From f7afe7a62c214ccd50dd0aebbb14c61f9143aac5 Mon Sep 17 00:00:00 2001 From: 0a35d458c4dfeaae90cc26c29bebf511 <0a35d458c4dfeaae90cc26c29bebf511@app-learninglab.inria.fr> Date: Mon, 11 May 2020 15:22:02 +0000 Subject: [PATCH] calculs --- module2/exo2/exercice.ipynb | 185 +++++++++++++++++++++++++++++++++++- 1 file changed, 182 insertions(+), 3 deletions(-) diff --git a/module2/exo2/exercice.ipynb b/module2/exo2/exercice.ipynb index 0bbbe37..92bcf47 100644 --- a/module2/exo2/exercice.ipynb +++ b/module2/exo2/exercice.ipynb @@ -1,6 +1,186 @@ { - "cells": [], + "cells": [ + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "# Savoir faire un calcul simple soi-même" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "Voici les valeurs dont on demande les statistiques :" + ] + }, + { + "cell_type": "code", + "execution_count": 1, + "metadata": {}, + "outputs": [], + "source": [ + "valeurs = [\n", + " 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", + "]" + ] + }, + { + "cell_type": "code", + "execution_count": 2, + "metadata": { + "hideCode": true, + "hideOutput": true, + "hidePrompt": true + }, + "outputs": [], + "source": [ + "import numpy" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "## Calcul de la moyenne\n", + "Calcul en utilisant [numpy.mean](https://numpy.org/devdocs/reference/generated/numpy.mean.html) :" + ] + }, + { + "cell_type": "code", + "execution_count": 3, + "metadata": {}, + "outputs": [ + { + "data": { + "text/plain": [ + "14.113000000000001" + ] + }, + "execution_count": 3, + "metadata": {}, + "output_type": "execute_result" + } + ], + "source": [ + "numpy.mean(valeurs)" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "## Calcul du minimum\n", + "Calcul en utilisant [numpy.amin](https://numpy.org/devdocs/reference/generated/numpy.amin.html) :" + ] + }, + { + "cell_type": "code", + "execution_count": 4, + "metadata": {}, + "outputs": [ + { + "data": { + "text/plain": [ + "2.8" + ] + }, + "execution_count": 4, + "metadata": {}, + "output_type": "execute_result" + } + ], + "source": [ + "numpy.amin(valeurs)" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "## Calcul du maximum\n", + "Calcul en utilisant [numpy.amin](https://numpy.org/devdocs/reference/generated/numpy.amin.html) :" + ] + }, + { + "cell_type": "code", + "execution_count": 5, + "metadata": {}, + "outputs": [ + { + "data": { + "text/plain": [ + "23.4" + ] + }, + "execution_count": 5, + "metadata": {}, + "output_type": "execute_result" + } + ], + "source": [ + "numpy.amax(valeurs)" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "## Calcul de la médiane\n", + "Calcul en utilisant [numpy.median](https://numpy.org/devdocs/reference/generated/numpy.median.html) :" + ] + }, + { + "cell_type": "code", + "execution_count": 6, + "metadata": {}, + "outputs": [ + { + "data": { + "text/plain": [ + "14.5" + ] + }, + "execution_count": 6, + "metadata": {}, + "output_type": "execute_result" + } + ], + "source": [ + "numpy.median(valeurs)" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "## Calcul de l'écart type\n", + "Calcul en utilisant [numpy.std](https://numpy.org/devdocs/reference/generated/numpy.std.html) :" + ] + }, + { + "cell_type": "code", + "execution_count": 7, + "metadata": {}, + "outputs": [ + { + "data": { + "text/plain": [ + "4.334094455301447" + ] + }, + "execution_count": 7, + "metadata": {}, + "output_type": "execute_result" + } + ], + "source": [ + "numpy.std(valeurs, ddof=1)" + ] + } + ], "metadata": { + "celltoolbar": "Aucun(e)", "kernelspec": { "display_name": "Python 3", "language": "python", @@ -16,10 +196,9 @@ "name": "python", "nbconvert_exporter": "python", "pygments_lexer": "ipython3", - "version": "3.6.3" + "version": "3.6.4" } }, "nbformat": 4, "nbformat_minor": 2 } - -- 2.18.1