555 lines
24 KiB
Plaintext
555 lines
24 KiB
Plaintext
{
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"cells": [
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{
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"cell_type": "markdown",
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"metadata": {},
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"source": [
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"# Coûts d'une entreprises\n",
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"\n",
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"Dans ce TP, on propose d'étudier les coûts d'une entreprises. Nous commencerons pas étudier les coûts \"classiques\" puis le coût moyen et enfin les coûts marginal.\n",
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"\n",
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"Des aides sont disponibles à la fin de ce TP."
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]
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},
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{
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"cell_type": "markdown",
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"metadata": {},
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"source": [
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"## Coût total\n",
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"\n",
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"L'étude des coûts totaux d'une entreprise a mené à la formule suivante où $q$ décrit la quantité produite (entre 0 et 500):\n",
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"$$ Coût(q) = 0.3q^3 + 1.25q^2 + 7,5q + 900$$"
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]
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},
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{
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"cell_type": "markdown",
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"metadata": {},
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"source": [
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"1. En vous inspirant de l'annexe sur les fonctions, programmer la fonction coût."
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]
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},
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{
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"cell_type": "code",
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"execution_count": null,
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"metadata": {},
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"outputs": [],
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"source": []
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},
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{
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"cell_type": "markdown",
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"metadata": {},
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"source": [
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"2. Calculer les coûts pour 0, 5 et 10 objets"
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]
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},
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{
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"cell_type": "code",
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"execution_count": null,
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"metadata": {},
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"outputs": [],
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"source": []
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},
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{
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"cell_type": "markdown",
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"metadata": {},
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"source": [
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"3. On souhaite calculer tous les coûts possibles. Pour cela, inspirer vous de l'annexe sur les boucles et les listes pour calculer les coûts pour les quantités allant de 0 à 500."
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]
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},
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{
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"cell_type": "code",
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"execution_count": 1,
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"metadata": {},
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"outputs": [],
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"source": [
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"quantites = list(range(0, 11))"
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]
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},
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{
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"cell_type": "code",
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"execution_count": null,
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"metadata": {},
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"outputs": [],
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"source": []
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},
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{
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"cell_type": "markdown",
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"metadata": {},
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"source": [
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"4. En vous inspirant de l'annexe sur les graphiques, tracer le graphique qui permet de visualiser l'évolution de ces coûts."
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]
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},
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{
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"cell_type": "code",
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"execution_count": 2,
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"metadata": {},
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"outputs": [],
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"source": [
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"import matplotlib.pyplot as plt\n",
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"%matplotlib inline"
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]
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},
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{
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"cell_type": "code",
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"execution_count": null,
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"metadata": {},
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"outputs": [],
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"source": []
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},
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{
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"cell_type": "markdown",
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"metadata": {},
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"source": [
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"5. Décrire l'évolution des coûts pour cette entreprise."
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]
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},
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{
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"cell_type": "markdown",
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"metadata": {},
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"source": []
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},
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{
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"cell_type": "markdown",
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"metadata": {},
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"source": [
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"## Étude du coût moyen\n",
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"\n",
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"Le coût moyen est le coût pour une unité produite. Plus ce coût moyen est faible plus le coût unitaire d'une unité est faible. Ce coût se calcule à partir du coût total avec la formule suivante\n",
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"$$ C_m(q) = \\frac{C(q)}{q}$$\n",
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"Dans la suite, on reprend la formule du coût de la partie précédente."
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]
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},
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{
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"cell_type": "markdown",
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"metadata": {},
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"source": [
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"1. Programmer la fonction qui permet de calculer le coût moyen."
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]
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},
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{
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"cell_type": "code",
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"execution_count": null,
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"metadata": {},
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"outputs": [],
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"source": []
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},
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{
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"cell_type": "markdown",
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"metadata": {},
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"source": [
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"2. Calculer les coûts moyennes quand les quantités varient de 1 à 500."
