{"cells": [{"cell_type": "markdown", "metadata": {}, "source": ["# Timeseries\n", "\n", "Ce notebook pr\u00e9sente quelques \u00e9tapes simples pour une s\u00e9rie temporelle. La plupart utilise le module [statsmodels.tsa](https://www.statsmodels.org/stable/tsa.html#module-statsmodels.tsa)."]}, {"cell_type": "code", "execution_count": 1, "metadata": {}, "outputs": [{"data": {"text/html": ["
\n", ""], "text/plain": [""]}, "execution_count": 2, "metadata": {}, "output_type": "execute_result"}], "source": ["from jyquickhelper import add_notebook_menu\n", "add_notebook_menu()"]}, {"cell_type": "code", "execution_count": 2, "metadata": {}, "outputs": [], "source": ["%matplotlib inline"]}, {"cell_type": "markdown", "metadata": {}, "source": ["## Donn\u00e9es\n", "\n", "Les donn\u00e9es sont artificielles mais simulent ce que pourraient \u00eatre le chiffre d'affaires d'un magasin de quartier, des samedi tr\u00e8s forts, une semaine morne, un No\u00ebl charg\u00e9, un \u00e9t\u00e9 plat."]}, {"cell_type": "code", "execution_count": 3, "metadata": {}, "outputs": [{"data": {"text/html": ["\n", "\n", "
\n", " \n", " \n", " \n", " date \n", " value \n", " \n", " \n", " \n", " \n", " 0 \n", " 2020-02-13 18:54:23.461489 \n", " 0.005357 \n", " \n", " \n", " 1 \n", " 2020-02-14 18:54:23.461489 \n", " 0.009562 \n", " \n", " \n", " 2 \n", " 2020-02-15 18:54:23.461489 \n", " 0.014353 \n", " \n", " \n", " 3 \n", " 2020-02-16 18:54:23.461489 \n", " 0.000000 \n", " \n", " \n", " 4 \n", " 2020-02-17 18:54:23.461489 \n", " 0.003475 \n", " \n", " \n", "
\n", "
"], "text/plain": [" date value\n", "0 2020-02-13 18:54:23.461489 0.005357\n", "1 2020-02-14 18:54:23.461489 0.009562\n", "2 2020-02-15 18:54:23.461489 0.014353\n", "3 2020-02-16 18:54:23.461489 0.000000\n", "4 2020-02-17 18:54:23.461489 0.003475"]}, "execution_count": 4, "metadata": {}, "output_type": "execute_result"}], "source": ["from ensae_teaching_cs.data import generate_sells\n", "import pandas\n", "df = pandas.DataFrame(generate_sells())\n", "df.head()"]}, {"cell_type": "markdown", "metadata": {}, "source": ["## Premiers graphiques\n", "\n", "La s\u00e9rie a deux saisonnalit\u00e9s, hebdomadaire, mensuelle."]}, {"cell_type": "code", "execution_count": 4, "metadata": {}, "outputs": [{"data": {"image/png": 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\n", "text/plain": [""]}, "metadata": {"needs_background": "light"}, "output_type": "display_data"}], "source": ["import matplotlib.pyplot as plt\n", "fig, ax = plt.subplots(1, 2, figsize=(14, 4))\n", "df.iloc[-30:].set_index('date').plot(ax=ax[0])\n", "df.set_index('date').plot(ax=ax[1])\n", "ax[0].set_title(\"chiffre d'affaire sur le dernier mois\")\n", "ax[1].set_title(\"chiffre d'affaire sur deux ans\");"]}, {"cell_type": "markdown", "metadata": {}, "source": ["Elle a une vague tendance, on peut calculer un tendance \u00e0 l'ordre 1, 2, ..."]}, {"cell_type": "code", "execution_count": 5, "metadata": {}, "outputs": [{"data": {"image/png": 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\n", "text/plain": [""]}, "metadata": {"needs_background": "light"}, "output_type": "display_data"}], "source": ["from statsmodels.tsa.tsatools import detrend\n", "notrend = detrend(df.value, order=1)\n", "df[\"notrend\"] = notrend\n", "df[\"trend\"] = df['value'] - notrend\n", "ax = df.plot(x=\"date\", y=[\"value\", \"trend\"], figsize=(14,4))\n", "ax.set_title('tendance');"]}, {"cell_type": "markdown", "metadata": {}, "source": ["Autocorr\u00e9lations..."]}, {"cell_type": "code", "execution_count": 6, "metadata": {}, "outputs": [{"name": "stderr", "output_type": "stream", "text": ["C:\\Python395_x64\\lib\\site-packages\\statsmodels\\tsa\\base\\tsa_model.py:7: FutureWarning: pandas.Int64Index is deprecated and will be removed from pandas in a future version. Use pandas.Index with the appropriate dtype instead.\n", " from pandas import (to_datetime, Int64Index, DatetimeIndex, Period,\n", "C:\\Python395_x64\\lib\\site-packages\\statsmodels\\tsa\\base\\tsa_model.py:7: FutureWarning: pandas.Float64Index is deprecated and will be removed from pandas in a future version. Use pandas.Index with the appropriate dtype instead.\n", " from pandas import (to_datetime, Int64Index, DatetimeIndex, Period,\n", "C:\\Python395_x64\\lib\\site-packages\\statsmodels\\tsa\\stattools.py:657: FutureWarning: The default number of lags is changing from 40 tomin(int(10 * np.log10(nobs)), nobs - 1) after 0.12is released. Set the number of lags to an integer to silence this warning.\n", " warnings.warn(\n", "C:\\Python395_x64\\lib\\site-packages\\statsmodels\\tsa\\stattools.py:667: FutureWarning: fft=True will become the default after the release of the 0.12 release of statsmodels. To suppress this warning, explicitly set fft=False.\n", " warnings.warn(\n"]}, {"data": {"text/plain": ["array([ 1. , 0.03577944, -0.06235687, -0.02029818, -0.02898255,\n", " -0.06825401, 0.0250769 , 0.93062748, 0.0120951 , -0.08157127,\n", " -0.04537123, -0.05365516, -0.08887674, 0.00289459, 0.88395645,\n", " -0.01531838, -0.1028712 , -0.06616495, -0.07120575, -0.10659382,\n", " -0.01690792, 0.84848022, -0.0335295 , -0.12382299, -0.08744705,\n", " -0.09339856, -0.12657065, -0.04305763, 0.80550906, -0.05483815,\n", " -0.14409999, -0.10895806, -0.10812254, -0.14125818, -0.05846692,\n", " 0.79099037, -0.05773434, -0.14731918, -0.10789494, -0.10483253,\n", " -0.14058412])"]}, "execution_count": 7, "metadata": {}, "output_type": "execute_result"}], "source": ["from statsmodels.tsa.stattools import acf\n", "cor = acf(df.value)\n", "cor"]}, {"cell_type": "code", "execution_count": 7, "metadata": {}, "outputs": [{"data": {"image/png": 