{ "cells": [ { "cell_type": "markdown", "metadata": {}, "source": [ "# Analyse de la concentration de CO2 dans l'atmosphère depuis 1958" ] }, { "cell_type": "code", "execution_count": 1, "metadata": {}, "outputs": [], "source": [ " %matplotlib inline\n", "import matplotlib.pyplot as plt\n", "import pandas as pd\n", "import requests\n", "import os" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "## Préparation des données" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ " Les données de concentration du CO2 sont disponibles du site [Scripps CO2 Program](https://scrippsco2.ucsd.edu/data/atmospheric_co2/primary_mlo_co2_record.html). Nous téléchargeons les données le 07 mai 2022 à 09:32. " ] }, { "cell_type": "code", "execution_count": 2, "metadata": {}, "outputs": [ { "name": "stdout", "output_type": "stream", "text": [ "[b'\"-------------------------------------------------------------------------------------------\"\\n', b'\" Atmospheric CO2 concentrations (ppm) derived from in situ air measurements \"\\n', b'\" at Mauna Loa, Observatory, Hawaii: Latitude 19.5\\xc3\\x82\\xc2\\xb0N Longitude 155.6\\xc3\\x82\\xc2\\xb0W Elevation 3397m \"\\n', b'\" \"\\n', b'\" Source: R. F. Keeling, S. J. Walker, S. C. Piper and A. F. Bollenbacher \"\\n', b'\" Scripps CO2 Program ( http://scrippsco2.ucsd.edu ) \"\\n', b'\" Scripps Institution of Oceanography (SIO) \"\\n', b'\" University of California \"\\n', b'\" La Jolla, California USA 92093-0244 \"\\n', b'\" \"\\n', b'\" Status of data and correspondence: \"\\n', b'\" \"\\n', b'\" These data are subject to revision based on recalibration of standard gases. Questions \"\\n', b'\" about the data should be directed to Dr. Ralph Keeling (rkeeling@ucsd.edu), Stephen Walker\"\\n', b'\" (sjwalker@ucsd.edu) and Stephen Piper (scpiper@ucsd.edu), Scripps CO2 Program. \"\\n', b'\" \"\\n', b'\" Baseline data in this file through 03-May-2022 from archive dated 04-May-2022 09:22:14 \"\\n', b'\" \"\\n', b'\"-------------------------------------------------------------------------------------------\"\\n', b'\" \"\\n', b'\" Please cite as: \"\\n', b'\" \"\\n', b'\" C. D. Keeling, S. C. Piper, R. B. Bacastow, M. Wahlen, T. P. Whorf, M. Heimann, and \"\\n', b'\" H. A. Meijer, Exchanges of atmospheric CO2 and 13CO2 with the terrestrial biosphere and \"\\n', b'\" oceans from 1978 to 2000. I. Global aspects, SIO Reference Series, No. 01-06, Scripps \"\\n', b'\" Institution of Oceanography, San Diego, 88 pages, 2001. \"\\n', b'\" \"\\n', b'\" If it is necessary to cite a peer-reviewed article, please cite as: \"\\n', b'\" \"\\n', b'\" C. D. Keeling, S. C. Piper, R. B. Bacastow, M. Wahlen, T. P. Whorf, M. Heimann, and \"\\n', b'\" H. A. Meijer, Atmospheric CO2 and 13CO2 exchange with the terrestrial biosphere and \"\\n', b'\" oceans from 1978 to 2000: observations and carbon cycle implications, pages 83-113, \"\\n', b'\" in \"A History of Atmospheric CO2 and its effects on Plants, Animals, and Ecosystems\", \"\\n', b'\" editors, Ehleringer, J.R., T. E. Cerling, M. D. Dearing, Springer Verlag, \"\\n', b'\" New York, 2005. \"\\n', b'\" \"\\n', b'\"-------------------------------------------------------------------------------------------\"\\n', b'\" \"\\n', b'\" The data file below contains 10 columns. Columns 1-4 give the dates in several redundant \"\\n', b'\" formats. Column 5 below gives monthly Mauna Loa CO2 concentrations in micro-mol CO2 per \"\\n', b'\" mole (ppm), reported on the 2012 SIO manometric mole fraction scale. This is the \"\\n', b'\" standard version of the data most often sought. The monthly values have been adjusted \"\\n', b'\" to 24:00 hours on the 15th of each month. Column 6 gives the same data after a seasonal \"\\n', b'\" adjustment to remove the quasi-regular seasonal cycle. The adjustment involves \"\\n', b'\" subtracting from the data a 4-harmonic fit with a linear gain factor. Column 7 is a \"\\n', b'\" smoothed version of the data generated from a stiff cubic spline function plus 4-harmonic \"\\n', b'\" functions with linear gain. Column 8 is the same smoothed version with the seasonal \"\\n', b'\" cycle removed. Column 9 is identical to Column 5 except that the missing values from \"\\n', b'\" Column 5 have been filled with values from Column 7. Column 10 is identical to Column 6 \"\\n', b'\" except missing values have been filled with values from Column 8. Missing values are \"\\n', b'\" denoted by -99.99 \"\\n', b'\" \"\\n', b'\" CO2 concentrations are measured on the \\'12\\' calibration scale \"\\n', b'\" \"\\n', b' Yr, Mn, Date, Date, CO2,seasonally, fit, seasonally, CO2, seasonally\\n', b' , , , , , adjusted, ,adjusted fit, filled,adjusted filled\\n', b' , , Excel, , [ppm], [ppm] , [ppm], [ppm], [ppm], [ppm]\\n', b'1958, 01, 21200, 1958.0411, -99.99, -99.99, -99.99, -99.99, -99.99, -99.99\\n', b'1958, 02, 21231, 1958.1260, -99.99, -99.99, -99.99, -99.99, -99.99, -99.99\\n', b'1958, 03, 21259, 1958.2027, 315.71, 314.44, 316.19, 314.91, 315.71, 314.44\\n', b'1958, 04, 21290, 1958.2877, 317.45, 315.16, 317.29, 314.99, 317.45, 315.16\\n', b'1958, 05, 21320, 1958.3699, 317.51, 314.70, 317.87, 315.06, 317.51, 314.70\\n', b'1958, 06, 21351, 1958.4548, -99.99, -99.99, 317.25, 315.14, 317.25, 315.14\\n', b'1958, 07, 21381, 1958.5370, 315.86, 315.20, 315.85, 315.22, 315.86, 315.20\\n', b'1958, 08, 21412, 1958.6219, 314.93, 316.21, 313.97, 315.29, 314.93, 316.21\\n', b'1958, 09, 21443, 1958.7068, 313.21, 316.10, 312.44, 315.35, 313.21, 316.10\\n', b'1958, 10, 21473, 1958.7890, -99.99, -99.99, 312.43, 315.40, 312.43, 315.40\\n', b'1958, 11, 21504, 1958.8740, 313.33, 315.20, 313.60, 315.46, 313.33, 315.20\\n', b'1958, 12, 21534, 1958.9562, 314.67, 315.43, 314.76, 315.51, 314.67, 315.43\\n', b'1959, 01, 21565, 1959.0411, 315.58, 315.52, 315.64, 315.57, 315.58, 315.52\\n', b'1959, 02, 21596, 1959.1260, 316.49, 315.84, 316.28, 315.63, 316.49, 315.84\\n', b'1959, 03, 21624, 1959.2027, 316.65, 315.37, 316.98, 315.69, 316.65, 315.37\\n', b'1959, 04, 21655, 1959.2877, 317.72, 315.42, 318.08, 315.76, 317.72, 315.42\\n', b'1959, 05, 21685, 1959.3699, 318.29, 315.48, 318.66, 315.84, 318.29, 315.48\\n', b'1959, 06, 21716, 1959.4548, 318.15, 316.02, 318.05, 315.93, 318.15, 316.02\\n', b'1959, 07, 21746, 1959.5370, 316.54, 315.87, 316.66, 316.02, 316.54, 315.87\\n', b'1959, 08, 21777, 1959.6219, 314.80, 316.08, 314.80, 316.12, 314.80, 316.08\\n', b'1959, 09, 21808, 1959.7068, 313.84, 316.74, 313.30, 316.21, 313.84, 316.74\\n', b'1959, 10, 21838, 1959.7890, 313.33, 316.33, 313.32, 316.30, 313.33, 316.33\\n', b'1959, 11, 21869, 1959.8740, 314.81, 316.69, 314.53, 316.39, 314.81, 316.69\\n', b'1959, 12, 21899, 1959.9562, 315.58, 316.35, 315.72, 316.47, 315.58, 316.35\\n', b'1960, 01, 21930, 1960.0410, 316.43, 316.37, 316.62, 316.55, 316.43, 316.37\\n', b'1960, 02, 21961, 1960.1257, 316.98, 316.33, 317.29, 316.63, 316.98, 316.33\\n', b'1960, 03, 21990, 1960.2049, 317.58, 316.27, 318.03, 316.71, 317.58, 316.27\\n', b'1960, 04, 22021, 1960.2896, 319.03, 316.70, 319.14, 316.79, 319.03, 316.70\\n', b'1960, 05, 22051, 1960.3716, 320.03, 317.21, 319.68, 316.86, 320.03, 317.21\\n', b'1960, 06, 22082, 1960.4563, 319.58, 317.46, 319.02, 316.92, 319.58, 317.46\\n', b'1960, 07, 22112, 1960.5383, 318.18, 317.53, 317.59, 316.97, 318.18, 317.53\\n', b'1960, 08, 22143, 1960.6230, 315.90, 317.22, 315.67, 317.01, 315.90, 317.22\\n', b'1960, 09, 22174, 1960.7077, 314.17, 317.09, 314.11, 317.04, 314.17, 317.09\\n', b'1960, 10, 22204, 1960.7896, 313.83, 316.84, 314.08, 317.07, 313.83, 316.84\\n', b'1960, 11, 22235, 1960.8743, 315.00, 316.88, 315.24, 317.11, 315.00, 316.88\\n', b'1960, 12, 22265, 1960.9563, 316.19, 316.96, 316.39, 317.15, 316.19, 316.96\\n', b'1961, 01, 22296, 1961.0411, 316.89, 316.84, 317.27, 317.20, 316.89, 316.84\\n', b'1961, 02, 22327, 1961.1260, 317.70, 317.05, 317.92, 317.26, 317.70, 317.05\\n', b'1961, 03, 22355, 1961.2027, 318.54, 317.25, 318.63, 317.33, 318.54, 317.25\\n', b'1961, 04, 22386, 1961.2877, 319.48, 317.16, 319.74, 317.41, 319.48, 317.16\\n', b'1961, 05, 22416, 1961.3699, 320.58, 317.75, 320.33, 317.50, 320.58, 317.75\\n', b'1961, 06, 22447, 1961.4548, 319.77, 317.62, 319.72, 317.59, 319.77, 317.62\\n', b'1961, 07, 22477, 1961.5370, 318.56, 317.89, 318.32, 317.67, 318.56, 317.89\\n', b'1961, 08, 22508, 1961.6219, 316.79, 318.08, 316.44, 317.76, 316.79, 318.08\\n', b'1961, 09, 22539, 1961.7068, 314.99, 317.91, 314.91, 317.84, 314.99, 317.91\\n', b'1961, 10, 22569, 1961.7890, 315.31, 318.33, 314.91, 317.92, 315.31, 318.33\\n', b'1961, 11, 22600, 1961.8740, 316.10, 318.00, 316.12, 317.99, 316.10, 318.00\\n', b'1961, 12, 22630, 1961.9562, 317.01, 317.78, 317.30, 318.05, 317.01, 317.78\\n', b'1962, 01, 22661, 1962.0411, 317.94, 317.88, 318.19, 318.12, 317.94, 317.88\\n', b'1962, 02, 22692, 1962.1260, 318.55, 317.89, 318.85, 318.19, 318.55, 317.89\\n', b'1962, 03, 22720, 1962.2027, 319.68, 318.39, 319.55, 318.25, 319.68, 318.39\\n', b'1962, 04, 22751, 1962.2877, 320.57, 318.25, 320.66, 318.32, 320.57, 318.25\\n', b'1962, 05, 22781, 1962.3699, 321.02, 318.17, 321.23, 318.38, 321.02, 318.17\\n', b'1962, 06, 22812, 1962.4548, 320.62, 318.46, 320.58, 318.44, 320.62, 318.46\\n', b'1962, 07, 22842, 1962.5370, 319.61, 318.94, 319.15, 318.50, 319.61, 318.94\\n', b'1962, 08, 22873, 1962.6219, 317.40, 318.70, 317.22, 318.55, 317.40, 318.70\\n', b'1962, 09, 22904, 1962.7068, 316.24, 319.18, 315.65, 318.60, 316.24, 319.18\\n', b'1962, 10, 22934, 1962.7890, 315.42, 318.45, 315.62, 318.64, 315.42, 318.45\\n', b'1962, 11, 22965, 1962.8740, 316.69, 318.59, 316.80, 318.68, 316.69, 318.59\\n', b'1962, 12, 22995, 1962.9562, 317.70, 318.48, 317.95, 318.71, 317.70, 318.48\\n', b'1963, 01, 23026, 1963.0411, 318.74, 318.68, 318.83, 318.76, 318.74, 318.68\\n', b'1963, 02, 23057, 1963.1260, 319.07, 318.41, 319.47, 318.81, 319.07, 318.41\\n', b'1963, 03, 23085, 1963.2027, 319.86, 318.57, 320.16, 318.85, 319.86, 318.57\\n', b'1963, 04, 23116, 1963.2877, 321.38, 319.05, 321.25, 318.91, 321.38, 319.05\\n', b'1963, 05, 23146, 1963.3699, 322.25, 319.39, 321.81, 318.96, 322.25, 319.39\\n', b'1963, 06, 23177, 1963.4548, 321.48, 319.32, 321.15, 319.01, 321.48, 319.32\\n', b'1963, 07, 23207, 1963.5370, 319.74, 319.06, 319.70, 319.05, 319.74, 319.06\\n', b'1963, 08, 23238, 1963.6219, 317.77, 319.07, 317.76, 319.10, 317.77, 319.07\\n', b'1963, 09, 23269, 1963.7068, 316.21, 319.15, 316.18, 319.14, 316.21, 319.15\\n', b'1963, 10, 23299, 1963.7890, 315.99, 319.02, 316.15, 319.18, 315.99, 319.02\\n', b'1963, 11, 23330, 1963.8740, 317.07, 318.97, 317.34, 319.23, 317.07, 318.97\\n', b'1963, 12, 23360, 1963.9562, 318.35, 319.13, 318.51, 319.27, 318.35, 319.13\\n', b'1964, 01, 23391, 1964.0410, 319.57, 319.51, 319.39, 319.32, 319.57, 319.51\\n', b'1964, 02, 23422, 1964.1257, -99.99, -99.99, 320.03, 319.36, 320.03, 319.36\\n', b'1964, 03, 23451, 1964.2049, -99.99, -99.99, 320.74, 319.41, 320.74, 319.41\\n', b'1964, 04, 23482, 1964.2896, -99.99, -99.99, 321.83, 319.45, 321.83, 319.45\\n', b'1964, 05, 23512, 1964.3716, 322.25, 319.39, 322.35, 319.49, 322.25, 319.39\\n', b'1964, 06, 23543, 1964.4563, 321.89, 319.75, 321.65, 319.52, 321.89, 319.75\\n', b'1964, 07, 23573, 1964.5383, 320.44, 319.79, 320.18, 319.55, 320.44, 319.79\\n', b'1964, 08, 23604, 1964.6230, 318.69, 320.02, 318.22, 319.58, 318.69, 320.02\\n', b'1964, 09, 23635, 1964.7077, 316.71, 319.67, 316.62, 319.60, 316.71, 319.67\\n', b'1964, 10, 23665, 1964.7896, 316.87, 319.92, 316.58, 319.62, 316.87, 319.92\\n', b'1964, 11, 23696, 1964.8743, 317.68, 319.59, 317.75, 319.63, 317.68, 319.59\\n', b'1964, 12, 23726, 1964.9563, 318.71, 319.49, 318.89, 319.65, 318.71, 319.49\\n', b'1965, 01, 23757, 1965.0411, 319.44, 319.38, 319.75, 319.68, 319.44, 319.38\\n', b'1965, 02, 23788, 1965.1260, 320.44, 319.79, 320.39, 319.72, 320.44, 319.79\\n', b'1965, 03, 23816, 1965.2027, 320.89, 319.59, 321.08, 319.76, 320.89, 319.59\\n', b'1965, 04, 23847, 1965.2877, 322.14, 319.79, 322.19, 319.83, 322.14, 319.79\\n', b'1965, 05, 23877, 1965.3699, 322.17, 319.29, 322.78, 319.90, 322.17, 319.29\\n', b'1965, 06, 23908, 1965.4548, 321.87, 319.69, 322.16, 320.00, 321.87, 319.69\\n', b'1965, 07, 23938, 1965.5370, 321.21, 320.52, 320.75, 320.10, 321.21, 320.52\\n', b'1965, 08, 23969, 1965.6219, 318.87, 320.18, 318.86, 320.21, 318.87, 320.18\\n', b'1965, 09, 24000, 1965.7068, 317.82, 320.78, 317.34, 320.32, 317.82, 320.78\\n', b'1965, 10, 24030, 1965.7890, 317.30, 320.36, 317.38, 320.43, 317.30, 320.36\\n', b'1965, 11, 24061, 1965.8740, 318.87, 320.79, 318.65, 320.55, 318.87, 320.79\\n', b'1965, 12, 24091, 1965.9562, 319.42, 320.20, 319.89, 320.66, 319.42, 320.20\\n', b'1966, 01, 24122, 1966.0411, 320.62, 320.57, 320.85, 320.78, 320.62, 320.57\\n', b'1966, 02, 24153, 1966.1260, 321.60, 320.94, 321.57, 320.90, 321.60, 320.94\\n', b'1966, 03, 24181, 1966.2027, 322.39, 321.08, 322.33, 321.01, 322.39, 321.08\\n', b'1966, 04, 24212, 1966.2877, 323.70, 321.34, 323.49, 321.12, 323.70, 321.34\\n', b'1966, 05, 24242, 1966.3699, 324.08, 321.20, 324.10, 321.22, 324.08, 321.20\\n', b'1966, 06, 24273, 1966.4548, 323.75, 321.57, 323.48, 321.32, 323.75, 321.57\\n', b'1966, 07, 24303, 1966.5370, 322.38, 321.69, 322.06, 321.40, 322.38, 321.69\\n', b'1966, 08, 24334, 1966.6219, 320.36, 321.68, 320.13, 321.48, 320.36, 321.68\\n', b'1966, 09, 24365, 1966.7068, 318.64, 321.61, 318.56, 321.55, 318.64, 321.61\\n', b'1966, 10, 24395, 1966.7890, 318.10, 321.17, 318.56, 321.62, 318.10, 321.17\\n', b'1966, 11, 24426, 1966.8740, 319.78, 321.71, 319.77, 321.68, 319.78, 321.71\\n', b'1966, 12, 24456, 1966.9562, 321.02, 321.81, 320.97, 321.74, 321.02, 321.81\\n', b'1967, 01, 24487, 1967.0411, 322.33, 322.27, 321.87, 321.80, 322.33, 322.27\\n', b'1967, 02, 24518, 1967.1260, 322.50, 321.83, 322.53, 321.85, 322.50, 321.83\\n', b'1967, 03, 24546, 1967.2027, 323.03, 321.72, 323.23, 321.90, 323.03, 321.72\\n', b'1967, 04, 24577, 1967.2877, 324.41, 322.05, 324.34, 321.96, 324.41, 322.05\\n', b'1967, 05, 24607, 1967.3699, 325.00, 322.11, 324.90, 322.01, 325.00, 322.11\\n', b'1967, 06, 24638, 1967.4548, 324.09, 321.90, 324.24, 322.07, 324.09, 321.90\\n', b'1967, 07, 24668, 1967.5370, 322.54, 321.86, 322.79, 322.13, 322.54, 321.86\\n', b'1967, 08, 24699, 1967.6219, 320.92, 322.24, 320.85, 322.20, 320.92, 322.24\\n', b'1967, 09, 24730, 1967.7068, 319.25, 322.23, 319.27, 322.27, 319.25, 322.23\\n', b'1967, 10, 24760, 1967.7890, 319.39, 322.47, 319.28, 322.34, 319.39, 