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]
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},
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{
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"cell_type": "code",
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"execution_count": null,
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"metadata": {},
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"outputs": [],
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"source": []
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},
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{
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"cell_type": "markdown",
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"metadata": {},
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"source": [
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"3. Tracer le graphique représentant les coûts moyens"
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]
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},
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{
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"cell_type": "code",
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"execution_count": null,
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"metadata": {},
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"outputs": [],
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"source": []
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},
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{
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"cell_type": "markdown",
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"metadata": {},
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"source": [
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"4. Décrire la courbe représentative des coûts marginaux. Quelle quantité doit ont produire pour que le coût d'un objet soit le plus faible?"
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]
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},
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{
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"cell_type": "markdown",
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"metadata": {},
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"source": []
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},
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{
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"cell_type": "markdown",
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"metadata": {},
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"source": [
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"## Coût marginal\n",
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"\n",
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"Le coût marginal est le coût supplémentaire si l'on décide de produire une unité de plus. Il se calcule à partir du coût total avec la formule suivante:\n",
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"$$ C_M(q) = C(q+1) - C(q)$$"
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]
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},
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{
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"cell_type": "markdown",
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"metadata": {},
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"source": [
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"1. Programmer la fonction qui permet de calculer le coût marginal.\n"
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]
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},
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{
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"cell_type": "code",
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"execution_count": null,
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"metadata": {},
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"outputs": [],
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"source": []
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},
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{
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"cell_type": "markdown",
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"metadata": {},
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"source": [
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"2. Calculer le coût marginal pour les quantités allant de 1 à 499."
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]
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},
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{
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"cell_type": "code",
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"execution_count": null,
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"metadata": {},
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"outputs": [],
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"source": []
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},
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{
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"cell_type": "markdown",
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"metadata": {},
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"source": [
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"3. Tracer le graphique représentant les coûts marginaux."
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]
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},
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{
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"cell_type": "code",
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"execution_count": null,
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"metadata": {},
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"outputs": [],
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"source": []
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},
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{
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"cell_type": "markdown",
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"metadata": {},
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"source": [
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"4. Décrire la courbe des coûts marginaux. Que peut-on dire du coût de production si l'on chercher à augmenter la production."
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]
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},
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{
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"cell_type": "markdown",
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"metadata": {},
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"source": []
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},
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{
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"cell_type": "markdown",
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"metadata": {},
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"source": [
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"# Annexe"
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]
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},
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{
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"cell_type": "markdown",
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"metadata": {},
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"source": [
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"## Programmer des fonctions\n",
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"\n",
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"Les fonctions mathématiques peuvent aisement se programmer avec des fonctions de programmation. Seul la syntaxe change.\n",
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"\n",
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"Si l'on souhaite programmer la fonction\n",
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"\n",
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"$$ f(x) = \\frac{x + 1}{3x - 1} $$\n",
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"On écrira"
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]
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},
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{
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"cell_type": "code",
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"execution_count": 3,
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"metadata": {},
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"outputs": [],
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"source": [
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"def f(x):\n",
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" return (x+1)/(3*x-1)"
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]
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},
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{
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"cell_type": "markdown",
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"metadata": {},
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"source": [
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"Quelques éléments sont à noter:\n",
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"\n",
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"- Il y a deux points à la fin de la première ligne\n",
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"- Le mot clé `return` est indenté\n",
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"- Toutes les opérations sont écrites avec les parenthèses appropriées.\n",
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"\n",
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"On pourra ensuite utiliser cette fonction pour calculer des images de nombres. Dans ce cas, la syntaxe est la même qu'en math."
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]
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},
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{
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"cell_type": "code",
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"execution_count": 4,
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"metadata": {},
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"outputs": [
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{
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"name": "stdout",
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"output_type": "stream",
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"text": [
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"1.0\n",
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"0.3377926421404682\n"
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]
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}
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],
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"source": [
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"print(f(1))\n",
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"print(f(100))"
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]
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},
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{
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"cell_type": "markdown",
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"metadata": {},
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"source": [
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"## Boucles et listes\n",
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"\n",
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"En programmation, il existe plusieurs types de variables. Vous connaissez par exemples les `integer` qui sont des nombres entiers, les `string` qui sont les chaines de caractères. Il existe aussi les listes qui permettent de stocker plusieurs valeurs dans une seule variable."
