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Commit 1d638d67 authored by 61cbc2a4c93a3237a08f8b8e6c523229's avatar 61cbc2a4c93a3237a08f8b8e6c523229
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Version 2

parent 2850adb2
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Showing with 18 additions and 33 deletions
Projet Maman 2/Untitled.ipynb
View file @ 1d638d67
...@@ -82,38 +82,14 @@ ...@@ -82,38 +82,14 @@
}, },
{ {
"cell_type": "code", "cell_type": "code",
"execution_count": 114, "execution_count": 155,
"metadata": {}, "metadata": {},
"outputs": [ "outputs": [
{
"ename": "TypeError",
"evalue": "cannot compare a dtyped [object] array with a scalar of type [bool]",
"output_type": "error",
"traceback": [
"\u001b[0;31m---------------------------------------------------------------------------\u001b[0m",
"\u001b[0;31mTypeError\u001b[0m Traceback (most recent call last)",
"\u001b[0;32m/opt/conda/lib/python3.6/site-packages/pandas/core/ops.py\u001b[0m in \u001b[0;36mna_op\u001b[0;34m(x, y)\u001b[0m\n\u001b[1;32m 900\u001b[0m \u001b[0;32mtry\u001b[0m\u001b[0;34m:\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0;32m--> 901\u001b[0;31m \u001b[0mresult\u001b[0m \u001b[0;34m=\u001b[0m \u001b[0mop\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0mx\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0my\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0m\u001b[1;32m 902\u001b[0m \u001b[0;32mexcept\u001b[0m \u001b[0mTypeError\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/pandas/core/ops.py\u001b[0m in \u001b[0;36m<lambda>\u001b[0;34m(x, y)\u001b[0m\n\u001b[1;32m 132\u001b[0m \u001b[0mxor\u001b[0m\u001b[0;34m=\u001b[0m\u001b[0mbool_method\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0moperator\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0mxor\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0mnames\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0;34m'xor'\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0mop\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0;34m'^'\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m,\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0;32m--> 133\u001b[0;31m rand_=bool_method(lambda x, y: operator.and_(y, x),\n\u001b[0m\u001b[1;32m 134\u001b[0m names('rand_'), op('&')),\n",
"\u001b[0;31mTypeError\u001b[0m: unsupported operand type(s) for &: 'str' and 'str'",
"\nDuring handling of the above exception, another exception occurred:\n",
"\u001b[0;31mTypeError\u001b[0m Traceback (most recent call last)",
"\u001b[0;32m/opt/conda/lib/python3.6/site-packages/pandas/core/ops.py\u001b[0m in \u001b[0;36mna_op\u001b[0;34m(x, y)\u001b[0m\n\u001b[1;32m 918\u001b[0m \u001b[0my\u001b[0m \u001b[0;34m=\u001b[0m \u001b[0mbool\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0my\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0;32m--> 919\u001b[0;31m \u001b[0mresult\u001b[0m \u001b[0;34m=\u001b[0m \u001b[0mlib\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0mscalar_binop\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0mx\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0my\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0mop\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0m\u001b[1;32m 920\u001b[0m \u001b[0;32mexcept\u001b[0m\u001b[0;34m:\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n",
"\u001b[0;32mpandas/_libs/lib.pyx\u001b[0m in \u001b[0;36mpandas._libs.lib.scalar_binop\u001b[0;34m()\u001b[0m\n",
"\u001b[0;32m/opt/conda/lib/python3.6/site-packages/pandas/core/ops.py\u001b[0m in \u001b[0;36m<lambda>\u001b[0;34m(x, y)\u001b[0m\n\u001b[1;32m 132\u001b[0m \u001b[0mxor\u001b[0m\u001b[0;34m=\u001b[0m\u001b[0mbool_method\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0moperator\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0mxor\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0mnames\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0;34m'xor'\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0mop\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0;34m'^'\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m,\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0;32m--> 133\u001b[0;31m rand_=bool_method(lambda x, y: operator.and_(y, x),\n\u001b[0m\u001b[1;32m 134\u001b[0m names('rand_'), op('&')),\n",
"\u001b[0;31mTypeError\u001b[0m: unsupported operand type(s) for &: 'bool' and 'str'",
"\nDuring handling of the above exception, another exception occurred:\n",
"\u001b[0;31mTypeError\u001b[0m Traceback (most recent call last)",