322.47\\n', b'1967, 11, 24791, 1967.8740, 320.73, 322.66, 320.51, 322.42, 320.73, 322.66\\n', b'1967, 12, 24821, 1967.9562, 321.95, 322.75, 321.72, 322.49, 321.95, 322.75\\n', b'1968, 01, 24852, 1968.0410, 322.57, 322.51, 322.64, 322.57, 322.57, 322.51\\n', b'1968, 02, 24883, 1968.1257, 323.15, 322.48, 323.32, 322.65, 323.15, 322.48\\n', b'1968, 03, 24912, 1968.2049, 323.89, 322.55, 324.08, 322.73, 323.89, 322.55\\n', b'1968, 04, 24943, 1968.2896, 325.02, 322.63, 325.23, 322.82, 325.02, 322.63\\n', b'1968, 05, 24973, 1968.3716, 325.57, 322.67, 325.82, 322.92, 325.57, 322.67\\n', b'1968, 06, 25004, 1968.4563, 325.36, 323.18, 325.19, 323.03, 325.36, 323.18\\n', b'1968, 07, 25034, 1968.5383, 324.14, 323.48, 323.77, 323.14, 324.14, 323.48\\n', b'1968, 08, 25065, 1968.6230, 322.11, 323.46, 321.87, 323.25, 322.11, 323.46\\n', b'1968, 09, 25096, 1968.7077, 320.33, 323.33, 320.35, 323.37, 320.33, 323.33\\n', b'1968, 10, 25126, 1968.7896, 320.25, 323.33, 320.41, 323.48, 320.25, 323.33\\n', b'1968, 11, 25157, 1968.8743, 321.32, 323.26, 321.70, 323.61, 321.32, 323.26\\n', b'1968, 12, 25187, 1968.9563, 322.89, 323.68, 322.97, 323.74, 322.89, 323.68\\n', b'1969, 01, 25218, 1969.0411, 324.00, 323.94, 323.95, 323.88, 324.00, 323.94\\n', b'1969, 02, 25249, 1969.1260, 324.41, 323.75, 324.70, 324.03, 324.41, 323.75\\n', b'1969, 03, 25277, 1969.2027, 325.63, 324.31, 325.49, 324.16, 325.63, 324.31\\n', b'1969, 04, 25308, 1969.2877, 326.66, 324.28, 326.69, 324.30, 326.66, 324.28\\n', b'1969, 05, 25338, 1969.3699, 327.38, 324.47, 327.35, 324.43, 327.38, 324.47\\n', b'1969, 06, 25369, 1969.4548, 326.71, 324.50, 326.75, 324.57, 326.71, 324.50\\n', b'1969, 07, 25399, 1969.5370, 325.88, 325.19, 325.35, 324.69, 325.88, 325.19\\n', b'1969, 08, 25430, 1969.6219, 323.66, 324.99, 323.44, 324.80, 323.66, 324.99\\n', b'1969, 09, 25461, 1969.7068, 322.38, 325.38, 321.88, 324.90, 322.38, 325.38\\n', b'1969, 10, 25491, 1969.7890, 321.78, 324.88, 321.90, 324.99, 321.78, 324.88\\n', b'1969, 11, 25522, 1969.8740, 322.85, 324.80, 323.15, 325.07, 322.85, 324.80\\n', b'1969, 12, 25552, 1969.9562, 324.11, 324.91, 324.38, 325.15, 324.11, 324.91\\n', b'1970, 01, 25583, 1970.0411, 325.06, 325.00, 325.31, 325.24, 325.06, 325.00\\n', b'1970, 02, 25614, 1970.1260, 325.99, 325.31, 326.00, 325.32, 325.99, 325.31\\n', b'1970, 03, 25642, 1970.2027, 326.93, 325.61, 326.73, 325.39, 326.93, 325.61\\n', b'1970, 04, 25673, 1970.2877, 328.13, 325.75, 327.88, 325.47, 328.13, 325.75\\n', b'1970, 05, 25703, 1970.3699, 328.08, 325.16, 328.47, 325.55, 328.08, 325.16\\n', b'1970, 06, 25734, 1970.4548, 327.67, 325.45, 327.82, 325.63, 327.67, 325.45\\n', b'1970, 07, 25764, 1970.5370, 326.34, 325.65, 326.36, 325.70, 326.34, 325.65\\n', b'1970, 08, 25795, 1970.6219, 324.68, 326.02, 324.40, 325.77, 324.68, 326.02\\n', b'1970, 09, 25826, 1970.7068, 323.10, 326.11, 322.80, 325.83, 323.10, 326.11\\n', b'1970, 10, 25856, 1970.7890, 323.07, 326.18, 322.78, 325.88, 323.07, 326.18\\n', b'1970, 11, 25887, 1970.8740, 324.01, 325.96, 324.00, 325.93, 324.01, 325.96\\n', b'1970, 12, 25917, 1970.9562, 325.13, 325.93, 325.18, 325.96, 325.13, 325.93\\n', b'1971, 01, 25948, 1971.0411, 326.17, 326.11, 326.07, 326.00, 326.17, 326.11\\n', b'1971, 02, 25979, 1971.1260, 326.68, 326.01, 326.72, 326.04, 326.68, 326.01\\n', b'1971, 03, 26007, 1971.2027, 327.18, 325.85, 327.42, 326.08, 327.18, 325.85\\n', b'1971, 04, 26038, 1971.2877, 327.79, 325.39, 328.54, 326.13, 327.79, 325.39\\n', b'1971, 05, 26068, 1971.3699, 328.93, 326.00, 329.12, 326.19, 328.93, 326.00\\n', b'1971, 06, 26099, 1971.4548, 328.57, 326.35, 328.46, 326.26, 328.57, 326.35\\n', b'1971, 07, 26129, 1971.5370, 327.36, 326.66, 326.99, 326.33, 327.36, 326.66\\n', b'1971, 08, 26160, 1971.6219, 325.43, 326.76, 325.03, 326.40, 325.43, 326.76\\n', b'1971, 09, 26191, 1971.7068, 323.36, 326.38, 323.43, 326.47, 323.36, 326.38\\n', b'1971, 10, 26221, 1971.7890, 323.56, 326.68, 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334.01, 335.99, 333.93, 335.93\\n', b'1978, 12, 28839, 1978.9562, 334.96, 335.77, 335.29, 336.09, 334.96, 335.77\\n', b'1979, 01, 28870, 1979.0411, 336.24, 336.18, 336.27, 336.20, 336.24, 336.18\\n', b'1979, 02, 28901, 1979.1260, 336.77, 336.08, 337.01, 336.31, 336.77, 336.08\\n', b'1979, 03, 28929, 1979.2027, 337.97, 336.61, 337.80, 336.42, 337.97, 336.61\\n', b'1979, 04, 28960, 1979.2877, 338.89, 336.43, 339.02, 336.55, 338.89, 336.43\\n', b'1979, 05, 28990, 1979.3699, 339.48, 336.48, 339.68, 336.67, 339.48, 336.48\\n', b'1979, 06, 29021, 1979.4548, 339.30, 337.02, 339.07, 336.81, 339.30, 337.02\\n', b'1979, 07, 29051, 1979.5370, 337.74, 337.03, 337.63, 336.94, 337.74, 337.03\\n', b'1979, 08, 29082, 1979.6219, 336.10, 337.47, 335.68, 337.09, 336.10, 337.47\\n', b'1979, 09, 29113, 1979.7068, 333.93, 337.03, 334.12, 337.23, 333.93, 337.03\\n', b'1979, 10, 29143, 1979.7890, 333.87, 337.07, 334.19, 337.38, 333.87, 337.07\\n', b'1979, 11, 29174, 1979.8740, 335.30, 337.31, 335.55, 337.53, 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1983.9562, 342.98, 343.81, 342.85, 343.67, 342.98, 343.81\\n', b'1984, 01, 30696, 1984.0410, 343.82, 343.76, 343.88, 343.81, 343.82, 343.76\\n', b'1984, 02, 30727, 1984.1257, 344.62, 343.92, 344.66, 343.95, 344.62, 343.92\\n', b'1984, 03, 30756, 1984.2049, 345.38, 343.98, 345.50, 344.08, 345.38, 343.98\\n', b'1984, 04, 30787, 1984.2896, 347.15, 344.63, 346.74, 344.21, 347.15, 344.63\\n', b'1984, 05, 30817, 1984.3716, 347.52, 344.47, 347.38, 344.33, 347.52, 344.47\\n', b'1984, 06, 30848, 1984.4563, 346.88, 344.59, 346.72, 344.45, 346.88, 344.59\\n', b'1984, 07, 30878, 1984.5383, 345.47, 344.77, 345.23, 344.56, 345.47, 344.77\\n', b'1984, 08, 30909, 1984.6230, 343.34, 344.76, 343.22, 344.68, 343.34, 344.76\\n', b'1984, 09, 30940, 1984.7077, 341.13, 344.29, 341.62, 344.79, 341.13, 344.29\\n', b'1984, 10, 30970, 1984.7896, 341.40, 344.64, 341.67, 344.91, 341.40, 344.64\\n', b'1984, 11, 31001, 1984.8743, 343.02, 345.05, 343.02, 345.03, 343.02, 345.05\\n', b'1984, 12, 31031, 1984.9563, 344.25, 345.08, 344.33, 345.15, 344.25, 345.08\\n', b'1985, 01, 31062, 1985.0411, 344.99, 344.93, 345.35, 345.27, 344.99, 344.93\\n', b'1985, 02, 31093, 1985.1260, 346.01, 345.31, 346.11, 345.40, 346.01, 345.31\\n', b'1985, 03, 31121, 1985.2027, 347.43, 346.04, 346.91, 345.51, 347.43, 346.04\\n', b'1985, 04, 31152, 1985.2877, 348.34, 345.84, 348.14, 345.62, 348.34, 345.84\\n', b'1985, 05, 31182, 1985.3699, 348.92, 345.86, 348.79, 345.72, 348.92, 345.86\\n', b'1985, 06, 31213, 1985.4548, 348.24, 345.92, 348.12, 345.82, 348.24, 345.92\\n', b'1985, 07, 31243, 1985.5370, 346.54, 345.81, 346.60, 345.91, 346.54, 345.81\\n', b'1985, 08, 31274, 1985.6219, 344.64, 346.04, 344.56, 346.00, 344.64, 346.04\\n', b'1985, 09, 31305, 1985.7068, 343.06, 346.21, 342.91, 346.08, 343.06, 346.21\\n', b'1985, 10, 31335, 1985.7890, 342.78, 346.04, 342.91, 346.16, 342.78, 346.04\\n', b'1985, 11, 31366, 1985.8740, 344.21, 346.26, 344.23, 346.25, 344.21, 346.26\\n', b'1985, 12, 31396, 1985.9562, 345.53, 346.37, 345.52, 346.34, 345.53, 346.37\\n', b'1986, 01, 31427, 1986.0411, 346.28, 346.21, 346.52, 346.44, 346.28, 346.21\\n', b'1986, 02, 31458, 1986.1260, 346.93, 346.23, 347.27, 346.55, 346.93, 346.23\\n', b'1986, 03, 31486, 1986.2027, 347.83, 346.44, 348.07, 346.66, 347.83, 346.44\\n', b'1986, 04, 31517, 1986.2877, 349.53, 347.02, 349.31, 346.79, 349.53, 347.02\\n', b'1986, 05, 31547, 1986.3699, 350.19, 347.12, 349.98, 346.91, 350.19, 347.12\\n', b'1986, 06, 31578, 1986.4548, 349.53, 347.20, 349.35, 347.04, 349.53, 347.20\\n', b'1986, 07, 31608, 1986.5370, 347.92, 347.19, 347.86, 347.17, 347.92, 347.19\\n', b'1986, 08, 31639, 1986.6219, 345.88, 347.28, 345.86, 347.30, 345.88, 347.28\\n', b'1986, 09, 31670, 1986.7068, 344.83, 348.00, 344.24, 347.42, 344.83, 348.00\\n', b'1986, 10, 31700, 1986.7890, 344.16, 347.43, 344.29, 347.55, 344.16, 347.43\\n', b'1986, 11, 31731, 1986.8740, 345.64, 347.69, 345.65, 347.68, 345.64, 347.69\\n', b'1986, 12, 31761, 1986.9562, 346.88, 347.72, 346.99, 347.81, 346.88, 347.72\\n', b'1987, 01, 31792, 1987.0411, 348.00, 347.94, 348.03, 347.96, 348.00, 347.94\\n', b'1987, 02, 31823, 1987.1260, 348.47, 347.76, 348.83, 348.11, 348.47, 347.76\\n', b'1987, 03, 31851, 1987.2027, 349.40, 348.01, 349.67, 348.26, 349.40, 348.01\\n', b'1987, 04, 31882, 1987.2877, 350.97, 348.45, 350.97, 348.43, 350.97, 348.45\\n', b'1987, 05, 31912, 1987.3699, 351.84, 348.75, 351.69, 348.61, 351.84, 348.75\\n', b'1987, 06, 31943, 1987.4548, 351.25, 348.91, 351.11, 348.79, 351.25, 348.91\\n', b'1987, 07, 31973, 1987.5370, 349.50, 348.76, 349.68, 348.98, 349.50, 348.76\\n', b'1987, 08, 32004, 1987.6219, 348.09, 349.49, 347.73, 349.17, 348.09, 349.49\\n', b'1987, 09, 32035, 1987.7068, 346.44, 349.61, 346.17, 349.37, 346.44, 349.61\\n', b'1987, 10, 32065, 1987.7890, 346.09, 349.38, 346.29, 349.56, 346.09, 349.38\\n', b'1987, 11, 32096, 1987.8740, 347.54, 349.60, 347.72, 349.76, 347.54, 349.60\\n', b'1987, 12, 32126, 1987.9562, 348.69, 349.54, 349.14, 349.96, 348.69, 349.54\\n', b'1988, 01, 32157, 1988.0410, 350.16, 350.10, 350.24, 350.17, 350.16, 350.10\\n', b'1988, 02, 32188, 1988.1257, 351.47, 350.76, 351.10, 350.38, 351.47, 350.76\\n', b'1988, 03, 32217, 1988.2049, 351.96, 350.53, 352.01, 350.57, 351.96, 350.53\\n', b'1988, 04, 32248, 1988.2896, 353.33, 350.78, 353.34, 350.77, 353.33, 350.78\\n', b'1988, 05, 32278, 1988.3716, 353.97, 350.88, 354.05, 350.96, 353.97, 350.88\\n', b'1988, 06, 32309, 1988.4563, 353.55, 351.23, 353.45, 351.15, 353.55, 351.23\\n', b'1988, 07, 32339, 1988.5383, 352.14, 351.43, 352.00, 351.32, 352.14, 351.43\\n', b'1988, 08, 32370, 1988.6230, 350.19, 351.63, 350.02, 351.49, 350.19, 351.63\\n', b'1988, 09, 32401, 1988.7077, 348.50, 351.69, 348.43, 351.65, 348.50, 351.69\\n', b'1988, 10, 32431, 1988.7896, 348.66, 351.95, 348.51, 351.79, 348.66, 351.95\\n', b'1988, 11, 32462, 1988.8743, 349.85, 351.91, 349.89, 351.92, 349.85, 351.91\\n', b'1988, 12, 32492, 1988.9563, 351.12, 351.96, 351.22, 352.05, 351.12, 351.96\\n', b'1989, 01, 32523, 1989.0411, 352.55, 352.49, 352.24, 352.16, 352.55, 352.49\\n', b'1989, 02, 32554, 1989.1260, 352.86, 352.15, 353.00, 352.28, 352.86, 352.15\\n', b'1989, 03, 32582, 1989.2027, 353.48, 352.07, 353.80, 352.38, 353.48, 352.07\\n', b'1989, 04, 32613, 1989.2877, 355.21, 352.68, 355.03, 352.48, 355.21, 352.68\\n', b'1989, 05, 32643, 1989.3699, 355.47, 352.37, 355.68, 352.58, 355.47, 352.37\\n', b'1989, 06, 32674, 1989.4548, 354.92, 352.57, 355.01, 352.68, 354.92, 352.57\\n', b'1989, 07, 32704, 1989.5370, 353.70, 352.96, 353.49, 352.78, 353.70, 352.96\\n', b'1989, 08, 32735, 1989.6219, 351.47, 352.88, 351.43, 352.88, 351.47, 352.88\\n', b'1989, 09, 32766, 1989.7068, 349.61, 352.80, 349.76, 352.98, 349.61, 352.80\\n', b'1989, 10, 32796, 1989.7890, 349.79, 353.09, 349.78, 353.07, 349.79, 353.09\\n', b'1989, 11, 32827, 1989.8740, 351.10, 353.17, 351.13, 353.17, 351.10, 353.17\\n', b'1989, 12, 32857, 1989.9562, 352.32, 353.17, 352.44, 353.27, 352.32, 353.17\\n', b'1990, 01, 32888, 1990.0411, 353.46, 353.40, 353.45, 353.38, 353.46, 353.40\\n', b'1990, 02, 32919, 1990.1260, 354.50, 353.79, 354.20, 353.48, 354.50, 353.79\\n', b'1990, 03, 32947, 1990.2027, 355.19, 353.78, 355.00, 353.57, 355.19, 353.78\\n', b'1990, 04, 32978, 1990.2877, 356.00, 353.46, 356.24, 353.68, 356.00, 353.46\\n', b'1990, 05, 33008, 1990.3699, 356.96, 353.85, 356.89, 353.78, 356.96, 353.85\\n', b'1990, 06, 33039, 1990.4548, 356.04, 353.68, 356.23, 353.90, 356.04, 353.68\\n', b'1990, 07, 33069, 1990.5370, 354.62, 353.88, 354.72, 354.02, 354.62, 353.88\\n', b'1990, 08, 33100, 1990.6219, 352.71, 354.13, 352.69, 354.15, 352.71, 354.13\\n', b'1990, 09, 33131, 1990.7068, 350.77, 353.98, 351.06, 354.29, 350.77, 353.98\\n', b'1990, 10, 33161, 1990.7890, 350.99, 354.30, 351.13, 354.43, 350.99, 354.30\\n', b'1990, 11, 33192, 1990.8740, 352.64, 354.71, 352.52, 354.58, 352.64, 354.71\\n', b'1990, 12, 33222, 1990.9562, 354.02, 354.87, 353.89, 354.73, 354.02, 354.87\\n', b'1991, 01, 33253, 1991.0411, 354.53, 354.46, 354.95, 354.87, 354.53, 354.46\\n', b'1991, 02, 33284, 1991.1260, 355.55, 354.84, 355.74, 355.01, 355.55, 354.84\\n', b'1991, 03, 33312, 1991.2027, 356.96, 355.54, 356.56, 355.13, 356.96, 355.54\\n', b'1991, 04, 33343, 1991.2877, 358.40, 355.85, 357.81, 355.25, 358.40, 355.85\\n', b'1991, 05, 33373, 1991.3699, 359.14, 356.02, 358.46, 355.34, 359.14, 356.02\\n', b'1991, 06, 33404, 1991.4548, 358.04, 355.68, 357.76, 355.42, 358.04, 355.68\\n', b'1991, 07, 33434, 1991.5370, 355.98, 355.23, 356.19, 355.48, 355.98, 355.23\\n', b'1991, 08, 33465, 1991.6219, 353.81, 355.24, 354.08, 355.54, 353.81, 355.24\\n', b'1991, 09, 33496, 1991.7068, 351.95, 355.17, 352.36, 355.60, 351.95, 355.17\\n', b'1991, 10, 33526, 1991.7890, 352.02, 355.34, 352.35, 355.66, 352.02, 355.34\\n', b'1991, 11, 33557, 1991.8740, 353.55, 355.63, 353.66, 355.72, 353.55, 355.63\\n', b'1991, 12, 33587, 1991.9562, 354.79, 355.64, 354.95, 355.79, 354.79, 355.64\\n', b'1992, 01, 33618, 1992.0410, 355.79, 355.72, 355.93, 355.86, 355.79, 355.72\\n', b'1992, 02, 33649, 1992.1257, 356.52, 355.81, 356.65, 355.93, 356.52, 355.81\\n', b'1992, 03, 33678, 1992.2049, 357.61, 356.17, 357.45, 355.99, 357.61, 356.17\\n', b'1992, 04, 33709, 1992.2896, 358.95, 356.37, 358.65, 356.06, 358.95, 356.37\\n', b'1992, 05, 33739, 1992.3716, 359.46, 356.33, 359.24, 356.11, 359.46, 356.33\\n', b'1992, 06, 33770, 1992.4563, 359.05, 356.70, 358.48, 356.15, 359.05, 356.70\\n', b'1992, 07, 33800, 1992.5383, 356.82, 356.11, 356.87, 356.19, 356.82, 356.11\\n', b'1992, 08, 33831, 1992.6230, 354.80, 356.25, 354.73, 356.22, 354.80, 356.25\\n', b'1992, 09, 33862, 1992.7077, 352.81, 356.04, 353.00, 356.25, 352.81, 356.04\\n', b'1992, 10, 33892, 1992.7896, 353.11, 356.44, 352.97, 356.28, 353.11, 356.44\\n', b'1992, 11, 33923, 1992.8743, 353.96, 356.05, 354.26, 356.32, 353.96, 356.05\\n', b'1992, 12, 33953, 1992.9563, 355.20, 356.05, 355.53, 356.36, 355.20, 356.05\\n', b'1993, 01, 33984, 1993.0411, 356.50, 356.44, 356.49, 356.42, 356.50, 356.44\\n', b'1993, 02, 34015, 1993.1260, 356.97, 356.25, 357.21, 356.48, 356.97, 356.25\\n', b'1993, 03, 34043, 1993.2027, 358.18, 356.75, 357.98, 356.54, 358.18, 356.75\\n', b'1993, 04, 34074, 1993.2877, 359.26, 356.69, 359.20, 356.62, 359.26, 356.69\\n', b'1993, 05, 34104, 1993.3699, 360.08, 356.94, 359.84, 356.70, 360.08, 356.94\\n', b'1993, 06, 34135, 1993.4548, 359.40, 357.02, 359.15, 356.79, 359.40, 357.02\\n', b'1993, 07, 