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]
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},
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{
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"cell_type": "code",
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"execution_count": 5,
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"metadata": {},
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"outputs": [
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{
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"name": "stdout",
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"output_type": "stream",
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"text": [
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"[1, 5, 'a', 10]\n"
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]
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}
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],
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"source": [
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"liste = [1, 5, 'a', 10]\n",
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"print(liste)"
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]
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},
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{
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"cell_type": "markdown",
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"metadata": {},
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"source": [
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"On peut accéder à des valeurs particulières avec des crochets"
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]
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},
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{
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"cell_type": "code",
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"execution_count": 6,
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"metadata": {},
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"outputs": [
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{
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"name": "stdout",
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"output_type": "stream",
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"text": [
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"1\n",
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"a\n"
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]
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}
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],
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"source": [
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"print(liste[0])\n",
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"print(liste[2])"
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]
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},
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{
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"cell_type": "markdown",
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"metadata": {},
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"source": [
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"On peut ajouter des éléments à une liste"
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]
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},
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{
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"cell_type": "code",
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"execution_count": 7,
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"metadata": {},
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"outputs": [
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{
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"name": "stdout",
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"output_type": "stream",
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"text": [
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"[1, 5, 'a', 10, 100]\n"
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]
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}
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],
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"source": [
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"liste.append(100)\n",
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"print(liste)"
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]
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},
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{
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"cell_type": "markdown",
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"metadata": {},
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"source": [
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"Les listes marchent particulièrement bien avec les boucles. On peut alors faire des actions sur chacune des valeurs de la liste."
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]
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},
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{
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"cell_type": "code",
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"execution_count": 8,
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"metadata": {},
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"outputs": [
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{
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"name": "stdout",
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"output_type": "stream",
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"text": [
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"5\n",
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"25\n",
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"aaaaa\n",
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"50\n",
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"500\n"
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]
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}
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],
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"source": [
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"for valeur in liste:\n",
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" print(valeur * 5)"
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]
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},
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{
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"cell_type": "markdown",
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"metadata": {},
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"source": [
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"Quand on fait des calculs sur des listes, il est utile garder les résultats dans une deuxième liste"
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]
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},
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{
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"cell_type": "code",
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"execution_count": 9,
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"metadata": {},
