From bb3b397d25e4e2cd54c5d4335e1bff91c543a1a1 Mon Sep 17 00:00:00 2001 From: 82f87673860e95491d80fdbed66a168b <82f87673860e95491d80fdbed66a168b@app-learninglab.inria.fr> Date: Sat, 18 Apr 2020 22:44:56 +0000 Subject: [PATCH] no commit message --- module3/exo3/exercice.ipynb | 519 +----------------------------------- 1 file changed, 14 insertions(+), 505 deletions(-) diff --git a/module3/exo3/exercice.ipynb b/module3/exo3/exercice.ipynb index 80feb87..2303f56 100644 --- a/module3/exo3/exercice.ipynb +++ b/module3/exo3/exercice.ipynb @@ -48,9 +48,10 @@ "## 0 Récuperation des données\n", "Des valeurs obtenues par numérisation du graphe sont aujourd'hui téléchargeables, avec la version en format CSV sur [ce site](https://raw.githubusercontent.com/vincentarelbundock/Rdatasets/master/csv/HistData/Wheat.csv).\n", "\n", - "1. Déposer le fichier csv en locale si ce fichier local n'existe pas. \n", + "- Déposer le fichier csv en locale si ce fichier local n'existe pas. \n", "\n", - "2. Lisez le fichier CSV local." + "\n", + "- Lisez le fichier CSV local." ] }, { @@ -634,14 +635,14 @@ "metadata": {}, "source": [ "## 2 Amélioration de la présentation\n", - "1. Utiliser plutôt les unités modernes pour les deux quantités :\n", + "- Utiliser plutôt les unités modernes pour les deux quantités :\n", "\n", " 1) Pour le prix du blé, 1 shillings pour un quart de boisseau de blé = (1/20) £ / 6.8kg = 0.00735 £/kg \n", " \n", " 2) Pour les salaires, 1 shilling par semaine = (1/20)£ /semaine = 0.05 £ / semaine\n", " \n", "\n", - "2. Transfomer les données et les sauvegarder dans un nouveau dataframe" + "- Transfomer les données et les sauvegarder dans un nouveau dataframe" ] }, { @@ -729,7 +730,7 @@ "\n", "### 3.1 Mission 1\n", "\n", - "1. Définir comme la quantité de blé qu'un ouvrier peut acheter avec son salaire hebdomadaire.\n", + "- Définir comme la quantité de blé qu'un ouvrier peut acheter avec son salaire hebdomadaire.\n", "\n", " Sauvegarder cette quantité *PurchasingPower* dans le dataframe *transf_data* et supprimer les années où il manque des infos sur les salaires." ] @@ -738,510 +739,17 @@ "cell_type": "code", "execution_count": 7, "metadata": {}, - "outputs": [ - { - "data": { - "text/html": [ - "
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" - ], - "text/plain": [ - " Unnamed: 0 Year Wheat Wages PurchasingPower\n", - "0 1 1565 0.301350 0.2500 0.829600\n", - "1 2 1570 0.330750 0.2525 0.763416\n", - "2 3 1575 0.308700 0.2540 0.822805\n", - "3 4 1580 0.360150 0.2560 0.710815\n", - "4 5 1585 0.305025 0.2575 0.844193\n", - "5 6 1590 0.345450 0.2625 0.759878\n", - "6 7 1595 0.470400 0.2770 0.588861\n", - "7 8 1600 0.198450 0.2805 1.413454\n", - "8 9 1605 0.242550 0.2845 1.172954\n", - "9 10 1610 0.235200 0.2890 1.228741\n", - "10 11 1615 0.242550 0.2970 1.224490\n", - "11 12 1620 0.257250 0.3005 1.168124\n", - "12 13 1625 0.242550 0.3060 1.261596\n", - "13 14 1630 0.330750 0.3110 0.940287\n", - "14 15 1635 0.242550 0.3150 1.298701\n", - "15 16 1640 0.286650 0.3185 1.111111\n", - "16 17 1645 0.389550 0.3225 0.827878\n", - "17 18 1650 0.308700 