 is invalid in this locale”Warning message in FUN(X[[i]], ...):\n", + "“input string 4 is invalid in this locale”Warning message in FUN(X[[i]], ...):\n", + "“input string 2 is invalid in this locale”Warning message in FUN(X[[i]], ...):\n", + "“input string 4 is invalid in this locale”Warning message in FUN(X[[i]], ...):\n", + "“input string 2 is invalid in this locale”Warning message in FUN(X[[i]], ...):\n", + "“input string 4 is invalid in this locale”Warning message in FUN(X[[i]], ...):\n", + "“input string 2 is invalid 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...):\n", + "“input string 2 is invalid in this locale”Warning message in FUN(X[[i]], ...):\n", + "“input string 4 is invalid in this locale”Warning message in FUN(X[[i]], ...):\n", + "“input string 2 is invalid in this locale”Warning message in FUN(X[[i]], ...):\n", + "“input string 4 is invalid in this locale”Warning message in FUN(X[[i]], ...):\n", + "“input string 2 is invalid in this locale”Warning message in FUN(X[[i]], ...):\n", + "“input string 4 is invalid in this locale”Warning message in FUN(X[[i]], ...):\n", + "“input string 12 is invalid in this locale”Warning message in FUN(X[[i]], ...):\n", + "“input string 2 is invalid in this locale”Warning message in FUN(X[[i]], ...):\n", + "“input string 4 is invalid in this locale”Warning message in FUN(X[[i]], ...):\n", + "“input string 12 is invalid in this locale”Warning message in FUN(X[[i]], ...):\n", + "“input string 2 is invalid in this locale”Warning message in FUN(X[[i]], ...):\n", + "“input string 4 is invalid in this locale”Warning message in FUN(X[[i]], ...):\n", + "“input string 12 is invalid in this locale”Warning message in FUN(X[[i]], ...):\n", + "“input string 2 is invalid in this locale”Warning message in FUN(X[[i]], ...):\n", + "“input string 4 is invalid in this locale”Warning message in FUN(X[[i]], ...):\n", + "“input string 12 is invalid in this locale”Warning message in FUN(X[[i]], ...):\n", + "“input string 2 is invalid in this locale”Warning message in FUN(X[[i]], ...):\n", + "“input string 4 is invalid in this locale”Warning message in FUN(X[[i]], ...):\n", + "“input string 12 is invalid in this locale”Warning message in FUN(X[[i]], ...):\n", + "“input string 2 is invalid in this locale”Warning message in FUN(X[[i]], ...):\n", + "“input string 4 is invalid in this locale”Warning message in FUN(X[[i]], ...):\n", + "“input string 12 is invalid in this locale”Warning message in FUN(X[[i]], ...):\n", + "“input string 2 is invalid in this locale”Warning message in FUN(X[[i]], ...):\n", + "“input string 4 is invalid in this locale”Warning message in FUN(X[[i]], ...):\n", + "“input string 12 is invalid in this locale”Warning message in FUN(X[[i]], ...):\n", + "“input string 2 is invalid in this locale”Warning message in FUN(X[[i]], ...):\n", + "“input string 4 is invalid in this locale”Warning message in FUN(X[[i]], ...):\n", + "“input string 12 is invalid in this locale”Warning message in FUN(X[[i]], ...):\n", + "“input string 2 is invalid in this locale”Warning message in FUN(X[[i]], ...):\n", + "“input string 4 is invalid in this locale”Warning message in FUN(X[[i]], ...):\n", + "“input string 12 is invalid in this locale”Warning message in FUN(X[[i]], ...):\n", + "“input string 2 is invalid in this locale”Warning message in FUN(X[[i]], ...):\n", + "“input string 4 is invalid in this locale”Warning message in FUN(X[[i]], ...):\n", + "“input string 12 is invalid in this locale”Warning message in FUN(X[[i]], ...):\n", + "“input string 2 is invalid in this locale”Warning message in FUN(X[[i]], ...):\n", + "“input string 4 is invalid in this locale”Warning message in FUN(X[[i]], ...):\n", + "“input string 12 is invalid in this locale”Warning message in FUN(X[[i]], ...):\n", + "“input string 2 is invalid in this locale”Warning message in FUN(X[[i]], ...):\n", + "“input string 4 is invalid in this locale”Warning message in FUN(X[[i]], ...):\n", + "“input string 12 is invalid in this locale”Warning message in FUN(X[[i]], ...):\n", + "“input string 2 is invalid in this locale”Warning message in FUN(X[[i]], ...):\n", + "“input string 4 is invalid in this locale”Warning message in FUN(X[[i]], ...):\n", + "“input string 12 is invalid in this locale”Warning message in FUN(X[[i]], ...):\n", + "“input string 4 is invalid in this locale”Warning message in FUN(X[[i]], ...):\n", + "“input string 12 is invalid in this locale”Warning message in FUN(X[[i]], ...):\n", + "“input string 4 is invalid in this locale”Warning message in FUN(X[[i]], ...):\n", + "“input string 12 is invalid in this locale”Warning message in FUN(X[[i]], ...):\n", + "“input string 4 is invalid in this locale”Warning message in