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"outputs": [],
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"source": [
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"deuxieme_liste = [] # On crée une liste vide\n",
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"for valeur in liste:\n",
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" deuxieme_liste.append(valeur*5)"
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]
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},
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{
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"cell_type": "code",
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"execution_count": 10,
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"metadata": {},
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"outputs": [
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{
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"name": "stdout",
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"output_type": "stream",
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"text": [
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"[5, 25, 'aaaaa', 50, 500]\n"
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]
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}
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],
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"source": [
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"print(deuxieme_liste)"
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]
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},
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{
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"cell_type": "markdown",
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"metadata": {},
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"source": [
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"## Tracer une graphique\n",
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"\n",
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"On peut tracer des graphiques à partir de deux listes:\n",
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"\n",
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"- la liste des abcisses (les x)\n",
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"- la liste des ordonnées (les y)\n",
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"\n",
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"avant de pouvoir tracer ce graphique, il faut s'assurer d'avoir importer la biliothèque qui permet de les réaliser. Il faut donc valider (une seule fois) les lignes suivantes"
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]
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},
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{
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"cell_type": "code",
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"execution_count": 11,
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"metadata": {},
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"outputs": [],
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"source": [
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"import matplotlib.pyplot as plt\n",
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"%matplotlib inline"
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]
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},
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{
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"cell_type": "markdown",
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"metadata": {},
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"source": [
