From ad5087ccffbf21e47dafb10077e3e91e4a33c1b7 Mon Sep 17 00:00:00 2001 From: 521adc37f04e8509ebf5ce131815aa0a <521adc37f04e8509ebf5ce131815aa0a@app-learninglab.inria.fr> Date: Wed, 10 Feb 2021 09:59:39 +0000 Subject: [PATCH] Calcul du pouvoir d'achat (insertion d'une nouvelle colonne) --- module3/exo3/exercice.ipynb | 1117 ++++++++++++++++++++++++++++++++++- 1 file changed, 1088 insertions(+), 29 deletions(-) diff --git a/module3/exo3/exercice.ipynb b/module3/exo3/exercice.ipynb index 2bc7761..6eddd45 100644 --- a/module3/exo3/exercice.ipynb +++ b/module3/exo3/exercice.ipynb @@ -9,7 +9,7 @@ }, { "cell_type": "code", - "execution_count": 2, + "execution_count": 1, "metadata": {}, "outputs": [], "source": [ @@ -21,7 +21,7 @@ }, { "cell_type": "code", - "execution_count": 3, + "execution_count": 2, "metadata": {}, "outputs": [ { @@ -484,7 +484,7 @@ "52 53 1821 54.0 NaN" ] }, - "execution_count": 3, + "execution_count": 2, "metadata": {}, "output_type": "execute_result" } @@ -496,7 +496,7 @@ }, { "cell_type": "code", - "execution_count": 4, + "execution_count": 3, "metadata": {}, "outputs": [ { @@ -559,7 +559,7 @@ "52 53 1821 54.0 NaN" ] }, - "execution_count": 4, + "execution_count": 3, "metadata": {}, "output_type": "execute_result" } @@ -572,7 +572,7 @@ }, { "cell_type": "code", - "execution_count": 5, + "execution_count": 4, "metadata": {}, "outputs": [ { @@ -1011,7 +1011,7 @@ "49 50 1810 99.0 30.00" ] }, - "execution_count": 5, + "execution_count": 4, "metadata": {}, "output_type": "execute_result" } @@ -1032,7 +1032,7 @@ }, { "cell_type": "code", - "execution_count": 21, + "execution_count": 5, "metadata": {}, "outputs": [ { @@ -1041,7 +1041,7 @@ "" ] }, - "execution_count": 21, + "execution_count": 5, "metadata": {}, "output_type": "execute_result" }, @@ -1071,22 +1071,22 @@ }, { "cell_type": "code", - "execution_count": 22, + "execution_count": 6, "metadata": {}, "outputs": [ { "data": { "text/plain": [ - "" + "" ] }, - "execution_count": 22, + "execution_count": 6, "metadata": {}, "output_type": "execute_result" }, { "data": { - "image/png": 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\n", + "image/png": 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\n", "text/plain": [ "
" ] @@ -1098,7 +1098,7 @@ } ], "source": [ - "plt.plot(my_data[\"Year\"], my_data[\"Wages\"], \"r--\")\n", + "plt.plot(my_data[\"Year\"], my_data[\"Wages\"], \"r\")\n", "\n", " \n", "y1 = my_data[\"Wages\"]\n", @@ -1116,22 +1116,22 @@ }, { "cell_type": "code", - "execution_count": 23, + "execution_count": 7, "metadata": {}, "outputs": [ { "data": { "text/plain": [ - "" + "" ] }, - "execution_count": 23, + "execution_count": 7, "metadata": {}, "output_type": "execute_result" }, { "data": { - "image/png": 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\n", + "image/png": 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\n", "text/plain": [ "
" ] @@ -1145,7 +1145,7 @@ "source": [ "\n", "\n", - "p = plt.bar(my_data[\"Year\"], my_data[\"Wheat\"]), plt.plot(my_data[\"Year\"], my_data[\"Wages\"], \"r--\")\n", + "p = plt.bar(my_data[\"Year\"], my_data[\"Wheat\"]), plt.plot(my_data[\"Year\"], my_data[\"Wages\"], \"r\")\n", "\n", "\n", "x = my_data[\"Year\"]\n", @@ -1165,12 +1165,12 @@ }, { "cell_type": "code", - "execution_count": 24, + "execution_count": 8, "metadata": {}, "outputs": [ { "data": { - "image/png": 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\n", + "image/png": 