34165, 1993.5370, 357.38, 356.63, 357.61, 356.89, 357.38, 356.63\\n', b'1993, 08, 34196, 1993.6219, 355.33, 356.76, 355.54, 357.01, 355.33, 356.76\\n', b'1993, 09, 34227, 1993.7068, 353.50, 356.74, 353.88, 357.13, 353.50, 356.74\\n', b'1993, 10, 34257, 1993.7890, 353.80, 357.14, 353.94, 357.27, 353.80, 357.14\\n', b'1993, 11, 34288, 1993.8740, 355.15, 357.24, 355.35, 357.42, 355.15, 357.24\\n', b'1993, 12, 34318, 1993.9562, 356.62, 357.47, 356.74, 357.58, 356.62, 357.47\\n', b'1994, 01, 34349, 1994.0411, 358.19, 358.12, 357.83, 357.75, 358.19, 358.12\\n', b'1994, 02, 34380, 1994.1260, 358.73, 358.01, 358.66, 357.92, 358.73, 358.01\\n', b'1994, 03, 34408, 1994.2027, 359.79, 358.36, 359.52, 358.08, 359.79, 358.36\\n', b'1994, 04, 34439, 1994.2877, 361.09, 358.51, 360.84, 358.25, 361.09, 358.51\\n', b'1994, 05, 34469, 1994.3699, 361.52, 358.37, 361.56, 358.41, 361.52, 358.37\\n', b'1994, 06, 34500, 1994.4548, 360.77, 358.39, 360.95, 358.58, 360.77, 358.39\\n', b'1994, 07, 34530, 1994.5370, 359.38, 358.63, 359.46, 358.75, 359.38, 358.63\\n', b'1994, 08, 34561, 1994.6219, 357.31, 358.74, 357.45, 358.92, 357.31, 358.74\\n', b'1994, 09, 34592, 1994.7068, 355.68, 358.92, 355.84, 359.10, 355.68, 358.92\\n', b'1994, 10, 34622, 1994.7890, 355.83, 359.19, 355.94, 359.28, 355.83, 359.19\\n', b'1994, 11, 34653, 1994.8740, 357.42, 359.52, 357.38, 359.46, 357.42, 359.52\\n', b'1994, 12, 34683, 1994.9562, 358.87, 359.73, 358.80, 359.64, 358.87, 359.73\\n', b'1995, 01, 34714, 1995.0411, 359.81, 359.74, 359.90, 359.83, 359.81, 359.74\\n', b'1995, 02, 34745, 1995.1260, 360.84, 360.12, 360.74, 360.01, 360.84, 360.12\\n', b'1995, 03, 34773, 1995.2027, 361.48, 360.05, 361.62, 360.17, 361.48, 360.05\\n', b'1995, 04, 34804, 1995.2877, 363.30, 360.72, 362.94, 360.35, 363.30, 360.72\\n', b'1995, 05, 34834, 1995.3699, 363.64, 360.49, 363.67, 360.51, 363.64, 360.49\\n', b'1995, 06, 34865, 1995.4548, 363.11, 360.72, 363.05, 360.68, 363.11, 360.72\\n', b'1995, 07, 34895, 1995.5370, 361.75, 361.00, 361.56, 360.84, 361.75, 361.00\\n', b'1995, 08, 34926, 1995.6219, 359.31, 360.75, 359.52, 361.00, 359.31, 360.75\\n', b'1995, 09, 34957, 1995.7068, 357.91, 361.17, 357.89, 361.16, 357.91, 361.17\\n', b'1995, 10, 34987, 1995.7890, 357.62, 360.98, 357.97, 361.32, 357.62, 360.98\\n', b'1995, 11, 35018, 1995.8740, 359.42, 361.53, 359.40, 361.48, 359.42, 361.53\\n', b'1995, 12, 35048, 1995.9562, 360.56, 361.42, 360.79, 361.64, 360.56, 361.42\\n', b'1996, 01, 35079, 1996.0410, 361.91, 361.85, 361.87, 361.79, 361.91, 361.85\\n', b'1996, 02, 35110, 1996.1257, 363.11, 362.38, 362.67, 361.94, 363.11, 362.38\\n', b'1996, 03, 35139, 1996.2049, 363.88, 362.42, 363.55, 362.07, 363.88, 362.42\\n', b'1996, 04, 35170, 1996.2896, 364.58, 361.97, 364.83, 362.20, 364.58, 361.97\\n', b'1996, 05, 35200, 1996.3716, 365.29, 362.12, 365.48, 362.31, 365.29, 362.12\\n', b'1996, 06, 35231, 1996.4563, 364.84, 362.46, 364.78, 362.42, 364.84, 362.46\\n', b'1996, 07, 35261, 1996.5383, 363.52, 362.80, 363.21, 362.52, 363.52, 362.80\\n', b'1996, 08, 35292, 1996.6230, 361.35, 362.82, 361.11, 362.61, 361.35, 362.82\\n', b'1996, 09, 35323, 1996.7077, 359.32, 362.59, 359.41, 362.70, 359.32, 362.59\\n', b'1996, 10, 35353, 1996.7896, 359.48, 362.85, 359.43, 362.78, 359.48, 362.85\\n', b'1996, 11, 35384, 1996.8743, 360.64, 362.75, 360.77, 362.86, 360.64, 362.75\\n', b'1996, 12, 35414, 1996.9563, 362.21, 363.07, 362.09, 362.94, 362.21, 363.07\\n', b'1997, 01, 35445, 1997.0411, 363.07, 363.00, 363.10, 363.02, 363.07, 363.00\\n', b'1997, 02, 35476, 1997.1260, 363.87, 363.14, 363.85, 363.11, 363.87, 363.14\\n', b'1997, 03, 35504, 1997.2027, 364.44, 363.00, 364.65, 363.20, 364.44, 363.00\\n', b'1997, 04, 35535, 1997.2877, 366.23, 363.64, 365.92, 363.30, 366.23, 363.64\\n', b'1997, 05, 35565, 1997.3699, 366.68, 363.50, 366.60, 363.42, 366.68, 363.50\\n', b'1997, 06, 35596, 1997.4548, 365.52, 363.11, 365.94, 363.56, 365.52, 363.11\\n', b'1997, 07, 35626, 1997.5370, 364.36, 363.60, 364.43, 363.71, 364.36, 363.60\\n', b'1997, 08, 35657, 1997.6219, 362.39, 363.84, 362.40, 363.88, 362.39, 363.84\\n', b'1997, 09, 35688, 1997.7068, 360.08, 363.35, 360.79, 364.08, 360.08, 363.35\\n', b'1997, 10, 35718, 1997.7890, 360.67, 364.05, 360.93, 364.30, 360.67, 364.05\\n', b'1997, 11, 35749, 1997.8740, 362.32, 364.44, 362.45, 364.54, 362.32, 364.44\\n', b'1997, 12, 35779, 1997.9562, 364.16, 365.03, 363.95, 364.80, 364.16, 365.03\\n', b'1998, 01, 35810, 1998.0411, 365.22, 365.15, 365.14, 365.07, 365.22, 365.15\\n', b'1998, 02, 35841, 1998.1260, 366.04, 365.31, 366.08, 365.34, 366.04, 365.31\\n', b'1998, 03, 35869, 1998.2027, 367.20, 365.76, 367.05, 365.59, 367.20, 365.76\\n', b'1998, 04, 35900, 1998.2877, 368.50, 365.90, 368.49, 365.87, 368.50, 365.90\\n', b'1998, 05, 35930, 1998.3699, 369.19, 366.00, 369.32, 366.13, 369.19, 366.00\\n', b'1998, 06, 35961, 1998.4548, 368.77, 366.35, 368.79, 366.39, 368.77, 366.35\\n', b'1998, 07, 35991, 1998.5370, 367.53, 366.77, 367.36, 366.64, 367.53, 366.77\\n', b'1998, 08, 36022, 1998.6219, 365.67, 367.13, 365.38, 366.87, 365.67, 367.13\\n', b'1998, 09, 36053, 1998.7068, 363.80, 367.09, 363.79, 367.09, 363.80, 367.09\\n', b'1998, 10, 36083, 1998.7890, 364.13, 367.53, 363.90, 367.28, 364.13, 367.53\\n', b'1998, 11, 36114, 1998.8740, 365.36, 367.49, 365.35, 367.46, 365.36, 367.49\\n', b'1998, 12, 36144, 1998.9562, 366.87, 367.74, 366.76, 367.61, 366.87, 367.74\\n', b'1999, 01, 36175, 1999.0411, 368.05, 367.99, 367.82, 367.74, 368.05, 367.99\\n', b'1999, 02, 36206, 1999.1260, 368.77, 368.04, 368.60, 367.86, 368.77, 368.04\\n', b'1999, 03, 36234, 1999.2027, 369.49, 368.04, 369.41, 367.94, 369.49, 368.04\\n', b'1999, 04, 36265, 1999.2877, 371.04, 368.43, 370.66, 368.03, 371.04, 368.43\\n', b'1999, 05, 36295, 1999.3699, 370.90, 367.71, 371.29, 368.10, 370.90, 367.71\\n', b'1999, 06, 36326, 1999.4548, 370.25, 367.83, 370.57, 368.17, 370.25, 367.83\\n', b'1999, 07, 36356, 1999.5370, 369.17, 368.41, 368.96, 368.23, 369.17, 368.41\\n', b'1999, 08, 36387, 1999.6219, 366.83, 368.29, 366.81, 368.30, 366.83, 368.29\\n', b'1999, 09, 36418, 1999.7068, 364.54, 367.84, 365.07, 368.38, 364.54, 367.84\\n', b'1999, 10, 36448, 1999.7890, 365.04, 368.44, 365.07, 368.46, 365.04, 368.44\\n', b'1999, 11, 36479, 1999.8740, 366.58, 368.71, 366.43, 368.54, 366.58, 368.71\\n', b'1999, 12, 36509, 1999.9562, 367.92, 368.79, 367.78, 368.63, 367.92, 368.79\\n', b'2000, 01, 36540, 2000.0410, 369.05, 368.99, 368.80, 368.72, 369.05, 368.99\\n', b'2000, 02, 36571, 2000.1257, 369.37, 368.64, 369.56, 368.82, 369.37, 368.64\\n', b'2000, 03, 36600, 2000.2049, 370.42, 368.94, 370.41, 368.91, 370.42, 368.94\\n', b'2000, 04, 36631, 2000.2896, 371.57, 368.92, 371.69, 369.02, 371.57, 368.92\\n', b'2000, 05, 36661, 2000.3716, 371.74, 368.53, 372.34, 369.14, 371.74, 368.53\\n', b'2000, 06, 36692, 2000.4563, 371.60, 369.20, 371.66, 369.27, 371.60, 369.20\\n', b'2000, 07, 36722, 2000.5383, 370.02, 369.29, 370.10, 369.41, 370.02, 369.29\\n', b'2000, 08, 36753, 2000.6230, 368.03, 369.52, 368.02, 369.55, 368.03, 369.52\\n', b'2000, 09, 36784, 2000.7077, 366.53, 369.85, 366.37, 369.70, 366.53, 369.85\\n', b'2000, 10, 36814, 2000.7896, 366.64, 370.05, 366.44, 369.84, 366.64, 370.05\\n', b'2000, 11, 36845, 2000.8743, 368.20, 370.34, 367.87, 369.98, 368.20, 370.34\\n', b'2000, 12, 36875, 2000.9563, 369.44, 370.31, 369.25, 370.11, 369.44, 370.31\\n', b'2001, 01, 36906, 2001.0411, 370.20, 370.13, 370.31, 370.24, 370.20, 370.13\\n', b'2001, 02, 36937, 2001.1260, 371.42, 370.68, 371.11, 370.36, 371.42, 370.68\\n', b'2001, 03, 36965, 2001.2027, 372.04, 370.58, 371.94, 370.47, 372.04, 370.58\\n', b'2001, 04, 36996, 2001.2877, 372.78, 370.15, 373.23, 370.59, 372.78, 370.15\\n', b'2001, 05, 37026, 2001.3699, 373.94, 370.72, 373.92, 370.71, 373.94, 370.72\\n', b'2001, 06, 37057, 2001.4548, 373.23, 370.79, 373.25, 370.84, 373.23, 370.79\\n', b'2001, 07, 37087, 2001.5370, 371.54, 370.77, 371.70, 370.97, 371.54, 370.77\\n', b'2001, 08, 37118, 2001.6219, 369.47, 370.94, 369.61, 371.12, 369.47, 370.94\\n', b'2001, 09, 37149, 2001.7068, 367.88, 371.19, 367.94, 371.27, 367.88, 371.19\\n', b'2001, 10, 37179, 2001.7890, 368.01, 371.44, 368.01, 371.42, 368.01, 371.44\\n', b'2001, 11, 37210, 2001.8740, 369.60, 371.75, 369.46, 371.59, 369.60, 371.75\\n', b'2001, 12, 37240, 2001.9562, 371.15, 372.03, 370.89, 371.75, 371.15, 372.03\\n', b'2002, 01, 37271, 2002.0411, 372.36, 372.29, 372.00, 371.92, 372.36, 372.29\\n', b'2002, 02, 37302, 2002.1260, 373.00, 372.26, 372.84, 372.09, 373.00, 372.26\\n', b'2002, 03, 37330, 2002.2027, 373.44, 371.98, 373.73, 372.25, 373.44, 371.98\\n', b'2002, 04, 37361, 2002.2877, 374.77, 372.14, 375.10, 372.44, 374.77, 372.14\\n', b'2002, 05, 37391, 2002.3699, 375.48, 372.26, 375.86, 372.64, 375.48, 372.26\\n', b'2002, 06, 37422, 2002.4548, 375.33, 372.89, 375.27, 372.85, 375.33, 372.89\\n', b'2002, 07, 37452, 2002.5370, 373.95, 373.18, 373.79, 373.06, 373.95, 373.18\\n', b'2002, 08, 37483, 2002.6219, 371.41, 372.88, 371.78, 373.29, 371.41, 372.88\\n', b'2002, 09, 37514, 2002.7068, 370.63, 373.95, 370.18, 373.52, 370.63, 373.95\\n', b'2002, 10, 37544, 2002.7890, 370.18, 373.61, 370.33, 373.75, 370.18, 373.61\\n', b'2002, 11, 37575, 2002.8740, 372.01, 374.16, 371.85, 373.98, 372.01, 374.16\\n', b'2002, 12, 37605, 2002.9562, 373.71, 374.59, 373.34, 374.21, 373.71, 374.59\\n', b'2003, 01, 37636, 2003.0411, 374.61, 374.55, 374.51, 374.43, 374.61, 374.55\\n', b'2003, 02, 37667, 2003.1260, 375.55, 374.81, 375.40, 374.65, 375.55, 374.81\\n', b'2003, 03, 37695, 2003.2027, 376.04, 374.57, 376.33, 374.84, 376.04, 374.57\\n', b'2003, 04, 37726, 2003.2877, 377.58, 374.94, 377.72, 375.06, 377.58, 374.94\\n', b'2003, 05, 37756, 2003.3699, 378.28, 375.05, 378.49, 375.26, 378.28, 375.05\\n', b'2003, 06, 37787, 2003.4548, 378.07, 375.62, 377.90, 375.47, 378.07, 375.62\\n', b'2003, 07, 37817, 2003.5370, 376.54, 375.78, 376.39, 375.66, 376.54, 375.78\\n', b'2003, 08, 37848, 2003.6219, 374.42, 375.90, 374.34, 375.85, 374.42, 375.90\\n', b'2003, 09, 37879, 2003.7068, 372.92, 376.25, 372.68, 376.03, 372.92, 376.25\\n', b'2003, 10, 37909, 2003.7890, 372.94, 376.38, 372.77, 376.20, 372.94, 376.38\\n', b'2003, 11, 37940, 2003.8740, 374.29, 376.45, 374.22, 376.36, 374.29, 376.45\\n', b'2003, 12, 37970, 2003.9562, 375.63, 376.51, 375.64, 376.50, 375.63, 376.51\\n', b'2004, 01, 38001, 2004.0410, 376.73, 376.66, 376.72, 376.64, 376.73, 376.66\\n', b'2004, 02, 38032, 2004.1257, 377.31, 376.57, 377.53, 376.78, 377.31, 376.57\\n', b'2004, 03, 38061, 2004.2049, 378.33, 376.84, 378.41, 376.89, 378.33, 376.84\\n', b'2004, 04, 38092, 2004.2896, 380.44, 377.76, 379.71, 377.02, 380.44, 377.76\\n', b'2004, 05, 38122, 2004.3716, 380.56, 377.31, 380.37, 377.13, 380.56, 377.31\\n', b'2004, 06, 38153, 2004.4563, 379.49, 377.06, 379.66, 377.25, 379.49, 377.06\\n', b'2004, 07, 38183, 2004.5383, 377.71, 376.97, 378.08, 377.37, 377.71, 376.97\\n', b'2004, 08, 38214, 2004.6230, 375.77, 377.28, 375.96, 377.51, 375.77, 377.28\\n', b'2004, 09, 38245, 2004.7077, 373.99, 377.35, 374.29, 377.66, 373.99, 377.35\\n', b'2004, 10, 38275, 2004.7896, 374.17, 377.62, 374.39, 377.82, 374.17, 377.62\\n', b'2004, 11, 38306, 2004.8743, 375.79, 377.95, 375.87, 378.00, 375.79, 377.95\\n', b'2004, 12, 38336, 2004.9563, 377.39, 378.28, 377.33, 378.19, 377.39, 378.28\\n', b'2005, 01, 38367, 2005.0411, 378.29, 378.22, 378.48, 378.40, 378.29, 378.22\\n', b'2005, 02, 38398, 2005.1260, 379.56, 378.81, 379.37, 378.61, 379.56, 378.81\\n', b'2005, 03, 38426, 2005.2027, 380.06, 378.59, 380.30, 378.81, 380.06, 378.59\\n', b'2005, 04, 38457, 2005.2877, 382.01, 379.36, 381.71, 379.03, 382.01, 379.36\\n', b'2005, 05, 38487, 2005.3699, 382.21, 378.95, 382.50, 379.25, 382.21, 378.95\\n', b'2005, 06, 38518, 2005.4548, 382.05, 379.58, 381.91, 379.47, 382.05, 379.58\\n', b'2005, 07, 38548, 2005.5370, 380.63, 379.86, 380.42, 379.68, 380.63, 379.86\\n', b'2005, 08, 38579, 2005.6219, 378.64, 380.12, 378.38, 379.90, 378.64, 380.12\\n', b'2005, 09, 38610, 2005.7068, 376.38, 379.74, 376.74, 380.11, 376.38, 379.74\\n', b'2005, 10, 38640, 2005.7890, 376.77, 380.23, 376.85, 380.31, 376.77, 380.23\\n', b'2005, 11, 38671, 2005.8740, 378.27, 380.44, 378.36, 380.50, 378.27, 380.44\\n', b'2005, 12, 38701, 2005.9562, 379.92, 380.81, 379.82, 380.69, 379.92, 380.81\\n', b'2006, 01, 38732, 2006.0411, 381.33, 381.27, 380.95, 380.87, 381.33, 381.27\\n', b'2006, 02, 38763, 2006.1260, 381.98, 381.23, 381.81, 381.05, 381.98, 381.23\\n', b'2006, 03, 38791, 2006.2027, 382.53, 381.05, 382.69, 381.19, 382.53, 381.05\\n', b'2006, 04, 38822, 2006.2877, 384.33, 381.66, 384.04, 381.35, 384.33, 381.66\\n', b'2006, 05, 38852, 2006.3699, 384.89, 381.63, 384.76, 381.50, 384.89, 381.63\\n', b'2006, 06, 38883, 2006.4548, 383.99, 381.52, 384.10, 381.64, 383.99, 381.52\\n', b'2006, 07, 38913, 2006.5370, 382.25, 381.47, 382.53, 381.79, 382.25, 381.47\\n', b'2006, 08, 38944, 2006.6219, 380.44, 381.93, 380.41, 381.93, 380.44, 381.93\\n', b'2006, 09, 38975, 2006.7068, 378.77, 382.13, 378.70, 382.08, 378.77, 382.13\\n', b'2006, 10, 39005, 2006.7890, 379.03, 382.50, 378.77, 382.23, 379.03, 382.50\\n', b'2006, 11, 39036, 2006.8740, 380.11, 382.29, 380.22, 382.38, 380.11, 382.29\\n', b'2006, 12, 39066, 2006.9562, 381.62, 382.52, 381.65, 382.52, 381.62, 382.52\\n', b'2007, 01, 39097, 2007.0411, 382.55, 382.49, 382.76, 382.68, 382.55, 382.49\\n', b'2007, 02, 39128, 2007.1260, 383.68, 382.93, 383.59, 382.83, 383.68, 382.93\\n', b'2007, 03, 39156, 2007.2027, 384.31, 382.82, 384.47, 382.97, 384.31, 382.82\\n', b'2007, 04, 39187, 2007.2877, 386.20, 383.52, 385.83, 383.13, 386.20, 383.52\\n', b'2007, 05, 39217, 2007.3699, 386.38, 383.11, 386.56, 383.29, 386.38, 383.11\\n', b'2007, 06, 39248, 2007.4548, 385.85, 383.36, 385.91, 383.45, 385.85, 383.36\\n', b'2007, 07, 39278, 2007.5370, 384.42, 383.64, 384.35, 383.61, 384.42, 383.64\\n', b'2007, 08, 39309, 2007.6219, 381.81, 383.31, 382.24, 383.78, 381.81, 383.31\\n', b'2007, 09, 39340, 2007.7068, 380.83, 384.20, 380.55, 383.94, 380.83, 384.20\\n', b'2007, 10, 39370, 2007.7890, 380.83, 384.32, 380.62, 384.10, 380.83, 384.32\\n', b'2007, 11, 39401, 2007.8740, 382.32, 384.51, 382.09, 384.25, 382.32, 384.51\\n', b'2007, 12, 39431, 2007.9562, 383.58, 384.47, 383.52, 384.40, 383.58, 384.47\\n', b'2008, 01, 39462, 2008.0410, 385.04, 384.97, 384.62, 384.55, 385.04, 384.97\\n', b'2008, 02, 39493, 2008.1257, 385.81, 385.06, 385.45, 384.69, 385.81, 385.06\\n', b'2008, 03, 