0.3250 1.052802\n", - "18 19 1655 0.297675 0.3300 1.108592\n", - "19 20 1660 0.341775 0.3375 0.987492\n", - "20 21 1665 0.235200 0.3400 1.445578\n", - "21 22 1670 0.271950 0.3450 1.268616\n", - "22 23 1675 0.316050 0.3500 1.107420\n", - "23 24 1680 0.257250 0.3650 1.418853\n", - "24 25 1685 0.198450 0.3800 1.914840\n", - "25 26 1690 0.294000 0.4000 1.360544\n", - "26 27 1695 0.367500 0.4250 1.156463\n", - "27 28 1700 0.220500 0.4500 2.040816\n", - "28 29 1705 0.235200 0.5000 2.125850\n", - "29 30 1710 0.323400 0.5500 1.700680\n", - "30 31 1715 0.242550 0.5875 2.422181\n", - "31 32 1720 0.213150 0.6250 2.932207\n", - "32 33 1725 0.286650 0.6500 2.267574\n", - "33 34 1730 0.191100 0.6650 3.479853\n", - "34 35 1735 0.235200 0.6800 2.891156\n", - "35 36 1740 0.198450 0.7000 3.527337\n", - "36 37 1745 0.202125 0.7250 3.586889\n", - "37 38 1750 0.227850 0.7500 3.291639\n", - "38 39 1755 0.260925 0.7850 3.008527\n", - "39 40 1760 0.227850 0.8250 3.620803\n", - "40 41 1765 0.316050 0.8800 2.784370\n", - "41 42 1770 0.345450 0.9250 2.677667\n", - "42 43 1775 0.323400 0.9750 3.014842\n", - "43 44 1780 0.338100 1.0500 3.105590\n", - "44 45 1785 0.308700 1.1500 3.725300\n", - "45 46 1790 0.349125 1.2750 3.651987\n", - "46 47 1795 0.558600 1.3750 2.461511\n", - "47 48 1800 0.580650 1.4250 2.454146\n", - "48 49 1805 0.595350 1.4750 2.477534\n", - "49 50 1810 0.727650 1.5000 2.061431" - ] - }, - "execution_count": 7, - "metadata": {}, - "output_type": "execute_result" - } - ], + "outputs": [], "source": [ "transf_data['PurchasingPower'] = transf_data['Wages'] / transf_data['Wheat']\n", - "transf_data = transf_data.dropna().copy()\n", - "transf_data" + "transf_data = transf_data.dropna().copy()" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ - "2. Faire une représentation graphique du pouvoir d'achat au cours du temps." + "- Faire une représentation graphique du pouvoir d'achat au cours du temps." ] }, { @@ -1311,7 +819,7 @@ "cell_type": "markdown", "metadata": {}, "source": [ - "3. Remarques\n", + "- Remarques\n", "\n", " 1) Il y a évidement une grande augmentation du pouvoir d'achat au travers du 17ème siècle, qui montre d'environ **1.0 kg** du blé par les salaires hebdomentaires à plus de **3.0 kg**. \n", "\n", @@ -1323,10 +831,11 @@ "metadata": {}, "source": [ "### 3.2 Mission 2\n", - "1. Montrez les deux quantités (prix du blé, salaire) sur deux axes différents, sans l'axe du temps. \n", + "\n", + "- Montrez les deux quantités (prix du blé, salaire) sur deux axes différents, sans l'axe du temps. \n", "\n", "\n", - "2. Trouvez une autre façon d'indiquer la progression du temps dans ce graphique.\n", + "- Trouvez une autre façon d'indiquer la progression du temps dans ce graphique.\n", "\n", " **Proposition** : La progression du temps est présentée par la couleur des points, dans la figure ci-dessous. " ] @@ -1391,7 +900,7 @@ "cell_type": "markdown", "metadata": {}, "source": [ - "3. Remarques\n", + "- Remarques\n", "\n", " 1) La progression du temps est présentée par la couleur des *points*, de la couleur bleu à la rouge.\n", "\n", -- 2.18.1