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a5PXQG5xnaFKu2maa88PTTC2EaTUDmcO7isnPdq60YxaZpy0mffTwrmIKcpySTigkkLmRI7VuXhuckpPbNHesO0RBjpMDO1w3fE5jnVuu0meQmwWvZUW57C4vlM5lGaYjECTH6eCImRZssQKbTtnfGSf26jwYs+uNXjftcpEiY7X7gzT7jPTRbKeDJq9HAhkhgcyNNNS6CUc1Zwam7B6K2IKunhANtW6ynDc+1Butgn+pk8kIHYEQ+6qKcBfkrPp4k9dDV3dIFs/LIO3+ILfXlJCXfW1N1CHzKr3MwGWedn+Qanc+NZ6ClftafWWcG5picn7ZxpGJRBibWeTSyMxKShnAHfWlnBuaZmJuycaRCbtJIHMDR80re5Jelr5mF8O8Njh907QygPKiXLxlBVLwnwEiUc2x7tA168dcr8nrITS3LF0JM8TcUpjT/ZO01L9+n2c7HRytc0vnsgyjtabNP74yG2NpqfegtawVlYmsmfbYfb5SFyUXKrY1CWRuoLI4j10leRLIpLGTvRNEonplxuVmmuo8HOuZkKv0ae780DTTi+FV62MszeZj0s0qM5zomSAc1bTeIHht9pXy2uAUM4vhJI9MJMqVsVnGZpZWCv0tR2s9ZDsV7VLwn3Ha/EHysh3cVn21pf7tNSXkZDlouyJ1UduZBDI3caTWLS2Y05g1w9JYu3Ygc9TrYWxmkd6gLIyZzqwrsc2rdCyz7C4vwl2QLTNwGaI9EEQpbnjBotnrIarhuKwVlTGur4+x5Oc4ua26RGbgMlC731hGISfr6mlrXraThlq3dC7b5iSQuYmGWjc9wTnGZxbtHorYhK4eo1aipCB7zec21cnCmJmgIxBiR3EeNZ7XL35qcTgUjXUeKQDPEB2BIAd2FFOSv/rP+dE6Nw4l6SeZpN0fpLwol/rywtc91lJfyqm+CWnUk0GmFpY5OzhFq6/sdY/dUV/K6f5JmXHdxiSQuYmVhTH7Jmwdh9i4qFkrsVZ9jGX/DheFOU4JZNJcZ8DoaqOUuunzmrweLo/OEpqVItF0thyJcqx7gtabpBK68rI5uLN4JcdepD9r/ZjVfs5bfcZaUcdlbbCM0RUIofXrZ+AA7qgvI6qRGfZtTAKZm7i1ugSHMnKwRXq5NDrD1EKYxrr1BTJOh+JIrVt+Gaax/ol5BiYXaF5H8Go9RwLX9HZmYIr55ciqhf6xWnylHO+ZYDkSTdLIRKL0Bufon5hf9aQWjLRSpZD0sgzyin+cbKfiqLkOWKxGr5ssh5L1g7YxCWRuojA3i31VLk70yfoi6cYKSG7Wvep6TV4P54ammZUp6rRkXXFfzz6/vcb449cpgWta67BqJdbY580+D/PLEV4blHb66e5G9TGWkoJs9le5ZH2RDNLuD3Kkxv269uoABTlZ3FpdIvt7G5NAZg1H64yCf+lmlV66ukOUFubgKytY+8mmxjoPkaiWVMI01REIUpSbddPFTy35OU4OV5dI57I01x4I4i0roLI476bPs5o/SJ1M+mv3BynJN4KVG2mtL+VYT4iwzMClvbmlMK/2Td4wcAWjTuZk76TURW1TEsisoaHWzeT8Mn5ZcyKtdHWHaKxbu1YiljVtLbnV6akzEOJo3c0XP43V7PVwsm+CpbCc7KSjaFTTGQjSso4ZuB0lRgMIqZNJf+3mPnc4bvy7vbW+lLmliCxonQGOW+3VbxLItNaXshSJyt/ubUoCmTUckYUx0874zCL+sdl1F/pb3AU53FJRKHUyaWhybpnzw9PrOqm1NHk9LIajnBmQ1NF0dHl0htDc8pppZZYWXykdgZDMrqexkakF/GOzr1s/5nrWMSHpRumvzR/Eobjp3/Nmn1EXJft7e5JAZg17K41uVrKeTPo4Zl6Vab5JJ6MbafJ6ONYjJzvpxthnG9vnVsG/BK7pyVo7Yq1Cf0uzz1grqnt8LpHDEgnUvsrq7qupLM7DW1Yg64tkgHb/OId3leDKu/EyCiX52RzcUUx7QAr+t6N1BTJKqQeUUueVUpeUUh9f5fFHlVKjSqkT5v/fif9Q7eF0KG6rKZEZmTTS1R0i26muWQF4vRrrPEzMLXNFUgnTSkcgSJZDrbRMX4/K4jxqS/MlkElTHeZaIuutg7Nm66SbVfpquxKkIMfJ4V3Faz631VdKZyBINCoXpdLVYjjC8Z6JNWfgwAhuu7pDkiq8Da0ZyCilnMDngLcCh4D3KKUOrfLUp7XWDeb/L8R5nLY6Uuvm7OCUFJKlia7uIId3laza4WQt1urgx+TkNq10doc4XF1CQU7Whr6uqc5DZ7fMwKWjjkCI1vr118HtqSiiJD9bAtc0Zq3uvp46uJb6UkJzy1wenUnCyEQivNo3yWI4uuYMHBgF/wvLUU5LqvC2s54ZmVbgktb6itZ6CXgKeDCxw0otR2vdLEe0tO5MA0vhKCf7JjdcH2PZU1GEKy9rJT1NpL7FcISTvRPrWj/mek2+UkanF+kNzidgZCJR+ifm6Z+Y31BNlMOhaPJ6ZEYmTYVmlzg/PM2du1+/uvtqrDqZNqmbSFvWvlvPz7mVYtp2Rfb3drOeQKYa6I253Wfed73fVEqdUkp9UylVG5fRpYiGWuMESdLLUt+ZgUmWwtFNndSCcbJztM4jMzJp5HT/FIvhKC2bqIlaqZPpkT9+6aRjAyc4sZp9Hi6PzjI+s5iIYYkE6lhnfYzFW1ZApStXAtc01uYPsr/KhacwZ83nlhflcktFoSyMuQ3Fq9j/u4BPa3078Czw5dWepJT6sFKqUynVOTo6Gqe3TrwdJXnsKM6TQCYNWGkjjZsMZMBIN7owMs3UwnK8hiUSyGqp2+Td2EktwL4qF67cLDplfZG00h4I4srN4uDOtWslYlmBj6SXpZ92f5CcLAe316yv9lEpRUt9Ke3+oKSOpqFwJEpXILjuwBWgtb6MzkCIiNRFbSvrCWT6gdgZlhrzvhVa63GttXWJ6wtA02ovpLX+vNa6WWvdXFFRsZnx2uZIrRT8p4Ou7hA1nnyq1lgg72YavW60hhOSXpYWOgIh6ssLqXDlbvhrnQ5FQ51bTmzTTIc/SKPXg/Mma4ms5rbqEnKcDjplf6edNn+Qo7VucrPWX/vY6itlcHKBvpCkjqabs4NTzC5FNhTI3Lm7lOnFsJQBbDPrCWQ6gL1KqXqlVA7wEPBM7BOUUjtjbr4DeC1+Q0wNDbUeusfnCM0u2T0UcQNaazq7Q5uuj7E01LpRymjpK1JbNKrp6g5uOpUQjFXfzw/LDFy6CM0ucXFkZkMnOJa8bCe315TIwphpZnphmTMDk+vqXhXLOkYkvSz9WGvCbOTnvEXWD9qW1gxktNZh4PeA/8AIUL6htT6jlPqkUuod5tM+opQ6o5Q6CXwEeDRRA7aL1db1RN+EreMQN9YXmmd0enFLJ7UArrxs9le55Cp9GrgyZiyKuNFaiVhNXg9aI6tCpwlrNmWz+7zZV8qr/ZPShTKNdHWHiGojdWgj9le5KM7LkkAmDbX5g/jKCjaUXbHLnU9tab4EMtvMumpktNbf11rv01rforX+C/O+/661fsb8/I+11oe11ke01m/SWp9L5KDtcFtNCUpJulEqs2ZQtlIfY2n0ejjROyFrEKS4DrO2ZTOLn1oa6tw4FHTJyU5a6AgEyXGuv1bies1eD8sRLYscp5F2v7FOVKPXvaGvczgUzb5S6VyWZqJRTccG62Msrb4y2gNSF7WdxKvYP+MV5Waxr9IldTIprDMQojDHyf4q15Zfq7HOw/RCmEuyBkFK6wgEKSvMob68cNOvUWQWjXdJKmFaaPcHub1mc+tEASupp1Inkz7a/UFuq9n4OlFgpCZdGZ1lTDrVpY2LIzNMzC1veAYOjPVkgrNLXBqRv93bhQQyG9BQ6+Zk34RE+imqqztEQ517XYulraWxzr3ymiJ1dZk1UetdFPFGmrwejvdMEI7IqtCpbG4pzOn+yZU1IzbDU5jD3soiSTdKEwvLEU72TWzq6jxcTUGUuqj0YbVQ3mhNFMAdu2X9oO1GApkNaKhzMzG3TPf4nN1DEdeZWQxzbmhqUy14V1NfXoinIFvWk0lhI1MLdI/Pbak+xtLk9TC3FOHc0HQcRiYS5UTPBOGoXlnscLOafaVG3YWkjqa8Yz0hliN6Uye1YHSqy8t2yIltGnnFH2RXSR41nvwNf21daQFVxblSJ7ONSCCzAUdq3IAsjJmKTvRMENVsuWOZRSlFY51H0o1SmJUatJX6GEuzrC+SFtoDQZTaeh1ci89IHb0wIoFrqmv3G/t8sxepcrIcHK31yAxcmtBa0+436mM2M9OulKK1vkzWD9pGJJDZgH1VReRnOyWQSUFd3SGUutpdLh4avR6ujM5Ky+0U1REIkpft4PCuzRV9x6p257OzJE/qJlJcRyDIgR3FlORnb+l1mr1WW17Z36mu3R/k0M6t7fOW+lLODkwxLS3WU15gfI7R6cVN1cdYWutLGZpaoDco6wdtBxLIbECW08FtNbIwZirq6gmxr9K15ROcWI11xlXf471yspOKOgMhGmrd5GTF59dYo9cjnctS2HIkyrHuCVrjMANXW5pPpStX6iZS3FI4yrGe0KbrYyytvlKiWmZc04FVH7OVfW6lIbaZryUymwQyG9RQ6+bswBSLYVmDIFVEo5rj3SGa4nCCE+tIbQlOh+JY90RcX1ds3cximDMDk3Gpj7E0ez0MTC4wMCFX8VLRmYEp5pcjWyr0tyilaPGV0ikzMinNWO8nuun6GEuj102WQ0l6WRpo8xudKG+p2Hwnyj0VRXgKsqUuapuQQGaDGmrdLEWivDYoudWp4sLINNOLYZrq4hvIFORkcXCnLIyZiqyaqOa4BjJSJ5PKOqyVvuO0z5t9Hvon5iVwTWFWwfZWL1gU5GRxuLqEDr/8bKe6rdTHWBwORWt9qRT8bxMSyGyQVYMhi6mlDuvEM16F/rGa6jyc7JO2vKmmIxDEoa62yY6HAztd5Gc7JZBJUe2BIN6yAio3sNL3zay05ZX9nbLa/OPsqSyirCh3y6/V6jMWOV5YlmyKVNU/MU9faH7LqYQArfVl9ATnGJyUCxWZTgKZDdpZkkelK1fqZFJIV3eIssIcvGUFcX/tRrMt7/lhmYFLJZ3dQfbvKMaVF7+aqGyng4ZatwQyKSga1XQGgnFNJTyww0VhjlPqZFJUJKrpDGy9PsbSWl/GUiTKqb7JuLyeiL+VWdc47HMrHVFmZTKfBDIbpJTiSK1bApkUcixOiyKuxir4l/VkUkc4EuV4zwQtca6JAiPd6OzgFLOL4bi/tti8y6MzhOaW45ZWBkbzlqN1HulclqJeG5xiZjG85foYS7M5Yy91MqmrzR+kOC+LAzuKt/xaB3cWU5SbJYHMNiCBzCY01Lrxj80yMSdtee02Or1IYHwuIWllADWefCpcuRzrmUjI64uNe21wmrmlSFzrYyyNXg+RqJbU0RTTbp58xqPQP1azz8O5oSmmpC1vymmL49V5AE9hDvuqiqQAPIW1+cdp8ZXidGz9oqTToWj2eSSQ2QYkkNmEo1adjExR2+5YT+LqY8BaGFPSjVKJdUU1ETMyjXUelJKC/1TT4Q9SXpSLL87poy2+UrSWGddU1O4fp660gJ0lG1/d/UZa60s51h0iEpWFElPN6PQiV0Zn4xa4grG/L47MMD6zGLfXFKlHAplNuK2mBKWMzknCXse6Q+Q4HdxavfVFEW+kyeuhJ2gs0iXs19kdNBewjN8JjqUkP5t9lS4pAE8xHYEQrfXxTx9tqHXjdCgJXFNMNHp1dfd4avGVMrMY5rXBqbi+rtg66wJVPPf5HeaimpJOmNkkkNkEV142eyqKOCELJdquqzvErdXF5GU7E/YeK3UyPbK/7aa1piMQSshsjKXR6+FYT4ioXLVNCf0T8/RPzMe10N9SmJvF4V3FcqKTYi5ZNVFxDmRaVxZKlP2datr9QfKznXG9KHlbdQl52Q7Z3xlOAplNaqh1c7JvEq3lZMcui+EIp/onE5ZWZrm1uoRsp5JAJgVYM2OJqI+xNHs9TC+EuTgyk7D3EOvXEae1RG6kyWu05V0KS4v1VGGdeMar0N+ysySfGk/+yjElUkebP0iT10O2M36npTlZDhrrpE4m00kgs0kNdW6Cs0v0BqVHuV1O90+xFI4mPJDJy3ZyeFcJx7snEvo+Ym1Wh6lEndSCUQAORgqbsF97IIgrN4uDO7feyWg1Lb5SFpajnBmQmsdU0e4PsqM4j7rS+LfUb60vpSMQlIuQKWRybplzQ1Nxn4EDY3+fHZSGHplMAplNOlLjBuC4pJfZxirQbUxwIAPGVduTfXLV1m6dAaM9597KooS9R11pAeVFOXRJW96U0OEP0uj1xKWT0Wqstrydsr9Tgtaadv/4lld3v5FWXynjs0tcHp2N+2uLzensDqJ1fOtjLK31RkMP+X2euSSQ2aQDO1zkZTtkPRkbdXWHqCstoNIVn5W+b6axzsNiOCpFojbrCBjpB44EndSC0amuyeuhS1IJbReaXeLiyExCTnAslcV5eMsKpE4mRfQE5xieWkzYPrdaeMv+Th3t/iA55oLE8Xa01kO2U0mdTAaTQGaTspwObqsukfUmbKK1ptNcCDMZGr1uQNry2iloXkVNZH2MpdlbSve4dKqz29VW24nd583eUrq6Q5JulALariSmPsayu7yQ8qIcqZNJIW3+IEdqSxLStCc/x8mRGjdt/vG4v7ZIDRLIbEFDrZvTA1OSbmSD3uA8YzOLSUkrA6NIdFdJnhT828gKIhN9UgtX0xW7pE7GVh0B40rt7TWJa68OxppE47NL+Mck3chubf4gpYU57ElQ+qhSihZfqVyhTxGzi2Fe7Z9caZWcCK31pbzaN8ncUjhh7yHsI4HMFhypdbMUjnJuSNKNkq2rx/gj1JykQAbgqNcjC+fZqDNJJ7UAt1YXk5PlkBk4m7UHQgm7UhtrpcGD5NHbrj0wTosv/msGxWrxldI/Mc/AhDTrsduxHmOB0kSmj7bWlxKOao7L2n8ZSQKZLbDyOaVOJvk6AyGKcrPYV+VK2ns21XkYmFxgcFL++NmhIxDktprEn9QC5GY5OVJTIgtj2mhuKcyZ/smkzMDdUlGEpyBb6iZsNjAxT29wPqFX5+FqUbnsb/u1+4M4HSqh2RVNXg8OJesHZSoJZLag2p1PeVGuBDI26OoOcbTOnbBORquxftEekzbMSbewHOHV/smVK+fJ0Oj1cLp/koXlSNLeU1x1vGeCcFSvFGcnktHgoVQCV5slYnX31RzcWYwrN0tObFNAmz/IrbuKKcrNSth7uPKyObyrhHapk8lIEshsgVKKhtoSCWSSbHphmfPD0zTWJe+kFuDQzmJysxxSJ2ODk70TLEc0Ld7En9Ramr2lLEc0r/bL+iJ2aPcHUYqkNfRo8Xnwj80yNiMNHuzS5k/smkEWawZACv7ttbAc4UTvRMIDVzCaRxzvmWAxLBemMo0EMlvUUOvmyugsk3Oy2FKynOidQGuSenUejFWCb68pkUDGBtaV8mSd1Ma+l9RN2KMjEOTAjmKK87KT8n5WNzzZ3/ZpuzJOsy9xawbFaq0v5eLIDMHZpYS/l1jdqb5JlsJRWhOcSgjG/l4MRznVJxemMo0EMlvUUGuc7Jzqn7B3INtIZyCEUiSk5/xaGusk3cgOHYEgeyqL8BTmJO09Swtz2F1eKJ3LbLAciXK8Z4LWJF6ssBo8dErdhC3GZha5PDqblJNakDqZVGClerUk4efcqrVrl1m4jCOBzBbdXmt0UDoh3TCS5lhPiP1VLlxJulIbq9HrYTmiOTMgV3WSJRLVdHWHkvLH7npNXo+sL2KD0/2TzC9HklIfY8nNctJQ46ZD6mRsYaV5JSPNCOD2mhJyshySXmajNn+QAztcuAsSf4HKU5jD/iqX1EVlIAlktqg4L5tbKgqlTiZJImYLxWSmGMWy6nKkLW/yXBieZnohTHMS62MszT4Pobllrsj6Ikm1UvSdhI5lsZp9Hs70TzK/JDOuydbmD5Kf7eS26sS3VwczcK11y4yMTcKRKF3doaQFrmAEyV2BIOGIrP2XSSSQiYOGWo9ZtyFXbRPtwvA0M4vhpNfHWCpcudSVFkjnsiTqTOJCmNezAuYuqZtIqnZ/CG9ZAZXFeUl93xafsd6EXJhKvnZ/kEavm5ys5J2WtPpKOT0wxeyiLJSYbKcHpphbiiS81Xas1vpSZpcinB2Utf8yiQQycdBQ52Z8dom+kKwvkmgrRd91yT+ptTTWuenqkXSjZOkMBKl05VJbmp/0995dXoS7IFtm4JIoGtV0dQdtCVwb6zwohdTJJNnk3DKvDU3R6kveSS1AS30pkaiWBi42WKmPqU/eRck76qVOJhNJIBMHDTVuQBbGTIZj3SHKi+w5qbU0eT2MTi9K4JoknYEQLb7ShK70fSMOh6KpzkOnFPwnzeXRGUJzy0lPKwMoKchmf5VL6mSSrLM7iNbJq4+xWAslSp1M8rX7g+wuL6TSlbxZ18riPOrLC3nliuzvTCKBTBwc2OkiN8shgUwSdHWHaPK6bTmptRw162TkKl7i9U/M0z8xb1sqIRgNHi6PzhKSNq1J0W7OhiSz0D9Wk9fDse4QkajMuCZLuz9IjtPB0Tp3Ut+3KDeLw7tKpAA8yaJRTbs/mPTAFYx0wo5AkKj8fGcMCWTiINvp4NZqWRgz0UamF+gJztlS9B3rwA4XBTlOjslV24SzUnzsSDOyNHslcE2mDn+Q8qJcfGUFtrx/i6+UmcUw54Ykjz5Z2vxBjtSWkJftTPp7t/hKOdErCyUm0/nhaaYWwvYEMvWlTM4vc2FkOunvLRJjXYGMUuoBpdR5pdQlpdTHV3k8Vyn1tPl4m1LKF/eRpriGWjen+yd5VRZbShgrcGi0qWOZJcvp4EiNm2PScjvhOgMhCnKcHNjhsm0MR2rdZDnUSn2WSKyOQIjWeo9ts67W7J8sjJkcs4thTvdP2nJSC1cXSjzdL3+7k6U9ya22Y7VKnUzGWTOQUUo5gc8BbwUOAe9RSh267mkfBEJa6z3Ap4G/jPdAU92DDbvIyXLwq3/3Eu9/vJ22K+NSDB5HAxPzPNXRS47Twa3VxXYPh0avm7ODU8wtSbebROoIBGms85DltG/yOC/byeHqEulclgRWKqGdM3DV7nx2luRJ4Jokx3smCEd10hbCvJ61PpWklyVPuz9ItTufGk/yZ11rPPnsKsmT/Z1B1nN20Apc0lpf0VovAU8BD173nAeBL5uffxN4s7KziMEGt9e4efnj9/NHD+znTP8k7/78K7zzf/6c586NSECzBWcGJvk/nj7BG/+f53jx4hgfemM9uVnJTz+4XpPXQySq+fbxfsm1TZDJ+WXOD0/bWh9jafZ6ONk3wVJY1h9IJKvo2s5ARilFs6+UDn9QfncnQZt/HIfCtrXByopyuaWiUAr+k0RrTZtN9TFg/HzfsbuMdvn5zhjrCWSqgd6Y233mfas+R2sdBiYBey6v2Kg4L5v/7b49vPSx+/nzdxxmcHKBx57o4G1/+xLfOzUgxaPrpLXm+fMjvO8LbfzK377Ef5wZ4v13+Xj+D+7jD3/5gN3DA6C1vozdFYX86bdP85ZP/ydPtfewsCw51vEyMr3A3/zoPFrbe1JrafZ6WAxHOTMg6SeJ1B4I4srN4uBOe2ddm70ehqYW6J+QzoSJ1uYPcmt1CUW5WbaNobW+jE5p8JAUV8ZmGZtZtC2QASO9bHR6kcD4nG1jEPGT1N8cSqkPAx8GqKurS+ZbJ1V+jpNH7vbx8B11/NuJAf7++Uv83pPHqS+/wH/5hd38+tGapC76lS4WwxGeOTHAF170c354mkpXLh974AAPt9ZRUpBt9/CuUZSbxX989I18/9VBPv/CFT7+rVf5qx9d4NG7vbz3Di+ewhy7h5iWXhuc4osv+XnmxADL0Shvv31nSgQy1tXizkBopWudiL8Of5BGrwenw94J/dg6GTvSX7aLheUIJ3oneP+dXlvH0Vrv4evtPZwbmuLwrhJbx5Lp7KyPsVjv3XZlnPryQtvGIeJjPYFMP1Abc7vGvG+15/QppbKAEmD8+hfSWn8e+DxAc3Nzxl/6yHY6+K2mGn79aDU/OjPE556/xMf+9VU+8+OLfOgNu3motZaCnPjEkpGo5vLoDCd7J3i1f5LT/ZMsLEcpyHGSn+MkP9tpfp4V87n5Mdv6PIuCHCd55uMFOU4Kc7MoK8xJaOHt5NwyX2vv5omXA4xML7K/ysVfvfMI7ziyK6UDvmyngwcbqnnHkV38/PI4n3/xCn/1owt87rnLvKu5hg/eu5s6mzovpROtNf95YZQvvOjnpUtj5Gc7eai1lsfuqU+ZPzKVxXnsrSziL394jlP9kzx6t9dcPHFbZdAmhNaaV64EefxlPxdHZviNxhq7h8SBHcUU5WbREQjya0evT0AQ8XKqb5KlcJQ7dtubwGFdLOnwByWQSbB2syvhbht/t+8uL6S8KId2f5CHWjP3ovp2sZ6z6A5gr1KqHiNgeQh4+LrnPAM8Avwc+C3gp1qSD1c4HYq33raTB27dwQsXx/jcc5f45PfO8nfPXeID9/j47bt8lOSvf8YhGtUExmc51TfJqb5JXu2f4HT/FPNmalNhjlGcvKswl/nlMDOLYUanF5lfjjC3FGF+KcLcUpj1zqKX5GdzaGcxh3cVc7i6mEM7S7ilonDLBdi9wTkef9nP0x29zC1FuHdPOf/vO4/wxr3laXWCqJTi7j3l3L2nnPND0/zTi1d4sr2Hr7zSzVtv3cmH3ribhlq33cNMOQvLEb5zvJ8vvmScwFYV5/JHD+zn4dY63AWpN6P1xAdaefwlP9/o7OW7Jwe4tbqY99/l4x1HdtnSNjbdLSxHeObkAI+/5Ofc0DSegmx+90238Ng9PruHhtOhaPR6eP78KGcGJuXkNkFWVne3uQ6uxlNAtTufjkCIR++pt3Usma7dH+SOensWOLYopWitL5WC/wyh1hNvKKXeBnwGcAKPa63/Qin1SaBTa/2MUioP+ApwFAgCD2mtr9zsNZubm3VnZ+dWx5+2OgNB/v75y/z03AhFuVn89l1ePnBPPRWu3Guep7WmLzRvBi0TnOozZlumF41uWXnZDg7vKuG26hJurynh9ho3u8sLcayRmqG1ZjEcZcEMbmIDnPll6/MIUwvLXBie4ezAJOeGplk0i51zsxwc2OHi0K4SDu8q5tCuYg7uKCY/Z+0TulN9E3z+hSt8/9VBHErxjiO7+OAb6jPqZGFocoEnfhbga23dTJv98j/8ht3cf6ByzX2zXlMLy1wYmubc0DQXhqcZn10yZtfMGbW87KuzcSsfrc9vcDs7Cd3BRqcX+eor3Xz1lW7GZ5c4tLOYD72xnl+5LbVn4Cyzi2G+c6KfL/8swIXhGTwF2TzUWsf77vRS7c63e3gpb2Rqga+80s2TbT2Mzy5xYIeLx+7x8WBDdUoFhM+eHeb3nzrO3FKEO+pL+cC99fziwSrb094ywWI4wg9PD/HXP7pAQY6TH370jXYPiY8+dZyXLo3T8advTqsLaemkLzTHvX/5HH/+jsM8crfP1rE88bKfT3z3LC997E2SPpoGlFJdWuvmVR+za+JkuwcyljMDk/zD85f591cHyXE6eKilljt3l3FmYIqTfUaa2MTcMgA5TgcHd7q4raaE26vd3FZTwt7KoqS1pg1HolweneXs4CRn+qc4MzDFmYFJphaMoMqhYHdFkRHY7CzmsBnkeApziEY1z50f4fMvXKHNbxT0PnxHHY/e42NnSeae/M0shnm6o5fHX/LTPzHPLRWFfOgNu/m1o+s/aVsKR7kyNsN5M2g5b/6PLUQuys2isjiXxeWoOfMWZmF54x22shyKne489le52FvlYn+Vi31VLnZXFG75JPPC8DRffNHPt0/0sxSO8osHK/ngvbu5c7e9V+c2S2vNz6+M8+WfBXj27DAAbzlUxSN3+7hrd1lafk+JdKpvgsdf8vPvrw4SjmrefKCKD9zj465bUndbTc4v842OXp74WYD+iXlqS/N59O563tVcgysvter20kH3+CxPtvfwL519BGeXqCst4M/fcZg3Hai0e2h8ra2bP/32aT7y5r08cpeXsqLctb9IrFs4EuXvn7/M3zx7gR/8/htsb+jx2uAUb/3si3zk/j383v170+Ii2nYmgUwauDI6wz/+5xW+dbyP5YjG6VDsr3Jxe03JSuCyb0dRSrQejmXNGJ0dNAKbswOTnBmYYnByYeU5u0ryyM5y0D0+x66SPD5wbz3vbqndVicCy5HoSmOAMwNTlBfl8MhdPt5359XGAFpr+ifmXxewXBmbYTli/JxmORS3VBSxf4eL/TtcHDA/VrvzX3cyGI0as27WLNvCcoT5petux6QbLixHmF2K0Bea58J17+t0KLxlBSuBzf4dLvZVFeEru3mKodaaFy+O8YWX/LxwYZS8bKNu7LF76rmloihBWzv5+kJzfK2th6faewjNLbOvqoj33+XjNxqr41IHt7Ac4eLwDK8NTXFucJrzw1N0j8/hdCiynQ5ynA6ysxzkOM3bWY6r9zvVym3rsRzz8+wshTs/h31VReytcm0oxXU9wpEoPzwzxJdeDtDVHaIoN4t3NtfwyF0+fClS/7Qe4UiUZ88O88WX/HSa38e7mmt59G6f1MGtYTkS5SevDfO1th5evDiG06F4y8EqHr6jjnv3lMdthnqrphaW+cjXj/P8+VFyshw8eGQXj91Tz6Fd9q9bls76J+Z5ur2Hpzt7GZ5a5PCuYr77e/favt+jUc07//HndHWHqHTl8v67vLyntU4C2BQlgUwaGZ5aYHBygQM7XCmVZrFRwdklzpozNmcGpgjNLfFbTTW87badSUlfSlVa65XGAM+fHyU/28n9ByoZmlrgwtD0SsogGAvzXR+w7C4vStqVo+VIlMDYLOeHp7kwNM354WkuDs8QGJ9dqa/KcTrYXVFoBjZmkFPlorI41+hA99IVLgzPUOHK5dG7fTzcWpfRHd2suo8v/yzAmYEpXHnGCe9v3+ld14l7NGpcGHhtaMoMaKc4NzRNYOzqNs/LdrC/yrXSCGE5YgSsyxHj/5L5+VJEsxSOsBzRK49dfZ5etdXszpI8cz8WrQSseytd60oZjTUxt8TX23v5ys8DDEwu4C0r4JG7fLwzA2YyTvZO8KWX/Xzv1CARrXnLwSo+cG99wvP+F8MRtDbSelN1BitW/8Q8T7X38HRHLyPTi+wsyeM9rXW8u6WWquI8u4d3Q5dGpvnSywG+dayf+WUjrfCxe+p5yyFJK1yvcCTK8+dHebK9h+fPj6CB+/ZV8J7WOu4/UGnrAsexolHNf14c5UsvB3jhghHA/lqDEcDaPWMkriWBjBApyGoM8MKFUXxlhdcELft2uChO0RO+heUIl0ZmuDB8Nbi5PtVNKdAaDu4s5nfureftR3am3GxiImmtOdYT4omfdfODV40T3vv2VfDI3T7euLcCh0MxObe8EqicM4OWC0PTzC4ZTTuUAm9pgXlMFHNgh4sDO4upKy2IywlVJGoEOGMzi8Y+jA1YR2ZWFv9UCupKC1aC1H07XCuB1PVB9cXhab70swDfOtbHwnKUu28p47F76rn/QGXGnQQOTy3wlZ9387W2bkJzyxzaWcwH7q3nV7d4rEeimu7xWc4PTfPa0DTnzaC2OziHjrmAkJPlIDfr+o/OlRm33Gzro/Oa2wU5TnzlheypLGJPZVFcf89Eopr/vDDC117p4TnzBPZN+yt5uLWO+/ZXpMwJ7HpMzi3zdGcPX/5ZN/0T89R48nnkLh/vaqmN+8xlphicnOep9l6+0dnL4OQCla5c3t1Sy7tbalO+DuX6APau3WU8do+PN0tdXEqQQEYIkXDTC8tcHJnh4vA0gfE53rCnPKXrH5JleGqBr7X18GRbD2Mzi9R48olE9TXpl+6CbCNQMQMWa4ar0KZFAsORKD3BOSNYHboatPrHZldmcrIcit0VheyrcrGnsoiu7hAvXhwjJ8vBrzdU8+g9vm1xVdPqvvf4y34uDM9QXpTLb9/p5b131lG+RprK6PTiNTNv54emuTgyvVLfphTUmxc59la5yM1ysBg2Zt2WwlEWwxHzo3lf5Op9sfcvrnxupJKGY2bjKl257KksYq8Z2Nxifqwoyl33z+7I1AJPd/TyVEcv/RPzVLhyeXdzLQ+1pv4J7FrCkSg/fm2Yx18O0O4PUpDj5Dcba3j0Hl/C0mOjUSPNODS3hNagMS6OGB8BdMz91z6mrcfMzxWKHSV5eMsKEpINYQWvT7b18NNzRvD6hr0VPNxax5sPVqZdBsbE3BJPdfTyzz8zZpPrSgt4/11e3tVSm7CLi5Goxj82Q09wjrA5Wx6OGh+t/8bt6DX33+g57oKclQtPNZ5829P44kECGSGEsNlSOMoPTg/yneP9uAtyVmbfDu4sptK1/pNGOy2GI1wZnTUDnOmVAKc3OE9VsXECv13zzLXWvHRpjMdf8vPc+VFynA4eNNNU6ssLV7aZlTZ4fsjoNGgpL8rhwI7ia2ZmN5PWt5ZIVNMbnOPSyAwXR2a4NDLDpdEZLo/MMBOT2lqcl8XeKhd7KopWZm/2VBZR7TZOjKJRzcuXx3iyrYdnzw4Tjmru3VPOe++o4xcPVaXdCex6nO6f5ImfBXjmxABLkSi/sK+Cx+65Osu6UVprhqcWr0vfnebC8MzKcgrxku1UeMsK2VNRxN4qM2itMP5v5hgbmjSC16c7ehiYXKDClcu7mmt4qKWO2tL0Dl7BCGB/dHaYL73spyMQojDHyTuba3nkbt+W1jdbWI5wYXh6pVnSmQGj7nGr+9vpUMZ/pa55rYIcp9m4p4j9O4rZb6YMlxcldn3AeJNARgghRMLMLYXJcTrSKnUokS6PzvDEywG+2dXH/HJkJdUSjBqnfVVW3dvVGbi1Zm8STWvN0NSCEdiY/y+OGAFObMCVn+1kd0UhM4thusfn8BRk887mWt7TWpcyC9gm2tjMIk+2GWuFjU4vsruikEfv9vGbjTU3nEUdn7kasFwYmVkJXKYXrgaP5UW57N9RxN7Kq8eEQxkzcwqF+Q+llPnRuF+Z96PAsfKYcb81uxO7P7uDcyszq0oZ9Zh7KouuCXL2VLgoKbh2BiIS1bxwcXRl9iUS1bxhbzkPt2Zu8Arwat8kX3rZz3dPDRCOat60v5IP3FPPPXtunnEwtbBs1gobQcvZgSkujcyszIi6crM4uMtco29XCbsrCs3fo0ZA4nQoshwOnE5FlkPhUMZH67YVuDgd6ppxzCyGuRATHFsXncZmrv4clxYaTV4O7Ci+poFPqtYwSiAjhBBCJNnk3DL/0tXLzGJ4JXCJV41TMoVml7g0agY3w8YMjtaa32qq4ZcP70jrxjRbsRQ2ulF+6WU/J/smceVl8e7mWt50oJLA+OxK/aC1zpelJD/bbHFfdE2jlNIkNUJZDEfoHp+7Zn9eGpnhyujMylpxYARWeyqNeipXXjbPnBigf2Ke8qIcI3htqdtWXftGphf46is9PNnWzdjMEvuqinj07np+/Wg1UwvLxgxL/9RKF9ee4NzK11a6clcCFutjbenru40m0tjM4jXBjRVYW3WZcLXJ0L4qF/cfqKS1vjRp47sZCWSEEEIIIRLAaO5hdLP7wemhldmOwpW0nqtBy/4qFxUpmkoaiWr6Q/NcHJm+OjNnBjnTC2Hu2VPGw61e3nKoaluvu7IYjvDdk4M8/pKfs4NTZDnUNXVnvrICDu8q4VDMbMv1i52nCmvG7sLw1cW1zw9Nc3l0hv/9/r185M177R4iIIGMEEIIIUTCDU7Oc2F4hlsqCtlVkhmF1lpr5pcjcVkTK5NorWn3B/nR2WFqPPkc3lXCwZ2ulE3P2girlb9dDWeud7NAJjVGKIQQQgiR5naW5LOzJN/uYcSVUkqCmFUopbhjdxl37C6zeyhxZy2gnA7SY5RCCCGEEEIIEUMCGSGEEEIIIUTakUBGCCGEEEIIkXZsK/ZXSo0C3ba8+erKgTG7B5HBZPsmnmzjxJNtnHiyjRNLtm/iyTZOPNnGiZdK29irta5Y7QHbAplUo5TqvFFHBLF1sn0TT7Zx4sk2TjzZxokl2zfxZBsnnmzjxEuXbSypZUIIIYQQQoi0I4GMEEIIIYQQIu1IIHPV5+0eQIaT7Zt4so0TT7Zx4sk2TizZvokn2zjxZBsnXlpsY6mREUIIIYQQQqQdmZERQgghhBBCpJ1tH8gopR5QSp1XSl1SSn3c7vFkIqVUQCn1qlLqhFKq0+7xZAKl1ONKqRGl1OmY+0qVUs8qpS6aHz12jjHd3WAbf0Ip1W8eyyeUUm+zc4zpTClVq5R6Til1Vil1Rin1++b9chzHyU22sRzHcaKUylNKtSulTprb+M/N++uVUm3mucXTSqkcu8eajm6yfZ9QSvljjuEGm4ea9pRSTqXUcaXU98zbaXEMb+tARinlBD4HvBU4BLxHKXXI3lFlrDdprRvSoZVfmngCeOC6+z4O/ERrvRf4iXlbbN4TvH4bA3zaPJYbtNbfT/KYMkkY+K9a60PAncDvmr9/5TiOnxttY5DjOF4Wgfu11keABuABpdSdwF9ibOM9QAj4oH1DTGs32r4AfxhzDJ+wa4AZ5PeB12Jup8UxvK0DGaAVuKS1vqK1XgKeAh60eUxCrElr/QIQvO7uB4Evm59/Gfi1ZI4p09xgG4s40VoPaq2PmZ9PY/wBrUaO47i5yTYWcaINM+bNbPO/Bu4HvmneL8fxJt1k+4o4UkrVAL8CfMG8rUiTY3i7BzLVQG/M7T7kl3wiaOBHSqkupdSH7R5MBqvSWg+anw8BVXYOJoP9nlLqlJl6JmlPcaCU8gFHgTbkOE6I67YxyHEcN2ZKzglgBHgWuAxMaK3D5lPk3GILrt++WmvrGP4L8xj+tFIq174RZoTPAH8ERM3bZaTJMbzdAxmRHPdqrRsxUvh+Vyn1RrsHlOm00Y5QrlrF3z8At2CkOAwCf23raDKAUqoI+Ffgo1rrqdjH5DiOj1W2sRzHcaS1jmitG4AajEyPA/aOKLNcv32VUrcCf4yxnVuAUuBj9o0wvSml3g6MaK277B7LZmz3QKYfqI25XWPeJ+JIa91vfhwBvo3xi17E37BSaieA+XHE5vFkHK31sPlHNQr8E3Isb4lSKhvjBPtrWutvmXfLcRxHq21jOY4TQ2s9ATwH3AW4lVJZ5kNybhEHMdv3ATNtUmutF4EvIcfwVtwDvEMpFcAosbgf+Cxpcgxv90CmA9hrdmbIAR4CnrF5TBlFKVWolHJZnwO/BJy++VeJTXoGeMT8/BHg32wcS0ayTrBNv44cy5tm5mB/EXhNa/03MQ/JcRwnN9rGchzHj1KqQinlNj/PB96CUYv0HPBb5tPkON6kG2zfczEXOxRG7YYcw5uktf5jrXWN1tqHcR78U631e0mTY3jbL4hptp38DOAEHtda/4W9I8osSqndGLMwAFnAk7KNt04p9XXgPqAcGAb+DPgO8A2gDugG3qW1lmL1TbrBNr4PIx1HAwHgf4mp5xAboJS6F3gReJWredl/glHDIcdxHNxkG78HOY7jQil1O0YhtBPj4vA3tNafNP/2PYWR9nQceJ85eyA24Cbb96dABaCAE8B/iWkKIDZJKXUf8Ada67enyzG87QMZIYQQQgghRPrZ7qllQgghhBBCiDQkgYwQQgghhBAi7UggI4QQQgghhEg7EsgIIYQQQggh0o4EMkIIIYQQQoi0I4GMEEIIIYQQIu1IICOEEEIIIYRIOxLICCGEEEIIIdLO/w+nLPpkFrsLvQAAAABJRU5ErkJggg==\n", "text/plain": [""]}, "metadata": {"needs_background": "light"}, "output_type": "display_data"}], "source": ["fig, ax = plt.subplots(1, 1, figsize=(14,2))\n", "ax.plot(cor)\n", "ax.set_title(\"Autocorr\u00e9logramme\");"]}, {"cell_type": "markdown", "metadata": {}, "source": ["La premi\u00e8re saisonalit\u00e9 appara\u00eet, 7, 14, 21... Les autocorr\u00e9lations partielles confirment cela, plut\u00f4t 7 jours."]}, {"cell_type": "code", "execution_count": 8, "metadata": {}, "outputs": [{"data": {"image/png": 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\n", "text/plain": [""]}, "metadata": {"needs_background": "light"}, "output_type": "display_data"}], "source": ["from statsmodels.tsa.stattools import pacf\n", "from statsmodels.graphics.tsaplots import plot_pacf\n", "plot_pacf(df.value, lags=50);"]}, {"cell_type": "markdown", "metadata": {}, "source": ["Comme il n'y a rien le dimanche, il vaut mieux les enlever. Garder des z\u00e9ros nous priverait de mod\u00e8les multiplicatifs."]}, {"cell_type": "code", "execution_count": 9, "metadata": {}, "outputs": [{"data": {"text/html": ["\n", "\n", "
\n", " \n", " \n", " \n", " date \n", " value \n", " notrend \n", " trend \n", " weekday \n", " \n", " \n", " \n", " \n", " 0 \n", " 2020-02-13 18:54:23.461489 \n", " 0.005357 \n", " -0.000507 \n", " 0.005864 \n", " 3 \n", " \n", " \n", " 1 \n", " 2020-02-14 18:54:23.461489 \n", " 0.009562 \n", " 0.003694 \n", " 0.005868 \n", " 4 \n", " \n", " \n", " 2 \n", " 2020-02-15 18:54:23.461489 \n", " 0.014353 \n", " 0.008481 \n", " 0.005873 \n", " 5 \n", " \n", " \n", " 3 \n", " 2020-02-16 18:54:23.461489 \n", " 0.000000 \n", " -0.005877 \n", " 0.005877 \n", " 6 \n", " \n", " \n", " 4 \n", " 2020-02-17 18:54:23.461489 \n", " 0.003475 \n", " -0.002407 \n", " 0.005882 \n", " 0 \n", " \n", " \n", "
\n", "
"], "text/plain": [" date value notrend trend weekday\n", "0 2020-02-13 18:54:23.461489 0.005357 -0.000507 0.005864 3\n", "1 2020-02-14 18:54:23.461489 0.009562 0.003694 0.005868 4\n", "2 2020-02-15 18:54:23.461489 0.014353 0.008481 0.005873 5\n", "3 2020-02-16 18:54:23.461489 0.000000 -0.005877 0.005877 6\n", "4 2020-02-17 18:54:23.461489 0.003475 -0.002407 0.005882 0"]}, "execution_count": 10, "metadata": {}, "output_type": "execute_result"}], "source": ["df[\"weekday\"] = df.date.dt.weekday\n", "df.head()"]}, {"cell_type": "code", "execution_count": 10, "metadata": {}, "outputs": [{"data": {"text/html": ["\n", "\n", "