FUN(X[[i]], ...):\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "“input string 12 is invalid in this locale”Warning message in FUN(X[[i]], ...):\n", + "“input string 4 is invalid in this locale”Warning message in FUN(X[[i]], ...):\n", + "“input string 12 is invalid in this locale”Warning message in FUN(X[[i]], ...):\n", + "“input string 4 is invalid in this locale”Warning message in FUN(X[[i]], ...):\n", + "“input string 12 is invalid in this locale”Warning message in FUN(X[[i]], ...):\n", + "“input string 4 is invalid in this locale”Warning message in FUN(X[[i]], ...):\n", + "“input string 12 is invalid in this locale”Warning message in FUN(X[[i]], ...):\n", + "“input string 4 is invalid in this locale”Warning message in FUN(X[[i]], ...):\n", + "“input string 12 is invalid in this locale”Warning message in FUN(X[[i]], ...):\n", + "“input string 4 is invalid in this locale”Warning message in FUN(X[[i]], ...):\n", + "“input string 12 is invalid in this locale”Warning message in FUN(X[[i]], ...):\n", + "“input string 4 is invalid in this locale”Warning message in FUN(X[[i]], ...):\n", + "“input string 12 is invalid in this locale”Warning message in FUN(X[[i]], ...):\n", + "“input string 4 is invalid in this locale”Warning message in FUN(X[[i]], ...):\n", + "“input string 12 is invalid in this locale”Warning message in FUN(X[[i]], ...):\n", + "“input string 4 is invalid in this locale”Warning message in FUN(X[[i]], ...):\n", + "“input string 12 is invalid in this locale”Warning message in FUN(X[[i]], ...):\n", + "“input string 4 is invalid in this locale”Warning message in FUN(X[[i]], ...):\n", + "“input string 12 is invalid in this locale”Warning message in FUN(X[[i]], ...):\n", + "“input string 4 is invalid in this locale”Warning message in FUN(X[[i]], ...):\n", + "“input string 12 is invalid in this locale”Warning message in FUN(X[[i]], ...):\n", + "“input string 4 is invalid in this locale”Warning message in FUN(X[[i]], ...):\n", + "“input string 12 is invalid in this locale”Warning message in FUN(X[[i]], ...):\n", + "“input string 4 is invalid in this locale”Warning message in FUN(X[[i]], ...):\n", + "“input string 12 is invalid in this locale”Warning message in FUN(X[[i]], ...):\n", + "“input string 4 is invalid in this locale”Warning message in FUN(X[[i]], ...):\n", + "“input string 12 is invalid in this locale”Warning message in FUN(X[[i]], ...):\n", + "“input string 4 is invalid in this locale”Warning message in FUN(X[[i]], ...):\n", + "“input string 12 is invalid in this locale”Warning message in FUN(X[[i]], ...):\n", + "“input string 4 is invalid in this locale”Warning message in FUN(X[[i]], ...):\n", + "“input string 12 is invalid in this locale”Warning message in FUN(X[[i]], ...):\n", + "“input string 4 is invalid in this locale”Warning message in FUN(X[[i]], ...):\n", + "“input string 12 is invalid in this locale”Warning message in FUN(X[[i]], ...):\n", + "“input string 4 is invalid in this locale”Warning message in FUN(X[[i]], ...):\n", + "“input string 12 is invalid in this locale”Warning message in FUN(X[[i]], ...):\n", + "“input string 4 is invalid in this locale”Warning message in FUN(X[[i]], ...):\n", + "“input string 12 is invalid in this locale”Warning message in FUN(X[[i]], ...):\n", + "“input string 4 is invalid in this locale”Warning message in FUN(X[[i]], ...):\n", + "“input string 12 is invalid in this locale”Warning message in FUN(X[[i]], ...):\n", + "“input string 4 is invalid in this locale”Warning message in FUN(X[[i]], ...):\n", + "“input string 12 is invalid in this locale”Warning message in FUN(X[[i]], ...):\n", + "“input string 4 is invalid in this locale”Warning message in FUN(X[[i]], ...):\n", + "“input string 12 is invalid in this locale”Warning message in FUN(X[[i]], ...):\n", + "“input string 4 is invalid in this locale”Warning message in FUN(X[[i]], ...):\n", + "“input string 12 is invalid in this locale”Warning message in FUN(X[[i]], ...):\n", + "“input string 4 is invalid in this locale”Warning message in FUN(X[[i]], ...):\n", + "“input string 12 is invalid in this locale”Warning message in FUN(X[[i]], ...):\n", + "“input string 6 is invalid in this locale”Warning message in FUN(X[[i]], ...):\n", + "“input string 14 is invalid in this locale”Warning message in FUN(X[[i]], ...):\n", + "“input string 6 is invalid in this locale”Warning message in FUN(X[[i]], ...):\n", + "“input string 14 is invalid in this locale”Warning message in FUN(X[[i]], ...):\n", + "“input string 6 is invalid in this locale”Warning message in FUN(X[[i]], ...):\n", + "“input string 14 is invalid in this locale”Warning message in FUN(X[[i]], ...):\n", + "“input string 6 is invalid in this locale”Warning message in