39522, 2008.2049, 385.80, 384.29, 386.36, 384.83, 385.80, 384.29\\n', b'2008, 04, 39553, 2008.2896, 386.74, 384.03, 387.71, 384.98, 386.74, 384.03\\n', b'2008, 05, 39583, 2008.3716, 388.49, 385.20, 388.42, 385.14, 388.49, 385.20\\n', b'2008, 06, 39614, 2008.4563, 388.02, 385.56, 387.75, 385.31, 388.02, 385.56\\n', b'2008, 07, 39644, 2008.5383, 386.22, 385.47, 386.19, 385.47, 386.22, 385.47\\n', b'2008, 08, 39675, 2008.6230, 384.05, 385.58, 384.08, 385.64, 384.05, 385.58\\n', b'2008, 09, 39706, 2008.7077, 383.05, 386.45, 382.40, 385.81, 383.05, 386.45\\n', b'2008, 10, 39736, 2008.7896, 382.75, 386.24, 382.49, 385.97, 382.75, 386.24\\n', b'2008, 11, 39767, 2008.8743, 383.98, 386.17, 383.96, 386.13, 383.98, 386.17\\n', b'2008, 12, 39797, 2008.9563, 385.08, 385.98, 385.40, 386.28, 385.08, 385.98\\n', b'2009, 01, 39828, 2009.0411, 386.63, 386.56, 386.51, 386.43, 386.63, 386.56\\n', b'2009, 02, 39859, 2009.1260, 387.10, 386.35, 387.36, 386.59, 387.10, 386.35\\n', b'2009, 03, 39887, 2009.2027, 388.50, 387.01, 388.25, 386.74, 388.50, 387.01\\n', b'2009, 04, 39918, 2009.2877, 389.54, 386.85, 389.61, 386.91, 389.54, 386.85\\n', b'2009, 05, 39948, 2009.3699, 390.15, 386.85, 390.37, 387.08, 390.15, 386.85\\n', b'2009, 06, 39979, 2009.4548, 389.60, 387.11, 389.73, 387.26, 389.60, 387.11\\n', b'2009, 07, 40009, 2009.5370, 388.05, 387.27, 388.20, 387.45, 388.05, 387.27\\n', b'2009, 08, 40040, 2009.6219, 386.06, 387.57, 386.11, 387.65, 386.06, 387.57\\n', b'2009, 09, 40071, 2009.7068, 384.64, 388.03, 384.45, 387.86, 384.64, 388.03\\n', b'2009, 10, 40101, 2009.7890, 384.32, 387.83, 384.59, 388.08, 384.32, 387.83\\n', b'2009, 11, 40132, 2009.8740, 386.05, 388.25, 386.13, 388.30, 386.05, 388.25\\n', b'2009, 12, 40162, 2009.9562, 387.48, 388.38, 387.64, 388.52, 387.48, 388.38\\n', b'2010, 01, 40193, 2010.0411, 388.55, 388.49, 388.83, 388.75, 388.55, 388.49\\n', b'2010, 02, 40224, 2010.1260, 390.08, 389.32, 389.75, 388.98, 390.08, 389.32\\n', b'2010, 03, 40252, 2010.2027, 391.02, 389.53, 390.69, 389.18, 391.02, 389.53\\n', b'2010, 04, 40283, 2010.2877, 392.39, 389.69, 392.11, 389.39, 392.39, 389.69\\n', b'2010, 05, 40313, 2010.3699, 393.24, 389.94, 392.88, 389.58, 393.24, 389.94\\n', b'2010, 06, 40344, 2010.4548, 392.26, 389.75, 392.25, 389.77, 392.26, 389.75\\n', b'2010, 07, 40374, 2010.5370, 390.35, 389.56, 390.70, 389.95, 390.35, 389.56\\n', b'2010, 08, 40405, 2010.6219, 388.53, 390.04, 388.58, 390.12, 388.53, 390.04\\n', b'2010, 09, 40436, 2010.7068, 386.85, 390.25, 386.87, 390.29, 386.85, 390.25\\n', b'2010, 10, 40466, 2010.7890, 387.18, 390.70, 386.94, 390.44, 387.18, 390.70\\n', b'2010, 11, 40497, 2010.8740, 388.69, 390.90, 388.41, 390.59, 388.69, 390.90\\n', b'2010, 12, 40527, 2010.9562, 389.83, 390.74, 389.85, 390.73, 389.83, 390.74\\n', b'2011, 01, 40558, 2011.0411, 391.33, 391.26, 390.95, 390.87, 391.33, 391.26\\n', b'2011, 02, 40589, 2011.1260, 391.96, 391.20, 391.77, 391.00, 391.96, 391.20\\n', b'2011, 03, 40617, 2011.2027, 392.49, 390.99, 392.64, 391.12, 392.49, 390.99\\n', b'2011, 04, 40648, 2011.2877, 393.40, 390.70, 393.98, 391.26, 393.40, 390.70\\n', b'2011, 05, 40678, 2011.3699, 394.33, 391.02, 394.71, 391.40, 394.33, 391.02\\n', b'2011, 06, 40709, 2011.4548, 393.75, 391.24, 394.05, 391.56, 393.75, 391.24\\n', b'2011, 07, 40739, 2011.5370, 392.64, 391.86, 392.48, 391.73, 392.64, 391.86\\n', b'2011, 08, 40770, 2011.6219, 390.25, 391.76, 390.36, 391.91, 390.25, 391.76\\n', b'2011, 09, 40801, 2011.7068, 389.05, 392.46, 388.66, 392.09, 389.05, 392.46\\n', b'2011, 10, 40831, 2011.7890, 388.98, 392.51, 388.76, 392.27, 388.98, 392.51\\n', b'2011, 11, 40862, 2011.8740, 390.30, 392.51, 390.27, 392.46, 390.30, 392.51\\n', b'2011, 12, 40892, 2011.9562, 391.86, 392.76, 391.75, 392.64, 391.86, 392.76\\n', b'2012, 01, 40923, 2012.0410, 393.13, 393.07, 392.90, 392.83, 393.13, 393.07\\n', b'2012, 02, 40954, 2012.1257, 393.42, 392.66, 393.79, 393.02, 393.42, 392.66\\n', b'2012, 03, 40983, 2012.2049, 394.43, 392.90, 394.75, 393.20, 394.43, 392.90\\n', b'2012, 04, 41014, 2012.2896, 396.51, 393.77, 396.16, 393.41, 396.51, 393.77\\n', b'2012, 05, 41044, 2012.3716, 396.96, 393.64, 396.93, 393.61, 396.96, 393.64\\n', b'2012, 06, 41075, 2012.4563, 395.97, 393.48, 396.30, 393.83, 395.97, 393.48\\n', b'2012, 07, 41105, 2012.5383, 394.60, 393.85, 394.77, 394.05, 394.60, 393.85\\n', b'2012, 08, 41136, 2012.6230, 392.61, 394.15, 392.71, 394.29, 392.61, 394.15\\n', b'2012, 09, 41167, 2012.7077, 391.20, 394.63, 391.08, 394.53, 391.20, 394.63\\n', b'2012, 10, 41197, 2012.7896, 391.09, 394.62, 391.25, 394.77, 391.09, 394.62\\n', b'2012, 11, 41228, 2012.8743, 393.03, 395.24, 392.82, 395.01, 393.03, 395.24\\n', b'2012, 12, 41258, 2012.9563, 394.42, 395.32, 394.35, 395.24, 394.42, 395.32\\n', b'2013, 01, 41289, 2013.0411, 395.69, 395.63, 395.56, 395.48, 395.69, 395.63\\n', b'2013, 02, 41320, 2013.1260, 396.94, 396.17, 396.48, 395.70, 396.94, 396.17\\n', b'2013, 03, 41348, 2013.2027, 397.35, 395.85, 397.43, 395.90, 397.35, 395.85\\n', b'2013, 04, 41379, 2013.2877, 398.44, 395.72, 398.85, 396.12, 398.44, 395.72\\n', b'2013, 05, 41409, 2013.3699, 400.06, 396.73, 399.65, 396.32, 400.06, 396.73\\n', b'2013, 06, 41440, 2013.4548, 398.95, 396.43, 399.02, 396.52, 398.95, 396.43\\n', b'2013, 07, 41470, 2013.5370, 397.45, 396.66, 397.47, 396.71, 397.45, 396.66\\n', b'2013, 08, 41501, 2013.6219, 395.49, 397.01, 395.35, 396.90, 395.49, 397.01\\n', b'2013, 09, 41532, 2013.7068, 393.47, 396.91, 393.64, 397.09, 393.47, 396.91\\n', b'2013, 10, 41562, 2013.7890, 393.77, 397.32, 393.74, 397.27, 393.77, 397.32\\n', b'2013, 11, 41593, 2013.8740, 395.27, 397.50, 395.25, 397.45, 395.27, 397.50\\n', b'2013, 12, 41623, 2013.9562, 396.90, 397.81, 396.73, 397.63, 396.90, 397.81\\n', b'2014, 01, 41654, 2014.0411, 398.01, 397.94, 397.88, 397.80, 398.01, 397.94\\n', b'2014, 02, 41685, 2014.1260, 398.18, 397.41, 398.75, 397.97, 398.18, 397.41\\n', b'2014, 03, 41713, 2014.2027, 399.56, 398.05, 399.65, 398.12, 399.56, 398.05\\n', b'2014, 04, 41744, 2014.2877, 401.44, 398.71, 401.04, 398.29, 401.44, 398.71\\n', b'2014, 05, 41774, 2014.3699, 401.98, 398.64, 401.79, 398.45, 401.98, 398.64\\n', b'2014, 06, 41805, 2014.4548, 401.41, 398.88, 401.12, 398.61, 401.41, 398.88\\n', b'2014, 07, 41835, 2014.5370, 399.17, 398.37, 399.52, 398.76, 399.17, 398.37\\n', b'2014, 08, 41866, 2014.6219, 397.30, 398.82, 397.36, 398.93, 397.30, 398.82\\n', b'2014, 09, 41897, 2014.7068, 395.49, 398.93, 395.63, 399.09, 395.49, 398.93\\n', b'2014, 10, 41927, 2014.7890, 395.74, 399.29, 395.71, 399.25, 395.74, 399.29\\n', b'2014, 11, 41958, 2014.8740, 397.32, 399.55, 397.21, 399.42, 397.32, 399.55\\n', b'2014, 12, 41988, 2014.9562, 398.88, 399.80, 398.69, 399.58, 398.88, 399.80\\n', b'2015, 01, 42019, 2015.0411, 399.94, 399.88, 399.83, 399.75, 399.94, 399.88\\n', b'2015, 02, 42050, 2015.1260, 400.40, 399.63, 400.71, 399.93, 400.40, 399.63\\n', b'2015, 03, 42078, 2015.2027, 401.60, 400.08, 401.63, 400.10, 401.60, 400.08\\n', b'2015, 04, 42109, 2015.2877, 403.53, 400.79, 403.05, 400.29, 403.53, 400.79\\n', b'2015, 05, 42139, 2015.3699, 404.04, 400.69, 403.84, 400.49, 404.04, 400.69\\n', b'2015, 06, 42170, 2015.4548, 402.81, 400.27, 403.22, 400.71, 402.81, 400.27\\n', b'2015, 07, 42200, 2015.5370, 401.54, 400.74, 401.70, 400.94, 401.54, 400.74\\n', b'2015, 08, 42231, 2015.6219, 398.93, 400.45, 399.64, 401.20, 398.93, 400.45\\n', b'2015, 09, 42262, 2015.7068, 397.43, 400.88, 398.02, 401.49, 397.43, 400.88\\n', b'2015, 10, 42292, 2015.7890, 398.22, 401.78, 398.23, 401.78, 398.22, 401.78\\n', b'2015, 11, 42323, 2015.8740, 400.17, 402.41, 399.89, 402.10, 400.17, 402.41\\n', b'2015, 12, 42353, 2015.9562, 401.82, 402.74, 401.51, 402.41, 401.82, 402.74\\n', b'2016, 01, 42384, 2016.0410, 402.58, 402.51, 402.80, 402.72, 402.58, 402.51\\n', b'2016, 02, 42415, 2016.1257, 404.09, 403.32, 403.81, 403.03, 404.09, 403.32\\n', b'2016, 03, 42444, 2016.2049, 404.79, 403.24, 404.88, 403.31, 404.79, 403.24\\n', b'2016, 04, 42475, 2016.2896, 407.50, 404.73, 406.38, 403.59, 407.50, 404.73\\n', b'2016, 05, 42505, 2016.3716, 407.59, 404.23, 407.20, 403.84, 407.59, 404.23\\n', b'2016, 06, 42536, 2016.4563, 406.94, 404.42, 406.58, 404.08, 406.94, 404.42\\n', b'2016, 07, 42566, 2016.5383, 404.43, 403.67, 405.03, 404.30, 404.43, 403.67\\n', b'2016, 08, 42597, 2016.6230, 402.17, 403.73, 402.93, 404.52, 402.17, 403.73\\n', b'2016, 09, 42628, 2016.7077, 400.95, 404.42, 401.26, 404.75, 400.95, 404.42\\n', b'2016, 10, 42658, 2016.7896, 401.43, 405.00, 401.40, 404.96, 401.43, 405.00\\n', b'2016, 11, 42689, 2016.8743, 403.57, 405.81, 402.95, 405.17, 403.57, 405.81\\n', b'2016, 12, 42719, 2016.9563, 404.48, 405.40, 404.46, 405.36, 404.48, 405.40\\n', b'2017, 01, 42750, 2017.0411, 406.00, 405.94, 405.63, 405.55, 406.00, 405.94\\n', b'2017, 02, 42781, 2017.1260, 406.57, 405.80, 406.52, 405.73, 406.57, 405.80\\n', b'2017, 03, 42809, 2017.2027, 406.99, 405.46, 407.43, 405.89, 406.99, 405.46\\n', b'2017, 04, 42840, 2017.2877, 408.88, 406.13, 408.83, 406.06, 408.88, 406.13\\n', b'2017, 05, 42870, 2017.3699, 409.84, 406.47, 409.59, 406.22, 409.84, 406.47\\n', b'2017, 06, 42901, 2017.4548, 409.05, 406.50, 408.91, 406.38, 409.05, 406.50\\n', b'2017, 07, 42931, 2017.5370, 407.13, 406.33, 407.30, 406.54, 407.13, 406.33\\n', b'2017, 08, 42962, 2017.6219, 405.17, 406.71, 405.12, 406.69, 405.17, 406.71\\n', b'2017, 09, 42993, 2017.7068, 403.20, 406.67, 403.36, 406.85, 403.20, 406.67\\n', b'2017, 10, 43023, 2017.7890, 403.57, 407.16, 403.43, 407.00, 403.57, 407.16\\n', b'2017, 11, 43054, 2017.8740, 405.10, 407.35, 404.93, 407.16, 405.10, 407.35\\n', b'2017, 12, 43084, 2017.9562, 406.68, 407.60, 406.41, 407.31, 406.68, 407.60\\n', b'2018, 01, 43115, 2018.0411, 407.98, 407.91, 407.54, 407.46, 407.98, 407.91\\n', b'2018, 02, 43146, 2018.1260, 408.36, 407.58, 408.40, 407.62, 408.36, 407.58\\n', b'2018, 03, 43174, 2018.2027, 409.21, 407.68, 409.32, 407.77, 409.21, 407.68\\n', b'2018, 04, 43205, 2018.2877, 410.24, 407.48, 410.73, 407.95, 410.24, 407.48\\n', b'2018, 05, 43235, 2018.3699, 411.23, 407.86, 411.52, 408.14, 411.23, 407.86\\n', b'2018, 06, 43266, 2018.4548, 410.81, 408.25, 410.90, 408.36, 410.81, 408.25\\n', b'2018, 07, 43296, 2018.5370, 408.83, 408.03, 409.36, 408.59, 408.83, 408.03\\n', b'2018, 08, 43327, 2018.6219, 407.02, 408.56, 407.26, 408.84, 407.02, 408.56\\n', b'2018, 09, 43358, 2018.7068, 405.52, 409.01, 405.61, 409.11, 405.52, 409.01\\n', b'2018, 10, 43388, 2018.7890, 405.93, 409.52, 405.80, 409.38, 405.93, 409.52\\n', b'2018, 11, 43419, 2018.8740, 408.04, 410.30, 407.42, 409.65, 408.04, 410.30\\n', b'2018, 12, 43449, 2018.9562, 409.17, 410.09, 409.01, 409.91, 409.17, 410.09\\n', b'2019, 01, 43480, 2019.0411, 410.85, 410.78, 410.25, 410.17, 410.85, 410.78\\n', b'2019, 02, 43511, 2019.1260, 411.59, 410.81, 411.20, 410.41, 411.59, 410.81\\n', b'2019, 03, 43539, 2019.2027, 411.91, 410.37, 412.17, 410.62, 411.91, 410.37\\n', b'2019, 04, 43570, 2019.2877, 413.46, 410.69, 413.64, 410.85, 413.46, 410.69\\n', b'2019, 05, 43600, 2019.3699, 414.76, 411.38, 414.45, 411.07, 414.76, 411.38\\n', b'2019, 06, 43631, 2019.4548, 413.89, 411.32, 413.83, 411.29, 413.89, 411.32\\n', b'2019, 07, 43661, 2019.5370, 411.78, 410.98, 412.27, 411.50, 411.78, 410.98\\n', b'2019, 08, 43692, 2019.6219, 410.01, 411.56, 410.14, 411.72, 410.01, 411.56\\n', b'2019, 09, 43723, 2019.7068, 408.48, 411.97, 408.44, 411.95, 408.48, 411.97\\n', b'2019, 10, 43753, 2019.7890, 408.40, 412.00, 408.57, 412.16, 408.40, 412.00\\n', b'2019, 11, 43784, 2019.8740, 410.16, 412.43, 410.15, 412.39, 410.16, 412.43\\n', b'2019, 12, 43814, 2019.9562, 411.81, 412.74, 411.69, 412.60, 411.81, 412.74\\n', b'2020, 01, 43845, 2020.0410, 413.30, 413.24, 412.90, 412.82, 413.30, 413.24\\n', b'2020, 02, 43876, 2020.1257, 414.05, 413.27, 413.81, 413.03, 414.05, 413.27\\n', b'2020, 03, 43905, 2020.2049, 414.45, 412.88, 414.80, 413.22, 414.45, 412.88\\n', b'2020, 04, 43936, 2020.2896, 416.11, 413.31, 416.24, 413.42, 416.11, 413.31\\n', b'2020, 05, 43966, 2020.3716, 417.15, 413.76, 417.01, 413.62, 417.15, 413.76\\n', b'2020, 06, 43997, 2020.4563, 416.29, 413.74, 416.34, 413.82, 416.29, 413.74\\n', b'2020, 07, 44027, 2020.5383, 414.42, 413.64, 414.75, 414.01, 414.42, 413.64\\n', b'2020, 08, 44058, 2020.6230, 412.52, 414.10, 412.60, 414.22, 412.52, 414.10\\n', b'2020, 09, 44089, 2020.7077, 411.18, 414.69, 410.88, 414.41, 411.18, 414.69\\n', b'2020, 10, 44119, 2020.7896, 411.12, 414.73, 411.01, 414.60, 411.12, 414.73\\n', b'2020, 11, 44150, 2020.8743, 412.88, 415.15, 412.55, 414.79, 412.88, 415.15\\n', b'2020, 12, 44180, 2020.9563, 413.89, 414.81, 414.06, 414.97, 413.89, 414.81\\n', b'2021, 01, 44211, 2021.0411, 415.15, 415.08, 415.23, 415.15, 415.15, 415.08\\n', b'2021, 02, 44242, 2021.1260, 416.47, 415.69, 416.12, 415.32, 416.47, 415.69\\n', b'2021, 03, 44270, 2021.2027, 417.16, 415.62, 417.04, 415.48, 417.16, 415.62\\n', b'2021, 04, 44301, 2021.2877, 418.24, 415.46, 418.45, 415.65, 418.24, 415.46\\n', b'2021, 05, 44331, 2021.3699, 418.95, 415.55, 419.23, 415.82, 418.95, 415.55\\n', b'2021, 06, 44362, 2021.4548, 418.70, 416.12, 418.56, 416.00, 418.70, 416.12\\n', b'2021, 07, 44392, 2021.5370, 416.65, 415.84, 416.96, 416.18, 416.65, 415.84\\n', b'2021, 08, 44423, 2021.6219, 414.34, 415.89, 414.78, 416.37, 414.34, 415.89\\n', b'2021, 09, 44454, 2021.7068, 412.90, 416.42, 413.04, 416.57, 412.90, 416.42\\n', b'2021, 10, 44484, 2021.7890, 413.55, 417.17, 413.15, 416.76, 413.55, 417.17\\n', b'2021, 11, 44515, 2021.8740, 414.82, 417.09, 414.70, 416.95, 414.82, 417.09\\n', b'2021, 12, 44545, 2021.9562, 416.43, 417.36, 416.21, 417.12, 416.43, 417.36\\n', b'2022, 01, 44576, 2022.0411, 418.01, 417.94, 417.37, 417.28, 418.01, 417.94\\n', b'2022, 02, 44607, 2022.1260, 418.99, 418.20, 418.23, 417.43, 418.99, 418.20\\n', b'2022, 03, 44635, 2022.2027, 418.45, 416.90, 419.12, 417.56, 418.45, 416.90\\n', b'2022, 04, 44666, 2022.2877, 420.02, 417.23, -99.99, -99.99, 420.02, 417.23\\n', b'2022, 05, 44696, 2022.3699, -99.99, -99.99, -99.99, -99.99, -99.99, -99.99\\n', b'2022, 06, 44727, 2022.4548, -99.99, -99.99, -99.99, -99.99, -99.99, -99.99\\n', b'2022, 07, 44757, 2022.5370, -99.99, -99.99, -99.99, -99.99, -99.99, -99.99\\n', b'2022, 08, 44788, 2022.6219, -99.99, -99.99, -99.99, -99.99, -99.99, -99.99\\n', b'2022, 09, 44819, 2022.7068, -99.99, -99.99, -99.99, -99.99, -99.99, -99.99\\n', b'2022, 10, 44849, 2022.7890, -99.99, -99.99, -99.99, -99.99, -99.99, -99.99\\n', b'2022, 11, 