\n", " \n", " \n", " \n", " date \n", " value \n", " notrend \n", " trend \n", " weekday \n", " \n", " \n", " \n", " \n", " 0 \n", " 2020-02-13 18:54:23.461489 \n", " 0.005357 \n", " -0.000507 \n", " 0.005864 \n", " 3 \n", " \n", " \n", " 1 \n", " 2020-02-14 18:54:23.461489 \n", " 0.009562 \n", " 0.003694 \n", " 0.005868 \n", " 4 \n", " \n", " \n", " 2 \n", " 2020-02-15 18:54:23.461489 \n", " 0.014353 \n", " 0.008481 \n", " 0.005873 \n", " 5 \n", " \n", " \n", " 4 \n", " 2020-02-17 18:54:23.461489 \n", " 0.003475 \n", " -0.002407 \n", " 0.005882 \n", " 0 \n", " \n", " \n", " 5 \n", " 2020-02-18 18:54:23.461489 \n", " 0.005454 \n", " -0.000432 \n", " 0.005886 \n", " 1 \n", " \n", " \n", " 6 \n", " 2020-02-19 18:54:23.461489 \n", " 0.005075 \n", " -0.000816 \n", " 0.005891 \n", " 2 \n", " \n", " \n", " 7 \n", " 2020-02-20 18:54:23.461489 \n", " 0.006801 \n", " 0.000906 \n", " 0.005896 \n", " 3 \n", " \n", " \n", " 8 \n", " 2020-02-21 18:54:23.461489 \n", " 0.009831 \n", " 0.003931 \n", " 0.005900 \n", " 4 \n", " \n", " \n", " 9 \n", " 2020-02-22 18:54:23.461489 \n", " 0.014204 \n", " 0.008299 \n", " 0.005905 \n", " 5 \n", " \n", " \n", " 11 \n", " 2020-02-24 18:54:23.461489 \n", " 0.003875 \n", " -0.002039 \n", " 0.005914 \n", " 0 \n", " \n", " \n", "
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"], "text/plain": [" date value notrend trend weekday\n", "0 2020-02-13 18:54:23.461489 0.005357 -0.000507 0.005864 3\n", "1 2020-02-14 18:54:23.461489 0.009562 0.003694 0.005868 4\n", "2 2020-02-15 18:54:23.461489 0.014353 0.008481 0.005873 5\n", "4 2020-02-17 18:54:23.461489 0.003475 -0.002407 0.005882 0\n", "5 2020-02-18 18:54:23.461489 0.005454 -0.000432 0.005886 1\n", "6 2020-02-19 18:54:23.461489 0.005075 -0.000816 0.005891 2\n", "7 2020-02-20 18:54:23.461489 0.006801 0.000906 0.005896 3\n", "8 2020-02-21 18:54:23.461489 0.009831 0.003931 0.005900 4\n", "9 2020-02-22 18:54:23.461489 0.014204 0.008299 0.005905 5\n", "11 2020-02-24 18:54:23.461489 0.003875 -0.002039 0.005914 0"]}, "execution_count": 11, "metadata": {}, "output_type": "execute_result"}], "source": ["df_nosunday = df[df.weekday != 6]\n", "df_nosunday.head(n=10)"]}, {"cell_type": "code", "execution_count": 11, "metadata": {}, "outputs": [{"name": "stderr", "output_type": "stream", "text": ["C:\\Python395_x64\\lib\\site-packages\\statsmodels\\tsa\\stattools.py:657: FutureWarning: The default number of lags is changing from 40 tomin(int(10 * np.log10(nobs)), nobs - 1) after 0.12is released. Set the number of lags to an integer to silence this warning.\n", " warnings.warn(\n", "C:\\Python395_x64\\lib\\site-packages\\statsmodels\\tsa\\stattools.py:667: FutureWarning: fft=True will become the default after the release of the 0.12 release of statsmodels. To suppress this warning, explicitly set fft=False.\n", " warnings.warn(\n"]}, {"data": {"image/png": 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\n", "text/plain": [""]}, "metadata": {"needs_background": "light"}, "output_type": "display_data"}], "source": ["fig, ax = plt.subplots(1, 1, figsize=(14,2))\n", "cor = acf(df_nosunday.value)\n", "ax.plot(cor)\n", "ax.set_title(\"Autocorr\u00e9logramme\");"]}, {"cell_type": "code", "execution_count": 12, "metadata": {}, "outputs": [{"data": {"image/png": 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\n", "text/plain": [""]}, "metadata": {"needs_background": "light"}, "output_type": "display_data"}], "source": ["plot_pacf(df_nosunday.value, lags=50);"]}, {"cell_type": "markdown", "metadata": {}, "source": ["On d\u00e9compose la s\u00e9rie en tendance + saisonnalit\u00e9. Les \u00e9t\u00e9s et No\u00ebl apparaissent."]}, {"cell_type": "code", "execution_count": 13, "metadata": {}, "outputs": [{"name": "stderr", "output_type": "stream", "text": [":2: FutureWarning: the 'freq'' keyword is deprecated, use 'period' instead.\n", " res = seasonal_decompose(df_nosunday.value, freq=7)\n"]}, {"data": {"image/png": 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\n", "text/plain": [""]}, "metadata": {"needs_background": "light"}, "output_type": "display_data"}], "source": ["from statsmodels.tsa.seasonal import seasonal_decompose\n", "res = seasonal_decompose(df_nosunday.value, freq=7)\n", "res.plot();"]}, {"cell_type": "code", "execution_count": 14, "metadata": {}, "outputs": [{"data": {"image/png": 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\n", "text/plain": [""]}, "metadata": {"needs_background": "light"}, "output_type": "display_data"}], "source": ["plt.plot(res.seasonal[-30:])\n", "plt.title(\"Saisonnalit\u00e9\");"]}, {"cell_type": "code", "execution_count": 15, "metadata": {}, "outputs": [{"name": "stderr", "output_type": "stream", "text": ["C:\\Python395_x64\\lib\\site-packages\\statsmodels\\tsa\\stattools.py:657: FutureWarning: The default number of lags is changing from 40 tomin(int(10 * np.log10(nobs)), nobs - 1) after 0.12is released. Set the number of lags to an integer to silence this warning.\n", " warnings.warn(\n", "C:\\Python395_x64\\lib\\site-packages\\statsmodels\\tsa\\stattools.py:667: FutureWarning: fft=True will become the default after the release of the 0.12 release of statsmodels. To suppress this warning, explicitly set fft=False.\n", " warnings.warn(\n"]}, {"data": {"image/png": 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\n", "text/plain": [""]}, "metadata": {"needs_background": "light"}, "output_type": "display_data"}], "source": ["cor = acf(res.trend[5:-5]);\n", "plt.plot(cor);"]}, {"cell_type": "markdown", "metadata": {}, "source": ["On cherche maintenant la saisonnalit\u00e9 de la s\u00e9rie d\u00e9barrass\u00e9e de sa tendance herbdomadaire. On retrouve la saisonnalit\u00e9 mensuelle."]}, {"cell_type": "code", "execution_count": 16, "metadata": {}, "outputs": [{"name": "stderr", "output_type": "stream", "text": [":1: FutureWarning: the 'freq'' keyword is deprecated, use 'period' instead.\n", " res_year = seasonal_decompose(res.trend[5:-5], freq=25)\n"]}, {"data": {"image/png": 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\n", "text/plain": [""]}, "metadata": {"needs_background": "light"}, "output_type": "display_data"}], "source": ["res_year = seasonal_decompose(res.trend[5:-5], freq=25)\n", "res_year.plot();"]}, {"cell_type": "markdown", "metadata": {}, "source": ["## Test de stationnarit\u00e9\n", "\n", "Le test [KPSS](https://en.wikipedia.org/wiki/KPSS_test) permet de tester la stationnarit\u00e9 d'une s\u00e9rie."]}, {"cell_type": "code", "execution_count": 17, "metadata": {}, "outputs": [{"name": "stderr", "output_type": "stream", "text": ["C:\\Python395_x64\\lib\\site-packages\\statsmodels\\tsa\\stattools.py:1875: FutureWarning: The behavior of using nlags=None will change in release 0.13.Currently nlags=None is the same as nlags=\"legacy\", and so a sample-size lag length is used. After the next release, the default will change to be the same as nlags=\"auto\" which uses an automatic lag length selection method. To silence this warning, either use \"auto\" or \"legacy\"\n", " warnings.warn(msg, FutureWarning)\n", "C:\\Python395_x64\\lib\\site-packages\\statsmodels\\tsa\\stattools.py:1906: InterpolationWarning: The test statistic is outside of the range of p-values available in the\n", "look-up table. The actual p-value is smaller than the p-value returned.