FUN(X[[i]], ...):\n", + "“input string 14 is invalid in this locale”Warning message in FUN(X[[i]], ...):\n", + "“input string 6 is invalid in this locale”Warning message in FUN(X[[i]], ...):\n", + "“input string 14 is invalid in this locale”Warning message in FUN(X[[i]], ...):\n", + "“input string 6 is invalid in this locale”Warning message in FUN(X[[i]], ...):\n", + "“input string 14 is invalid in this locale”Warning message in FUN(X[[i]], ...):\n", + "“input string 6 is invalid in this locale”Warning message in FUN(X[[i]], ...):\n", + "“input string 14 is invalid in this locale”Warning message in FUN(X[[i]], ...):\n", + "“input string 6 is invalid in this locale”Warning message in FUN(X[[i]], ...):\n", + "“input string 14 is invalid in this locale”Warning message in FUN(X[[i]], ...):\n", + "“input string 6 is invalid in this locale”Warning message in FUN(X[[i]], ...):\n", + "“input string 14 is invalid in this locale”Warning message in FUN(X[[i]], ...):\n", + "“input string 6 is invalid in this locale”Warning message in FUN(X[[i]], ...):\n", + "“input string 14 is invalid in this locale”Warning message in FUN(X[[i]], ...):\n", + "“input string 6 is invalid in this locale”Warning message in FUN(X[[i]], ...):\n", + "“input string 14 is invalid in this locale”Warning message in FUN(X[[i]], ...):\n", + "“input string 6 is invalid in this locale”Warning message in FUN(X[[i]], ...):\n", + "“input string 14 is invalid in this locale”Warning message in FUN(X[[i]], ...):\n", + "“input string 6 is invalid in this locale”Warning message in FUN(X[[i]], ...):\n", + "“input string 14 is invalid in this locale”ERROR while rich displaying an object: Error in gsub(\" &\\\\\", \"\\\\\", r, fixed = TRUE): input string 1 is invalid in this locale\n", + "\n", + "Traceback:\n", + "1. FUN(X[[i]], ...)\n", + "2. tryCatch(withCallingHandlers({\n", + " . if (!mime %in% names(repr::mime2repr)) \n", + " . stop(\"No repr_* for mimetype \", mime, \" in repr::mime2repr\")\n", + " . rpr <- repr::mime2repr[[mime]](obj)\n", + " . if (is.null(rpr)) \n", + " . return(NULL)\n", + " . prepare_content(is.raw(rpr), rpr)\n", + " . }, error = error_handler), error = outer_handler)\n", + "3. tryCatchList(expr, classes, parentenv, handlers)\n", + "4. tryCatchOne(expr, names, parentenv, handlers[[1L]])\n", + "5. doTryCatch(return(expr), name, parentenv, handler)\n", + "6. withCallingHandlers({\n", + " . if (!mime %in% names(repr::mime2repr)) \n", + " . stop(\"No repr_* for mimetype \", mime, \" in repr::mime2repr\")\n", + " . rpr <- repr::mime2repr[[mime]](obj)\n", + " . if (is.null(rpr)) \n", + " . return(NULL)\n", + " . prepare_content(is.raw(rpr), rpr)\n", + " . }, error = error_handler)\n", + "7. repr::mime2repr[[mime]](obj)\n", + "8. repr_latex.data.frame(obj)\n", + "9. gsub(\" &\\\\\", \"\\\\\", r, fixed = TRUE)\n", + "Warning message in grepl(\"\", data[[\"text/html\"]], ignore.case = TRUE):\n", + "“input string 1 is invalid in this locale”" + ] + }, + { + "data": { + "text/html": [ + "\n", + "\n", + "\n", + "\t\n", + "\t\n", + "\t\n", + "\t\n", + "\t\n", + "\t\n", + "\n", + "
code_faoProduitCode_DomaineDomaineProduction_SourceExportations_SourceImportations_SourceProductionImportationsExportationsCode_annee_pieDispo_alim_SourceDispo_alimCode_annee_dispo
01199.02 Crales mlanges SCL Compte Disponibilits et Utilisations (CDU) (2010-)Chiffre officiel 458850 2019-2021 2014-2015
01199.90 Cerales n.a.c. SCL Compte Disponibilits et Utilisations (CDU) (2010-)Chiffre officiel Chiffre officiel Chiffre officiel 257583.33333 8705.55 75722.893333 2019-2021 Valeur estime 14218.27 2014-2015
01241.01 Haricots verts SCL Compte Disponibilits et Utilisations (CDU) (2010-) 2019-2021 Valeur estime 273285.2 2014-2015
01241.90 Autres haricots frais SCL Compte Disponibilits et Utilisations (CDU) (2010-)Chiffre officiel Chiffre officiel Chiffre officiel 369030 50019.883333 115180.46 2019-2021 Valeur estime 0 2014-2015
01253.01 Oignons echalotes frais SCL Compte Disponibilits et Utilisations (CDU) (2010-) Chiffre officiel Chiffre officiel 2573.4766667 29585.933333 2019-2021 Valeur estime
16600.565 2014-2015
