From 9cf90cd7f8171a0f7896678ba095e0e6167321dc Mon Sep 17 00:00:00 2001 From: be338296bfc44819a17966a724334dd4 Date: Wed, 18 Jun 2025 18:12:05 +0000 Subject: [PATCH] Update exercice --- module2/exo3/exercice.ipynb | 63 +++++++++++++++++++++++++++++++++++-- 1 file changed, 60 insertions(+), 3 deletions(-) diff --git a/module2/exo3/exercice.ipynb b/module2/exo3/exercice.ipynb index 0bbbe37..c9b7658 100644 --- a/module2/exo3/exercice.ipynb +++ b/module2/exo3/exercice.ipynb @@ -1,5 +1,63 @@ { - "cells": [], + "cells": [ + { + "cell_type": "code", + "execution_count": 11, + "metadata": {}, + "outputs": [ + { + "data": { + "image/png": "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\n", + "text/plain": [ + "
" + ] + }, + "metadata": { + "needs_background": "light" + }, + "output_type": "display_data" + } + ], + "source": [ + "import numpy as np\n", + "import matplotlib.pyplot as plt\n", + "\n", + "# Données\n", + "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,\n", + " 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,\n", + " 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,\n", + " 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,\n", + " 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,\n", + " 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,\n", + " 16.2, 20.3, 23.4, 12.1, 15.5, 15.4, 18.4, 15.7, 10.2, 8.9, 21.0]\n", + "\n", + "# Séquence plot\n", + "plt.figure(figsize=(10, 5))\n", + "\n", + "plt.subplot(1, 2, 1)\n", + "plt.plot(data, linestyle='-', color='blue')\n", + "plt.xlim(0, 100) # bornes X\n", + "plt.ylim(0, 25) # bornes Y\n", + "\n", + "\n", + "# Histogramme\n", + "plt.subplot(1, 2, 2)\n", + "plt.hist(data, bins=10, color='blue', edgecolor='black')\n", + "plt.xlim(0, 25) # bornes X\n", + "plt.ylim(0, 25) # bornes Y\n", + "\n", + "plt.tight_layout()\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 } - -- 2.18.1