check

module2/exo3/exercice.ipynb

 {
- "cells": [],
+ "cells": [
+  {
+   "cell_type": "code",
+   "execution_count": 22,
+   "metadata": {},
+   "outputs": [
+    {
+     "data": {
+      "text/plain": [
+       "(0, 24.4)"
+      ]
+     },
+     "execution_count": 22,
+     "metadata": {},
+     "output_type": "execute_result"
+    },
+    {
+     "data": {
+      "image/png": "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\n",
+      "text/plain": [
+       "<Figure size 432x288 with 1 Axes>"
+      ]
+     },
+     "metadata": {
+      "needs_background": "light"
+     },
+     "output_type": "display_data"
+    }
+   ],
+   "source": [
+    "%matplotlib inline\n",
+    "import matplotlib.pyplot as plt\n",
+    "import numpy as np\n",
+    "\n",
+    "data =  [14.0, 7.6, 11.2, 12.8, 12.5, 9.9, 14.9, 9.4, 16.9, 10.2, 14.9, 18.1, 7.3, 9.8, 10.9,\n",
+    "        12.2, 9.9, 2.9, 2.8, 15.4, 15.7, 9.7, 13.1, 13.2, 12.3, 11.7, 16.0, 12.4, 17.9, 12.2,\n",
+    "        16.2, 18.7, 8.9, 11.9, 12.1, 14.6, 12.1, 4.7, 3.9, 16.9, 16.8, 11.3, 14.4, 15.7, 14.0,\n",
+    "        13.6, 18.0, 13.6, 19.9, 13.7, 17.0, 20.5, 9.9, 12.5, 13.2, 16.1, 13.5, 6.3, 6.4, 17.6,\n",
+    "        19.1, 12.8, 15.5, 16.3, 15.2, 14.6, 19.1, 14.4, 21.4, 15.1, 19.6, 21.7, 11.3, 15.0, 14.3,\n",
+    "        16.8, 14.0, 6.8, 8.2, 19.9, 20.4, 14.6, 16.4, 18.7, 16.8, 15.8, 20.4, 15.8, 22.4, 16.2,\n",
+    "        20.3, 23.4, 12.1, 15.5, 15.4, 18.4, 15.7, 10.2, 8.9, 21.0]\n",
+    "\n",
+    "\n",
+    "plt.plot(data, color='b', linewidth = '0.6')\n",
+    "plt.grid(linestyle='--')\n",
+    "plt.xlim(0, len(data)-1)\n",
+    "plt.ylim(0, max(data)+1)"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 37,
+   "metadata": {},
+   "outputs": [
+    {
+     "data": {
+      "text/plain": [
+       "(array([ 4.,  3.,  5.,  9., 16., 20., 22.,  9.,  8.,  4.]),\n",
+       " array([ 2.8 ,  4.86,  6.92,  8.98, 11.04, 13.1 , 15.16, 17.22, 19.28,\n",
+       "        21.34, 23.4 ]),\n",
+       " <a list of 10 Patch objects>)"
+      ]
+     },
+     "execution_count": 37,
+     "metadata": {},
+     "output_type": "execute_result"
+    },
+    {
+     "data": {
+      "image/png": "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\n",
+      "text/plain": [
+       "<Figure size 432x288 with 1 Axes>"
+      ]
+     },
+     "metadata": {
+      "needs_background": "light"
+     },
+     "output_type": "display_data"
+    }
+   ],
+   "source": [
+    "%matplotlib inline\n",
+    "import matplotlib.pyplot as plt\n",
+    "import numpy as np\n",
+    "\n",
+    "data =  [14.0, 7.6, 11.2, 12.8, 12.5, 9.9, 14.9, 9.4, 16.9, 10.2, 14.9, 18.1, 7.3, 9.8, 10.9,\n",
+    "        12.2, 9.9, 2.9, 2.8, 15.4, 15.7, 9.7, 13.1, 13.2, 12.3, 11.7, 16.0, 12.4, 17.9, 12.2,\n",
+    "        16.2, 18.7, 8.9, 11.9, 12.1, 14.6, 12.1, 4.7, 3.9, 16.9, 16.8, 11.3, 14.4, 15.7, 14.0,\n",
+    "        13.6, 18.0, 13.6, 19.9, 13.7, 17.0, 20.5, 9.9, 12.5, 13.2, 16.1, 13.5, 6.3, 6.4, 17.6,\n",
+    "        19.1, 12.8, 15.5, 16.3, 15.2, 14.6, 19.1, 14.4, 21.4, 15.1, 19.6, 21.7, 11.3, 15.0, 14.3,\n",
+    "        16.8, 14.0, 6.8, 8.2, 19.9, 20.4, 14.6, 16.4, 18.7, 16.8, 15.8, 20.4, 15.8, 22.4, 16.2,\n",
+    "        20.3, 23.4, 12.1, 15.5, 15.4, 18.4, 15.7, 10.2, 8.9, 21.0]\n",
+    "plt.grid(linestyle='--')\n",
+    "plt.hist(data, color = 'b', edgecolor = 'black')\n"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "metadata": {},
+   "outputs": [],
+   "source": []
+  }
+ ],
  "metadata": {
   "kernelspec": {
    "display_name": "Python 3",
@@ -16,10 +119,9 @@
    "name": "python",
    "nbconvert_exporter": "python",
    "pygments_lexer": "ipython3",
-   "version": "3.6.3"
+   "version": "3.6.4"
   }
  },
  "nbformat": 4,
  "nbformat_minor": 2
 }
-