\n" + ], + "text/markdown": [ + "\n", + "code_fao | Produit | Code_Domaine | Domaine | Production_Source | Exportations_Source | Importations_Source | Production | Importations | Exportations | Code_annee_pie | Dispo_alim_Source | Dispo_alim | Code_annee_dispo | \n", + "|---|---|---|---|---|---|\n", + "| 01199.02 | Crales mlanges | SCL | Compte Disponibilits et Utilisations (CDU) (2010-) | Chiffre officiel | | | 458850 | | | 2019-2021 | | | 2014-2015 | \n", + "| 01199.90 | Cerales n.a.c. | SCL | Compte Disponibilits et Utilisations (CDU) (2010-) | Chiffre officiel | Chiffre officiel | Chiffre officiel | 257583.33333 | 8705.55 | 75722.893333 | 2019-2021 | Valeur estime | 14218.27 | 2014-2015 | \n", + "| 01241.01 | Haricots verts | SCL | Compte Disponibilits et Utilisations (CDU) (2010-) | | | | | | | 2019-2021 | Valeur estime | 273285.2 | 2014-2015 | \n", + "| 01241.90 | Autres haricots frais | SCL | Compte Disponibilits et Utilisations (CDU) (2010-) | Chiffre officiel | Chiffre officiel | Chiffre officiel | 369030 | 50019.883333 | 115180.46 | 2019-2021 | Valeur estime | 0 | 2014-2015 | \n", + "| 01253.01 | Oignons | echalotes | frais | SCL | Compte Disponibilits et Utilisations (CDU) (2010-) | | Chiffre officiel | Chiffre officiel | | 2573.4766667 | 29585.933333 | 2019-2021 | Valeur estime | \n", + "| 16600.565 | 2014-2015 | | | | | | | | | | | | | \n", + "\n", + "\n" + ], + "text/plain": [ + " code_fao Produit Code_Domaine\n", + "1 01199.02 C\\xe9r\\xe9ales m\\xe9lang\\xe9es SCL \n", + "2 01199.90 Cer\\xe9ales n.a.c. SCL \n", + "3 01241.01 Haricots verts SCL \n", + "4 01241.90 Autres haricots frais SCL \n", + "5 01253.01 Oignons echalotes \n", + "6 16600.565 2014-2015 \n", + " Domaine Production_Source\n", + "1 Compte Disponibilit\\xe9s et Utilisations (CDU) (2010-) Chiffre officiel \n", + "2 Compte Disponibilit\\xe9s et Utilisations (CDU) (2010-) Chiffre officiel \n", + "3 Compte Disponibilit\\xe9s et Utilisations (CDU) (2010-) \n", + "4 Compte Disponibilit\\xe9s et Utilisations (CDU) (2010-) Chiffre officiel \n", + "5 frais SCL \n", + "6 \n", + " Exportations_Source Importations_Source\n", + "1 \n", + "2 Chiffre officiel Chiffre officiel \n", + "3 \n", + "4 Chiffre officiel Chiffre officiel \n", + "5 Compte Disponibilit\\xe9s et Utilisations (CDU) (2010-) \n", + "6 \n", + " Production Importations Exportations Code_annee_pie\n", + "1 458850 2019-2021 \n", + "2 257583.33333 8705.55 75722.893333 2019-2021 \n", + "3 2019-2021 \n", + "4 369030 50019.883333 115180.46 2019-2021 \n", + "5 Chiffre officiel Chiffre officiel 2573.4766667 \n", + "6 \n", + " Dispo_alim_Source Dispo_alim Code_annee_dispo \n", + "1 2014-2015 \n", + "2 Valeur estim\\xe9e 14218.27 2014-2015 \n", + "3 Valeur estim\\xe9e 273285.2 2014-2015 \n", + "4 Valeur estim\\xe9e 0 2014-2015 \n", + "5 29585.933333 2019-2021 Valeur estim\\xe9e\n", + "6 " + ] + }, + "metadata": {}, + "output_type": "display_data" + } + ], + "source": [ + "# Specify the URL of the raw CSV file on GitLab\n", + "url <- 'https://app-learninglab.inria.fr/moocrr/gitlab/3f624f2cce5b76d09dcee501242941ad/mooc-rr/raw/master/module2/exo4/cdu_ba_pied.csv'\n", + "\n", + "# Define a temporary file to store the downloaded CSV\n", + "temp_file <- tempfile()\n", + "\n", + "# Download the file from the URL\n", + "download.file(url, temp_file)\n", + "\n", + "# Read the CSV file into a data frame\n", + "data <- read.csv(temp_file)\n", + "\n", + "# Display the first few rows of the data\n", + "head(data)" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "Il faut bien un fichier csv avec des délimitateurs en \",\" et pas \";\" comme je peux avoir...\n", + "ça affiche plusieurs messages d'erreurs, jsp pourquoi mais j'arrive quand même à avoir un tableau donc on va faire avec.\n", + "\n", + "Par contre comme j'ai modifié les délimitateurs les données ne ressemblent à rien (décalage) donc je change de fichier : impact env des groupes alimentaires.\n", + "\n", + "# Analyse des données d'impact env des groupes alimentaires\n", + "## Importation des données" + ] + }, + { + "cell_type": "code", + "execution_count": 32, + "metadata": { + "scrolled": true + }, + "outputs": [ + { + "data": { + "text/html": [ + "\n", + "\n", + "\n", + "\t\n", + "\t\n", + "\t\n", + "\t\n", + "\t\n", + "\t\n", + "\n", + "
GROUPE_CODEX_FREQ_Score_unique_EF_MeanScore_unique_EF_StdDevChangement_climatique_MeanChangement_climatique_StdDevAppauvrissement_couche_oz_MeanAppauvrissement_couche__StdDevRayonnements_ionisants_MeanRayonnements_ionisants_StdDev⋯ecotoxicite_ecosystemes_a_Meanecotoxicite_ecosystemes_StdDevUtilisation_sol_MeanUtilisation_sol_StdDevepuisement_des_ressources_Meanepuisement_des_ressourc_StdDevepuisement_ressources_ene_Meanepuisement_ressources_e_StdDevepuisement_ressources_min_Meanepuisement_ressources_m_StdDev
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03_00 148 0.3757590 0.159867273.452280 1.9798605 0.148128770.055571630.6703031 0.08027937⋯ 204.61011 128.26250 48.02076 37.685328 3.2385071 4.698552 29.00469 6.830369 10.367855 6.006572
04_01 19 0.3820526 0.513222983.685033 4.9710141 0.235242150.275255620.2283650 0.06213468⋯ 301.07316 537.94551 26.02446 45.525157 0.4947791 0.194756 15.01469 6.848735 7.092651 7.256771
04_02 39 0.2280956 0.063667132.060701 0.8268534 0.284851050.317277650.6158955 0.12766589⋯ 107.21770 55.19385 30.41174 30.502889 0.9428732 0.571074 23.07049 3.782505 12.374241 7.419407
