diff --git a/module2/exo2/exercice.ipynb b/module2/exo2/exercice.ipynb index 93131c40d36736fd518968f6f4a2f2e0a2867c80..4be9e30b7b2fc89da15d186196841109253bd074 100644 --- a/module2/exo2/exercice.ipynb +++ b/module2/exo2/exercice.ipynb @@ -9,11 +9,12 @@ }, { "cell_type": "code", - "execution_count": 4, + "execution_count": 45, "metadata": {}, "outputs": [], "source": [ - "import numpy as np" + "import numpy as np\n", + "import matplotlib as plt" ] }, { @@ -39,143 +40,41 @@ }, { "cell_type": "code", - "execution_count": 5, - "metadata": {}, - "outputs": [ - { - "data": { - "text/plain": [ - "(14.0,\n", - " 7.6,\n", - " 11.2,\n", - " 12.8,\n", - " 12.5,\n", - " 9.9,\n", - " 14.9,\n", - " 9.4,\n", - " 16.9,\n", - " 10.2,\n", - " 14.9,\n", - " 18.1,\n", - " 7.3,\n", - " 9.8,\n", - " 10.9,\n", - " 12.2,\n", - " 9.9,\n", - " 2.9,\n", - " 2.8,\n", - " 15.4,\n", - " 15.7,\n", - " 9.7,\n", - " 13.1,\n", - " 13.2,\n", - " 12.3,\n", - " 11.7,\n", - " 16.0,\n", - " 12.4,\n", - " 17.9,\n", - " 12.2,\n", - " 16.2,\n", - " 18.7,\n", - " 8.9,\n", - " 11.9,\n", - " 12.1,\n", - " 14.6,\n", - " 12.1,\n", - " 4.7,\n", - " 3.9,\n", - " 16.9,\n", - " 16.8,\n", - " 11.3,\n", - " 14.4,\n", - " 15.7,\n", - " 14.0,\n", - " 13.6,\n", - " 18.0,\n", - " 13.6,\n", - " 19.9,\n", - " 13.7,\n", - " 17.0,\n", - " 20.5,\n", - " 9.9,\n", - " 12.5,\n", - " 13.2,\n", - " 16.1,\n", - " 13.5,\n", - " 6.3,\n", - " 6.4,\n", - " 17.6,\n", - " 19.1,\n", - " 12.8,\n", - " 15.5,\n", - " 16.3,\n", - " 15.2,\n", - " 14.6,\n", - " 19.1,\n", - " 14.4,\n", - " 21.4,\n", - " 15.1,\n", - " 19.6,\n", - " 21.7,\n", - " 11.3,\n", - " 15.0,\n", - " 14.3,\n", - " 16.8,\n", - " 14.0,\n", - " 6.8,\n", - " 8.2,\n", - " 19.9,\n", - " 20.4,\n", - " 14.6,\n", - " 16.4,\n", - " 18.7,\n", - " 16.8,\n", - " 15.8,\n", - " 20.4,\n", - " 15.8,\n", - " 22.4,\n", - " 16.2,\n", - " 20.3,\n", - " 23.4,\n", - " 12.1,\n", - " 15.5,\n", - " 15.4,\n", - " 18.4,\n", - " 15.7,\n", - " 10.2,\n", - " 8.9,\n", - " 21.0)" - ] - }, - "execution_count": 5, - "metadata": {}, - "output_type": "execute_result" - } - ], - "source": [ - "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" - ] - }, - { - "cell_type": "code", - "execution_count": 8, + "execution_count": 17, "metadata": {}, "outputs": [], "source": [ - "list=[]" + "list = (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)" ] }, { "cell_type": "code", - "execution_count": 9, + "execution_count": 21, "metadata": {}, - "outputs": [], + "outputs": [ + { + "name": "stdout", + "output_type": "stream", + "text": [ + "la moyenne des nombres est : 14.113000000000007\n", + "la moyenne de 1 et 2 est : 1.5\n", + "le minimum est : 2.8\n", + "le maximum est : 23.4\n" + ] + } + ], "source": [ - "def moyenne(liste=[]) :\n", - " somme = sum(liste)\n", - " nb_elements = len(liste)\n", + "def moyenne(l):\n", + " somme = sum(l)\n", + " nb_elements = len(l)\n", " moyenne = somme / nb_elements\n", - " return moyenne" + " return moyenne\n", + "\n", + "print(\"la moyenne des nombres est : \", moyenne(list))\n", + "print(\"la moyenne de 1 et 2 est : \", moyenne((1, 2)))\n", + "\n", + "print(\"le minimum est : \", min(list))\n", + "print(\"le maximum est : \", max(list))" ] }, { @@ -326,28 +225,25 @@ }, { "cell_type": "code", - "execution_count": null, + "execution_count": 16, "metadata": {}, "outputs": [ { "name": "stdout", "output_type": "stream", "text": [ - "calcul de la moyenne\n" + "calcul de la moyenne\n", + "Entrer une note ou écrire fin s'il n'y a plus de notes à entrer : \n", + "fin\n", + "Vous avez entré 100 notes\n", + "La moyenne de cette série est 14.113000000000007\n" ] } ], "source": [ "print (\"calcul de la moyenne\")\n", "list=[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", - "n=0\n", - "while n!