"Requirement already satisfied: ipython-genutils in /opt/conda/lib/python3.6/site-packages (from traitlets>=4.2->ipython>=7->sas_kernel) (0.2.0)\n",
"Requirement already satisfied: six in /opt/conda/lib/python3.6/site-packages (from traitlets>=4.2->ipython>=7->sas_kernel) (1.14.0)\n",
"Requirement already satisfied: wcwidth in /opt/conda/lib/python3.6/site-packages (from prompt-toolkit!=3.0.0,!=3.0.1,<3.1.0,>=2.0.0->ipython>=7->sas_kernel) (0.1.8)\n",
"Note: you may need to restart the kernel to use updated packages.\n"
]
}
],
"source": [
"pip install sas_kernel"
]
},
{
"cell_type": "markdown",
"metadata": {},
"source": [
"Une fois les deux commandes lancées, il faut enregistrer et quitter (et restart the kernel ?). Mais quand on revient on a bien SAS proposé dans les kernel (Kernel > Change kernel)."
]
},
{
"cell_type": "code",
"execution_count": null,
"metadata": {},
"outputs": [
{
"name": "stderr",
"output_type": "stream",
"text": [
"\u001b[0;31m[<class 'saspy.sasexceptions.SASIOConnectionTerminated'>, SASIOConnectionTerminated(<class 'Exception'>,), <traceback object at 0x7fe1cf696688>]\n",
"\u001b[0m"
]
}
],
"source": [
"%load_ext saspy.ipython\n",
"%%SAS\n",
"proc import out=table\n",
"datafile='module2/exo4/cdu_ba_pied.csv' \n",
"dbms=dlm replace;\n",
"delimiter=';'; /*csv*/\n",
"getnames=yes; /*la première ligne donne les noms des variables*/\n",
"guessingrows=max; /*utilisation du max de lignes pour déterminer le type de variable (numérique / nombre de caractères, etc*/\n",
"run;\n"
]
},
{
"cell_type": "markdown",
"metadata": {},
"source": [
"ça ne marche pas parce qu'il faut réussir à connecter Jupyter avec SAS (pour la licence je pense) donc j'abandonne (pas sûre que ça vale le coût de passer du temps dessus, mais à voir) et je reste en R."
"5. stop(\"'\", path, \"' does not exist\", if (!is_absolute_path(path)) paste0(\" in current working directory ('\", \n . getwd(), \"')\"), \".\", call. = FALSE)"
]
}
],
"source": [
"data1 <- read_csv('/cdu_ba_pied.csv')\n",
"head(data1)"
]
},
{
"cell_type": "code",
"execution_count": 16,
"metadata": {},
"outputs": [
{
"name": "stdout",
"output_type": "stream",
"text": [
"Classes ‘tbl_df’, ‘tbl’ and 'data.frame':\t1 obs. of 1 variable:\n",