44880, 2022.8740, -99.99, -99.99, -99.99, -99.99, -99.99, -99.99\\n', b'2022, 12, 44910, 2022.9562, -99.99, -99.99, -99.99, -99.99, -99.99, -99.99\\n']\n" ] } ], "source": [ "csv_name = \"monthly_in_situ_co2_mlo.csv\"\n", "data_url = \"https://scrippsco2.ucsd.edu/assets/data/atmospheric/stations/in_situ_co2/monthly/\" + csv_name\n", "file_exists = os.path.exists(csv_name)\n", "if not file_exists:\n", " print('file doesnt exist: dowloading')\n", " r = requests.get(data_url)\n", " data = r.text\n", " with open(csv_name, \"w\", encoding='UTF-8') as text_file:\n", " text_file.write(data)\n", "\n", "with open(csv_name, \"rb\") as text_file:\n", " print(text_file.readlines())" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "Nous chargeons le jeu de données dans une DataFrame à l'aide de Pandas." ] }, { "cell_type": "code", "execution_count": 3, "metadata": {}, "outputs": [], "source": [ "raw_data = pd.read_csv(csv_name, encoding = 'UTF-8', comment='\"', index_col=False)" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "On ajuste les noms de la première colonne pour compléter les noms et s'y retrouver." ] }, { "cell_type": "code", "execution_count": 4, "metadata": {}, "outputs": [], "source": [ "data = raw_data.copy()" ] }, { "cell_type": "code", "execution_count": 5, "metadata": {}, "outputs": [ { "name": "stdout", "output_type": "stream", "text": [ "['Yr', 'Mn', 'Date', 'Date', 'CO2', 'seasonally adjusted', 'fit', 'seasonally adjusted fit', 'CO2 filled', 'seasonally adjusted filled']\n" ] }, { "data": { "text/plain": [ "10" ] }, "execution_count": 5, "metadata": {}, "output_type": "execute_result" } ], "source": [ "column_names = raw_data.columns.values\n", "column_names\n", "first_row = raw_data.iloc[0].values\n", "first_row\n", "new_columns = []\n", "for (item1, item2) in zip(column_names, first_row):\n", " item1 = item1.strip()\n", " item2 = item2.strip()\n", " new_name = item1\n", " if item2 != '':\n", " new_name += ' ' + item2\n", " new_columns.append(new_name)\n", "print(new_columns)\n", "len(new_columns)" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "On remplace les titres des colonnes." ] }, { "cell_type": "code", "execution_count": 6, "metadata": {}, "outputs": [], "source": [ "data.columns = new_columns" ] }, { "cell_type": "code", "execution_count": 7, "metadata": {}, "outputs": [ { "data": { "text/html": [ "
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YrMnDateDateCO2seasonally adjustedfitseasonally adjusted fitCO2 filledseasonally adjusted filled
0adjustedadjusted fitfilledadjusted filled
1Excel[ppm][ppm][ppm][ppm][ppm][ppm]
2195801212001958.0411-99.99-99.99-99.99-99.99-99.99-99.99
3195802212311958.1260-99.99-99.99-99.99-99.99-99.99-99.99
4195803212591958.2027315.71314.44316.19314.91315.71314.44
5195804212901958.2877317.45315.16317.29314.99317.45315.16
6195805213201958.3699317.51314.70317.87315.06317.51314.70
7195806213511958.4548-99.99-99.99317.25315.14317.25315.14
8195807213811958.5370315.86315.20315.85315.22315.86315.20
9195808214121958.6219314.93316.21313.97315.29314.93316.21
10195809214431958.7068313.21316.10312.44315.35313.21316.10
11195810214731958.7890-99.99-99.99312.43315.40312.43315.40
12195811215041958.8740313.33315.20313.60315.46313.33315.20
13195812215341958.9562314.67315.43314.76315.51314.67315.43
14195901215651959.0411315.58315.52315.64315.57315.58315.52
15195902215961959.1260316.49315.84316.28315.63316.49315.84
16195903216241959.2027316.65315.37316.98315.69316.65315.37
17195904216551959.2877317.72315.42318.08315.76317.72315.42
18195905216851959.3699318.29315.48318.66315.84318.29315.48
19195906217161959.4548318.15316.02318.05315.93318.15316.02
20195907217461959.5370316.54315.87316.66316.02316.54315.87
21195908217771959.6219314.80316.08314.80316.12314.80316.08
22195909218081959.7068313.84316.74313.30316.21313.84316.74
23195910218381959.7890313.33316.33313.32316.30313.33316.33
24195911218691959.8740314.81316.69314.53316.39314.81316.69
25195912218991959.9562315.58316.35315.72316.47315.58316.35
26196001219301960.0410316.43316.37316.62316.55316.43316.37
27196002219611960.1257316.98316.33317.29316.63316.98316.33
28196003219901960.2049317.58316.27318.03316.71317.58316.27
29196004220211960.2896319.03316.70319.14316.79319.03316.70
.................................
752202007440272020.5383414.42413.64414.75414.01414.42413.64
753202008440582020.6230412.52414.10412.60414.22412.52414.10
754202009440892020.7077411.18414.69410.88414.41411.18414.69
755202010441192020.7896411.12414.73411.01414.60411.12414.73
756202011441502020.8743412.88415.15412.55414.79412.88415.15
757202012441802020.9563413.89414.81414.06414.97413.89414.81
758202101442112021.0411415.15415.08415.23415.15415.15415.08
759202102442422021.1260416.47415.69416.12415.32416.47415.69
760202103442702021.2027417.16415.62417.04415.48417.16415.62
761202104443012021.2877418.24415.46418.45415.65418.24415.46
762202105443312021.3699418.95415.55419.23415.82418.95415.55
763202106443622021.4548418.70416.12418.56416.00418.70416.12
764202107443922021.5370416.65415.84416.96416.18416.65415.84
765202108444232021.6219414.34415.89414.78416.37414.34415.89
766202109444542021.7068412.90416.42413.04416.57412.90416.42
767202110444842021.7890413.55417.17413.15416.76413.55417.17
768202111445152021.8740414.82417.09414.70416.95414.82417.09
769202112445452021.9562416.43417.36416.21417.12416.43417.36
770202201445762022.0411418.01417.94417.37417.28418.01417.94
771202202446072022.1260418.99418.20418.23417.43418.99418.20
772202203446352022.2027418.45416.90419.12417.56418.45416.90
773202204446662022.2877420.02417.23-99.99-99.99420.02417.23
774202205446962022.3699-99.99-99.99-99.99-99.99-99.99-99.99
775202206447272022.4548-99.99-99.99-99.99-99.99-99.99-99.99
776202207447572022.5370-99.99-99.99-99.99-99.99-99.99-99.99
777202208447882022.6219-99.99-99.99-99.99-99.99-99.99-99.99
778202209448192022.7068-99.99-99.99-99.99-99.99-99.99-99.99
779202210448492022.7890-99.99-99.99-99.99-99.99-99.99-99.99
780202211448802022.8740-99.99-99.99-99.99-99.99-99.99-99.99
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782 rows × 10 columns

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" ], "text/plain": [ " Yr Mn Date Date CO2 seasonally adjusted \\\n", "0 adjusted \n", "1 Excel [ppm] [ppm] \n", "2 1958 01 21200 1958.0411 -99.99 -99.99 \n", "3 1958 02 21231 1958.1260 -99.99 -99.99 \n", "4 1958 03 21259 1958.2027 315.71 314.44 \n", "5 1958 04 21290 1958.2877 317.45 315.16 \n", "6 1958 05 21320 1958.3699 317.51 314.70 \n", "7 1958 06 21351 1958.4548 -99.99 -99.99 \n", "8 1958 07 21381 1958.5370 315.86 315.20 \n", "9 1958 08 21412 1958.6219 314.93 316.21 \n", "10 1958 09 21443 1958.7068 313.21 316.10 \n", "11 1958 10 21473 1958.7890 -99.99 -99.99 \n", "12 1958 11 21504 1958.8740 313.33 315.20 \n", "13 1958 12 21534 1958.9562 314.67 315.43 \n", "14 1959 01 21565 1959.0411 315.58 315.52 \n", "15 1959 02 21596 1959.1260 316.49 315.84 \n", "16 1959 03 21624 1959.2027 316.65 315.37 \n", "17 1959 04 21655 1959.2877 317.72 315.42 \n", "18 1959 05 21685 1959.3699 318.29 315.48 \n", "19 1959 06 21716 1959.4548 318.15 316.02 \n", "20 1959 07 21746 1959.5370 316.54 315.87 \n", "21 1959 08 21777 1959.6219 314.80 316.08 \n", "22 1959 09 21808 1959.7068 313.84 316.74 \n", "23 1959 10 21838 1959.7890 313.33 316.33 \n", "24 1959 11 21869 1959.8740 314.81 316.69 \n", "25 1959 12 21899 1959.9562 315.58 316.35 \n", "26 1960 01 21930 1960.0410 316.43 316.37 \n", "27 1960 02 21961 1960.1257 316.98 316.33 \n", "28 1960 03 21990 1960.2049 317.58 316.27 \n", "29 1960 04 22021 1960.2896 319.03 316.70 \n", ".. ... ... ... ... ... ... \n", "752 2020 07 44027 2020.5383 414.42 413.64 \n", "753 2020 08 44058 2020.6230 412.52 414.10 \n", "754 2020 09 44089 2020.7077 411.18 414.69 \n", "755 2020 10 44119 2020.7896 411.12 414.73 \n", "756 2020 11 44150 2020.8743 412.88 415.15 \n", "757 2020 12 44180 2020.9563 413.89 414.81 \n", "758 2021 01 44211 2021.0411 415.15 415.08 \n", "759 2021 02 44242 2021.1260 416.47 415.69 \n", "760 2021 03 44270 2021.2027 417.16 415.62 \n", "761 2021 04 44301 2021.2877 418.24 415.46 \n", "762 2021 05 44331 2021.3699 418.95 415.55 \n", "763 2021 06 44362 2021.4548 418.70 416.12 \n", "764 2021 07 44392 2021.5370 416.65 415.84 \n", "765 2021 08 44423 2021.6219 414.34 415.89 \n", "766 2021 09 44454 2021.7068 412.90 416.42 \n", "767 2021 10 44484 2021.7890 413.55 417.17 \n", "768 2021 11 44515 2021.8740 414.82 417.09 \n", "769 2021 12 44545 2021.9562 416.43 417.36 \n", "770 2022 01 44576 2022.0411 418.01 417.94 \n", "771 2022 02 44607 2022.1260 418.99 418.20 \n", "772 2022 03 44635 2022.2027 418.45 416.90 \n", "773 2022 04 44666 2022.2877 420.02 417.23 \n", "774 2022 05 44696 2022.3699 -99.99 -99.99 \n", "775 2022 06 44727 2022.4548 -99.99 -99.99 \n", "776 2022 07 44757 2022.5370 -99.99 -99.99 \n", "777 2022 08 44788 2022.6219 -99.99 -99.99 \n", "778 2022 09 44819 2022.7068 -99.99 -99.99 \n", "779 2022 10 44849 2022.7890 -99.99 -99.99 \n", "780 2022 11 44880 2022.8740 -99.99 -99.99 \n", "781 2022 12 44910 2022.9562 -99.99 -99.99 \n", "\n", " fit seasonally adjusted fit CO2 filled \\\n", "0 adjusted fit filled \n", "1 [ppm] [ppm] [ppm] \n", "2 -99.99 -99.99 -99.99 \n", "3 -99.99 -99.99 -99.99 \n", "4 316.19 314.91 315.71 \n", "5 317.29 314.99 317.45 \n", "6 317.87 315.06 317.51 \n", "7 317.25 315.14 317.25 \n", "8 315.85 315.22 315.86 \n", "9 313.97 315.29 314.93 \n", "10 312.44 315.35 313.21 \n", "11 312.43 315.40 312.43 \n", "12 313.60 315.46 313.33 \n", "13 314.76 315.51 314.67 \n", "14 315.64 315.57 315.58 \n", "15 316.28 315.63 316.49 \n", "16 316.98 315.69 316.65 \n", "17 318.08 315.76 317.72 \n", "18 318.66 315.84 318.29 \n", "19 318.05 315.93 318.15 \n", "20 316.66 316.02 316.54 \n", "21 314.80 316.12 314.80 \n", "22 313.30 316.21 313.84 \n", "23 313.32 316.30 313.33 \n", "24 314.53 316.39 314.81 \n", "25 315.72 316.47 315.58 \n", "26 316.62 316.55 316.43 \n", "27 317.29 316.63 316.98 \n", "28 318.03 316.71 317.58 \n", "29 319.14 316.79 319.03 \n", ".. ... ... ... \n", "752 414.75 414.01 414.42 \n", "753 412.60 414.22 412.52 \n", "754 410.88 414.41 411.18 \n", "755 411.01 414.60 411.12 \n", "756 412.55 414.79 412.88 \n", "757 414.06 414.97 413.89 \n", "758 415.23 415.15 415.15 \n", "759 416.12 415.32 416.47 \n", "760 417.04 415.48 417.16 \n", "761 418.45 415.65 418.24 \n", "762 419.23 415.82 418.95 \n", "763 418.56 416.00 418.70 \n", "764 416.96 416.18 416.65 \n", "765 414.78 416.37 414.34 \n", "766 413.04 416.57 412.90 \n", "767 413.15 416.76 413.55 \n", "768 414.70 416.95 414.82 \n", "769 416.21 417.12 416.43 \n", "770 417.37 417.28 418.01 \n", "771 418.23 417.43 418.99 \n", "772 419.12 417.56 418.45 \n", "773 -99.99 -99.99 420.02 \n", "774 -99.99 -99.99 -99.99 \n", "775 -99.99 -99.99 -99.99 \n", "776 -99.99 -99.99 -99.99 \n", "777 -99.99 -99.99 -99.99 \n", "778 -99.99 -99.99 -99.99 \n", "779 -99.99 -99.99 -99.99 \n", "780 -99.99 -99.99 -99.99 \n", "781 -99.99 -99.99 -99.99 \n", "\n", " seasonally adjusted filled \n", "0 adjusted filled \n", "1 [ppm] \n", "2 -99.99 \n", "3 -99.99 \n", "4 314.44 \n", "5 315.16 \n", "6 314.70 \n", "7 315.14 \n", "8 315.20 \n", "9 316.21 \n", "10 316.10 \n", "11 315.40 \n", "12 315.20 \n", "13 315.43 \n", "14 315.52 \n", "15 315.84 \n", "16 315.37 \n", "17 315.42 \n", "18 315.48 \n", "19 316.02 \n", "20 315.87 \n", "21 316.08 \n", "22 316.74 \n", "23 316.33 \n", "24 316.69 \n", "25 316.35 \n", "26 316.37 \n", "27 316.33 \n", "28 316.27 \n", "29 316.70 \n", ".. ... \n", "752 413.64 \n", "753 414.10 \n", "754 414.69 \n", "755 414.73 \n", "756 415.15 \n", "757 414.81 \n", "758 415.08 \n", "759 415.69 \n", "760 415.62 \n", "761 415.46 \n", "762 415.55 \n", "763 416.12 \n", "764 415.84 \n", "765 415.89 \n", "766 416.42 \n", "767 417.17 \n", "768 417.09 \n", "769 417.36 \n", "770 417.94 \n", "771 418.20 \n", "772 416.90 \n", "773 417.23 \n", "774 -99.99 \n", "775 -99.99 \n", "776 -99.99 \n", "777 -99.99 \n", "778 -99.99 \n", "779 -99.99 \n", "780 -99.99 \n", "781 -99.99 \n", "\n", "[782 rows x 10 columns]" ] }, "execution_count": 7, "metadata": {}, "output_type": "execute_result" } ], "source": [ "data" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "On peut maintenant retirer les deux premières lignes et réindexer la DataFrame." ] }, { "cell_type": "code", "execution_count": 8, "metadata": {}, "outputs": [], "source": [ "data = data.iloc[2:].reset_index(drop=True)" ] }, { "cell_type": "code", "execution_count": 9, "metadata": {}, "outputs": [ { "data": { "text/html": [ "
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YrMnDateDateCO2seasonally adjustedfitseasonally adjusted fitCO2 filledseasonally adjusted filled
0195801212001958.0411-99.99-99.99-99.99-99.99-99.99-99.99
1195802212311958.1260-99.99-99.99-99.99-99.99-99.99-99.99
2195803212591958.2027315.71314.44316.19314.91315.71314.44
3195804212901958.2877317.45315.16317.29314.99317.45315.16
4195805213201958.3699317.51314.70317.87315.06317.51314.70
5195806213511958.4548-99.99-99.99317.25315.14317.25315.14
6195807213811958.5370315.86315.20315.85315.22315.86315.20
7195808214121958.6219314.93316.21313.97315.29314.93316.21
8195809214431958.7068313.21316.10312.44315.35313.21316.10
9195810214731958.7890-99.99-99.99312.43315.40312.43315.40
10195811215041958.8740313.33315.20313.60315.46313.33315.20
11195812215341958.9562314.67315.43314.76315.51314.67315.43
12195901215651959.0411315.58315.52315.64315.57315.58315.52
13195902215961959.1260316.49315.84316.28315.63316.49315.84
14195903216241959.2027316.65315.37316.98315.69316.65315.37
15195904216551959.2877317.72315.42318.08315.76317.72315.42
16195905216851959.3699318.29315.48318.66315.84318.29315.48
17195906217161959.4548318.15316.02318.05315.93318.15316.02
18195907217461959.5370316.54315.87316.66316.02316.54315.87
19195908217771959.6219314.80316.08314.80316.12314.80316.08
20195909218081959.7068313.84316.74313.30316.21313.84316.74
21195910218381959.7890313.33316.33313.32316.30313.33316.33
22195911218691959.8740314.81316.69314.53316.39314.81316.69
23195912218991959.9562315.58316.35315.72316.47315.58316.35
24196001219301960.0410316.43316.37316.62316.55316.43316.37
25196002219611960.1257316.98316.33317.29316.63316.98316.33
26196003219901960.2049317.58316.27318.03316.71317.58316.27
27196004220211960.2896319.03316.70319.14316.79319.03316.70
28196005220511960.3716320.03317.21319.68316.86320.03317.21
29196006220821960.4563319.58317.46319.02316.92319.58317.46
.................................