\n", "\n", " warnings.warn(\n"]}, {"data": {"text/plain": ["(0.980161988153884,\n", " 0.01,\n", " 19,\n", " {'10%': 0.347, '5%': 0.463, '2.5%': 0.574, '1%': 0.739})"]}, "execution_count": 18, "metadata": {}, "output_type": "execute_result"}], "source": ["from statsmodels.tsa.stattools import kpss\n", "kpss(res.trend[5:-5])"]}, {"cell_type": "markdown", "metadata": {}, "source": ["Comme ce n'est pas toujours facile \u00e0 interpr\u00e9ter, on simule une variable al\u00e9atoire gaussienne donc sans tendance."]}, {"cell_type": "code", "execution_count": 18, "metadata": {}, "outputs": [{"data": {"text/plain": ["(0.4813396167770415,\n", " 0.04586945568084651,\n", " 22,\n", " {'10%': 0.347, '5%': 0.463, '2.5%': 0.574, '1%': 0.739})"]}, "execution_count": 19, "metadata": {}, "output_type": "execute_result"}], "source": ["from numpy.random import randn\n", "bruit = randn(1000)\n", "kpss(bruit)"]}, {"cell_type": "markdown", "metadata": {}, "source": ["Et puis une s\u00e9rie avec une tendance forte."]}, {"cell_type": "code", "execution_count": 19, "metadata": {}, "outputs": [{"name": "stderr", "output_type": "stream", "text": ["C:\\Python395_x64\\lib\\site-packages\\statsmodels\\tsa\\stattools.py:1906: InterpolationWarning: The test statistic is outside of the range of p-values available in the\n", "look-up table. The actual p-value is smaller than the p-value returned.\n", "\n", " warnings.warn(\n"]}, {"data": {"text/plain": ["(2.9761535894770517,\n", " 0.01,\n", " 22,\n", " {'10%': 0.347, '5%': 0.463, '2.5%': 0.574, '1%': 0.739})"]}, "execution_count": 20, "metadata": {}, "output_type": "execute_result"}], "source": ["from numpy.random import randn\n", "from numpy import arange\n", "bruit = randn(1000) * 100 + arange(1000) / 10\n", "kpss(bruit)"]}, {"cell_type": "markdown", "metadata": {}, "source": ["Une valeur forte indique une tendance et la s\u00e9rie en a clairement une."]}, {"cell_type": "markdown", "metadata": {}, "source": ["## Pr\u00e9diction\n", "\n", "Les mod\u00e8les *AR*, *ARMA*, *ARIMA* se concentrent sur une s\u00e9rie \u00e0 une dimension. En machine learning, il y a la s\u00e9rie et plein d'autres informations. On construit une matrice avec des s\u00e9ries d\u00e9cal\u00e9es."]}, {"cell_type": "code", "execution_count": 20, "metadata": {}, "outputs": [{"data": {"text/html": ["\n", "\n", "
\n", " \n", " \n", " \n", " date \n", " value \n", " notrend \n", " trend \n", " weekday \n", " lag1 \n", " lag2 \n", " lag3 \n", " lag4 \n", " lag5 \n", " lag6 \n", " lag7 \n", " lag8 \n", " \n", " \n", " \n", " \n", " 726 \n", " 2022-02-08 18:54:23.461489 \n", " 0.008707 \n", " -0.000466 \n", " 0.009173 \n", " 1 \n", " 0.005806 \n", " 0.020552 \n", " 0.013143 \n", " 0.009727 \n", " 0.007346 \n", " 0.008504 \n", " 0.004580 \n", " 0.013786 \n", " \n", " \n", " 727 \n", " 2022-02-09 18:54:23.461489 \n", " 0.008582 \n", " -0.000596 \n", " 0.009178 \n", " 2 \n", " 0.008707 \n", " 0.005806 \n", " 0.020552 \n", " 0.013143 \n", " 0.009727 \n", " 0.007346 \n", " 0.008504 \n", " 0.004580 \n", " \n", " \n", " 728 \n", " 2022-02-10 18:54:23.461489 \n", " 0.009646 \n", " 0.000464 \n", " 0.009182 \n", " 3 \n", " 0.008582 \n", " 0.008707 \n", " 0.005806 \n", " 0.020552 \n", " 0.013143 \n", " 0.009727 \n", " 0.007346 \n", " 0.008504 \n", " \n", " \n", " 729 \n", " 2022-02-11 18:54:23.461489 \n", " 0.014557 \n", " 0.005370 \n", " 0.009187 \n", " 4 \n", " 0.009646 \n", " 0.008582 \n", " 0.008707 \n", " 0.005806 \n", " 0.020552 \n", " 0.013143 \n", " 0.009727 \n", " 0.007346 \n", " \n", " \n", " 730 \n", " 2022-02-12 18:54:23.461489 \n", " 0.019851 \n", " 0.010660 \n", " 0.009191 \n", " 5 \n", " 0.014557 \n", " 0.009646 \n", " 0.008582 \n", " 0.008707 \n", " 0.005806 \n", " 0.020552 \n", " 0.013143 \n", " 0.009727 \n", " \n", " \n", "
\n", "
"], "text/plain": [" date value notrend trend weekday \\\n", "726 2022-02-08 18:54:23.461489 0.008707 -0.000466 0.009173 1 \n", "727 2022-02-09 18:54:23.461489 0.008582 -0.000596 0.009178 2 \n", "728 2022-02-10 18:54:23.461489 0.009646 0.000464 0.009182 3 \n", "729 2022-02-11 18:54:23.461489 0.014557 0.005370 0.009187 4 \n", "730 2022-02-12 18:54:23.461489 0.019851 0.010660 0.009191 5 \n", "\n", " lag1 lag2 lag3 lag4 lag5 lag6 lag7 \\\n", "726 0.005806 0.020552 0.013143 0.009727 0.007346 0.008504 0.004580 \n", "727 0.008707 0.005806 0.020552 0.013143 0.009727 0.007346 0.008504 \n", "728 0.008582 0.008707 0.005806 0.020552 0.013143 0.009727 0.007346 \n", "729 0.009646 0.008582 0.008707 0.005806 0.020552 0.013143 0.009727 \n", "730 0.014557 0.009646 0.008582 0.008707 0.005806 0.020552 0.013143 \n", "\n", " lag8 \n", "726 0.013786 \n", "727 0.004580 \n", "728 0.008504 \n", "729 0.007346 \n", "730 0.009727 "]}, "execution_count": 21, "metadata": {}, "output_type": "execute_result"}], "source": ["from statsmodels.tsa.tsatools import lagmat\n", "lag = 8\n", "X = lagmat(df_nosunday[\"value\"], lag)\n", "lagged = df_nosunday.copy()\n", "for c in range(1,lag+1):\n", " lagged[\"lag%d\" % c] = X[:, c-1]\n", "lagged.tail()"]}, {"cell_type": "markdown", "metadata": {}, "source": ["On ajoute ou on r\u00e9\u00e9crit le jour de la semaine qu'on utilise comme variable suppl\u00e9mentaire."]}, {"cell_type": "code", "execution_count": 21, "metadata": {}, "outputs": [], "source": ["lagged[\"weekday\"] = lagged.date.dt.weekday"]}, {"cell_type": "code", "execution_count": 22, "metadata": {}, "outputs": [{"data": {"text/plain": ["((627, 9), (627,))"]}, "execution_count": 23, "metadata": {}, "output_type": "execute_result"}], "source": ["X = lagged.drop([\"date\", \"value\", \"notrend\", \"trend\"], axis=1)\n", "Y = lagged[\"value\"]\n", "X.shape, Y.shape"]}, {"cell_type": "code", "execution_count": 23, "metadata": {}, "outputs": [{"data": {"text/plain": ["array([[1. , 0.99999912, 0.99999792, ..., 0.99999049, 0.99999476,\n", " 0.99999663],\n", " [0.99999912, 1. , 0.99999936, ..., 0.99998874, 0.99999358,\n", " 0.99999672],\n", " [0.99999792, 0.99999936, 1. , ..., 0.99998653, 0.99999169,\n", " 0.99999553],\n", " ...,\n", " [0.99999049, 0.99998874, 0.99998653, ..., 1. , 0.9999852 ,\n", " 0.99998403],\n", " [0.99999476, 0.99999358, 0.99999169, ..., 0.9999852 , 1. ,\n", " 0.99999084],\n", " [0.99999663, 0.99999672, 0.99999553, ..., 0.99998403, 0.99999084,\n", " 1. ]])"]}, "execution_count": 24, "metadata": {}, "output_type": "execute_result"}], "source": ["from numpy import corrcoef\n", "corrcoef(X)"]}, {"cell_type": "markdown", "metadata": {}, "source": ["Etrange autant de grandes valeurs, cela veut dire que la tendance est trop forte pour calculer des corr\u00e9lations, il vaudrait mieux tout recommencer avec la s\u00e9rie $\\Delta Y_t = Y_t - Y_{t-1}$. Bref, passons..."]