diff --git a/module3/exo3/exercice.ipynb b/module3/exo3/exercice.ipynb index f7b109b8aab1ea0f3df0338a26b19556d03ed8e6..ba413f5c2361b41a40012857bb29a1d4984481e2 100644 --- a/module3/exo3/exercice.ipynb +++ b/module3/exo3/exercice.ipynb @@ -9,7 +9,7 @@ }, { "cell_type": "code", - "execution_count": 107, + "execution_count": 5, "metadata": {}, "outputs": [], "source": [ @@ -29,7 +29,7 @@ }, { "cell_type": "code", - "execution_count": 108, + "execution_count": 6, "metadata": {}, "outputs": [], "source": [ @@ -54,7 +54,7 @@ }, { "cell_type": "code", - "execution_count": 130, + "execution_count": 7, "metadata": {}, "outputs": [ { @@ -226,7 +226,7 @@ }, { "cell_type": "code", - "execution_count": 117, + "execution_count": 8, "metadata": {}, "outputs": [ { @@ -333,7 +333,7 @@ }, { "cell_type": "code", - "execution_count": 146, + "execution_count": 9, "metadata": {}, "outputs": [ { @@ -479,7 +479,7 @@ }, { "cell_type": "code", - "execution_count": 216, + "execution_count": 10, "metadata": { "scrolled": true }, @@ -666,24 +666,59 @@ }, { "cell_type": "code", - "execution_count": 224, + "execution_count": 34, "metadata": {}, "outputs": [ { - "ename": "SyntaxError", - "evalue": "invalid syntax (, line 5)", - "output_type": "error", - "traceback": [ - "\u001b[0;36m File \u001b[0;32m\"\"\u001b[0;36m, line \u001b[0;32m5\u001b[0m\n\u001b[0;31m plt.hist(x2, bins = bins, color = 'green',edgecolor = 'blue', hatch = '\\', label = 'x2')\u001b[0m\n\u001b[0m ^\u001b[0m\n\u001b[0;31mSyntaxError\u001b[0m\u001b[0;31m:\u001b[0m invalid syntax\n" + "name": "stdout", + "output_type": "stream", + "text": [ + "[55.75304022450889, 0.0, 0.0, 0.0, 69.3854748603352, 0.0, 0.0, 0.0, 0.0, 0.0, 14.817036592681463, 32.945736434108525, 0.0, 0.0, 0.0, 0.0, 0.5055611729019212, 0.0, 4.081632653061225, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 57.859848484848484, 6.779661016949152, 30.846605196982395, 0.0]\n" ] + }, + { + "data": { + "text/plain": [ + "" + ] + }, + "execution_count": 34, + "metadata": {}, + "output_type": "execute_result" + }, + { + "data": { + "image/png": "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\n", + "text/plain": [ + "
" + ] + }, + "metadata": { + "needs_background": "light" + }, + "output_type": "display_data" } ], "source": [ - "x1 = [1, 2, 2, 3, 4, 4, 4, 4, 4, 5, 5]\n", - "x2 = [1, 1, 1, 2, 2, 3, 3, 3, 3, 4, 5, 5, 5]\n", - "bins = nbscenetotal\n", - "plt.hist(x1, bins = bins, color = 'yellow',edgecolor = 'red', hatch = '/', label = 'x1')\n", - "plt.hist(x2, bins = bins, color = 'green', alpha = 0.5 ,edgecolor = 'blue', hatch = '\\', label = 'x2')\n", + "def pourcentagemotsparscene(a):\n", + " liste=[]\n", + " sommemotsscene=0\n", + " for i in range(len(listeacte)):\n", + " for j in range(len(listeacte[i])):\n", + " sommemotsscene=0\n", + " for k in range(len(listeacte[i][j])):\n", + " sommemotsscene=sommemotsscene+listeacte[i][j][k]\n", + " \n", + " pourcentage=listeacte[i][j][a]/sommemotsscene*100\n", + " liste.append(pourcentage)\n", + " return liste\n", + "\n", + "print(pourcentagemotsparscene(0))\n", + "bins = 32\n", + "plt.hist(pourcentagemotsparscene(0), bins = bins, color = 'yellow',edgecolor = 'red', hatch = '/',orientation = 'horizontal', label = 'valere')\n", + "plt.hist(pourcentagemotsparscene(1), bins = bins, color = 'green', alpha = 0.5 ,edgecolor = 'blue', hatch = '\\'',orientation = 'horizontal', label = 'elise')\n", + "plt.hist(pourcentagemotsparscene(2), bins = bins, color = 'blue',edgecolor = 'red', hatch = '/',orientation = 'horizontal', label = 'cleante')\n", + "plt.hist(pourcentagemotsparscene(3), bins = bins, color = 'red', alpha = 0.5 ,edgecolor = 'blue', hatch = '\\'' ,orientation = 'horizontal', label = 'harpagon')\n", "plt.ylabel('valeurs')\n", "plt.xlabel('nombres')\n", "plt.title('superpose')\n",