"\u001b[0;32m<ipython-input-114-fc729485d06d>\u001b[0m in \u001b[0;36m<module>\u001b[0;34m\u001b[0m\n\u001b[1;32m 12\u001b[0m \u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m 13\u001b[0m \u001b[0mplt\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0msubplot\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0;36m1\u001b[0m\u001b[0;34m,\u001b[0m\u001b[0;36m3\u001b[0m\u001b[0;34m,\u001b[0m\u001b[0;36m3\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0;32m---> 14\u001b[0;31m \u001b[0mtableau\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0mloc\u001b[0m\u001b[0;34m[\u001b[0m\u001b[0mtableau\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0mloc\u001b[0m\u001b[0;34m[\u001b[0m\u001b[0;34m:\u001b[0m\u001b[0;34m,\u001b[0m\u001b[0;34m\"Type\"\u001b[0m\u001b[0;34m]\u001b[0m\u001b[0;34m==\u001b[0m\u001b[0;34m\"QuizP\"\u001b[0m \u001b[0;34m&\u001b[0m \u001b[0mtableau\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0mloc\u001b[0m\u001b[0;34m[\u001b[0m\u001b[0;34m:\u001b[0m\u001b[0;34m,\u001b[0m\u001b[0;34m\"Label\"\u001b[0m\u001b[0;34m]\u001b[0m\u001b[0;34m==\u001b[0m\u001b[0;34m\"Jupiter\"\u001b[0m\u001b[0;34m,\u001b[0m\u001b[0;34m\"Num\"\u001b[0m\u001b[0;34m]\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0mplot\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0m\u001b[1;32m 15\u001b[0m \u001b[0mplt\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0mtitle\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0;34m\"QuizP\"\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m 16\u001b[0m \u001b[0mplt\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0mshow\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/pandas/core/ops.py\u001b[0m in \u001b[0;36mwrapper\u001b[0;34m(self, other)\u001b[0m\n\u001b[1;32m 952\u001b[0m is_integer_dtype(np.asarray(other)) else fill_bool)\n\u001b[1;32m 953\u001b[0m return filler(self._constructor(\n\u001b[0;32m--> 954\u001b[0;31m \u001b[0mna_op\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0mself\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0mvalues\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0mother\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m,\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0m\u001b[1;32m 955\u001b[0m index=self.index)).__finalize__(self)\n\u001b[1;32m 956\u001b[0m \u001b[0;34m\u001b[0m\u001b[0m\n",
"\u001b[0;32m/opt/conda/lib/python3.6/site-packages/pandas/core/ops.py\u001b[0m in \u001b[0;36mna_op\u001b[0;34m(x, y)\u001b[0m\n\u001b[1;32m 922\u001b[0m \u001b[0;34m\"with a scalar of type [{type}]\"\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m 923\u001b[0m ).format(dtype=x.dtype, type=type(y).__name__)\n\u001b[0;32m--> 924\u001b[0;31m \u001b[0;32mraise\u001b[0m \u001b[0mTypeError\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0mmsg\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0m\u001b[1;32m 925\u001b[0m \u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m 926\u001b[0m \u001b[0;32mreturn\u001b[0m \u001b[0mresult\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n",
"\u001b[0;31mTypeError\u001b[0m: cannot compare a dtyped [object] array with a scalar of type [bool]"
]
},
{ {
"data": { "data": {
"image/png": 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\n", 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\n",
"text/plain": [ "text/plain": [
"<Figure size 1080x144 with 3 Axes>" "<Figure size 1440x360 with 3 Axes>"
] ]
}, },
"metadata": { "metadata": {
...@@ -125,19 +101,28 @@ ...@@ -125,19 +101,28 @@
"source": [ "source": [
"## Graphs\n", "## Graphs\n",
"\n", "\n",
"plt.figure(1,figsize=(15,2))\n", "plt.figure(1,figsize=(20,5))\n",
"plt.subplot(1,3,1)\n", "plt.subplot(131)\n",
"tableau.loc[tableau.loc[:,\"Type\"]==\"Exercices\",\"Num\"].plot()\n", "tableau.loc[tableau.loc[:,\"Type\"]==\"Exercices\",\"Num\"].plot()\n",
"plt.ylabel(\"Num\")\n",
"plt.title(\"Exercices\")\n", "plt.title(\"Exercices\")\n",
"\n", "\n",
"plt.subplot(132)\n",
"tableau.loc[(tableau.loc[:,\"Type\"]==\"Quiz\") & (tableau.loc[:,\"Label\"]==\"Module 1\"),\"Num\"].plot()\n",
"tableau.loc[(tableau.loc[:,\"Type\"]==\"Quiz\") & (tableau.loc[:,\"Label\"]==\"Module 2\"),\"Num\"].plot()\n",
"tableau.loc[(tableau.loc[:,\"Type\"]==\"Quiz\") & (tableau.loc[:,\"Label\"]==\"Module 3\"),\"Num\"].plot()\n",
"tableau.loc[(tableau.loc[:,\"Type\"]==\"Quiz\") & (tableau.loc[:,\"Label\"]==\"Module 4\"),\"Num\"].plot()\n",
"plt.legend([\"Module 1\",\"Module 2\",\"Module 3\",\"Module 4\"])\n",
"\n", "\n",
"plt.subplot(1,3,2)\n",
"tableau.loc[tableau.loc[:,\"Type\"]==\"Quiz\",\"Num\"].plot()\n",
"plt.title(\"Quiz\")\n", "plt.title(\"Quiz\")\n",
"\n", "\n",
"plt.subplot(1,3,3)\n", "plt.subplot(133)\n",
"tableau.loc[tableau.loc[:,\"Type\"]==\"QuizP\" & tableau.loc[:,\"Label\"]==\"Jupiter\",\"Num\"].plot()\n", "tableau.loc[(tableau.loc[:,\"Type\"]==\"QuizP\") & (tableau.loc[:,\"Label\"]==\"Jupiter\"),\"Num\"].plot()\n",
"tableau.loc[(tableau.loc[:,\"Type\"]==\"QuizP\") & (tableau.loc[:,\"Label\"]==\"R\"),\"Num\"].plot()\n",
"tableau.loc[(tableau.loc[:,\"Type\"]==\"QuizP\") & (tableau.loc[:,\"Label\"]==\"OrgMode\"),\"Num\"].plot()\n",
"plt.legend([\"Jupiter\",\"R\",\"Orgmode\"])\n",
"plt.title(\"QuizP\")\n", "plt.title(\"QuizP\")\n",
"\n",
"plt.show()" "plt.show()"
] ]
} }
......
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