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Commit 5c75142c authored by 906a4f494f4ba26c398ed74cb4de7b36's avatar 906a4f494f4ba26c398ed74cb4de7b36
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module2/exo1/cars.csv 0 → 100644
View file @ 5c75142c
"","speed","dist"
"1",4,2
"2",4,10
"3",7,4
"4",7,22
"5",8,16
"6",9,10
"7",10,18
"8",10,26
"9",10,34
"10",11,17
"11",11,28
"12",12,14
"13",12,20
"14",12,24
"15",12,28
"16",13,26
"17",13,34
"18",13,34
"19",13,46
"20",14,26
"21",14,36
"22",14,60
"23",14,80
"24",15,20
"25",15,26
"26",15,54
"27",16,32
"28",16,40
"29",17,32
"30",17,40
"31",17,50
"32",18,42
"33",18,56
"34",18,76
"35",18,84
"36",19,36
"37",19,46
"38",19,68
"39",20,32
"40",20,48
"41",20,52
"42",20,56
"43",20,64
"44",22,66
"45",23,54
"46",24,70
"47",24,92
"48",24,93
"49",24,120
"50",25,85
module2/exo1/documents_notebooks_notebook_Jupyter_Python_R.ipynb 0 → 100644
View file @ 5c75142c
{
"cells": [
{
"cell_type": "markdown",
"metadata": {},
"source": [
"# Notebook Python R\n",
"\n",
"## Import des données dans Python"
]
},
{
"cell_type": "code",
"execution_count": 3,
"metadata": {},
"outputs": [
{
"data": {
"text/html": [
"<div>\n",
"<style scoped>\n",
" .dataframe tbody tr th:only-of-type {\n",
" vertical-align: middle;\n",
" }\n",
"\n",
" .dataframe tbody tr th {\n",
" vertical-align: top;\n",
" }\n",
"\n",
" .dataframe thead th {\n",
" text-align: right;\n",
" }\n",
"</style>\n",
"<table border=\"1\" class=\"dataframe\">\n",
" <thead>\n",
" <tr style=\"text-align: right;\">\n",
" <th></th>\n",
" <th>Unnamed: 0</th>\n",
" <th>speed</th>\n",
" <th>dist</th>\n",
" </tr>\n",
" </thead>\n",
" <tbody>\n",
" <tr>\n",
" <th>0</th>\n",
" <td>1</td>\n",
" <td>4</td>\n",
" <td>2</td>\n",
" </tr>\n",
" <tr>\n",
" <th>1</th>\n",
" <td>2</td>\n",
" <td>4</td>\n",
" <td>10</td>\n",
" </tr>\n",
" <tr>\n",
" <th>2</th>\n",
" <td>3</td>\n",
" <td>7</td>\n",
" <td>4</td>\n",
" </tr>\n",
" <tr>\n",
" <th>3</th>\n",
" <td>4</td>\n",
" <td>7</td>\n",
" <td>22</td>\n",
" </tr>\n",
" <tr>\n",
" <th>4</th>\n",
" <td>5</td>\n",
" <td>8</td>\n",
" <td>16</td>\n",
" </tr>\n",
" </tbody>\n",
"</table>\n",
"</div>"
],
"text/plain": [
" Unnamed: 0 speed dist\n",
"0 1 4 2\n",
"1 2 4 10\n",
"2 3 7 4\n",
"3 4 7 22\n",
"4 5 8 16"
]
},
"execution_count": 3,
"metadata": {},
"output_type": "execute_result"
}
],
"source": [
"import pandas as pd\n",
"# data_url = \"https://forge.scilab.org/index.php/p/rdataset/source/file/master/csv/datasets/cars.csv\"\n",
"data_url = \"cars.csv\"\n",
"df_python = pd.read_csv(data_url)\n",
"df_python.head()"
]
},
{
"cell_type": "markdown",
"metadata": {},
"source": [
"Supression de la première colonne"
]
},
{
"cell_type": "code",
"execution_count": 4,
"metadata": {},
"outputs": [
{
"data": {
"text/html": [
"<div>\n",
"<style scoped>\n",
" .dataframe tbody tr th:only-of-type {\n",
" vertical-align: middle;\n",
" }\n",
"\n",
" .dataframe tbody tr th {\n",
" vertical-align: top;\n",
" }\n",
"\n",
" .dataframe thead th {\n",
" text-align: right;\n",
" }\n",
"</style>\n",
"<table border=\"1\" class=\"dataframe\">\n",
" <thead>\n",
" <tr style=\"text-align: right;\">\n",
" <th></th>\n",
" <th>speed</th>\n",
" <th>dist</th>\n",
" </tr>\n",
" </thead>\n",
" <tbody>\n",
" <tr>\n",
" <th>0</th>\n",
" <td>4</td>\n",
" <td>2</td>\n",
" </tr>\n",
" <tr>\n",
" <th>1</th>\n",
" <td>4</td>\n",
" <td>10</td>\n",
" </tr>\n",
" <tr>\n",
" <th>2</th>\n",
" <td>7</td>\n",
" <td>4</td>\n",
" </tr>\n",
" <tr>\n",
" <th>3</th>\n",
" <td>7</td>\n",
" <td>22</td>\n",
" </tr>\n",
" <tr>\n",
" <th>4</th>\n",
