Skip to content

M
mooc-rr
Commit a1edd1dc authored by 3f624f2cce5b76d09dcee501242941ad's avatar 3f624f2cce5b76d09dcee501242941ad
Browse files
Options

no commit message

parent bde72742
Hide whitespace changes
Inline Side-by-side
Showing with 789 additions and 1 deletion
module2/exo4/exercice.ipynb
View file @ a1edd1dc
......@@ -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 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 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 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(\"<html.*>\", data[[\"text/html\"]], ignore.case = TRUE):\n",
"“input string 1 is invalid in this locale”"
]
},
{
"data": {
"text/html": [
"<table>\n",
"<thead><tr><th scope=col>code_fao</th><th scope=col>Produit</th><th scope=col>Code_Domaine</th><th scope=col>Domaine</th><th scope=col>Production_Source</th><th scope=col>Exportations_Source</th><th scope=col>Importations_Source</th><th scope=col>Production</th><th scope=col>Importations</th><th scope=col>Exportations</th><th scope=col>Code_annee_pie</th><th scope=col>Dispo_alim_Source</th><th scope=col>Dispo_alim</th><th scope=col>Code_annee_dispo</th></tr></thead>\n",
"<tbody>\n",
"\t<tr><td>01199.02 </td><td>C<e9>r<e9>ales m<e9>lang<e9>es </td><td>SCL </td><td>Compte Disponibilit<e9>s et Utilisations (CDU) (2010-)</td><td>Chiffre officiel </td><td> </td><td> </td><td>458850 </td><td> </td><td> </td><td>2019-2021 </td><td> </td><td> </td><td>2014-2015 </td></tr>\n",
"\t<tr><td>01199.90 </td><td>Cer<e9>ales n.a.c. </td><td>SCL </td><td>Compte Disponibilit<e9>s et Utilisations (CDU) (2010-)</td><td>Chiffre officiel </td><td>Chiffre officiel </td><td>Chiffre officiel </td><td>257583.33333 </td><td>8705.55 </td><td>75722.893333 </td><td>2019-2021 </td><td>Valeur estim<e9>e </td><td>14218.27 </td><td>2014-2015 </td></tr>\n",
"\t<tr><td>01241.01 </td><td>Haricots verts </td><td>SCL </td><td>Compte Disponibilit<e9>s et Utilisations (CDU) (2010-)</td><td> </td><td> </td><td> </td><td> </td><td> </td><td> </td><td>2019-2021 </td><td>Valeur estim<e9>e </td><td>273285.2 </td><td>2014-2015 </td></tr>\n",
"\t<tr><td>01241.90 </td><td>Autres haricots frais </td><td>SCL </td><td>Compte Disponibilit<e9>s et Utilisations (CDU) (2010-)</td><td>Chiffre officiel </td><td>Chiffre officiel </td><td>Chiffre officiel </td><td>369030 </td><td>50019.883333 </td><td>115180.46 </td><td>2019-2021 </td><td>Valeur estim<e9>e </td><td>0 </td><td>2014-2015 </td></tr>\n",
"\t<tr><td>01253.01 </td><td>Oignons </td><td> echalotes </td><td> frais </td><td>SCL </td><td>Compte Disponibilit<e9>s et Utilisations (CDU) (2010-)</td><td> </td><td>Chiffre officiel </td><td>Chiffre officiel </td><td> </td><td>2573.4766667 </td><td>29585.933333 </td><td>2019-2021 </td><td>Valeur estim<e9>e </td></tr>\n",
"\t<tr><td>16600.565 </td><td>2014-2015 </td><td> </td><td> </td><td> </td><td> </td><td> </td><td> </td><td> </td><td> </td><td> </td><td> </td><td> </td><td> </td></tr>\n",
"</tbody>\n",
"</table>\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 | C<e9>r<e9>ales m<e9>lang<e9>es | SCL | Compte Disponibilit<e9>s et Utilisations (CDU) (2010-) | Chiffre officiel | | | 458850 | | | 2019-2021 | | | 2014-2015 | \n",
"| 01199.90 | Cer<e9>ales n.a.c. | SCL | Compte Disponibilit<e9>s et Utilisations (CDU) (2010-) | Chiffre officiel | Chiffre officiel | Chiffre officiel | 257583.33333 | 8705.55 | 75722.893333 | 2019-2021 | Valeur estim<e9>e | 14218.27 | 2014-2015 | \n",
"| 01241.01 | Haricots verts | SCL | Compte Disponibilit<e9>s et Utilisations (CDU) (2010-) | | | | | | | 2019-2021 | Valeur estim<e9>e | 273285.2 | 2014-2015 | \n",
"| 01241.90 | Autres haricots frais | SCL | Compte Disponibilit<e9>s et Utilisations (CDU) (2010-) | Chiffre officiel | Chiffre officiel | Chiffre officiel | 369030 | 50019.883333 | 115180.46 | 2019-2021 | Valeur estim<e9>e | 0 | 2014-2015 | \n",
"| 01253.01 | Oignons | echalotes | frais | SCL | Compte Disponibilit<e9>s et Utilisations (CDU) (2010-) | | Chiffre officiel | Chiffre officiel | | 2573.4766667 | 29585.933333 | 2019-2021 | Valeur estim<e9>e | \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": [