}, {"cell_type": "code", "execution_count": 24, "metadata": {}, "outputs": [{"data": {"text/plain": ["Index(['weekday', 'lag1', 'lag2', 'lag3', 'lag4', 'lag5', 'lag6', 'lag7',\n", " 'lag8'],\n", " dtype='object')"]}, "execution_count": 25, "metadata": {}, "output_type": "execute_result"}], "source": ["X.columns"]}, {"cell_type": "markdown", "metadata": {}, "source": ["Une r\u00e9gression lin\u00e9aire car les mod\u00e8les lin\u00e9aires sont toujours de bonnes baseline et pour conna\u00eetre le mod\u00e8le simul\u00e9, on ne fera pas beaucoup mieux."]}, {"cell_type": "code", "execution_count": 25, "metadata": {}, "outputs": [{"data": {"text/plain": ["LinearRegression()"]}, "execution_count": 26, "metadata": {}, "output_type": "execute_result"}], "source": ["from sklearn.linear_model import LinearRegression\n", "clr = LinearRegression()\n", "clr.fit(X, Y)"]}, {"cell_type": "code", "execution_count": 26, "metadata": {}, "outputs": [{"data": {"text/plain": ["0.8789132280236231"]}, "execution_count": 27, "metadata": {}, "output_type": "execute_result"}], "source": ["from sklearn.metrics import r2_score\n", "r2_score(Y, clr.predict(X))"]}, {"cell_type": "code", "execution_count": 27, "metadata": {}, "outputs": [{"data": {"text/plain": ["array([ 0.0016414 , 0.34593324, 0.26436686, 0.08632379, 0.01356802,\n", " -0.03755237, 0.40831821, -0.12106444, -0.07772163])"]}, "execution_count": 28, "metadata": {}, "output_type": "execute_result"}], "source": ["clr.coef_"]}, {"cell_type": "markdown", "metadata": {}, "source": ["On retrouve la saisonnalit\u00e9, $Y_t$ et $Y_{t-6}$ sont de m\u00e8ches."]}, {"cell_type": "code", "execution_count": 28, "metadata": {}, "outputs": [{"name": "stdout", "output_type": "stream", "text": ["X(t-1) -0.48934404097448847\n", "X(t-2) -1.0143639444424148\n", "X(t-3) -1.228186547024929\n", "X(t-4) -1.0378510803717922\n", "X(t-5) -0.5496246593771723\n", "X(t-6) 0.7876799792178883\n", "X(t-7) -0.5843479675288277\n", "X(t-8) -1.1145521360143462\n"]}], "source": ["for i in range(1, X.shape[1]):\n", " print(\"X(t-%d)\" % (i), r2_score(Y, X.iloc[:, i]))"]}, {"cell_type": "markdown", "metadata": {}, "source": ["Auparavant (l'ann\u00e9e derni\u00e8re en fait), je construisais deux bases, apprentissage et tests, comme ceci :"]}, {"cell_type": "code", "execution_count": 29, "metadata": {}, "outputs": [], "source": ["n = X.shape[0]\n", "X_train = X.iloc[:n * 2//3]\n", "X_test = X.iloc[n * 2//3:]\n", "Y_train = Y[:n * 2//3]\n", "Y_test = Y[n * 2//3:]"]}, {"cell_type": "markdown", "metadata": {}, "source": ["Et puis *scikit-learn* est arriv\u00e9e avec [TimeSeriesSplit](https://scikit-learn.org/stable/modules/generated/sklearn.model_selection.TimeSeriesSplit.html)."]}, {"cell_type": "code", "execution_count": 30, "metadata": {}, "outputs": [{"name": "stdout", "output_type": "stream", "text": ["TRAIN: (107, 13) TEST: (104, 13)\n", "TRAIN: (211, 13) TEST: (104, 13)\n", "TRAIN: (315, 13) TEST: (104, 13)\n", "TRAIN: (419, 13) TEST: (104, 13)\n", "TRAIN: (523, 13) TEST: (104, 13)\n"]}], "source": ["from sklearn.model_selection import TimeSeriesSplit\n", "tscv = TimeSeriesSplit(n_splits=5)\n", "for train_index, test_index in tscv.split(lagged):\n", " data_train, data_test = lagged.iloc[train_index, :], lagged.iloc[test_index, :]\n", " print(\"TRAIN:\", data_train.shape, \"TEST:\", data_test.shape)"]}, {"cell_type": "markdown", "metadata": {}, "source": ["Et on cal\u00e9 une for\u00eat al\u00e9atoire..."]}, {"cell_type": "code", "execution_count": 31, "metadata": {}, "outputs": [{"name": "stdout", "output_type": "stream", "text": ["0.8074141052461008\n", "0.740621811076557 0.6980805419883442\n", "0.9382338424157237 0.938776218559058\n", "0.8763703927657517 0.7726502689480175\n", "0.6429356690810921 0.6615420727005181\n"]}], "source": ["import warnings\n", "from sklearn.ensemble import RandomForestRegressor\n", "clr = RandomForestRegressor()\n", "\n", "def train_test(clr, train_index, test_index):\n", " data_train = lagged.iloc[train_index, :]\n", " data_test = lagged.iloc[test_index, :]\n", " clr.fit(data_train.drop([\"value\", \"date\", \"notrend\", \"trend\"], \n", " axis=1), \n", " data_train.value)\n", " r2 = r2_score(data_test.value,\n", " clr.predict(data_test.drop([\"value\", \"date\", \"notrend\",\n", " \"trend\"], axis=1).values))\n", " return r2\n", "\n", "warnings.simplefilter(\"ignore\")\n", "last_test_index = None\n", "for train_index, test_index in tscv.split(lagged):\n", " r2 = train_test(clr, train_index, test_index) \n", " if last_test_index is not None:\n", " r2_prime = train_test(clr, last_test_index, test_index) \n", " print(r2, r2_prime)\n", " else:\n", " print(r2)\n", " last_test_index = test_index"]}, {"cell_type": "markdown", "metadata": {}, "source": ["2 ans coup\u00e9 en 5, soit tous les 5 mois, \u00e7a veut dire que ce d\u00e9coupage inclut parfois No\u00ebl, parfois l'\u00e9t\u00e9 et que les performances y seront tr\u00e8s sensibles."]}, {"cell_type": "code", "execution_count": 32, "metadata": {}, "outputs": [{"data": {"text/plain": ["0.6615420727005181"]}, "execution_count": 33, "metadata": {}, "output_type": "execute_result"}], "source": ["from sklearn.metrics import r2_score\n", "r2 = r2_score(data_test.value,\n", " clr.predict(data_test.drop([\"value\", \"date\", \"notrend\",\n", " \"trend\"], axis=1).values))\n", "r2"]}, {"cell_type": "markdown", "metadata": {}, "source": ["On compare avec le $r_2$ avec le m\u00eame $r_2$ obtenu en utilisant $Y_{t-1}$, $Y_{t-2}$, ... $Y_{t-d}$ comme pr\u00e9diction."]}, {"cell_type": "code", "execution_count": 33, "metadata": {}, "outputs": [{"name": "stdout", "output_type": "stream", "text": ["1 : -0.5322711277436745\n", "2 : -1.0330346880701402\n", "3 : -1.2289501631550408\n", "4 : -1.0866973927813812\n", "5 : -0.6533003518045957\n", "6 : 0.683558097073121\n", "7 : -0.6863597347439538\n", "8 : -1.2181386641893033\n"]}], "source": ["for i in range(1, 9):\n", " print(i, \":\", r2_score(data_test.value, data_test[\"lag%d\" % i]))"]}, {"cell_type": "code", "execution_count": 34, "metadata": {}, "outputs": [{"data": {"text/html": ["\n", "\n", "