\n" + ], + "text/latex": [ + "\\begin{tabular}{r|llllllllllllllllllllllllllllllllllll}\n", + " GROUPE\\_CODE & X\\_FREQ\\_ & Score\\_unique\\_EF\\_Mean & Score\\_unique\\_EF\\_StdDev & Changement\\_climatique\\_Mean & Changement\\_climatique\\_StdDev & Appauvrissement\\_couche\\_oz\\_Mean & Appauvrissement\\_couche\\_\\_StdDev & Rayonnements\\_ionisants\\_Mean & Rayonnements\\_ionisants\\_StdDev & ⋯ & ecotoxicite\\_ecosystemes\\_a\\_Mean & ecotoxicite\\_ecosystemes\\_StdDev & Utilisation\\_sol\\_Mean & Utilisation\\_sol\\_StdDev & epuisement\\_des\\_ressources\\_Mean & epuisement\\_des\\_ressourc\\_StdDev & epuisement\\_ressources\\_ene\\_Mean & epuisement\\_ressources\\_e\\_StdDev & epuisement\\_ressources\\_min\\_Mean & epuisement\\_ressources\\_m\\_StdDev\\\\\n", + "\\hline\n", + "\t 01\\_01 & 40 & 0.1690671 & 0.08691235 & 1.102390 & 0.4075877 & 0.09824716 & 0.03426206 & 0.5267681 & 0.12902244 & ⋯ & 90.88954 & 67.41254 & 31.40162 & 74.027014 & 2.2063072 & 5.271515 & 20.05869 & 4.688664 & 5.768970 & 3.227286 \\\\\n", + "\t 01\\_02 & 7 & 0.1728571 & 0.10703804 & 1.100000 & 0.4086155 & 0.08857143 & 0.01864454 & 0.5014286 & 0.02544836 & ⋯ & 75.45571 & 30.04057 & 14.73429 & 5.741321 & 4.3042857 & 10.111060 & 19.27714 & 3.513985 & 4.832857 & 1.681881 \\\\\n", + "\t 02\\_00 & 37 & 0.5100868 & 0.15954683 & 3.135058 & 0.8759679 & 0.17721972 & 0.03010228 & 0.6426515 & 0.08304114 & ⋯ & 177.46081 & 72.01405 & 63.20811 & 67.605597 & 18.8161715 & 13.198296 & 30.80388 & 5.129368 & 10.623857 & 1.711190 \\\\\n", + "\t 03\\_00 & 148 & 0.3757590 & 0.15986727 & 3.452280 & 1.9798605 & 0.14812877 & 0.05557163 & 0.6703031 & 0.08027937 & ⋯ & 204.61011 & 128.26250 & 48.02076 & 37.685328 & 3.2385071 & 4.698552 & 29.00469 & 6.830369 & 10.367855 & 6.006572 \\\\\n", + "\t 04\\_01 & 19 & 0.3820526 & 0.51322298 & 3.685033 & 4.9710141 & 0.23524215 & 0.27525562 & 0.2283650 & 0.06213468 & ⋯ & 301.07316 & 537.94551 & 26.02446 & 45.525157 & 0.4947791 & 0.194756 & 15.01469 & 6.848735 & 7.092651 & 7.256771 \\\\\n", + "\t 04\\_02 & 39 & 0.2280956 & 0.06366713 & 2.060701 & 0.8268534 & 0.28485105 & 0.31727765 & 0.6158955 & 0.12766589 & ⋯ & 107.21770 & 55.19385 & 30.41174 & 30.502889 & 0.9428732 & 0.571074 & 23.07049 & 3.782505 & 12.374241 & 7.419407 \\\\\n", + "\\end{tabular}\n" + ], + "text/markdown": [ + "\n", + "GROUPE_CODE | X_FREQ_ | Score_unique_EF_Mean | Score_unique_EF_StdDev | Changement_climatique_Mean | Changement_climatique_StdDev | Appauvrissement_couche_oz_Mean | Appauvrissement_couche__StdDev | Rayonnements_ionisants_Mean | Rayonnements_ionisants_StdDev | ⋯ | ecotoxicite_ecosystemes_a_Mean | ecotoxicite_ecosystemes_StdDev | Utilisation_sol_Mean | Utilisation_sol_StdDev | epuisement_des_ressources_Mean | epuisement_des_ressourc_StdDev | epuisement_ressources_ene_Mean | epuisement_ressources_e_StdDev | epuisement_ressources_min_Mean | epuisement_ressources_m_StdDev | \n", + "|---|---|---|---|---|---|\n", + "| 01_01 | 40 | 0.1690671 | 0.08691235 | 1.102390 | 0.4075877 | 0.09824716 | 0.03426206 | 0.5267681 | 0.12902244 | ⋯ | 90.88954 | 67.41254 | 31.40162 | 74.027014 | 2.2063072 | 5.271515 | 20.05869 | 4.688664 | 5.768970 | 3.227286 | \n", + "| 01_02 | 7 | 0.1728571 | 0.10703804 | 1.100000 | 0.4086155 | 0.08857143 | 0.01864454 | 0.5014286 | 0.02544836 | ⋯ | 75.45571 | 30.04057 | 14.73429 | 5.741321 | 4.3042857 | 10.111060 | 19.27714 | 3.513985 | 4.832857 | 1.681881 | \n", + "| 02_00 | 37 | 0.5100868 | 0.15954683 | 3.135058 | 0.8759679 | 0.17721972 | 0.03010228 | 0.6426515 | 0.08304114 | ⋯ | 177.46081 | 72.01405 | 63.20811 | 67.605597 | 18.8161715 | 13.198296 | 30.80388 | 5.129368 | 10.623857 | 1.711190 | \n", + "| 03_00 | 148 | 0.3757590 | 0.15986727 | 3.452280 | 1.9798605 | 0.14812877 | 0.05557163 | 0.6703031 | 0.08027937 | ⋯ | 204.61011 | 128.26250 | 48.02076 | 37.685328 | 3.2385071 | 4.698552 | 29.00469 | 6.830369 | 10.367855 | 6.006572 | \n", + "| 04_01 | 19 | 0.3820526 | 0.51322298 | 3.685033 | 4.9710141 | 0.23524215 | 0.27525562 | 0.2283650 | 0.06213468 | ⋯ | 301.07316 | 537.94551 | 26.02446 | 45.525157 | 0.4947791 | 0.194756 | 15.01469 | 6.848735 | 7.092651 | 7.256771 | \n", + "| 04_02 | 39 | 0.2280956 | 0.06366713 | 2.060701 | 0.8268534 | 0.28485105 | 0.31727765 | 0.6158955 | 0.12766589 | ⋯ | 107.21770 | 55.19385 | 30.41174 | 30.502889 | 0.9428732 | 0.571074 | 23.07049 | 3.782505 | 12.374241 | 7.419407 | \n", + "\n", + "\n" + ], + "text/plain": [ + " GROUPE_CODE X_FREQ_ Score_unique_EF_Mean Score_unique_EF_StdDev\n", + "1 01_01 40 0.1690671 0.08691235 \n", + "2 01_02 7 0.1728571 0.10703804 \n", + "3 02_00 37 0.5100868 0.15954683 \n", + "4 03_00 148 0.3757590 0.15986727 \n", + "5 