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\n", 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" ] @@ -1191,7 +1191,7 @@ "# set x-axis l# set x-axis label\n", "ax.set_xlabel(\"Year\",fontsize = 14)\n", "# set y-axis l# set x-axis label\n", - "ax.set_ylabel(\"Wheat\", color = \"red\")\n", + "ax.set_ylabel(\"Wheat\", color = \"red\", fontsize = 14)\n", "\n", "# twin object for two different y-axis on the sample plot\n", "ax2 = ax.twinx()\n", @@ -1205,18 +1205,1077 @@ ] }, { - "cell_type": "code", - "execution_count": 18, + "cell_type": "markdown", "metadata": {}, - "outputs": [], - "source": [] + "source": [ + "**Pouvoir d'achat** : la quantité de blé qu’un ouvrier peut acheter avec son salaire hebdomadaire" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "- Avec un salaire donné, combien puis-je acheter de quantité de blé ?\n", + "- Quelle est la quantité de travail nécessaire pour acheter une unité de blé donnée ?" + ] }, { "cell_type": "code", - "execution_count": 19, + "execution_count": 13, "metadata": {}, - "outputs": [], - "source": [] + "outputs": [ + { + "data": { + "text/html": [ + "
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4950181099.030.000.303030
\n", + "
" + ], + "text/plain": [ + " Unnamed: 0 Year Wheat Wages Purchase_Power\n", + "0 1 1565 41.0 5.00 0.121951\n", + "1 2 1570 45.0 5.05 0.112222\n", + "2 3 1575 42.0 5.08 0.120952\n", + "3 4 1580 49.0 5.12 0.104490\n", + "4 5 1585 41.5 5.15 0.124096\n", + "5 6 1590 47.0 5.25 0.111702\n", + "6 7 1595 64.0 5.54 0.086563\n", + "7 8 1600 27.0 5.61 0.207778\n", + "8 9 1605 33.0 5.69 0.172424\n", + "9 10 1610 32.0 5.78 0.180625\n", + "10 11 1615 33.0 5.94 0.180000\n", + "11 12 1620 35.0 6.01 0.171714\n", + "12 13 1625 33.0 6.12 0.185455\n", + "13 14 1630 45.0 6.22 0.138222\n", + "14 15 1635 33.0 6.30 0.190909\n", + "15 16 1640 39.0 6.37 0.163333\n", + "16 17 1645 53.0 6.45 0.121698\n", + "17 18 1650 42.0 6.50 0.154762\n", + "18 19 1655 40.5 6.60 0.162963\n", + "19 20 1660 46.5 6.75 0.145161\n", + "20 21 1665 32.0 6.80 0.212500\n", + "21 22 1670 37.0 6.90 0.186486\n", + "22 23 1675 43.0 7.00 0.162791\n", + "23 24 1680 35.0 7.30 0.208571\n", + "24 25 1685 27.0 7.60 0.281481\n", + "25 26 1690 40.0 8.00 0.200000\n", + "26 27 1695 50.0 8.50 0.170000\n", + "27 28 1700 30.0 9.00 0.300000\n", + "28 29 1705 32.0 10.00 0.312500\n", + "29 30 1710 44.0 11.00 0.250000\n", + "30 31 1715 33.0 11.75 0.356061\n", + "31 32 1720 29.0 12.50 0.431034\n", + "32 33 1725 39.0 13.00 0.333333\n", + "33 34 1730 26.0 13.30 0.511538\n", + "34 35 1735 32.0 13.60 0.425000\n", + "35 36 1740 27.0 14.00 0.518519\n", + "36 37 1745 27.5 14.50 0.527273\n", + "37 38 1750 31.0 15.00 0.483871\n", + "38 39 1755 35.5 15.70 0.442254\n", + "39 40 1760 31.0 16.50 0.532258\n", + "40 41 1765 43.0 17.60 0.409302\n", + "41 42 1770 47.0 18.50 0.393617\n", + "42 43 1775 44.0 19.50 0.443182\n", + "43 44 1780 46.0 21.00 0.456522\n", + "44 45 1785 42.0 23.00 0.547619\n", + "45 46 1790 47.5 25.50 0.536842\n", + "46 47 1795 76.0 27.50 0.361842\n", + "47 48 1800 79.0 28.50 0.360759\n", + "48 49 1805 81.0 29.50 0.364198\n", + "49 50 1810 99.0 30.00 0.303030" + ] + }, + "execution_count": 19, + "metadata": {}, + "output_type": "execute_result" + } + ], + "source": [ + "# Effacer une colonne en double\n", + "# del my_data[\"purchase_power\"]\n", + "my_data" + ] }, { "cell_type": "code", -- 2.18.1