\n", " \n", " \n", " \n", " date \n", " value \n", " notrend \n", " trend \n", " weekday \n", " lag1 \n", " lag2 \n", " lag3 \n", " lag4 \n", " lag5 \n", " lag6 \n", " lag7 \n", " lag8 \n", " \n", " \n", " \n", " \n", " 0 \n", " 2020-02-13 18:54:23.461489 \n", " 0.005357 \n", " -0.000507 \n", " 0.005864 \n", " 3 \n", " 0.000000 \n", " 0.000000 \n", " 0.000000 \n", " 0.000000 \n", " 0.0 \n", " 0.0 \n", " 0.0 \n", " 0.0 \n", " \n", " \n", " 1 \n", " 2020-02-14 18:54:23.461489 \n", " 0.009562 \n", " 0.003694 \n", " 0.005868 \n", " 4 \n", " 0.005357 \n", " 0.000000 \n", " 0.000000 \n", " 0.000000 \n", " 0.0 \n", " 0.0 \n", " 0.0 \n", " 0.0 \n", " \n", " \n", " 2 \n", " 2020-02-15 18:54:23.461489 \n", " 0.014353 \n", " 0.008481 \n", " 0.005873 \n", " 5 \n", " 0.009562 \n", " 0.005357 \n", " 0.000000 \n", " 0.000000 \n", " 0.0 \n", " 0.0 \n", " 0.0 \n", " 0.0 \n", " \n", " \n", " 4 \n", " 2020-02-17 18:54:23.461489 \n", " 0.003475 \n", " -0.002407 \n", " 0.005882 \n", " 0 \n", " 0.014353 \n", " 0.009562 \n", " 0.005357 \n", " 0.000000 \n", " 0.0 \n", " 0.0 \n", " 0.0 \n", " 0.0 \n", " \n", " \n", " 5 \n", " 2020-02-18 18:54:23.461489 \n", " 0.005454 \n", " -0.000432 \n", " 0.005886 \n", " 1 \n", " 0.003475 \n", " 0.014353 \n", " 0.009562 \n", " 0.005357 \n", " 0.0 \n", " 0.0 \n", " 0.0 \n", " 0.0 \n", " \n", " \n", "
\n", "
"], "text/plain": [" date value notrend trend weekday lag1 \\\n", "0 2020-02-13 18:54:23.461489 0.005357 -0.000507 0.005864 3 0.000000 \n", "1 2020-02-14 18:54:23.461489 0.009562 0.003694 0.005868 4 0.005357 \n", "2 2020-02-15 18:54:23.461489 0.014353 0.008481 0.005873 5 0.009562 \n", "4 2020-02-17 18:54:23.461489 0.003475 -0.002407 0.005882 0 0.014353 \n", "5 2020-02-18 18:54:23.461489 0.005454 -0.000432 0.005886 1 0.003475 \n", "\n", " lag2 lag3 lag4 lag5 lag6 lag7 lag8 \n", "0 0.000000 0.000000 0.000000 0.0 0.0 0.0 0.0 \n", "1 0.000000 0.000000 0.000000 0.0 0.0 0.0 0.0 \n", "2 0.005357 0.000000 0.000000 0.0 0.0 0.0 0.0 \n", "4 0.009562 0.005357 0.000000 0.0 0.0 0.0 0.0 \n", "5 0.014353 0.009562 0.005357 0.0 0.0 0.0 0.0 "]}, "execution_count": 35, "metadata": {}, "output_type": "execute_result"}], "source": ["lagged[:5]"]}, {"cell_type": "markdown", "metadata": {}, "source": ["En fait le jour de la semaine est une variable cat\u00e9gorielle, on cr\u00e9e une colonne par jour."]}, {"cell_type": "code", "execution_count": 35, "metadata": {}, "outputs": [], "source": ["from sklearn.compose import ColumnTransformer\n", "from sklearn.preprocessing import OneHotEncoder"]}, {"cell_type": "code", "execution_count": 36, "metadata": {}, "outputs": [{"data": {"text/plain": ["array([[0. , 0. , 0. , 0. , 0. ,\n", " 0. , 0. , 0. , 0. , 0. ,\n", " 0. , 1. , 0. , 0. ],\n", " [0.0053571 , 0. , 0. , 0. , 0. ,\n", " 0. , 0. , 0. , 0. , 0. ,\n", " 0. , 0. , 1. , 0. ],\n", " [0.00956219, 0.0053571 , 0. , 0. , 0. ,\n", " 0. , 0. , 0. , 0. , 0. ,\n", " 0. , 0. , 0. , 1. ],\n", " [0.01435337, 0.00956219, 0.0053571 , 0. , 0. ,\n", " 0. , 0. , 0. , 1. , 0. ,\n", " 0. , 0. , 0. , 0. ],\n", " [0.00347454, 0.01435337, 0.00956219, 0.0053571 , 0. ,\n", " 0. , 0. , 0. , 0. , 1. ,\n", " 0. , 0. , 0. , 0. ]])"]}, "execution_count": 37, "metadata": {}, "output_type": "execute_result"}], "source": ["cols = ['lag1', 'lag2', 'lag3',\n", " 'lag4', 'lag5', 'lag6', 'lag7', 'lag8']\n", "ct = ColumnTransformer(\n", " [('pass', \"passthrough\", cols),\n", " (\"dummies\", OneHotEncoder(), [\"weekday\"])])\n", "pred = ct.fit(lagged).transform(lagged[:5])\n", "pred"]}, {"cell_type": "markdown", "metadata": {}, "source": ["On met tout dans un pipeline parce que c'est plus joli, plus pratique aussi."]}, {"cell_type": "code", "execution_count": 37, "metadata": {"scrolled": false}, "outputs": [{"data": {"text/plain": ["Pipeline(steps=[('pipeline',\n", " Pipeline(steps=[('columntransformer',\n", " ColumnTransformer(transformers=[('pass',\n", " 'passthrough',\n", " ['lag1',\n", " 'lag2',\n", " 'lag3',\n", " 'lag4',\n", " 'lag5',\n", " 'lag6',\n", " 'lag7',\n", " 'lag8']),\n", " ('dummies',\n", " Pipeline(steps=[('onehotencoder',\n", " OneHotEncoder()),\n", " ('truncatedsvd',\n", " TruncatedSVD())]),\n", " ['weekday'])])),\n", " ('linearregression', LinearRegression())]))])"]}, "execution_count": 38, "metadata": {}, "output_type": "execute_result"}], "source": ["from sklearn.pipeline import make_pipeline\n", "from sklearn.decomposition import PCA, TruncatedSVD \n", "cols = ['lag1', 'lag2', 'lag3',\n", " 'lag4', 'lag5', 'lag6', 'lag7', 'lag8']\n", "model = make_pipeline(\n", " make_pipeline(\n", " ColumnTransformer(\n", " [('pass', \"passthrough\", cols),\n", " (\"dummies\", make_pipeline(OneHotEncoder(), \n", " TruncatedSVD(n_components=2)), [\"weekday\"])]),\n", " LinearRegression()))\n", "model.fit(lagged, lagged[\"value\"])"]}, {"cell_type": "markdown", "metadata": {}, "source": ["C'est plus facile \u00e0 voir visuellement."]}, {"cell_type": "code", "execution_count": 38, "metadata": {}, "outputs": [{"data": {"text/html": ["\n", ""], "text/plain": [""]}, "execution_count": 39, "metadata": {}, "output_type": "execute_result"}], "source": ["from mlinsights.plotting import pipeline2dot\n", "dot = pipeline2dot(model, lagged)\n", "from jyquickhelper import RenderJsDot\n", "RenderJsDot(dot)"]}, {"cell_type": "code", "execution_count": 39, "metadata": {}, "outputs": [{"data": {"text/plain": ["0.8800492232136333"]}, "execution_count": 40, "metadata": {}, "output_type": "execute_result"}], "source": ["r2_score(lagged['value'], model.predict(lagged))"]}, {"cell_type": "markdown", "metadata": {}, "source": ["## Templating\n", "\n", "Compl\u00e8tement hors sujet mais utile."]}, {"cell_type": "code", "execution_count": 40, "metadata": {}, "outputs": [{"data": {"text/plain": ["'Hello John Doe!'"]}, "execution_count": 41, "metadata": {}, "output_type": "execute_result"}], "source": ["from jinja2 import Template\n", "template = Template('Hello {{ name }}!')\n", "template.render(name='John Doe')"]}, {"cell_type": "code", "execution_count": 41, "metadata": {}, "outputs": [{"name": "stdout", "output_type": "stream", "text": ["\n", "John Doe Doe\n", "------------\n", "Poss\u00e8de :\n", "\n", "- table\n", "- tabouret\n"]}], "source": ["template = Template(\"\"\"\n", "{{ name }}\n", "{{ \"-\" * len(name) }}\n", "Poss\u00e8de :\n", "{% for i in range(len(meubles)) %}\n", "- {{meubles[i]}}{% endfor %}\n", "\"\"\")\n", "meubles = ['table', \"tabouret\"]\n", "print(template.render(name='John Doe Doe', len=len,\n", " meubles=meubles))"]}, {"cell_type": "code", "execution_count": 42, "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": "3.9.5"}}, "nbformat": 4, "nbformat_minor": 2}