750202007440272020.5383414.42413.64414.75414.01414.42413.64
751202008440582020.6230412.52414.10412.60414.22412.52414.10
752202009440892020.7077411.18414.69410.88414.41411.18414.69
753202010441192020.7896411.12414.73411.01414.60411.12414.73
754202011441502020.8743412.88415.15412.55414.79412.88415.15
755202012441802020.9563413.89414.81414.06414.97413.89414.81
756202101442112021.0411415.15415.08415.23415.15415.15415.08
757202102442422021.1260416.47415.69416.12415.32416.47415.69
758202103442702021.2027417.16415.62417.04415.48417.16415.62
759202104443012021.2877418.24415.46418.45415.65418.24415.46
760202105443312021.3699418.95415.55419.23415.82418.95415.55
761202106443622021.4548418.70416.12418.56416.00418.70416.12
762202107443922021.5370416.65415.84416.96416.18416.65415.84
763202108444232021.6219414.34415.89414.78416.37414.34415.89
764202109444542021.7068412.90416.42413.04416.57412.90416.42
765202110444842021.7890413.55417.17413.15416.76413.55417.17
766202111445152021.8740414.82417.09414.70416.95414.82417.09
767202112445452021.9562416.43417.36416.21417.12416.43417.36
768202201445762022.0411418.01417.94417.37417.28418.01417.94
769202202446072022.1260418.99418.20418.23417.43418.99418.20
770202203446352022.2027418.45416.90419.12417.56418.45416.90
771202204446662022.2877420.02417.23-99.99-99.99420.02417.23
772202205446962022.3699-99.99-99.99-99.99-99.99-99.99-99.99
773202206447272022.4548-99.99-99.99-99.99-99.99-99.99-99.99
774202207447572022.5370-99.99-99.99-99.99-99.99-99.99-99.99
775202208447882022.6219-99.99-99.99-99.99-99.99-99.99-99.99
776202209448192022.7068-99.99-99.99-99.99-99.99-99.99-99.99
777202210448492022.7890-99.99-99.99-99.99-99.99-99.99-99.99
778202211448802022.8740-99.99-99.99-99.99-99.99-99.99-99.99
779202212449102022.9562-99.99-99.99-99.99-99.99-99.99-99.99
\n", "

780 rows × 10 columns

\n", "
" ], "text/plain": [ " Yr Mn Date Date CO2 seasonally adjusted \\\n", "0 1958 01 21200 1958.0411 -99.99 -99.99 \n", "1 1958 02 21231 1958.1260 -99.99 -99.99 \n", "2 1958 03 21259 1958.2027 315.71 314.44 \n", "3 1958 04 21290 1958.2877 317.45 315.16 \n", "4 1958 05 21320 1958.3699 317.51 314.70 \n", "5 1958 06 21351 1958.4548 -99.99 -99.99 \n", "6 1958 07 21381 1958.5370 315.86 315.20 \n", "7 1958 08 21412 1958.6219 314.93 316.21 \n", "8 1958 09 21443 1958.7068 313.21 316.10 \n", "9 1958 10 21473 1958.7890 -99.99 -99.99 \n", "10 1958 11 21504 1958.8740 313.33 315.20 \n", "11 1958 12 21534 1958.9562 314.67 315.43 \n", "12 1959 01 21565 1959.0411 315.58 315.52 \n", "13 1959 02 21596 1959.1260 316.49 315.84 \n", "14 1959 03 21624 1959.2027 316.65 315.37 \n", "15 1959 04 21655 1959.2877 317.72 315.42 \n", "16 1959 05 21685 1959.3699 318.29 315.48 \n", "17 1959 06 21716 1959.4548 318.15 316.02 \n", "18 1959 07 21746 1959.5370 316.54 315.87 \n", "19 1959 08 21777 1959.6219 314.80 316.08 \n", "20 1959 09 21808 1959.7068 313.84 316.74 \n", "21 1959 10 21838 1959.7890 313.33 316.33 \n", "22 1959 11 21869 1959.8740 314.81 316.69 \n", "23 1959 12 21899 1959.9562 315.58 316.35 \n", "24 1960 01 21930 1960.0410 316.43 316.37 \n", "25 1960 02 21961 1960.1257 316.98 316.33 \n", "26 1960 03 21990 1960.2049 317.58 316.27 \n", "27 1960 04 22021 1960.2896 319.03 316.70 \n", "28 1960 05 22051 1960.3716 320.03 317.21 \n", "29 1960 06 22082 1960.4563 319.58 317.46 \n", ".. ... ... ... ... ... ... \n", "750 2020 07 44027 2020.5383 414.42 413.64 \n", "751 2020 08 44058 2020.6230 412.52 414.10 \n", "752 2020 09 44089 2020.7077 411.18 414.69 \n", "753 2020 10 44119 2020.7896 411.12 414.73 \n", "754 2020 11 44150 2020.8743 412.88 415.15 \n", "755 2020 12 44180 2020.9563 413.89 414.81 \n", "756 2021 01 44211 2021.0411 415.15 415.08 \n", "757 2021 02 44242 2021.1260 416.47 415.69 \n", "758 2021 03 44270 2021.2027 417.16 415.62 \n", "759 2021 04 44301 2021.2877 418.24 415.46 \n", "760 2021 05 44331 2021.3699 418.95 415.55 \n", "761 2021 06 44362 2021.4548 418.70 416.12 \n", "762 2021 07 44392 2021.5370 416.65 415.84 \n", "763 2021 08 44423 2021.6219 414.34 415.89 \n", "764 2021 09 44454 2021.7068 412.90 416.42 \n", "765 2021 10 44484 2021.7890 413.55 417.17 \n", "766 2021 11 44515 2021.8740 414.82 417.09 \n", "767 2021 12 44545 2021.9562 416.43 417.36 \n", "768 2022 01 44576 2022.0411 418.01 417.94 \n", "769 2022 02 44607 2022.1260 418.99 418.20 \n", "770 2022 03 44635 2022.2027 418.45 416.90 \n", "771 2022 04 44666 2022.2877 420.02 417.23 \n", "772 2022 05 44696 2022.3699 -99.99 -99.99 \n", "773 2022 06 44727 2022.4548 -99.99 -99.99 \n", "774 2022 07 44757 2022.5370 -99.99 -99.99 \n", "775 2022 08 44788 2022.6219 -99.99 -99.99 \n", "776 2022 09 44819 2022.7068 -99.99 -99.99 \n", "777 2022 10 44849 2022.7890 -99.99 -99.99 \n", "778 2022 11 44880 2022.8740 -99.99 -99.99 \n", "779 2022 12 44910 2022.9562 -99.99 -99.99 \n", "\n", " fit seasonally adjusted fit CO2 filled \\\n", "0 -99.99 -99.99 -99.99 \n", "1 -99.99 -99.99 -99.99 \n", "2 316.19 314.91 315.71 \n", "3 317.29 314.99 317.45 \n", "4 317.87 315.06 317.51 \n", "5 317.25 315.14 317.25 \n", "6 315.85 315.22 315.86 \n", "7 313.97 315.29 314.93 \n", "8 312.44 315.35 313.21 \n", "9 312.43 315.40 312.43 \n", "10 313.60 315.46 313.33 \n", "11 314.76 315.51 314.67 \n", "12 315.64 315.57 315.58 \n", "13 316.28 315.63 316.49 \n", "14 316.98 315.69 316.65 \n", "15 318.08 315.76 317.72 \n", "16 318.66 315.84 318.29 \n", "17 318.05 315.93 318.15 \n", "18 316.66 316.02 316.54 \n", "19 314.80 316.12 314.80 \n", "20 313.30 316.21 313.84 \n", "21 313.32 316.30 313.33 \n", "22 314.53 316.39 314.81 \n", "23 315.72 316.47 315.58 \n", "24 316.62 316.55 316.43 \n", "25 317.29 316.63 316.98 \n", "26 318.03 316.71 317.58 \n", "27 319.14 316.79 319.03 \n", "28 319.68 316.86 320.03 \n", "29 319.02 316.92 319.58 \n", ".. ... ... ... \n", "750 414.75 414.01 414.42 \n", "751 412.60 414.22 412.52 \n", "752 410.88 414.41 411.18 \n", "753 411.01 414.60 411.12 \n", "754 412.55 414.79 412.88 \n", "755 414.06 414.97 413.89 \n", "756 415.23 415.15 415.15 \n", "757 416.12 415.32 416.47 \n", "758 417.04 415.48 417.16 \n", "759 418.45 415.65 418.24 \n", "760 419.23 415.82 418.95 \n", "761 418.56 416.00 418.70 \n", "762 416.96 416.18 416.65 \n", "763 414.78 416.37 414.34 \n", "764 413.04 416.57 412.90 \n", "765 413.15 416.76 413.55 \n", "766 414.70 416.95 414.82 \n", "767 416.21 417.12 416.43 \n", "768 417.37 417.28 418.01 \n", "769 418.23 417.43 418.99 \n", "770 419.12 417.56 418.45 \n", "771 -99.99 -99.99 420.02 \n", "772 -99.99 -99.99 -99.99 \n", "773 -99.99 -99.99 -99.99 \n", "774 -99.99 -99.99 -99.99 \n", "775 -99.99 -99.99 -99.99 \n", "776 -99.99 -99.99 -99.99 \n", "777 -99.99 -99.99 -99.99 \n", "778 -99.99 -99.99 -99.99 \n", "779 -99.99 -99.99 -99.99 \n", "\n", " seasonally adjusted filled \n", "0 -99.99 \n", "1 -99.99 \n", "2 314.44 \n", "3 315.16 \n", "4 314.70 \n", "5 315.14 \n", "6 315.20 \n", "7 316.21 \n", "8 316.10 \n", "9 315.40 \n", "10 315.20 \n", "11 315.43 \n", "12 315.52 \n", "13 315.84 \n", "14 315.37 \n", "15 315.42 \n", "16 315.48 \n", "17 316.02 \n", "18 315.87 \n", "19 316.08 \n", "20 316.74 \n", "21 316.33 \n", "22 316.69 \n", "23 316.35 \n", "24 316.37 \n", "25 316.33 \n", "26 316.27 \n", "27 316.70 \n", "28 317.21 \n", "29 317.46 \n", ".. ... \n", "750 413.64 \n", "751 414.10 \n", "752 414.69 \n", "753 414.73 \n", "754 415.15 \n", "755 414.81 \n", "756 415.08 \n", "757 415.69 \n", "758 415.62 \n", "759 415.46 \n", "760 415.55 \n", "761 416.12 \n", "762 415.84 \n", "763 415.89 \n", "764 416.42 \n", "765 417.17 \n", "766 417.09 \n", "767 417.36 \n", "768 417.94 \n", "769 418.20 \n", "770 416.90 \n", "771 417.23 \n", "772 -99.99 \n", "773 -99.99 \n", "774 -99.99 \n", "775 -99.99 \n", "776 -99.99 \n", "777 -99.99 \n", "778 -99.99 \n", "779 -99.99 \n", "\n", "[780 rows x 10 columns]" ] }, "execution_count": 9, "metadata": {}, "output_type": "execute_result" } ], "source": [ "data" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "## Inspection et traitement des données brutes" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "On peut déjà voir que les données manquantes sont représentées par \"-99.99\". On remplace d'abord celles-ci par np.Nan" ] }, { "cell_type": "code", "execution_count": 10, "metadata": {}, "outputs": [ { "data": { "text/plain": [ "array(['2022', ' 12', ' 44910', ' 2022.9562', ' -99.99', ' -99.99',\n", " ' -99.99', ' -99.99', ' -99.99', ' -99.99'],\n", " dtype=object)" ] }, "execution_count": 10, "metadata": {}, "output_type": "execute_result" } ], "source": [ "data.iloc[779].values" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "Il y a des espaces à retirer: on utilise une fonctions." ] }, { "cell_type": "code", "execution_count": 11, "metadata": {}, "outputs": [], "source": [ "data = data.apply(lambda x: x.str.strip() if x.dtype == \"object\" else x)" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "On regarde à nouveau la même ligne." ] }, { "cell_type": "code", "execution_count": 12, "metadata": {}, "outputs": [ { "data": { "text/plain": [ "array(['2022', '12', '44910', '2022.9562', '-99.99', '-99.99', '-99.99',\n", " '-99.99', '-99.99', '-99.99'], dtype=object)" ] }, "execution_count": 12, "metadata": {}, "output_type": "execute_result" } ], "source": [ "data.iloc[779].values" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "Maintenant, on replace '-99.99' par np.nan." ] }, { "cell_type": "code", "execution_count": 13, "metadata": {}, "outputs": [], "source": [ "import numpy as np\n", "data = data.replace('-99.99', np.nan)" ] }, { "cell_type": "code", "execution_count": 14, "metadata": {}, "outputs": [ { "data": { "text/plain": [ "array(['2022', '12', '44910', '2022.9562', nan, nan, nan, nan, nan, nan],\n", " dtype=object)" ] }, "execution_count": 14, "metadata": {}, "output_type": "execute_result" } ], "source": [ "data.iloc[779].values" ] }, { "cell_type": "code", "execution_count": 15, "metadata": {}, "outputs": [ { "data": { "text/plain": [ "array(['2021', '05', '44331', '2021.3699', '418.95', '415.55', '419.23',\n", " '415.82', '418.95', '415.55'], dtype=object)" ] }, "execution_count": 15, "metadata": {}, "output_type": "execute_result" } ], "source": [ "data.iloc[760].values" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "Desormais, nous pouvons convertir les colonnes avec le type requis. Nous allons seulement nous concentrer sur les valeurs corrigés de la dernière colonne." ] }, { "cell_type": "code", "execution_count": 16, "metadata": {}, "outputs": [], "source": [ "data['seasonally adjusted filled'] = data['seasonally adjusted filled'].astype(float)" ] }, { "cell_type": "code", "execution_count": 17, "metadata": {}, "outputs": [ { "data": { "text/plain": [ "0 NaN\n", "1 NaN\n", "2 314.44\n", "3 315.16\n", "4 314.70\n", "5 315.14\n", "6 315.20\n", "7 316.21\n", "8 316.10\n", "9 315.40\n", "10 315.20\n", "11 315.43\n", "12 315.52\n", "13 315.84\n", "14 315.37\n", "15 315.42\n", "16 315.48\n", "17 316.02\n", "18 315.87\n", "19 316.08\n", "20 316.74\n", "21 316.33\n", "22 316.69\n", "23 316.35\n", "24 316.37\n", "25 316.33\n", "26 316.27\n", "27 316.70\n", "28 317.21\n", "29 317.46\n", " ... \n", "750 413.64\n", "751 414.10\n", "752 414.69\n", "753 414.73\n", "754 415.15\n", "755 414.81\n", "756 415.08\n", "757 415.69\n", "758 415.62\n", "759 415.46\n", "760 415.55\n", "761 416.12\n", "762 415.84\n", "763 415.89\n", "764 416.42\n", "765 417.17\n", "766 417.09\n", "767 417.36\n", "768 417.94\n", "769 418.20\n", "770 416.90\n", "771 417.23\n", "772 NaN\n", "773 NaN\n", "774 NaN\n", "775 NaN\n", "776 NaN\n", "777 NaN\n", "778 NaN\n", "779 NaN\n", "Name: seasonally adjusted filled, Length: 780, dtype: float64" ] }, "execution_count": 17, "metadata": {}, "output_type": "execute_result" } ], "source": [ "data['seasonally adjusted filled']" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "Dans l'entête du document, on peut lire \"The monthly values have been adjusted to 24:00 hours on the 15th of each month.'. Cependant, nous prenons comme référence le 1er du mois comme référence, car cela sera sans conséquence pour la suite." ] }, { "cell_type": "code", "execution_count": 18, "metadata": {}, "outputs": [ { "name": "stdout", "output_type": "stream", "text": [ "[Timestamp('1958-01-01 00:00:00'), Timestamp('1958-02-01 00:00:00'), Timestamp('1958-03-01 00:00:00'), Timestamp('1958-04-01 00:00:00'), Timestamp('1958-05-01 00:00:00'), Timestamp('1958-06-01 00:00:00'), Timestamp('1958-07-01 00:00:00'), Timestamp('1958-08-01 00:00:00'), Timestamp('1958-09-01 00:00:00'), Timestamp('1958-10-01 00:00:00'), Timestamp('1958-11-01 00:00:00'), Timestamp('1958-12-01 00:00:00'), Timestamp('1959-01-01 00:00:00'), Timestamp('1959-02-01 00:00:00'), Timestamp('1959-03-01 00:00:00'), Timestamp('1959-04-01 00:00:00'), Timestamp('1959-05-01 00:00:00'), Timestamp('1959-06-01 00:00:00'), Timestamp('1959-07-01 00:00:00'), Timestamp('1959-08-01 00:00:00'), Timestamp('1959-09-01 00:00:00'), Timestamp('1959-10-01 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Timestamp('2017-11-01 00:00:00'), Timestamp('2017-12-01 00:00:00'), Timestamp('2018-01-01 00:00:00'), Timestamp('2018-02-01 00:00:00'), Timestamp('2018-03-01 00:00:00'), Timestamp('2018-04-01 00:00:00'), Timestamp('2018-05-01 00:00:00'), Timestamp('2018-06-01 00:00:00'), Timestamp('2018-07-01 00:00:00'), Timestamp('2018-08-01 00:00:00'), Timestamp('2018-09-01 00:00:00'), Timestamp('2018-10-01 00:00:00'), Timestamp('2018-11-01 00:00:00'), Timestamp('2018-12-01 00:00:00'), Timestamp('2019-01-01 00:00:00'), Timestamp('2019-02-01 00:00:00'), Timestamp('2019-03-01 00:00:00'), Timestamp('2019-04-01 00:00:00'), Timestamp('2019-05-01 00:00:00'), Timestamp('2019-06-01 00:00:00'), Timestamp('2019-07-01 00:00:00'), Timestamp('2019-08-01 00:00:00'), Timestamp('2019-09-01 00:00:00'), Timestamp('2019-10-01 00:00:00'), Timestamp('2019-11-01 00:00:00'), Timestamp('2019-12-01 00:00:00'), Timestamp('2020-01-01 00:00:00'), Timestamp('2020-02-01 00:00:00'), Timestamp('2020-03-01 00:00:00'), Timestamp('2020-04-01 00:00:00'), Timestamp('2020-05-01 00:00:00'), Timestamp('2020-06-01 00:00:00'), Timestamp('2020-07-01 00:00:00'), Timestamp('2020-08-01 00:00:00'), Timestamp('2020-09-01 00:00:00'), Timestamp('2020-10-01 00:00:00'), Timestamp('2020-11-01 00:00:00'), Timestamp('2020-12-01 00:00:00'), Timestamp('2021-01-01 00:00:00'), Timestamp('2021-02-01 00:00:00'), Timestamp('2021-03-01 00:00:00'), Timestamp('2021-04-01 00:00:00'), Timestamp('2021-05-01 00:00:00'), Timestamp('2021-06-01 00:00:00'), Timestamp('2021-07-01 00:00:00'), Timestamp('2021-08-01 00:00:00'), Timestamp('2021-09-01 00:00:00'), Timestamp('2021-10-01 00:00:00'), Timestamp('2021-11-01 00:00:00'), Timestamp('2021-12-01 00:00:00'), Timestamp('2022-01-01 00:00:00'), Timestamp('2022-02-01 00:00:00'), Timestamp('2022-03-01 00:00:00'), Timestamp('2022-04-01 00:00:00'), Timestamp('2022-05-01 00:00:00'), Timestamp('2022-06-01 00:00:00'), Timestamp('2022-07-01 00:00:00'), Timestamp('2022-08-01 00:00:00'), Timestamp('2022-09-01 00:00:00'), Timestamp('2022-10-01 00:00:00'), Timestamp('2022-11-01 00:00:00'), Timestamp('2022-12-01 00:00:00')]\n" ] } ], "source": [ "dates = []\n", "years = data.Yr\n", "months = data.Mn\n", "for year, month in zip(years, months):\n", " date = pd.Timestamp(year=int(year), month=int(month), day=1)\n", " dates.append(date)\n", "print(dates)" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "On va utiliser ces dates comme index de notre DataFrame." ] }, { "cell_type": "code", "execution_count": 19, "metadata": {}, "outputs": [], "source": [ "data['date'] = dates\n", "data.set_index('date', inplace=True)" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "Nous allons aussi retirer toutes les lignes avec des valeurs 'Nan' dans cette dernière colonne." ] }, { "cell_type": "code", "execution_count": 20, "metadata": {}, "outputs": [], "source": [ "data = data[data['seasonally adjusted filled'].notna()]" ] }, { "cell_type": "code", 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YrMnDateDateCO2seasonally adjustedfitseasonally adjusted fitCO2 filledseasonally adjusted filled