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"On calcule ou on entre les abscisses et les ordonnées"
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]
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},
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{
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"cell_type": "code",
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"execution_count": 12,
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"metadata": {},
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"outputs": [],
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"source": [
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"abscisses = [0, 1, 2, 3, 4]\n",
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"ordonnees = [2, 4, 5, 0, 1]"
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]
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},
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{
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"cell_type": "markdown",
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"metadata": {},
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"source": [
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"Et on peut tracer le graphique"
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]
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},
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{
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"cell_type": "code",
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"execution_count": 13,
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"metadata": {},
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"outputs": [
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{
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"data": {
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"text/plain": [
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"[<matplotlib.lines.Line2D at 0x7ff498343640>]"
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]
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},
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"execution_count": 13,
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"metadata": {},
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"output_type": "execute_result"
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},
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{
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"data": {
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"image/png": 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JTp6K+gQ1NFrumbOCD1fv4HcX9uXqEV2cjiR+5KJBnYmJDGOWLipKK1BRn4DGRst/vbmKt5dv49c/6c1NZ3RzOpL4mTYxkVzQvxPvalCTtAIVdQtZa7n/3TW8mlfMHaN78vNRPZ2OJH4qJ7tpUNOHqzWoSU6OiroFrLX85cNveeHrzdx8ZjfuGtPL6Ujix0Z0a0/XDnHM1ukPOUnHLWpjTIwxZrExZoUxZo0x5n5fBPNHj36yjqcXbmDyyK789oJTMMY4HUn8mDGGHLeLRRv2aFCTnBRPjqhrgNHW2kHAYGCcMWakV1P5oac+K+KRj9cxcVgG90/op5IWj1w+tGlQ05x8DWqSE3fcorZNqpr/GNn8FVI3hz7/5Ub+8uG3TBjUmb9cPpCwMJW0eCYtKYazNahJTpJH56iNMeHGmOVAKTDPWpt7lGVuMcbkG2Pyy8qCZyDNq4u38Id3v+En/TryUM4gwlXS0kKTsl3sqKhmYWHw7BfiWx4VtbW2wVo7GMgAhhtj+h9lmWestW5rrTslJTjmXLy5rITfvLmKc3qn8PerhhAZrmuv0nKj+3SkQ3yULirKCWtR81hr9wELgHFeSeNHPli1nXtmr+DU7h146tphREeEOx1JAtShQU0fr9WgJjkxntz1kWKMadv8OBYYA3zr5VyO+mTtTu54ZRlDu7Tj2evcxESqpOXk5GQ3DWp6c9lWp6NIAPLkiLoTsMAYsxLIo+kc9XvejeWcz9eV8bOXltK3cxum35BNfHSE05EkCPTqmMhgV1tm52tQk7ScJ3d9rLTWDrHWDrTW9rfW/tEXwZyQu2E3N7+YT/eUeF68cThtYiKdjiRBJMftonBnFSs0qElaSFfHmi3bspcbn88jvW0sL00dQdu4KKcjSZC5aFCnpkFNebqoKC2jogZWby3n+umLSU6MZubNI0lOiHY6kgShxJhILhjQiXdXaFCTtEzIF3Xhzkqum76YxJhIXp46go5tYpyOJEFskttFVU09H6zSoCbxXEgX9cZd+7lmWi4RYYaXp44go12c05EkyA3v1p5MDWqSFgrZoi7ec4Crn11EY6Nl5s0jyEyOdzqShABjDBPdLnI37mHTLg1qEs+EZFHvKK/m6mmLOFDbwIybRtAzNdHpSBJCDg1q0lG1eCrkirqssoarpy1i7/46XrxxOH07t3E6koSYtKQYzumdyutLS6hvaHQ6jgSAkCrqvftruXZaLtv3VfPPG7IZ5GrrdCQJUTluFzsrali4ToOa5PhCpqjLD9YxeXouG3fv57nr3WRntnc6koSw0X1SmwY15WlOtRxfSBR1VU09N/xzMQU7Knn62mGc1jPZ6UgS4qIiwrhsaNOgpl0a1CTHEfRFfbC2gakv5LGipJzHrhrKqD6pTkcSAZpOf9Q3Wt7SoCY5jqAu6pr6Bm59aQm5G/fwcM4gxvVPczqSyHeyOiYypEtbZuVpUJP8uKAt6rqGRn4xcxkLC8v438sHcvHgdKcjifxAjtvFutIqlhfvczqK+LGgLOqGRsuds5Yz75ud/OnifuS4XU5HEjmqCwd2IjYyXPdUy48KuqJubLT8+rUVvL9yO/91wSlMPjXT6Ugix/T9oKbtHKitdzqO+KmgKmprLf/99mreWLqVu8f04uazujsdSeS4JmUfGtS0w+ko4qeCpqittfzpvbXMzN3Cbef04PbRPZ2OJOKR7Mx2dEuO1+kPOaagKeoH5xYw/cuN3HB6Jr/+SW+MMU5HEvFI06CmDBZv3MNGDWqSowiKon58/jqeWFDEVcO78PsL+6qkJeBcMTSD8DCjo2o5qoAv6mmfb+DBuYVcNiSdP1/SXyUtASm1TQzn9Erh9SUa1CQ/FNBFPWPRZh54fy3jB3Ti/64YSFiYSloCV062i9LKGj4r1KAm+XcBW9Rz8ov53VurOe+UVB65cjAR4QH7nyICNA1qSk6I0ukP+YGAbLd3VmzjP15fyZlZyTx+9VAiVdISBCLDw7hsaAafrC2lrFKDmuR7AddwH63ZwV2zlpOd2Z5nJruJiQx3OpJIq8lxZ2hQk/xAQBX1pwWl/GLmUgZmJPHclGxio1TSElx6piYytEtbZuVrUJN8L2CK+quiXdw6Ywm9Oiby/A3DSYiOcDqSiFfkuF2sL61imQY1SbOAKOr8TXuY+kI+mR3imXHTCJJiI52OJOI1Fw7q3DSoKU8XFaWJ3xf1ypJ93PDPPNLaxDBj6nDax0c5HUnEqxKiIxg/sBPvrtimQU0C+HlRr91eweTnFtM2PpKXbx5BamKM05FEfGJStov9tQ28v3K701HED/htUa8vreLaabnERYUzc+pIOiXFOh1JxGfcXdvRXYOapJlfFvXm3fu5ZtoijDG8PHUErvZxTkcS8ammQU0u8jbtZUNZldNxxGHHLWpjjMsYs8AY840xZo0x5pfeDLR130GufjaX2vpGXp46gu4pCd5cnYjfunxoevOgphKno4jDPDmirgfusdb2BUYCPzfG9PVGmJ0V1Vz97CIqquuYcdMIeqclemM1IgEhtU0Mo3qn8PpSDWoKdcctamvtdmvt0ubHlcBaoNU/Kbb8QB3XTMtlV2UNL9w4nP7pSa29CpGAk+N2UVZZw6cFGtQUylp0jtoYkwkMAXKP8twtxph8Y0x+WVnLf6gSYyI4o2cyz03JZmiXdi3+fpFgNKpPKskJ0bqoGOI8LmpjTALwOnCntbbiyOettc9Ya93WWndKSkrLg4QZ/jChHyO7d2jx94oEq8jwMC4fms78bzWoKZR5VNTGmEiaSvpla+0b3o0kIoeb6HZR32h5c5kuKoYqT+76MMBzwFpr7cPejyQih+uZmsCwru2YladBTaHKkyPq04HJwGhjzPLmrwu8nEtEDpPjzqCobD9Lt+xzOoo4wJO7Pr6w1hpr7UBr7eDmrw98EU5Emowf2Jm4KA1qClV++c5EEfl3CdERjB/QifdWbmN/jQY1hRoVtUiA+G5Q0yoNago1KmqRADGsazu6p8Tr9EcIUlGLBAhjDDluF/mb91KkQU0hRUUtEkAu+25Qk46qQ4mKWiSApCbGMKp3Kq8v2UqdBjWFDBW1SICZlO1iV5UGNYUSFbVIgDmnd4oGNYUYFbVIgIkMD+PyYU2Dmkorq52OIz6gohYJQBOHuWhotLy5dKvTUcQHVNQiAahnagLuru2Yla9BTaFARS0SoHLcLjaU7Wfplr1ORxEvU1GLBKjxAzsRHxXOLL1TMeipqEUCVHx0BBcO7Mx7K7dTpUFNQU1FLRLAcrIzOFDbwAcrNagpmKmoRQLY0C7t6JESzyzdUx3UVNQiAezQoKYlm/eyvlSDmoKVilokwF02NIPwMMMcHVUHLRW1SIBLSYxmdJ9UXl+qQU3BSkUtEgQmuZsGNS34ttTpKOIFKmqRIHBO7xRSEqOZnV/idBTxAhW1SBCICA/j8qEZLCgopbRCg5qCjYpaJEhMdGfQ0Gh5Y5kGNQUbFbVIkOiRkkB2Zjtm52lQU7BRUYsEkYluFxt27WfJZg1qCiYqapEgMn6ABjUFIxW1SBCJj47gokGdeX+VBjUFExW1SJCZ6HZxoLaB91duczqKtBIVtUiQGdqlLT1TE3T6I4ioqEWCTNOgpgyWbtnH+tJKp+NIKzhuURtjphtjSo0xq30RSERO3qVDMogIM3qnYpDw5Ij6eWCcl3OISCs6NKjpjaUlGtQUBI5b1NbahcAeH2QRkVY0KdvFrqpa5mtQk09s2rWfd1Z45wJuRGu9kDHmFuAWgC5durTWy4rICTq7VwqpidHMyS/mJ/3SnI4TtLbuO8hjn6xjzpIS2sREMLZvR2Iiw1t1Ha1W1NbaZ4BnANxut96/KuKwiPAwLh+WwTMLN1BaUU1qmxinIwWVssoanliwnpm5WwCYPLIrt43q0eolDa1Y1CLifyYOy+DJT4t4felWfnZOD6fjBIV9B2p5euEGnv9yE7UNjUwclsHt52aR3jbWa+tUUYsEse4pCQzPbM+c/GJ+enZ3jDFORwpYVTX1TP9iI88u3EBVbT0XDezMXWN60S053uvrPm5RG2NeAc4Bko0xJcB91trnvB1MRFpHTraLX81ZQd6mvQzv1t7pOAGnuq6BGV9v5snPitizv5axfTty99he9Elr47MMxy1qa+1VvggiIt5xwYA0/vDOGmbnF6uoW6C2vpFZ+cU8Pn8dOytqODMrmXvG9mawq63Ps+jUh0iQi4uK4KJBnXhr2Tbuu6gviTGRTkfyaw2NljeXbeWRjwsp2XsQd9d2PHrlEEZ27+BYJhW1SAiY6HbxyuJi3l+5nSuH6/bZo2lstHy4egcPzyugqGw//dPb8KdL+nNOrxTHz+2rqEVCwBBXW7JSE5iVX6yiPoK1lgUFpTz4USHfbK8gKzWBJ68Zyrj+aY4X9CEqapEQ0DSoycWfP1jLup2VZHVMdDqSX/iqaBcPflTA0i376NI+jodzBnHx4HTCw/yjoA/R9DyREHHp0PTmQU0af7psy16umbaIq5/NZdu+av58aX8+uedsLhua4XclDTqiFgkZyQnRnHtKKm8s3cq94/oQGR56x2nfbKvg4XkFfLy2lA7xUfz3+FO4dmRXr7ybsDWpqEVCyKRsFx+t2ckna0sZ1z905n8UlVXxt3mFvLdyO4kxEfxqbC9uOL0b8dGBUYGBkVJEWsVZWd8PagqFoi7ec4C/f7KO15eWEBMZzs9H9eCWM3uQFBdYtyiqqEVCSER4GFcMy+Cpz4rYWVFNxyAd1FRaUc3jC9bzyuItGGOYclo3bhvVg+SEaKejnRAVtUiImeh28Y9Pi3htSQk/H9XT6Titau/+Wp76rIgXvt5EfYNlotvFHef2pFOS9wYm+YKKWiTEdEuOZ3i3pkFNt53Tw2/uFT4ZldV1TPt8I899sZH9tfVcOjidX56XRdcO3h+Y5AsqapEQNMnt4p45K1i8cQ8jHHxr9Mk6WNvAC19v4qnPith3oI5x/dK4e2wvegXZfeIqapEQdP6ANO57Zw2z80sCsqhr6ht4dXExjy9YT1llDWf3SuFXY3szICPJ6WheoaIWCUFNg5o689ayrfxhQuAMaqpvaOSNpVt59JN1bN13kOHd2vOPa4aSnRncUwFV1CIhKsedwSuLt/Deyu1c5efzPxobLe+t2s4j8wrZsGs/gzKS+J/LBnBmVnJQnGM/HhW1SIga7GpLr44JzMor9tuittby8dpSHppbwLc7KundMZGnJw9jbN+OIVHQh6ioRULUoUFND7y/lsKdlX51Ac5ay5frd/Pg3AKWF+8js0Mcj145mAsHdvbLWRzeFnpv9heR71w6pHlQU57/DGpasnkPVz27iGufy6W0opq/XDaAeXef7ZdT7XxFR9QiIaxDQjTnndKRN5c1DWqKinDu2G311nIemlvAgoIykhOiue+ivlw9ogvREf49MMkXVNQiIW5Stot/rdnB/G93Mq5/J5+vf31pJQ/PK+SDVTtIio3k3nG9mXJaJnFRqqdDtCVEQtyZWcl0bBPN7PwSnxb1lt0HeOSTQt5atpXYyHDuGN2Tm87sTlJsYNwq6EsqapEQd2hQ05OfFrGjvJq0JO8OatpRXs1j89cxK6+Y8DDDTWd046dn96BDgA5M8gUVtYgwcZiLJxYU8fpS7w1q2l1Vw5OfFjFj0WYareXK4S5uH50VtBP8WpOKWkTITI5nRLf2zPbCoKbyg3VM+3wD07/YyMG6Bi4dksGd52Xhah/XausIdipqEQGaLirePXsFuRv3MLIV5n8cqK3nn19u4pmFGyg/WMf4AZ24a0wWPVP9537tQKGiFhEAzu/fifveXsPs/OKTKurqugZm5m7hH5+uZ1dVLaP7pHL3mF70Tw/OgUm+oKIWEQBio8K5aHBn3lhawh8m9KNNCwc11TU08tqSEv7+yTq2l1dzavcOPD25N8O6tvNS4tChohaR7+S4XczM3cJ7K7Zz9QjP5n80NFreXbGNRz4uZNPuAwx2teXBiYM4vWeyl9OGDhW1iHxnUEYSvTsmMiu/+LhFba3lozU7eXheAYU7q+iTlsi069yce0pqSA1M8gUVtYh8xxjDRHcGD7y/loIdlfRO++GFP2stC9ft4qG5BawsKad7cjyPXTWE8QM6ERaiszi8TUOZROTfXDoknchww+z8Hw5qWrxxD5OeXsT10xezu6qW/7tiIHPvOouLBnVWSXuRR0fUxphxwKNAODDNWvsXr6YSEcccPqjpP5oHNa0s2ceDcwtZWFhGSmI0f7y4H5OyXRqY5CPHLWpjTDjwBDAGKAHyjDHvWGu/8XY4EXFGTraLD1fvYNoXG1hRvI+P1uykbVwkvzm/D9edmklslAralzw5oh4OrLfWbgAwxrwKXAyoqEWC1FlZKaS1ieH//lVAQnQEd56XxU1ndAuYz1YMNp4UdTpw+MmqEmDEkQsZY24BbgHo0sU/P9ZHRDwTHmb40yX9WbOtnOtPzaRdfJTTkUJaq931Ya19BngGwO1229Z6XRFxxpi+HRnTt6PTMQTP7vrYCrgO+3NG8/8nIiI+4ElR5wFZxphuxpgo4ErgHe/GEhGRQ4576sNaW2+M+QXwEU2350231q7xejIREQE8PEdtrf0A+MDLWURE5Cj0zkQRET+nohYR8XMqahERP6eiFhHxc8ba1n9vijGmDNh8gt+eDOxqxTitRblaRrlaRrlaJhhzdbXWphztCa8U9ckwxuRba91O5ziScrWMcrWMcrVMqOXSqQ8RET+nohYR8XP+WNTPOB3gGJSrZZSrZZSrZUIql9+doxYRkX/nj0fUIiJyGBW1iIifc6yojTHjjDEFxpj1xpj/PMrz0caYWc3P5xpjMv0k1xRjTJkxZnnz11QfZJpujCk1xqw+xvPGGPP35swrjTFDvZ3Jw1znGGPKD9tWv/dRLpcxZoEx5htjzBpjzC+PsozPt5mHuXy+zYwxMcaYxcaYFc257j/KMj7fHz3M5fP98bB1hxtjlhlj3jvKc627vay1Pv+iaVxqEdAdiAJWAH2PWOY24Knmx1cCs/wk1xTgcR9vr7OAocDqYzx/AfAhYICRQK6f5DoHeM+Bn69OwNDmx4lA4VH+Hn2+zTzM5fNt1rwNEpofRwK5wMgjlnFif/Qkl8/3x8PWfTcw82h/X629vZw6ov7uA3OttbXAoQ/MPdzFwAvNj18DzjXGGD/I5XPW2oXAnh9Z5GLgRdtkEdDWGNPJD3I5wlq73Vq7tPlxJbCWps/+PJzPt5mHuXyueRtUNf8xsvnryLsMfL4/epjLEcaYDGA8MO0Yi7Tq9nKqqI/2gblH/sB+t4y1th4oBzr4QS6Ay5t/XX7NGOM6yvO+5mluJ5za/Kvrh8aYfr5eefOvnENoOho7nKPb7EdygQPbrPnX+OVAKTDPWnvM7eXD/dGTXODM/vgIcC/QeIznW3V76WJiy70LZFprBwLz+P5fTfmhpTTNLxgEPAa85cuVG2MSgNeBO621Fb5c9485Ti5Htpm1tsFaO5imz0Qdbozp74v1Ho8HuXy+PxpjLgRKrbVLvL2uQ5wqak8+MPe7ZYwxEUASsNvpXNba3dbamuY/TgOGeTmTJ/zyA4ittRWHfnW1TZ8SFGmMSfbFuo0xkTSV4cvW2jeOsogj2+x4uZzcZs3r3AcsAMYd8ZQT++Nxczm0P54OTDDGbKLp9OhoY8xLRyzTqtvLqaL25ANz3wGub358BTDfNp+ZdzLXEecxJ9B0ntFp7wDXNd/JMBIot9ZudzqUMSbt0Hk5Y8xwmn7evL5zN6/zOWCttfbhYyzm823mSS4ntpkxJsUY07b5cSwwBvj2iMV8vj96ksuJ/dFa+xtrbYa1NpOmjphvrb32iMVadXt59JmJrc0e4wNzjTF/BPKtte/Q9AM9wxiznqYLVlf6Sa47jDETgPrmXFO8ncsY8wpNdwMkG2NKgPtourCCtfYpmj7P8gJgPXAAuMHbmTzMdQXwM2NMPXAQuNIH/9hC0xHPZGBV8/lNgN8CXQ7L5sQ28ySXE9usE/CCMSacpn8YZltr33N6f/Qwl8/3x2Px5vbSW8hFRPycLiaKiPg5FbWIiJ9TUYuI+DkVtYiIn1NRi4j4ORW1iIifU1GLiPi5/wdlf7ZQczP7fgAAAABJRU5ErkJggg==\n",
|
|
"text/plain": [
|
|
"<Figure size 432x288 with 1 Axes>"
|
|
]
|
|
},
|
|
"metadata": {
|
|
"needs_background": "light"
|
|
},
|
|
"output_type": "display_data"
|
|
}
|
|
],
|
|
"source": [
|
|
"plt.plot(abscisses, ordonnees)"
|
|
]
|
|
},
|
|
{
|
|
"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": "3.9.4"
|
|
}
|
|
},
|
|
"nbformat": 4,
|
|
"nbformat_minor": 4
|
|
}
|