{ "cells": [ { "cell_type": "markdown", "metadata": {}, "source": [ "# Savoir faire un calcul simple soi-même" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "## Données d'entrée" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "Les données d'entrée sont les suivantes :" ] }, { "cell_type": "code", "execution_count": 1, "metadata": {}, "outputs": [], "source": [ "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, 10.9,12.2, 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": "markdown", "metadata": {}, "source": [ "## Calculs statistiques" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "Le but est de faire des calculs statistiques sur ces valeurs (moyenne et l'écart-type, le min, la médiane et le max)" ] }, { "cell_type": "code", "execution_count": 3, "metadata": {}, "outputs": [ { "name": "stdout", "output_type": "stream", "text": [ "Moyenne: 14.113000000000001\n", "Écart-type: 4.334094455301447\n", "Min: 2.8\n", "Médiane: 14.5\n", "Max: 23.4\n" ] } ], "source": [ "import numpy as np\n", "\n", "mean = np.mean(data)\n", "std_dev = np.std(data, ddof=1)\n", "minimum = np.min(data)\n", "median = np.median(data)\n", "maximum = np.max(data)\n", "\n", "print(f\"Moyenne: {mean}\")\n", "print(f\"Écart-type: {std_dev}\")\n", "print(f\"Min: {minimum}\")\n", "print(f\"Médiane: {median}\")\n", "print(f\"Max: {maximum}\")" ] }, { "cell_type": "code", "execution_count": null, "metadata": {}, "outputs": [], "source": [] } ], "metadata": { "kernelspec": { "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, "nbformat_minor": 2 }