date
1958-03-01195803212591958.2027315.71314.44316.19314.91315.71314.44
1958-04-01195804212901958.2877317.45315.16317.29314.99317.45315.16
1958-05-01195805213201958.3699317.51314.70317.87315.06317.51314.70
1958-06-01195806213511958.4548NaNNaN317.25315.14317.25315.14
1958-07-01195807213811958.5370315.86315.20315.85315.22315.86315.20
1958-08-01195808214121958.6219314.93316.21313.97315.29314.93316.21
1958-09-01195809214431958.7068313.21316.10312.44315.35313.21316.10
1958-10-01195810214731958.7890NaNNaN312.43315.40312.43315.40
1958-11-01195811215041958.8740313.33315.20313.60315.46313.33315.20
1958-12-01195812215341958.9562314.67315.43314.76315.51314.67315.43
1959-01-01195901215651959.0411315.58315.52315.64315.57315.58315.52
1959-02-01195902215961959.1260316.49315.84316.28315.63316.49315.84
1959-03-01195903216241959.2027316.65315.37316.98315.69316.65315.37
1959-04-01195904216551959.2877317.72315.42318.08315.76317.72315.42
1959-05-01195905216851959.3699318.29315.48318.66315.84318.29315.48
1959-06-01195906217161959.4548318.15316.02318.05315.93318.15316.02
1959-07-01195907217461959.5370316.54315.87316.66316.02316.54315.87
1959-08-01195908217771959.6219314.80316.08314.80316.12314.80316.08
1959-09-01195909218081959.7068313.84316.74313.30316.21313.84316.74
1959-10-01195910218381959.7890313.33316.33313.32316.30313.33316.33
1959-11-01195911218691959.8740314.81316.69314.53316.39314.81316.69
1959-12-01195912218991959.9562315.58316.35315.72316.47315.58316.35
1960-01-01196001219301960.0410316.43316.37316.62316.55316.43316.37
1960-02-01196002219611960.1257316.98316.33317.29316.63316.98316.33
1960-03-01196003219901960.2049317.58316.27318.03316.71317.58316.27
1960-04-01196004220211960.2896319.03316.70319.14316.79319.03316.70
1960-05-01196005220511960.3716320.03317.21319.68316.86320.03317.21
1960-06-01196006220821960.4563319.58317.46319.02316.92319.58317.46
1960-07-01196007221121960.5383318.18317.53317.59316.97318.18317.53
1960-08-01196008221431960.6230315.90317.22315.67317.01315.90317.22
.................................
2019-11-01201911437842019.8740410.16412.43410.15412.39410.16412.43
2019-12-01201912438142019.9562411.81412.74411.69412.60411.81412.74
2020-01-01202001438452020.0410413.30413.24412.90412.82413.30413.24
2020-02-01202002438762020.1257414.05413.27413.81413.03414.05413.27
2020-03-01202003439052020.2049414.45412.88414.80413.22414.45412.88
2020-04-01202004439362020.2896416.11413.31416.24413.42416.11413.31
2020-05-01202005439662020.3716417.15413.76417.01413.62417.15413.76
2020-06-01202006439972020.4563416.29413.74416.34413.82416.29413.74
2020-07-01202007440272020.5383414.42413.64414.75414.01414.42413.64
2020-08-01202008440582020.6230412.52414.10412.60414.22412.52414.10
2020-09-01202009440892020.7077411.18414.69410.88414.41411.18414.69
2020-10-01202010441192020.7896411.12414.73411.01414.60411.12414.73
2020-11-01202011441502020.8743412.88415.15412.55414.79412.88415.15
2020-12-01202012441802020.9563413.89414.81414.06414.97413.89414.81
2021-01-01202101442112021.0411415.15415.08415.23415.15415.15415.08
2021-02-01202102442422021.1260416.47415.69416.12415.32416.47415.69
2021-03-01202103442702021.2027417.16415.62417.04415.48417.16415.62
2021-04-01202104443012021.2877418.24415.46418.45415.65418.24415.46
2021-05-01202105443312021.3699418.95415.55419.23415.82418.95415.55
2021-06-01202106443622021.4548418.70416.12418.56416.00418.70416.12
2021-07-01202107443922021.5370416.65415.84416.96416.18416.65415.84
2021-08-01202108444232021.6219414.34415.89414.78416.37414.34415.89
2021-09-01202109444542021.7068412.90416.42413.04416.57412.90416.42
2021-10-01202110444842021.7890413.55417.17413.15416.76413.55417.17
2021-11-01202111445152021.8740414.82417.09414.70416.95414.82417.09
2021-12-01202112445452021.9562416.43417.36416.21417.12416.43417.36
2022-01-01202201445762022.0411418.01417.94417.37417.28418.01417.94
2022-02-01202202446072022.1260418.99418.20418.23417.43418.99418.20
2022-03-01202203446352022.2027418.45416.90419.12417.56418.45416.90
2022-04-01202204446662022.2877420.02417.23NaNNaN420.02417.23
\n", "

770 rows × 10 columns

\n", "
" ], "text/plain": [ " Yr Mn Date Date CO2 seasonally adjusted fit \\\n", "date \n", "1958-03-01 1958 03 21259 1958.2027 315.71 314.44 316.19 \n", "1958-04-01 1958 04 21290 1958.2877 317.45 315.16 317.29 \n", "1958-05-01 1958 05 21320 1958.3699 317.51 314.70 317.87 \n", "1958-06-01 1958 06 21351 1958.4548 NaN NaN 317.25 \n", "1958-07-01 1958 07 21381 1958.5370 315.86 315.20 315.85 \n", "1958-08-01 1958 08 21412 1958.6219 314.93 316.21 313.97 \n", "1958-09-01 1958 09 21443 1958.7068 313.21 316.10 312.44 \n", "1958-10-01 1958 10 21473 1958.7890 NaN NaN 312.43 \n", "1958-11-01 1958 11 21504 1958.8740 313.33 315.20 313.60 \n", "1958-12-01 1958 12 21534 1958.9562 314.67 315.43 314.76 \n", "1959-01-01 1959 01 21565 1959.0411 315.58 315.52 315.64 \n", "1959-02-01 1959 02 21596 1959.1260 316.49 315.84 316.28 \n", "1959-03-01 1959 03 21624 1959.2027 316.65 315.37 316.98 \n", "1959-04-01 1959 04 21655 1959.2877 317.72 315.42 318.08 \n", "1959-05-01 1959 05 21685 1959.3699 318.29 315.48 318.66 \n", "1959-06-01 1959 06 21716 1959.4548 318.15 316.02 318.05 \n", "1959-07-01 1959 07 21746 1959.5370 316.54 315.87 316.66 \n", "1959-08-01 1959 08 21777 1959.6219 314.80 316.08 314.80 \n", "1959-09-01 1959 09 21808 1959.7068 313.84 316.74 313.30 \n", "1959-10-01 1959 10 21838 1959.7890 313.33 316.33 313.32 \n", "1959-11-01 1959 11 21869 1959.8740 314.81 316.69 314.53 \n", "1959-12-01 1959 12 21899 1959.9562 315.58 316.35 315.72 \n", "1960-01-01 1960 01 21930 1960.0410 316.43 316.37 316.62 \n", "1960-02-01 1960 02 21961 1960.1257 316.98 316.33 317.29 \n", "1960-03-01 1960 03 21990 1960.2049 317.58 316.27 318.03 \n", "1960-04-01 1960 04 22021 1960.2896 319.03 316.70 319.14 \n", "1960-05-01 1960 05 22051 1960.3716 320.03 317.21 319.68 \n", "1960-06-01 1960 06 22082 1960.4563 319.58 317.46 319.02 \n", "1960-07-01 1960 07 22112 1960.5383 318.18 317.53 317.59 \n", "1960-08-01 1960 08 22143 1960.6230 315.90 317.22 315.67 \n", "... ... .. ... ... ... ... ... \n", "2019-11-01 2019 11 43784 2019.8740 410.16 412.43 410.15 \n", "2019-12-01 2019 12 43814 2019.9562 411.81 412.74 411.69 \n", "2020-01-01 2020 01 43845 2020.0410 413.30 413.24 412.90 \n", "2020-02-01 2020 02 43876 2020.1257 414.05 413.27 413.81 \n", "2020-03-01 2020 03 43905 2020.2049 414.45 412.88 414.80 \n", "2020-04-01 2020 04 43936 2020.2896 416.11 413.31 416.24 \n", "2020-05-01 2020 05 43966 2020.3716 417.15 413.76 417.01 \n", "2020-06-01 2020 06 43997 2020.4563 416.29 413.74 416.34 \n", "2020-07-01 2020 07 44027 2020.5383 414.42 413.64 414.75 \n", "2020-08-01 2020 08 44058 2020.6230 412.52 414.10 412.60 \n", "2020-09-01 2020 09 44089 2020.7077 411.18 414.69 410.88 \n", "2020-10-01 2020 10 44119 2020.7896 411.12 414.73 411.01 \n", "2020-11-01 2020 11 44150 2020.8743 412.88 415.15 412.55 \n", "2020-12-01 2020 12 44180 2020.9563 413.89 414.81 414.06 \n", "2021-01-01 2021 01 44211 2021.0411 415.15 415.08 415.23 \n", "2021-02-01 2021 02 44242 2021.1260 416.47 415.69 416.12 \n", "2021-03-01 2021 03 44270 2021.2027 417.16 415.62 417.04 \n", "2021-04-01 2021 04 44301 2021.2877 418.24 415.46 418.45 \n", "2021-05-01 2021 05 44331 2021.3699 418.95 415.55 419.23 \n", "2021-06-01 2021 06 44362 2021.4548 418.70 416.12 418.56 \n", "2021-07-01 2021 07 44392 2021.5370 416.65 415.84 416.96 \n", "2021-08-01 2021 08 44423 2021.6219 414.34 415.89 414.78 \n", "2021-09-01 2021 09 44454 2021.7068 412.90 416.42 413.04 \n", "2021-10-01 2021 10 44484 2021.7890 413.55 417.17 413.15 \n", "2021-11-01 2021 11 44515 2021.8740 414.82 417.09 414.70 \n", "2021-12-01 2021 12 44545 2021.9562 416.43 417.36 416.21 \n", "2022-01-01 2022 01 44576 2022.0411 418.01 417.94 417.37 \n", "2022-02-01 2022 02 44607 2022.1260 418.99 418.20 418.23 \n", "2022-03-01 2022 03 44635 2022.2027 418.45 416.90 419.12 \n", "2022-04-01 2022 04 44666 2022.2877 420.02 417.23 NaN \n", "\n", " seasonally adjusted fit CO2 filled seasonally adjusted filled \n", "date \n", "1958-03-01 314.91 315.71 314.44 \n", "1958-04-01 314.99 317.45 315.16 \n", "1958-05-01 315.06 317.51 314.70 \n", "1958-06-01 315.14 317.25 315.14 \n", "1958-07-01 315.22 315.86 315.20 \n", "1958-08-01 315.29 314.93 316.21 \n", "1958-09-01 315.35 313.21 316.10 \n", "1958-10-01 315.40 312.43 315.40 \n", "1958-11-01 315.46 313.33 315.20 \n", "1958-12-01 315.51 314.67 315.43 \n", "1959-01-01 315.57 315.58 315.52 \n", "1959-02-01 315.63 316.49 315.84 \n", "1959-03-01 315.69 316.65 315.37 \n", "1959-04-01 315.76 317.72 315.42 \n", "1959-05-01 315.84 318.29 315.48 \n", "1959-06-01 315.93 318.15 316.02 \n", "1959-07-01 316.02 316.54 315.87 \n", "1959-08-01 316.12 314.80 316.08 \n", "1959-09-01 316.21 313.84 316.74 \n", "1959-10-01 316.30 313.33 316.33 \n", "1959-11-01 316.39 314.81 316.69 \n", "1959-12-01 316.47 315.58 316.35 \n", "1960-01-01 316.55 316.43 316.37 \n", "1960-02-01 316.63 316.98 316.33 \n", "1960-03-01 316.71 317.58 316.27 \n", "1960-04-01 316.79 319.03 316.70 \n", "1960-05-01 316.86 320.03 317.21 \n", "1960-06-01 316.92 319.58 317.46 \n", "1960-07-01 316.97 318.18 317.53 \n", "1960-08-01 317.01 315.90 317.22 \n", "... ... ... ... \n", "2019-11-01 412.39 410.16 412.43 \n", "2019-12-01 412.60 411.81 412.74 \n", "2020-01-01 412.82 413.30 413.24 \n", "2020-02-01 413.03 414.05 413.27 \n", "2020-03-01 413.22 414.45 412.88 \n", "2020-04-01 413.42 416.11 413.31 \n", "2020-05-01 413.62 417.15 413.76 \n", "2020-06-01 413.82 416.29 413.74 \n", "2020-07-01 414.01 414.42 413.64 \n", "2020-08-01 414.22 412.52 414.10 \n", "2020-09-01 414.41 411.18 414.69 \n", "2020-10-01 414.60 411.12 414.73 \n", "2020-11-01 414.79 412.88 415.15 \n", "2020-12-01 414.97 413.89 414.81 \n", "2021-01-01 415.15 415.15 415.08 \n", "2021-02-01 415.32 416.47 415.69 \n", "2021-03-01 415.48 417.16 415.62 \n", "2021-04-01 415.65 418.24 415.46 \n", "2021-05-01 415.82 418.95 415.55 \n", "2021-06-01 416.00 418.70 416.12 \n", "2021-07-01 416.18 416.65 415.84 \n", "2021-08-01 416.37 414.34 415.89 \n", "2021-09-01 416.57 412.90 416.42 \n", "2021-10-01 416.76 413.55 417.17 \n", "2021-11-01 416.95 414.82 417.09 \n", "2021-12-01 417.12 416.43 417.36 \n", "2022-01-01 417.28 418.01 417.94 \n", "2022-02-01 417.43 418.99 418.20 \n", "2022-03-01 417.56 418.45 416.90 \n", "2022-04-01 NaN 420.02 417.23 \n", "\n", "[770 rows x 10 columns]" ] }, "execution_count": 21, "metadata": {}, "output_type": "execute_result" } ], "source": [ "data" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "On peut constater la donnée prête à être traîtée. Essayons de traçer rapidement la donnée." ] }, { "cell_type": "code", "execution_count": 22, "metadata": {}, "outputs": [ { "data": { "text/plain": [ "" ] }, "execution_count": 22, "metadata": {}, "output_type": "execute_result" }, { "data": { "image/png": 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\n", 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" ] }, "metadata": { "needs_background": "light" }, "output_type": "display_data" } ], "source": [ "data['seasonally adjusted filled'].plot()" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "Regardons sur une période de 10 ans." ] }, { "cell_type": "code", "execution_count": 23, "metadata": {}, "outputs": [ { "data": { "text/plain": [ "" ] }, "execution_count": 23, "metadata": {}, "output_type": "execute_result" }, { "data": { "image/png": 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\n", 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" ] }, "metadata": { "needs_background": "light" }, "output_type": "display_data" } ], "source": [ "period = (pd.Timestamp(year=1969,month=1,day=1)<=data.index) & (data.index<=pd.Timestamp(year=1979,month=1,day=1))\n", "data[period].plot()" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "Il semble que l'évolution de la concentration atmosphérique de CO2 soit la somme d'une tendance linéaire et d'un signal périodique." ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "## Analyse saisonnière" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "Nous allons utiliser le module d'analyse saisonnière de `statsmodels` pour décomposer l'évolution de la concentration atmosphérique de CO2 en la somme d'une tendance et un motif périodique. On utiliste un modèle additif: Y[t] = T[t] + S[t] + e[t]. L'évolution est la somme d'une tendance, d'un signal périodique et d'un bruit." ] }, { "cell_type": "code", "execution_count": 24, "metadata": {}, "outputs": [], "source": [ "from statsmodels.tsa.seasonal import seasonal_decompose" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "Nous devons indiquer la fréquence des observations à statsmodels" ] }, { "cell_type": "code", "execution_count": 25, "metadata": {}, "outputs": [], "source": [ "data.index = pd.DatetimeIndex(data.index.values, freq = 'MS')" ] }, { "cell_type": "code", "execution_count": 26, "metadata": {}, "outputs": [ { "data": { "text/html": [ "
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YrMnDateDateCO2seasonally adjustedfitseasonally adjusted fitCO2 filledseasonally adjusted filled
1958-03-01195803212591958.2027315.71314.44316.19314.91315.71314.44
1958-04-01195804212901958.2877317.45315.16317.29314.99317.45315.16
1958-05-01195805213201958.3699317.51314.70317.87315.06317.51314.70
1958-06-01195806213511958.4548NaNNaN317.25315.14317.25315.14
1958-07-01195807213811958.5370315.86315.20315.85315.22315.86315.20
1958-08-01195808214121958.6219314.93316.21313.97315.29314.93316.21
1958-09-01195809214431958.7068313.21316.10312.44315.35313.21316.10
1958-10-01195810214731958.7890NaNNaN312.43315.40312.43315.40
1958-11-01195811215041958.8740313.33315.20313.60315.46313.33315.20
1958-12-01195812215341958.9562314.67315.43314.76315.51314.67315.43
1959-01-01195901215651959.0411315.58315.52315.64315.57315.58315.52
1959-02-01195902215961959.1260316.49315.84316.28315.63316.49315.84
1959-03-01195903216241959.2027316.65315.37316.98315.69316.65315.37
1959-04-01195904216551959.2877317.72315.42318.08315.76317.72315.42
1959-05-01195905216851959.3699318.29315.48318.66315.84318.29315.48
1959-06-01195906217161959.4548318.15316.02318.05315.93318.15316.02
1959-07-01195907217461959.5370316.54315.87316.66316.02316.54315.87
1959-08-01195908217771959.6219314.80316.08314.80316.12314.80316.08
1959-09-01195909218081959.7068313.84316.74313.30316.21313.84316.74
1959-10-01195910218381959.7890313.33316.33313.32316.30313.33316.33
1959-11-01195911218691959.8740314.81316.69314.53316.39314.81316.69
1959-12-01195912218991959.9562315.58316.35315.72316.47315.58316.35
1960-01-01196001219301960.0410316.43316.37316.62316.55316.43316.37
1960-02-01196002219611960.1257316.98316.33317.29316.63316.98316.33
1960-03-01196003219901960.2049317.58316.27318.03316.71317.58316.27
1960-04-01196004220211960.2896319.03316.70319.14316.79319.03316.70
1960-05-01196005220511960.3716320.03317.21319.68316.86320.03317.21
1960-06-01196006220821960.4563319.58317.46319.02316.92319.58317.46
1960-07-01196007221121960.5383318.18317.53317.59316.97318.18317.53
1960-08-01196008221431960.6230315.90317.22315.67317.01315.90317.22
.................................
