diff --git a/module2/exo3/exercice.ipynb b/module2/exo3/exercice.ipynb
index 0bbbe371b01e359e381e43239412d77bf53fb1fb..380ff5b1c1018922ccec84c8c826334b1f65f01f 100644
--- a/module2/exo3/exercice.ipynb
+++ b/module2/exo3/exercice.ipynb
@@ -1,5 +1,63 @@
 {
- "cells": [],
+ "cells": [
+  {
+   "cell_type": "code",
+   "execution_count": 1,
+   "metadata": {},
+   "outputs": [
+    {
+     "data": {
+      "text/plain": [
+       "<Figure size 640x480 with 1 Axes>"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    }
+   ],
+   "source": [
+    "import matplotlib.pyplot as plt\n",
+    "import numpy as np\n",
+    "\n",
+    "tab = np.array([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, 10.9,12.2, 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, 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, 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, 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, 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, 20.3, 23.4, 12.1, 15.5, 15.4, 18.4, 15.7, 10.2, 8.9, 21.0])\n",
+    "plt.plot(tab)\n",
+    "plt.grid(linestyle='--')\n",
+    "plt.show()"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 2,
+   "metadata": {},
+   "outputs": [
+    {
+     "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": [
+    "fig, ax = plt.subplots()\n",
+    "ax.hist(tab, lw=1, edgecolor=\"black\")\n",
+    "plt.grid(linestyle='--')\n",
+    "plt.show()"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "metadata": {},
+   "outputs": [],
+   "source": []
+  }
+ ],
  "metadata": {
   "kernelspec": {
    "display_name": "Python 3",
@@ -16,10 +74,9 @@
    "name": "python",
    "nbconvert_exporter": "python",
    "pygments_lexer": "ipython3",
-   "version": "3.6.3"
+   "version": "3.6.4"
   }
  },
  "nbformat": 4,
  "nbformat_minor": 2
 }
-