=\"fin\":\n", - " n=input((\"Entrer une note ou écrire fin s'il n'y a plus de notes à entrer : \\n\"))\n", - " if n!=\"fin\":\n", - " n=float(n)\n", - " liste.append(n)\n", - "print (\"Vous avez entré\", len(liste), \" notes\")\n", - "m=sum(list)/len(liste)\n", + "m=sum(list)/len(list)\n", "print(\"La moyenne de cette série est \", m)" ] }, @@ -389,24 +285,29 @@ }, { "cell_type": "code", - "execution_count": null, + "execution_count": 38, "metadata": {}, - "outputs": [], + "outputs": [ + { + "name": "stdout", + "output_type": "stream", + "text": [ + "Calcul de la médiane.\n", + "15.35\n", + "Vous avez entré 100 valeurs\n", + "La médiane de votre série est 15.35\n" + ] + } + ], "source": [ - "Print (\"Calcul de la médiane.\")\n", - "liste=[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", - "n=0\n", - "while n!=\"fin\":\n", - " 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)\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(\"Calcul de la médiane.\")\n", + "sorted_list = sorted(list)\n", + "print((list[49] + list[50]) / 2)\n", + "if len(sorted_list) % 2 == 0:\n", + " m = ((list[(len(sorted_list) - 1) // 2] + list[len(sorted_list) // 2]) / 2)\n", + "else:\n", + " m = list[len(sorted_list) / 2]\n", + "print (\"Vous avez entré \", len(list), \"valeurs\")\n", "print(\"La médiane de votre série est \", m)" ] }, @@ -427,7 +328,7 @@ }, { "cell_type": "code", - "execution_count": null, + "execution_count": 32, "metadata": {}, "outputs": [], "source": [ @@ -437,19 +338,34 @@ " 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", + " return ( l[(liste_len-1)/2] + l[(liste_len)/2] ) / 2.0\n", " else:\n", " return liste[(liste_len-1)/2]" ] }, { "cell_type": "code", - "execution_count": null, + "execution_count": 49, "metadata": {}, - "outputs": [], + "outputs": [ + { + "data": { + "text/plain": [ + "18.784374747474743" + ] + }, + "execution_count": 49, + "metadata": {}, + "output_type": "execute_result" + } + ], "source": [ "l = [1]\n", - "print calculate_median(l)" + "import pandas as pd\n", + "\n", + "df = pd.Series(list)\n", + "df.describe()\n", + "df.std()**2" ] }, { @@ -463,12 +379,42 @@ }, { "cell_type": "code", - "execution_count": null, + "execution_count": 28, "metadata": {}, - "outputs": [], + "outputs": [ + { + "name": "stdout", + "output_type": "stream", + "text": [ + "14.5\n" + ] + } + ], "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(list)))" + ] + }, + { + "cell_type": "code", + "execution_count": 40, + "metadata": {}, + "outputs": [ + { + "data": { + "text/plain": [ + "14.5" + ] + }, + "execution_count": 40, + "metadata": {}, + "output_type": "execute_result" + } + ], + "source": [ + "import statistics\n", "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))" + "statistics.median(list)" ] }, { @@ -484,18 +430,6 @@ "display_name": "Python 3", "language": "python", "name": "python3" - }, - "language_info": { - "codemirror_mode": { - "name": "ipython", - "version": 3 - }, - "file_extension": ".py", - "mimetype": "text/x-python", - "name": "python", - "nbconvert_exporter": "python", - "pygments_lexer": "ipython3", - "version": "3.6.4" } }, "nbformat": 4,