04_01 19 0.3820526 0.51322298 \n", + "6 04_02 39 0.2280956 0.06366713 \n", + " Changement_climatique_Mean Changement_climatique_StdDev\n", + "1 1.102390 0.4075877 \n", + "2 1.100000 0.4086155 \n", + "3 3.135058 0.8759679 \n", + "4 3.452280 1.9798605 \n", + "5 3.685033 4.9710141 \n", + "6 2.060701 0.8268534 \n", + " Appauvrissement_couche_oz_Mean Appauvrissement_couche__StdDev\n", + "1 0.09824716 0.03426206 \n", + "2 0.08857143 0.01864454 \n", + "3 0.17721972 0.03010228 \n", + "4 0.14812877 0.05557163 \n", + "5 0.23524215 0.27525562 \n", + "6 0.28485105 0.31727765 \n", + " Rayonnements_ionisants_Mean Rayonnements_ionisants_StdDev ⋯\n", + "1 0.5267681 0.12902244 ⋯\n", + "2 0.5014286 0.02544836 ⋯\n", + "3 0.6426515 0.08304114 ⋯\n", + "4 0.6703031 0.08027937 ⋯\n", + "5 0.2283650 0.06213468 ⋯\n", + "6 0.6158955 0.12766589 ⋯\n", + " ecotoxicite_ecosystemes_a_Mean ecotoxicite_ecosystemes_StdDev\n", + "1 90.88954 67.41254 \n", + "2 75.45571 30.04057 \n", + "3 177.46081 72.01405 \n", + "4 204.61011 128.26250 \n", + "5 301.07316 537.94551 \n", + "6 107.21770 55.19385 \n", + " Utilisation_sol_Mean Utilisation_sol_StdDev epuisement_des_ressources_Mean\n", + "1 31.40162 74.027014 2.2063072 \n", + "2 14.73429 5.741321 4.3042857 \n", + "3 63.20811 67.605597 18.8161715 \n", + "4 48.02076 37.685328 3.2385071 \n", + "5 26.02446 45.525157 0.4947791 \n", + "6 30.41174 30.502889 0.9428732 \n", + " epuisement_des_ressourc_StdDev epuisement_ressources_ene_Mean\n", + "1 5.271515 20.05869 \n", + "2 10.111060 19.27714 \n", + "3 13.198296 30.80388 \n", + "4 4.698552 29.00469 \n", + "5 0.194756 15.01469 \n", + "6 0.571074 23.07049 \n", + " epuisement_ressources_e_StdDev epuisement_ressources_min_Mean\n", + "1 4.688664 5.768970 \n", + "2 3.513985 4.832857 \n", + "3 5.129368 10.623857 \n", + "4 6.830369 10.367855 \n", + "5 6.848735 7.092651 \n", + "6 3.782505 12.374241 \n", + " epuisement_ressources_m_StdDev\n", + "1 3.227286 \n", + "2 1.681881 \n", + "3 1.711190 \n", + "4 6.006572 \n", + "5 7.256771 \n", + "6 7.419407 " + ] + }, + "metadata": {}, + "output_type": "display_data" + } + ], + "source": [ + "# Specify the URL of the raw CSV file on GitLab\n", + "url <- 'https://app-learninglab.inria.fr/moocrr/gitlab/3f624f2cce5b76d09dcee501242941ad/mooc-rr/raw/master/module2/exo4/impact_gpe_v8.csv'\n", + "\n", + "# Define a temporary file to store the downloaded CSV\n", + "temp_file <- tempfile()\n", + "\n", + "# Download the file from the URL\n", + "download.file(url, temp_file)\n", + "\n", + "# Read the CSV file into a data frame\n", + "data <- read.csv(temp_file)\n", + "\n", + "# Display the first few rows of the data\n", + "head(data)" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "Là j'ai aucun message d'erreur donc j'ai bien fait de changer de fichier." + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "## Analyse\n", + "### Statistiques\n", + "On s'intéresse d'abord à toutes les variables" + ] + }, + { + "cell_type": "code", + "execution_count": 37, + "metadata": { + "scrolled": true + }, + "outputs": [ + { + "name": "stdout", + "output_type": "stream", + "text": [ + "'data.frame':\t38 obs. of 36 variables:\n", + " $ GROUPE_CODE : Factor w/ 38 levels \"01_01\",\"01_02\",..: 1 2 3 4 5 6 7 8 9 10 ...\n", + " $ X_FREQ_ : int 40 7 37 148 19 39 105 47 18 86 ...\n", + " $ Score_unique_EF_Mean : num 0.169 0.173 0.51 0.376 0.382 ...\n", + " $ Score_unique_EF_StdDev : num 0.0869 0.107 0.1595 0.1599 0.5132 ...\n", + " $ Changement_climatique_Mean : num 1.1 1.1 3.14 3.45 3.69 ...\n", + " $ Changement_climatique_StdDev : num 0.408 0.409 0.876 1.98 4.971 ...\n", + " $ Appauvrissement_couche_oz_Mean: num 0.0982 0.0886 0.1772 0.1481 0.2352 ...\n", + " $ Appauvrissement_couche__StdDev: num 0.0343 0.0186 0.0301 0.0556 0.2753 ...\n", + " $ Rayonnements_ionisants_Mean : num 0.527 0.501 0.643 0.67 0.228 ...\n", + " $ Rayonnements_ionisants_StdDev : num 0.129 0.0254 0.083 0.0803 0.0621 ...\n", + " $ Formation_photochimique_o_Mean: num 3.37 3.05 8.37 7.58 7.77 ...\n", + " $ Formation_photochimique_StdDev: num 1.52 1.04 2.06 3.86 11.2 ...\n", + " $ Particules_Mean : num 0.099 0.0843 0.2187 0.2595 0.2818 ...\n", + " $ Particules_StdDev : num 0.0482 0.0276 0.0417 0.1282 0.3529 ...\n", + " $ Effets_toxicologique_non__Mean: num 0.0353 0.0514 0.1964 0.0628 0.0748 ...\n", + " $ Effets_toxicologique_no_StdDev: num 0.0479 0.084 0.1262 0.0431 0.1049 ...\n", + " $ Effets_toxicologique_canc_Mean: num 0.131 0.107 0.259 0.277 0.106 ...\n", + " $ Effets_toxicologique_ca_StdDev: num 0.0702 0.0304 0.0615 0.1902 0.0542 ...\n", + " $ Acidification_terrestre_e_Mean: num 0.0138 0.0129 0.0279 0.0359 0.0415 ...\n", + " $ Acidification_terrestre_StdDev: num 0.00585 0.00488 0.00495 0.01819 0.05815 ...