" <td>8</td>\n",
" <td>16</td>\n",
" </tr>\n",
" </tbody>\n",
"</table>\n",
"</div>"
],
"text/plain": [
" speed dist\n",
"0 4 2\n",
"1 4 10\n",
"2 7 4\n",
"3 7 22\n",
"4 8 16"
]
},
"execution_count": 4,
"metadata": {},
"output_type": "execute_result"
}
],
"source": [
"df_python.drop(df_python.columns[[0]], axis=1, inplace=True)\n",
"df_python.head()"
]
},
{
"cell_type": "markdown",
"metadata": {},
"source": [
"## Summary avec Python"
]
},
{
"cell_type": "code",
"execution_count": 5,
"metadata": {},
"outputs": [
{
"data": {
"text/html": [
"<div>\n",
"<style scoped>\n",
" .dataframe tbody tr th:only-of-type {\n",
" vertical-align: middle;\n",
" }\n",
"\n",
" .dataframe tbody tr th {\n",
" vertical-align: top;\n",
" }\n",
"\n",
" .dataframe thead th {\n",
" text-align: right;\n",
" }\n",
"</style>\n",
"<table border=\"1\" class=\"dataframe\">\n",
" <thead>\n",
" <tr style=\"text-align: right;\">\n",
" <th></th>\n",
" <th>speed</th>\n",
" <th>dist</th>\n",
" </tr>\n",
" </thead>\n",
" <tbody>\n",
" <tr>\n",
" <th>count</th>\n",
" <td>50.000000</td>\n",
" <td>50.000000</td>\n",
" </tr>\n",
" <tr>\n",
" <th>mean</th>\n",
" <td>15.400000</td>\n",
" <td>42.980000</td>\n",
" </tr>\n",
" <tr>\n",
" <th>std</th>\n",
" <td>5.287644</td>\n",
" <td>25.769377</td>\n",
" </tr>\n",
" <tr>\n",
" <th>min</th>\n",
" <td>4.000000</td>\n",
" <td>2.000000</td>\n",
" </tr>\n",
" <tr>\n",
" <th>25%</th>\n",
" <td>12.000000</td>\n",
" <td>26.000000</td>\n",
" </tr>\n",
" <tr>\n",
" <th>50%</th>\n",
" <td>15.000000</td>\n",
" <td>36.000000</td>\n",
" </tr>\n",
" <tr>\n",
" <th>75%</th>\n",
" <td>19.000000</td>\n",
" <td>56.000000</td>\n",
" </tr>\n",
" <tr>\n",
" <th>max</th>\n",
" <td>25.000000</td>\n",
" <td>120.000000</td>\n",
" </tr>\n",
" </tbody>\n",
"</table>\n",
"</div>"
],
"text/plain": [
" speed dist\n",
"count 50.000000 50.000000\n",
"mean 15.400000 42.980000\n",
"std 5.287644 25.769377\n",
"min 4.000000 2.000000\n",
"25% 12.000000 26.000000\n",
"50% 15.000000 36.000000\n",
"75% 19.000000 56.000000\n",
"max 25.000000 120.000000"
]
},
"execution_count": 5,
"metadata": {},
"output_type": "execute_result"
}
],
"source": [
"df_python.describe()"
]
},
{
"cell_type": "markdown",
"metadata": {},
"source": [
"## Summary avec R"
]
},
{
"cell_type": "code",
"execution_count": 6,
"metadata": {},
"outputs": [],
"source": [
"from rpy2.robjects import pandas2ri\n",
"pandas2ri.activate()\n",
"from rpy2.robjects.packages import importr"
]
},
{
"cell_type": "code",
"execution_count": 7,
"metadata": {
"scrolled": true
},
"outputs": [
{
"name": "stdout",
"output_type": "stream",
"text": [
" speed dist \n",
" Min. : 4.0 Min. : 2.00 \n",
" 1st Qu.:12.0 1st Qu.: 26.00 \n",
" Median :15.0 Median : 36.00 \n",
" Mean :15.4 Mean : 42.98 \n",
" 3rd Qu.:19.0 3rd Qu.: 56.00 \n",
" Max. :25.0 Max. :120.00 \n",
"\n"
]
}
],
"source": [
"base = importr('base')\n",
"print(base.summary(df_python))"
]
},
{
"cell_type": "code",
"execution_count": 9,
"metadata": {},
"outputs": [
{
"ename": "RRuntimeError",
"evalue": "Error in loadNamespace(name) : there is no package called ‘prettyR’\n",
"output_type": "error",
"traceback": [
"\u001b[0;31m---------------------------------------------------------------------------\u001b[0m",
"\u001b[0;31mRRuntimeError\u001b[0m Traceback (most recent call last)",
