From 14d02c100c7d47b147d82b26cedc0fde5126624c Mon Sep 17 00:00:00 2001
From: 6f892419cc99326ee525ed439d8ff5df
 <6f892419cc99326ee525ed439d8ff5df@app-learninglab.inria.fr>
Date: Wed, 3 Mar 2021 15:51:16 +0000
Subject: [PATCH] =?UTF-8?q?M=C3=A9diane=20bis?=
MIME-Version: 1.0
Content-Type: text/plain; charset=UTF-8
Content-Transfer-Encoding: 8bit

---
 module2/exo2/exercice.ipynb | 55 ++++++++++++++++++++++++++++++++++++-
 1 file changed, 54 insertions(+), 1 deletion(-)

diff --git a/module2/exo2/exercice.ipynb b/module2/exo2/exercice.ipynb
index bc0e070..93131c4 100644
--- a/module2/exo2/exercice.ipynb
+++ b/module2/exo2/exercice.ipynb
@@ -400,7 +400,14 @@
     "    n=input((Entrer une valeur de la série ou écrire fin s'il n'y a plus de valeur à entrer : \\n))\n",
     "    if n!= \"fin\":\n",
     "        n=float(n)\n",
-    "        liste.append(n)"
+    "        liste.append(n)\n",
+    "liste.sort()\n",
+    "if len(liste)%2==0 :\n",
+    "    m=((liste[(len(liste)-1)//2]+liste[len(liste)//2])/2)\n",
+    "else :\n",
+    "    m=liste[len(liste)//2]\n",
+    "print (\"Vous avez entré \", len(liste), \"valeurs\")\n",
+    "print(\"La médiane de votre série est \", m)"
    ]
   },
   {
@@ -418,6 +425,52 @@
     "print(\"La médiane de votre série est \", m)"
    ]
   },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "def calculate_median(liste):\n",
+    "    liste = sorted(liste)\n",
+    "    liste_len = len(liste)\n",
+    "    if liste_len < 1:\n",
+    "        return None\n",
+    "    if liste_len % 2 == 0 :\n",
+    "        return ( l[(liste_len-1)/2] + l[(liste_len+1)/2] ) / 2.0\n",
+    "    else:\n",
+    "        return liste[(liste_len-1)/2]"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "l = [1]\n",
+    "print calculate_median(l)"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "import numpy as np"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "l=[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",
+    "print np.median(np.array(l))"
+   ]
+  },
   {
    "cell_type": "code",
    "execution_count": null,
-- 
2.18.1