"<table>\n",
"<thead><tr><th scope=col>GROUPE_CODE</th><th scope=col>X_FREQ_</th><th scope=col>Score_unique_EF_Mean</th><th scope=col>Score_unique_EF_StdDev</th><th scope=col>Changement_climatique_Mean</th><th scope=col>Changement_climatique_StdDev</th><th scope=col>Appauvrissement_couche_oz_Mean</th><th scope=col>Appauvrissement_couche__StdDev</th><th scope=col>Rayonnements_ionisants_Mean</th><th scope=col>Rayonnements_ionisants_StdDev</th><th scope=col>⋯</th><th scope=col>ecotoxicite_ecosystemes_a_Mean</th><th scope=col>ecotoxicite_ecosystemes_StdDev</th><th scope=col>Utilisation_sol_Mean</th><th scope=col>Utilisation_sol_StdDev</th><th scope=col>epuisement_des_ressources_Mean</th><th scope=col>epuisement_des_ressourc_StdDev</th><th scope=col>epuisement_ressources_ene_Mean</th><th scope=col>epuisement_ressources_e_StdDev</th><th scope=col>epuisement_ressources_min_Mean</th><th scope=col>epuisement_ressources_m_StdDev</th></tr></thead>\n",
"<tbody>\n",
"\t<tr><td>01_01 </td><td> 40 </td><td>0.1690671 </td><td>0.08691235</td><td>1.102390 </td><td>0.4075877 </td><td>0.09824716</td><td>0.03426206</td><td>0.5267681 </td><td>0.12902244</td><td>⋯ </td><td> 90.88954 </td><td> 67.41254 </td><td>31.40162 </td><td>74.027014 </td><td> 2.2063072</td><td> 5.271515 </td><td>20.05869 </td><td>4.688664 </td><td> 5.768970 </td><td>3.227286 </td></tr>\n",
"\t<tr><td>01_02 </td><td> 7 </td><td>0.1728571 </td><td>0.10703804</td><td>1.100000 </td><td>0.4086155 </td><td>0.08857143</td><td>0.01864454</td><td>0.5014286 </td><td>0.02544836</td><td>⋯ </td><td> 75.45571 </td><td> 30.04057 </td><td>14.73429 </td><td> 5.741321 </td><td> 4.3042857</td><td>10.111060 </td><td>19.27714 </td><td>3.513985 </td><td> 4.832857 </td><td>1.681881 </td></tr>\n",
"\t<tr><td>02_00 </td><td> 37 </td><td>0.5100868 </td><td>0.15954683</td><td>3.135058 </td><td>0.8759679 </td><td>0.17721972</td><td>0.03010228</td><td>0.6426515 </td><td>0.08304114</td><td>⋯ </td><td>177.46081 </td><td> 72.01405 </td><td>63.20811 </td><td>67.605597 </td><td>18.8161715</td><td>13.198296 </td><td>30.80388 </td><td>5.129368 </td><td>10.623857 </td><td>1.711190 </td></tr>\n",
"\t<tr><td>03_00 </td><td>148 </td><td>0.3757590 </td><td>0.15986727</td><td>3.452280 </td><td>1.9798605 </td><td>0.14812877</td><td>0.05557163</td><td>0.6703031 </td><td>0.08027937</td><td>⋯ </td><td>204.61011 </td><td>128.26250 </td><td>48.02076 </td><td>37.685328 </td><td> 3.2385071</td><td> 4.698552 </td><td>29.00469 </td><td>6.830369 </td><td>10.367855 </td><td>6.006572 </td></tr>\n",
"\t<tr><td>04_01 </td><td> 19 </td><td>0.3820526 </td><td>0.51322298</td><td>3.685033 </td><td>4.9710141 </td><td>0.23524215</td><td>0.27525562</td><td>0.2283650 </td><td>0.06213468</td><td>⋯ </td><td>301.07316 </td><td>537.94551 </td><td>26.02446 </td><td>45.525157 </td><td> 0.4947791</td><td> 0.194756 </td><td>15.01469 </td><td>6.848735 </td><td> 7.092651 </td><td>7.256771 </td></tr>\n",
"\t<tr><td>04_02 </td><td> 39 </td><td>0.2280956 </td><td>0.06366713</td><td>2.060701 </td><td>0.8268534 </td><td>0.28485105</td><td>0.31727765</td><td>0.6158955 </td><td>0.12766589</td><td>⋯ </td><td>107.21770 </td><td> 55.19385 </td><td>30.41174 </td><td>30.502889 </td><td> 0.9428732</td><td> 0.571074 </td><td>23.07049 </td><td>3.782505 </td><td>12.374241 </td><td>7.419407 </td></tr>\n",
"</tbody>\n",
"</table>\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": "iVBORw0KGgoAAAANSUhEUgAAA0gAAANICAMAAADKOT/pAAADAFBMVEUAAAABAQECAgIDAwME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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": "iVBORw0KGgoAAAANSUhEUgAAA0gAAANICAMAAADKOT/pAAAC/VBMVEUAAAABAQECAgIDAwME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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": {
......
Markdown is supported
0% or
You are about to add 0 people to the discussion. Proceed with caution.
Finish editing this message first!
Please register or to comment