"\u001b[0;32m<ipython-input-9-d7480842a7ea>\u001b[0m in \u001b[0;36m<module>\u001b[0;34m\u001b[0m\n\u001b[0;32m----> 1\u001b[0;31m \u001b[0mprettyR\u001b[0m \u001b[0;34m=\u001b[0m \u001b[0mimportr\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0;34m'prettyR'\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0m\u001b[1;32m 2\u001b[0m \u001b[0mprint\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0mprettyR\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0mdescribe\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0mdf_python\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n",
"\u001b[0;32m/opt/conda/lib/python3.6/site-packages/rpy2/robjects/packages.py\u001b[0m in \u001b[0;36mimportr\u001b[0;34m(name, lib_loc, robject_translations, signature_translation, suppress_messages, on_conflict, symbol_r2python, symbol_check_after, data)\u001b[0m\n\u001b[1;32m 451\u001b[0m if _package_has_namespace(rname, \n\u001b[1;32m 452\u001b[0m _system_file(package = rname)):\n\u001b[0;32m--> 453\u001b[0;31m \u001b[0menv\u001b[0m \u001b[0;34m=\u001b[0m \u001b[0m_get_namespace\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0mrname\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0m\u001b[1;32m 454\u001b[0m \u001b[0mversion\u001b[0m \u001b[0;34m=\u001b[0m \u001b[0m_get_namespace_version\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0mrname\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m[\u001b[0m\u001b[0;36m0\u001b[0m\u001b[0;34m]\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m 455\u001b[0m \u001b[0mexported_names\u001b[0m \u001b[0;34m=\u001b[0m \u001b[0mset\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0m_get_namespace_exports\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0mrname\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n",
"\u001b[0;31mRRuntimeError\u001b[0m: Error in loadNamespace(name) : there is no package called ‘prettyR’\n"
]
}
],
"source": [
"prettyR = importr('prettyR')\n",
"print(prettyR.describe(df_python))"
]
},
{
"cell_type": "markdown",
"metadata": {},
"source": [
"## Liens utiles\n",
"\n",
"- http://rpy.sourceforge.net/rpy2/doc-2.4/html/introduction.html\n",
"- https://rpy2.readthedocs.io/en/version_2.8.x/"
]
}
],
"metadata": {
"kernelspec": {
"display_name": "Python 3",
"language": "python",
"name": "python3"
},
"language_info": {
"codemirror_mode": {
"name": "ipython",
"version": 3
},
"file_extension": ".py",
"mimetype": "text/x-python",
"name": "python",
"nbconvert_exporter": "python",
"pygments_lexer": "ipython3",
"version": "3.6.4"
}
},
"nbformat": 4,
"nbformat_minor": 2
}
module2/exo1/toy_notebook_en.ipynb deleted 100644 → 0
View file @ 5618a8de
{
"cells": [],
"metadata": {
"kernelspec": {
"display_name": "Python 3",
"language": "python",
"name": "python3"
},
"language_info": {
"codemirror_mode": {
"name": "ipython",
"version": 3
},
"file_extension": ".py",
"mimetype": "text/x-python",
"name": "python",
"nbconvert_exporter": "python",
"pygments_lexer": "ipython3",
"version": "3.6.3"
}
},
"nbformat": 4,
"nbformat_minor": 2
}
module2/exo1/toy_notebook_fr.ipynb
View file @ 5c75142c
...@@ -96,21 +96,17 @@ ...@@ -96,21 +96,17 @@
], ],
"metadata": { "metadata": {
"kernelspec": { "kernelspec": {
"display_name": "Python 3", "display_name": "R",
"language": "python", "language": "R",
"name": "python3" "name": "ir"
}, },
"language_info": { "language_info": {
"codemirror_mode": { "codemirror_mode": "r",
"name": "ipython", "file_extension": ".r",
"version": 3 "mimetype": "text/x-r-source",
}, "name": "R",
"file_extension": ".py", "pygments_lexer": "r",
"mimetype": "text/x-python", "version": "3.4.1"
"name": "python",
"nbconvert_exporter": "python",
"pygments_lexer": "ipython3",
"version": "3.6.4"
} }
}, },
"nbformat": 4, "nbformat": 4,
......
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