\n", + " $ Eutrophisation_eaux_douce_Mean: num 0.8992 0.0457 4.8364 0.3522 0.8822 ...\n", + " $ Eutrophisation_eaux_dou_StdDev: num 3.2795 0.0181 10.9825 1.4462 2.3001 ...\n", + " $ Eutrophisation_marine_Mean : num 0.233 0.227 0.542 0.499 0.328 ...\n", + " $ Eutrophisation_marine_StdDev : num 0.0961 0.082 0.2088 0.2598 0.3894 ...\n", + " $ Eutrophisation_terreste_Mean : num 6.91 7.03 26.65 14.15 36.46 ...\n", + " $ Eutrophisation_terreste_StdDev: num 3.21 2.04 15.47 7.39 76.16 ...\n", + " $ ecotoxicite_ecosystemes_a_Mean: num 90.9 75.5 177.5 204.6 301.1 ...\n", + " $ ecotoxicite_ecosystemes_StdDev: num 67.4 30 72 128.3 537.9 ...\n", + " $ Utilisation_sol_Mean : num 31.4 14.7 63.2 48 26 ...\n", + " $ Utilisation_sol_StdDev : num 74.03 5.74 67.61 37.69 45.53 ...\n", + " $ epuisement_des_ressources_Mean: num 2.206 4.304 18.816 3.239 0.495 ...\n", + " $ epuisement_des_ressourc_StdDev: num 5.272 10.111 13.198 4.699 0.195 ...\n", + " $ epuisement_ressources_ene_Mean: num 20.1 19.3 30.8 29 15 ...\n", + " $ epuisement_ressources_e_StdDev: num 4.69 3.51 5.13 6.83 6.85 ...\n", + " $ epuisement_ressources_min_Mean: num 5.77 4.83 10.62 10.37 7.09 ...\n", + " $ epuisement_ressources_m_StdDev: num 3.23 1.68 1.71 6.01 7.26 ...\n" + ] + } + ], + "source": [ + "str(data)" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "ça donne les infos globales sur la bdd." + ] + }, + { + "cell_type": "code", + "execution_count": 33, + "metadata": {}, + "outputs": [ + { + "data": { + "text/plain": [ + " GROUPE_CODE X_FREQ_ Score_unique_EF_Mean Score_unique_EF_StdDev\n", + " 01_01 : 1 Min. : 2.00 Min. :0.0400 Min. :0.00000 \n", + " 01_02 : 1 1st Qu.: 18.00 1st Qu.:0.1728 1st Qu.:0.08557 \n", + " 02_00 : 1 Median : 33.50 Median :0.2484 Median :0.16801 \n", + " 03_00 : 1 Mean : 46.63 Mean :0.5270 Mean :0.30424 \n", + " 04_01 : 1 3rd Qu.: 57.50 3rd Qu.:0.5825 3rd Qu.:0.31105 \n", + " 04_02 : 1 Max. :158.00 Max. :3.1376 Max. :1.49730 \n", + " (Other):32 \n", + " Changement_climatique_Mean Changement_climatique_StdDev\n", + " Min. : 0.270 Min. : 0.0000 \n", + " 1st Qu.: 1.101 1st Qu.: 0.4813 \n", + " Median : 2.068 Median : 0.9744 \n", + " Mean : 4.020 Mean : 2.2313 \n", + " 3rd Qu.: 3.697 3rd Qu.: 2.3812 \n", + " Max. :29.629 Max. :13.8123 \n", + " \n", + " Appauvrissement_couche_oz_Mean Appauvrissement_couche__StdDev\n", + " Min. :0.0800 Min. : 0.0000 \n", + " 1st Qu.:0.1357 1st Qu.: 0.0382 \n", + " Median :0.2171 Median : 0.1010 \n", + " Mean :0.4182 Mean : 1.0209 \n", + " 3rd Qu.:0.3482 3rd Qu.: 0.2903 \n", + " Max. :4.4051 Max. :31.9289 \n", + " \n", + " Rayonnements_ionisants_Mean Rayonnements_ionisants_StdDev\n", + " Min. :0.1100 Min. :0.00000 \n", + " 1st Qu.:0.3333 1st Qu.:0.08251 \n", + " Median :0.6324 Median :0.18682 \n", + " Mean :0.8689 Mean :0.61719 \n", + " 3rd Qu.:0.9761 3rd Qu.:0.51474 \n", + " Max. :4.5443 Max. :7.76010 \n", + " \n", + " Formation_photochimique_o_Mean Formation_photochimique_StdDev\n", + " Min. : 0.670 Min. : 0.000 \n", + " 1st Qu.: 3.533 1st Qu.: 1.639 \n", + " Median : 6.613 Median : 2.509 \n", + " Mean : 12.338 Mean : 8.936 \n", + " 3rd Qu.: 11.106 3rd Qu.: 10.057 \n", + " Max. :117.596 Max. :100.696 \n", + " \n", + " Particules_Mean Particules_StdDev Effets_toxicologique_non__Mean\n", + " Min. :0.01000 Min. :0.00000 Min. :0.00000 \n", + " 1st Qu.:0.07591 1st Qu.:0.04331 1st Qu.:0.03532 \n", + " Median :0.15265 Median :0.07823 Median :0.06334 \n", + " Mean :0.38711 Mean :0.23040 Mean :0.09518 \n", + " 3rd Qu.:0.35137 3rd Qu.:0.21672 3rd Qu.:0.11363 \n", + " Max. :2.94306 Max. :1.62950 Max. :0.55481 \n", + " \n", + " Effets_toxicologique_no_StdDev Effets_toxicologique_canc_Mean\n", + " Min. :0.00000 Min. :0.0100 \n", + " 1st Qu.:0.01978 1st Qu.:0.1240 \n", + " Median :0.04715 Median :0.1691 \n", + " Mean :0.07140 Mean :0.3168 \n", + " 3rd Qu.:0.10348 3rd Qu.:0.3969 \n", + " Max. :0.27928 Max. :1.5620 \n", + " \n", + " Effets_toxicologique_ca_StdDev Acidification_terrestre_e_Mean\n", + " Min. :0.00000 Min. :0.000000 \n", + " 1st Qu.:0.06378 1st Qu.:0.009893 \n", + " Median :0.12533 Median :0.020356 \n", + " Mean :0.18428 Mean :0.053325 \n", + " 3rd Qu.:0.18926 3rd Qu.:0.050070 \n", + " Max. :0.67315 Max. :0.434222 \n", + " \n", + " Acidification_terrestre_StdDev Eutrophisation_eaux_douce_Mean\n", + " Min. :0.000000 Min. : 0.01400 \n", + " 1st Qu.:0.006157 1st Qu.: 0.07713 \n", + " Median :0.012264 Median : 0.64370 \n", + " Mean :0.033180 Mean : 1.76189 \n", + " 3rd Qu.:0.029013 3rd Qu.: 1.46438 \n", + " Max. :0.243256 Max. :20.80024 \n", + " \n", + " Eutrophisation_eaux_dou_StdDev Eutrophisation_marine_Mean\n", + " Min. : 0.00944 Min. :0.06533 \n", + " 1st Qu.: 0.07356 1st Qu.:0.22862 \n", + " Median : 1.71391 Median :0.32385 \n", + " Mean : 4.90846 Mean :0.60516 \n", + " 3rd Qu.: 5.39792 3rd Qu.:0.74231 \n", + " Max. :49.18907 Max. :2.95879 \n", + " \n", + " Eutrophisation_marine_StdDev Eutrophisation_terreste_Mean\n", + " Min. :0.01766 Min. : 0.2007 \n", + " 1st Qu.:0.12797 1st Qu.: 6.0835 \n", + " Median :0.20261 Median : 10.8143 \n", + " Mean :0.46425 Mean : 19.0755 \n", + " 3rd Qu.:0.44607 3rd Qu.: 23.0735 \n", + " Max. :6.75216 Max. :100.1957 \n", + " \n", + " Eutrophisation_terreste_StdDev ecotoxicite_ecosystemes_a_Mean\n", + " Min. : 0.03532 Min. : 1.767 \n", + " 1st Qu.: 4.33741 1st Qu.: 59.586 \n", + " Median : 6.78650 Median : 109.491 \n", + " Mean : 16.34399 Mean : 259.546 \n", + " 3rd Qu.: 15.29029 3rd Qu.: 296.356 \n", + " Max. :120.97806 Max. :1948.050 \n", + " \n", + " ecotoxicite_ecosystemes_StdDev Utilisation_sol_Mean Utilisation_sol_StdDev\n", + " Min. : 0.1993 Min. : 1.083 Min. : 0.1993 \n", + " 1st Qu.: 41.2306 1st Qu.: 17.317 1st Qu.: 18.0447 \n", + " Median : 72.1084 Median : 32.281 Median : 38.6969 \n", + " Mean : 225.6050 Mean : 70.023 Mean : 89.6105 \n", + " 3rd Qu.: 226.8976 3rd Qu.: 71.199 3rd Qu.: 85.2467 \n", + " Max. :1600.1122 Max. :569.112 Max. :1085.3545 \n", + " \n", + " epuisement_des_ressources_Mean epuisement_des_ressourc_StdDev\n", + " Min. : 0.170 Min. : 0.000 \n", + " 1st Qu.: 1.347 1st Qu.: 1.049 \n", + " Median : 3.787 Median : 3.582 \n", + " Mean : 7.144 Mean : 9.432 \n", + " 3rd Qu.: 7.388 3rd Qu.: 9.407 \n", + " Max. :86.044 Max. :120.173 \n", + " \n", + " epuisement_ressources_ene_Mean epuisement_ressources_e_StdDev\n", + " Min. : 6.13 Min. : 0.000 \n", + " 1st Qu.: 18.75 1st Qu.: 4.971 \n", + " Median : 28.38 Median : 9.359 \n", + " Mean : 38.36 Mean : 20.039 \n", + " 3rd Qu.: 34.93 3rd Qu.: 22.719 \n", + " Max. :129.95 Max. :178.628 \n", + " \n", + " epuisement_ressources_min_Mean epuisement_ressources_m_StdDev\n", + " Min. : 3.790 Min. : 0.000 \n", + " 1st Qu.: 7.646 1st Qu.: 3.067 \n", + " Median :11.232 Median : 6.424 \n", + " Mean :17.047 Mean : 12.878 \n", + " 3rd Qu.:20.153 3rd Qu.: 12.850 \n", + " Max. :70.326 Max. :161.277 \n", + " " + ] + }, + "metadata": {}, + "output_type": "display_data" + } + ], + "source": [ + "summary(data)" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "Comme il y a beaucoup trop de variables, on va s'intéresser seulement à 2 : score unique et GES." + ] + }, + { + "cell_type": "code", + "execution_count": 35, + "metadata": {}, + "outputs": [ + { + "data": { + "text/plain": [ + " Min. 1st Qu. Median Mean 3rd Qu. Max. \n", + " 0.0400 0.1728 0.2484 0.5270 0.5825 3.1376 " + ] + }, + "metadata": {}, + "output_type": "display_data" + }, + { + "data": { + "text/plain": [ + " Min. 1st Qu. Median Mean 3rd Qu. Max. \n", + " 0.270 1.101 2.068 4.020 3.697 29.629 " + ] + }, + "metadata": {}, + "output_type": "display_data" + } + ], + "source": [ + "summary(data$Score_unique_EF_Mean)\n", + "summary(data$Changement_climatique_Mean)" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "Bon comme je n'ai plus toutes mes connaissances en R, on va passer aux graphiques.\n", + "\n", + "### Graphiques" + ] + }, + { + "cell_type": "code", + "execution_count": 45, + "metadata": {}, + "outputs": [ + { + "data": { + "image/png": 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WM0pNJ2WROiWyNCLVZ6DCQkBIzZ3yOt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\nEBIggJAAAYQECCAkQAAhAQL+F9W7sUtDQSXqAAAAAElFTkSuQmCC", + "text/plain": [ + "Plot with title “Score unique selon groupes”" + ] + }, + "metadata": {}, + "output_type": "display_data" + } + ], + "source": [ + "plot(x=data$GROUPE_CODE, y=data$Score_unique_EF_Mean, main = \"Score unique selon groupes\")" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "C'est pas mal, j'arrive pas à changer les tirets en point (même avec pch) mais c'est pas grave ça semble quand même fonctionner. \n", + "Je fais la même chose avec les GES." + ] + }, + { + "cell_type": "code", + "execution_count": 46, + "metadata": {}, + "outputs": [ + { + "data": { + "image/png": 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OtcDxJ2WNYHrudVWnxtBh08U78j5KV/S7Uewfw+1zT9QoviDNjfSx9xfjN+1zd8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\nAQIICRBASIAAQgIEEBIggJAAAf8Ltk3Xf22Gw8kAAAAASUVORK5CYII=", + "text/plain": [ + "Plot with title “GES selon groupes”" + ] + }, + "metadata": {}, + "output_type": "display_data" + } + ], + "source": [ + "plot(x=data$GROUPE_CODE, y=data$Changement_climatique_Mean, main = \"GES selon groupes\")" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "Et voila, on dit que c'est très bien pour l'instant :)" + ] + }, + { + "cell_type": "code", + "execution_count": null, + "metadata": {}, + "outputs": [], + "source": [] } ], "metadata": {