added style to look like required

module2/exo3/exercice.ipynb

@@ -37,6 +37,57 @@
     "mes_nombres = np.array(mes_nombres)"
    ]
   },
+  {
+   "cell_type": "code",
+   "execution_count": 13,
+   "metadata": {},
+   "outputs": [
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      "Moyenne =  14.113000000000001\n"
+     ]
+    }
+   ],
+   "source": [
+    "print('Moyenne = ', np.mean(mes_nombres))"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 14,
+   "metadata": {},
+   "outputs": [
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      "Std =  4.334094455301447\n"
+     ]
+    }
+   ],
+   "source": [
+    "print('Std = ', np.std(mes_nombres, ddof=1))"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 15,
+   "metadata": {},
+   "outputs": [
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      "median =  14.5\n"
+     ]
+    }
+   ],
+   "source": [
+    "print('median = ', np.median(mes_nombres))"
+   ]
+  },
   {
    "cell_type": "code",
    "execution_count": 11,
@@ -63,12 +114,12 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 12,
+   "execution_count": 16,
    "metadata": {},
    "outputs": [
     {
      "data": {
-      "image/png": "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\n",
+      "image/png": "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\n",
       "text/plain": [
        "<Figure size 432x288 with 1 Axes>"
       ]
@@ -81,7 +132,7 @@
    ],
    "source": [
     "%matplotlib inline\n",
-    "plt.hist(mes_nombres)\n",
+    "plt.hist(mes_nombres, edgecolor='black')\n",
     "plt.grid(True, which='both', linestyle='--', linewidth=0.5)"
    ]
   },