2019-11-01201911437842019.8740410.16412.43410.15412.39410.16412.43
2019-12-01201912438142019.9562411.81412.74411.69412.60411.81412.74
2020-01-01202001438452020.0410413.30413.24412.90412.82413.30413.24
2020-02-01202002438762020.1257414.05413.27413.81413.03414.05413.27
2020-03-01202003439052020.2049414.45412.88414.80413.22414.45412.88
2020-04-01202004439362020.2896416.11413.31416.24413.42416.11413.31
2020-05-01202005439662020.3716417.15413.76417.01413.62417.15413.76
2020-06-01202006439972020.4563416.29413.74416.34413.82416.29413.74
2020-07-01202007440272020.5383414.42413.64414.75414.01414.42413.64
2020-08-01202008440582020.6230412.52414.10412.60414.22412.52414.10
2020-09-01202009440892020.7077411.18414.69410.88414.41411.18414.69
2020-10-01202010441192020.7896411.12414.73411.01414.60411.12414.73
2020-11-01202011441502020.8743412.88415.15412.55414.79412.88415.15
2020-12-01202012441802020.9563413.89414.81414.06414.97413.89414.81
2021-01-01202101442112021.0411415.15415.08415.23415.15415.15415.08
2021-02-01202102442422021.1260416.47415.69416.12415.32416.47415.69
2021-03-01202103442702021.2027417.16415.62417.04415.48417.16415.62
2021-04-01202104443012021.2877418.24415.46418.45415.65418.24415.46
2021-05-01202105443312021.3699418.95415.55419.23415.82418.95415.55
2021-06-01202106443622021.4548418.70416.12418.56416.00418.70416.12
2021-07-01202107443922021.5370416.65415.84416.96416.18416.65415.84
2021-08-01202108444232021.6219414.34415.89414.78416.37414.34415.89
2021-09-01202109444542021.7068412.90416.42413.04416.57412.90416.42
2021-10-01202110444842021.7890413.55417.17413.15416.76413.55417.17
2021-11-01202111445152021.8740414.82417.09414.70416.95414.82417.09
2021-12-01202112445452021.9562416.43417.36416.21417.12416.43417.36
2022-01-01202201445762022.0411418.01417.94417.37417.28418.01417.94
2022-02-01202202446072022.1260418.99418.20418.23417.43418.99418.20
2022-03-01202203446352022.2027418.45416.90419.12417.56418.45416.90
2022-04-01202204446662022.2877420.02417.23NaNNaN420.02417.23
\n", "

770 rows × 10 columns

\n", "
" ], "text/plain": [ " Yr Mn Date Date CO2 seasonally adjusted fit \\\n", "1958-03-01 1958 03 21259 1958.2027 315.71 314.44 316.19 \n", "1958-04-01 1958 04 21290 1958.2877 317.45 315.16 317.29 \n", "1958-05-01 1958 05 21320 1958.3699 317.51 314.70 317.87 \n", "1958-06-01 1958 06 21351 1958.4548 NaN NaN 317.25 \n", "1958-07-01 1958 07 21381 1958.5370 315.86 315.20 315.85 \n", "1958-08-01 1958 08 21412 1958.6219 314.93 316.21 313.97 \n", "1958-09-01 1958 09 21443 1958.7068 313.21 316.10 312.44 \n", "1958-10-01 1958 10 21473 1958.7890 NaN NaN 312.43 \n", "1958-11-01 1958 11 21504 1958.8740 313.33 315.20 313.60 \n", "1958-12-01 1958 12 21534 1958.9562 314.67 315.43 314.76 \n", "1959-01-01 1959 01 21565 1959.0411 315.58 315.52 315.64 \n", "1959-02-01 1959 02 21596 1959.1260 316.49 315.84 316.28 \n", "1959-03-01 1959 03 21624 1959.2027 316.65 315.37 316.98 \n", "1959-04-01 1959 04 21655 1959.2877 317.72 315.42 318.08 \n", "1959-05-01 1959 05 21685 1959.3699 318.29 315.48 318.66 \n", "1959-06-01 1959 06 21716 1959.4548 318.15 316.02 318.05 \n", "1959-07-01 1959 07 21746 1959.5370 316.54 315.87 316.66 \n", "1959-08-01 1959 08 21777 1959.6219 314.80 316.08 314.80 \n", "1959-09-01 1959 09 21808 1959.7068 313.84 316.74 313.30 \n", "1959-10-01 1959 10 21838 1959.7890 313.33 316.33 313.32 \n", "1959-11-01 1959 11 21869 1959.8740 314.81 316.69 314.53 \n", "1959-12-01 1959 12 21899 1959.9562 315.58 316.35 315.72 \n", "1960-01-01 1960 01 21930 1960.0410 316.43 316.37 316.62 \n", "1960-02-01 1960 02 21961 1960.1257 316.98 316.33 317.29 \n", "1960-03-01 1960 03 21990 1960.2049 317.58 316.27 318.03 \n", "1960-04-01 1960 04 22021 1960.2896 319.03 316.70 319.14 \n", "1960-05-01 1960 05 22051 1960.3716 320.03 317.21 319.68 \n", "1960-06-01 1960 06 22082 1960.4563 319.58 317.46 319.02 \n", "1960-07-01 1960 07 22112 1960.5383 318.18 317.53 317.59 \n", "1960-08-01 1960 08 22143 1960.6230 315.90 317.22 315.67 \n", "... ... .. ... ... ... ... ... \n", "2019-11-01 2019 11 43784 2019.8740 410.16 412.43 410.15 \n", "2019-12-01 2019 12 43814 2019.9562 411.81 412.74 411.69 \n", "2020-01-01 2020 01 43845 2020.0410 413.30 413.24 412.90 \n", "2020-02-01 2020 02 43876 2020.1257 414.05 413.27 413.81 \n", "2020-03-01 2020 03 43905 2020.2049 414.45 412.88 414.80 \n", "2020-04-01 2020 04 43936 2020.2896 416.11 413.31 416.24 \n", "2020-05-01 2020 05 43966 2020.3716 417.15 413.76 417.01 \n", "2020-06-01 2020 06 43997 2020.4563 416.29 413.74 416.34 \n", "2020-07-01 2020 07 44027 2020.5383 414.42 413.64 414.75 \n", "2020-08-01 2020 08 44058 2020.6230 412.52 414.10 412.60 \n", "2020-09-01 2020 09 44089 2020.7077 411.18 414.69 410.88 \n", "2020-10-01 2020 10 44119 2020.7896 411.12 414.73 411.01 \n", "2020-11-01 2020 11 44150 2020.8743 412.88 415.15 412.55 \n", "2020-12-01 2020 12 44180 2020.9563 413.89 414.81 414.06 \n", "2021-01-01 2021 01 44211 2021.0411 415.15 415.08 415.23 \n", "2021-02-01 2021 02 44242 2021.1260 416.47 415.69 416.12 \n", "2021-03-01 2021 03 44270 2021.2027 417.16 415.62 417.04 \n", "2021-04-01 2021 04 44301 2021.2877 418.24 415.46 418.45 \n", "2021-05-01 2021 05 44331 2021.3699 418.95 415.55 419.23 \n", "2021-06-01 2021 06 44362 2021.4548 418.70 416.12 418.56 \n", "2021-07-01 2021 07 44392 2021.5370 416.65 415.84 416.96 \n", "2021-08-01 2021 08 44423 2021.6219 414.34 415.89 414.78 \n", "2021-09-01 2021 09 44454 2021.7068 412.90 416.42 413.04 \n", "2021-10-01 2021 10 44484 2021.7890 413.55 417.17 413.15 \n", "2021-11-01 2021 11 44515 2021.8740 414.82 417.09 414.70 \n", "2021-12-01 2021 12 44545 2021.9562 416.43 417.36 416.21 \n", "2022-01-01 2022 01 44576 2022.0411 418.01 417.94 417.37 \n", "2022-02-01 2022 02 44607 2022.1260 418.99 418.20 418.23 \n", "2022-03-01 2022 03 44635 2022.2027 418.45 416.90 419.12 \n", "2022-04-01 2022 04 44666 2022.2877 420.02 417.23 NaN \n", "\n", " seasonally adjusted fit CO2 filled seasonally adjusted filled \n", "1958-03-01 314.91 315.71 314.44 \n", "1958-04-01 314.99 317.45 315.16 \n", "1958-05-01 315.06 317.51 314.70 \n", "1958-06-01 315.14 317.25 315.14 \n", "1958-07-01 315.22 315.86 315.20 \n", "1958-08-01 315.29 314.93 316.21 \n", "1958-09-01 315.35 313.21 316.10 \n", "1958-10-01 315.40 312.43 315.40 \n", "1958-11-01 315.46 313.33 315.20 \n", "1958-12-01 315.51 314.67 315.43 \n", "1959-01-01 315.57 315.58 315.52 \n", "1959-02-01 315.63 316.49 315.84 \n", "1959-03-01 315.69 316.65 315.37 \n", "1959-04-01 315.76 317.72 315.42 \n", "1959-05-01 315.84 318.29 315.48 \n", "1959-06-01 315.93 318.15 316.02 \n", "1959-07-01 316.02 316.54 315.87 \n", "1959-08-01 316.12 314.80 316.08 \n", "1959-09-01 316.21 313.84 316.74 \n", "1959-10-01 316.30 313.33 316.33 \n", "1959-11-01 316.39 314.81 316.69 \n", "1959-12-01 316.47 315.58 316.35 \n", "1960-01-01 316.55 316.43 316.37 \n", "1960-02-01 316.63 316.98 316.33 \n", "1960-03-01 316.71 317.58 316.27 \n", "1960-04-01 316.79 319.03 316.70 \n", "1960-05-01 316.86 320.03 317.21 \n", "1960-06-01 316.92 319.58 317.46 \n", "1960-07-01 316.97 318.18 317.53 \n", "1960-08-01 317.01 315.90 317.22 \n", "... ... ... ... \n", "2019-11-01 412.39 410.16 412.43 \n", "2019-12-01 412.60 411.81 412.74 \n", "2020-01-01 412.82 413.30 413.24 \n", "2020-02-01 413.03 414.05 413.27 \n", "2020-03-01 413.22 414.45 412.88 \n", "2020-04-01 413.42 416.11 413.31 \n", "2020-05-01 413.62 417.15 413.76 \n", "2020-06-01 413.82 416.29 413.74 \n", "2020-07-01 414.01 414.42 413.64 \n", "2020-08-01 414.22 412.52 414.10 \n", "2020-09-01 414.41 411.18 414.69 \n", "2020-10-01 414.60 411.12 414.73 \n", "2020-11-01 414.79 412.88 415.15 \n", "2020-12-01 414.97 413.89 414.81 \n", "2021-01-01 415.15 415.15 415.08 \n", "2021-02-01 415.32 416.47 415.69 \n", "2021-03-01 415.48 417.16 415.62 \n", "2021-04-01 415.65 418.24 415.46 \n", "2021-05-01 415.82 418.95 415.55 \n", "2021-06-01 416.00 418.70 416.12 \n", "2021-07-01 416.18 416.65 415.84 \n", "2021-08-01 416.37 414.34 415.89 \n", "2021-09-01 416.57 412.90 416.42 \n", "2021-10-01 416.76 413.55 417.17 \n", "2021-11-01 416.95 414.82 417.09 \n", "2021-12-01 417.12 416.43 417.36 \n", "2022-01-01 417.28 418.01 417.94 \n", "2022-02-01 417.43 418.99 418.20 \n", "2022-03-01 417.56 418.45 416.90 \n", "2022-04-01 NaN 420.02 417.23 \n", "\n", "[770 rows x 10 columns]" ] }, "execution_count": 26, "metadata": {}, "output_type": "execute_result" } ], "source": [ "data" ] }, { "cell_type": "code", "execution_count": 27, "metadata": {}, "outputs": [], "source": [ "result = seasonal_decompose(data['seasonally adjusted filled'], model='ad')" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "Visualisons les résultats. Deux graphiques apparaissent à cause du notebook mais les deux sont absolument indentiques." ] }, { "cell_type": "code", "execution_count": 28, "metadata": {}, "outputs": [ { "data": { "image/png": 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\n", 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\n", "text/plain": [ "
" ] }, "metadata": { "needs_background": "light" }, "output_type": "display_data" } ], "source": [ "%matplotlib inline\n", "result.plot()" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "On peut voir que la courbe de mesure du C02 est bien la somme d'une tendance haussière, d'un motif saisonnier et d'un bruit qui appraît centré." ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "## Caractérisation du signal périodique" ] }, { "cell_type": "code", "execution_count": 29, "metadata": {}, "outputs": [], "source": [ "seasonal = result.seasonal" ] }, { "cell_type": "code", "execution_count": 30, "metadata": {}, "outputs": [ { "data": { "text/plain": [ "" ] }, "execution_count": 30, "metadata": {}, "output_type": "execute_result" }, { "data": { "image/png": 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\n", 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" ] }, "metadata": { "needs_background": "light" }, "output_type": "display_data" } ], "source": [ "seasonal[(pd.Timestamp(year=1969,month=1,day=1)<=data.index) & (data.index<=pd.Timestamp(year=1974,month=1,day=1))].plot()" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "Le signal périodique semble avoir une période d'un an, ce qui est cohérent avec ce que l'on s'imagine." ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "## Prédictions à 2025" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "Nous allons utiliser un simple modèle autoregessif pour prédire les valeurs de concentration jusqu'à fin 2025, basé la tendance des données historiques." ] }, { "cell_type": "code", "execution_count": 31, "metadata": {}, "outputs": [], "source": [ "import statsmodels.api as sm\n", "model = sm.tsa.AR(data['seasonally adjusted filled']).fit()" ] }, { "cell_type": "code", "execution_count": 32, "metadata": {}, "outputs": [ { "data": { "text/plain": [ "2022-04-01 417.474450\n", "2022-05-01 417.700892\n", "2022-06-01 418.026783\n", "2022-07-01 418.214831\n", "2022-08-01 418.477222\n", "2022-09-01 418.851828\n", "2022-10-01 419.125336\n", "2022-11-01 419.321020\n", "2022-12-01 419.557878\n", "2023-01-01 419.818090\n", "2023-02-01 419.956343\n", "2023-03-01 419.955904\n", "2023-04-01 420.153815\n", "2023-05-01 420.412869\n", "2023-06-01 420.724373\n", "2023-07-01 420.947375\n", "2023-08-01 421.261647\n", "2023-09-01 421.580019\n", "2023-10-01 421.843831\n", "2023-11-01 421.983701\n", "2023-12-01 422.175147\n", "2024-01-01 422.392138\n", "2024-02-01 422.581931\n", "2024-03-01 422.765989\n", "2024-04-01 422.985692\n", "2024-05-01 423.236671\n", "2024-06-01 423.486124\n", "2024-07-01 423.728360\n", "2024-08-01 423.988920\n", "2024-09-01 424.243029\n", "2024-10-01 424.470824\n", "2024-11-01 424.665367\n", "2024-12-01 424.872283\n", "2025-01-01 425.084218\n", "2025-02-01 425.301274\n", "2025-03-01 425.519118\n", "2025-04-01 425.755889\n", "2025-05-01 426.003422\n", "2025-06-01 426.248779\n", "2025-07-01 426.486635\n", "2025-08-01 426.724917\n", "2025-09-01 426.960411\n", "2025-10-01 427.186092\n", "2025-11-01 427.405423\n", "2025-12-01 427.627688\n", "Freq: MS, dtype: float64" ] }, "execution_count": 32, "metadata": {}, "output_type": "execute_result" } ], "source": [ "forecast_trend = model.predict(start=pd.Timestamp(year=2022,month=4,day=1), end=pd.Timestamp(year=2025,month=12,day=1))\n", "forecast_trend" ] }, { "cell_type": "code", "execution_count": 33, "metadata": {}, "outputs": [ { "data": { "text/plain": [ "1958-03-01 NaN\n", "1958-04-01 NaN\n", "1958-05-01 NaN\n", "1958-06-01 NaN\n", "1958-07-01 NaN\n", "1958-08-01 NaN\n", "1958-09-01 315.400417\n", "1958-10-01 315.450000\n", "1958-11-01 315.493333\n", "1958-12-01 315.562500\n", "1959-01-01 315.627083\n", "1959-02-01 315.649583\n", "1959-03-01 315.670833\n", "1959-04-01 315.736250\n", "1959-05-01 315.837083\n", "1959-06-01 315.937500\n", "1959-07-01 316.011250\n", "1959-08-01 316.067083\n", "1959-09-01 316.125000\n", "1959-10-01 316.215833\n", "1959-11-01 316.341250\n", "1959-12-01 316.473333\n", "1960-01-01 316.602500\n", "1960-02-01 316.719167\n", "1960-03-01 316.781250\n", "1960-04-01 316.817083\n", "1960-05-01 316.846250\n", "1960-06-01 316.879583\n", "1960-07-01 316.924583\n", "1960-08-01 316.974167\n", " ... \n", "2023-07-01 420.947375\n", "2023-08-01 421.261647\n", "2023-09-01 421.580019\n", "2023-10-01 421.843831\n", "2023-11-01 421.983701\n", "2023-12-01 422.175147\n", "2024-01-01 422.392138\n", "2024-02-01 422.581931\n", "2024-03-01 422.765989\n", "2024-04-01 422.985692\n", "2024-05-01 423.236671\n", "2024-06-01 423.486124\n", "2024-07-01 423.728360\n", "2024-08-01 423.988920\n", "2024-09-01 424.243029\n", "2024-10-01 424.470824\n", "2024-11-01 424.665367\n", "2024-12-01 424.872283\n", "2025-01-01 425.084218\n", "2025-02-01 425.301274\n", "2025-03-01 425.519118\n", "2025-04-01 425.755889\n", "2025-05-01 426.003422\n", "2025-06-01 426.248779\n", "2025-07-01 426.486635\n", "2025-08-01 426.724917\n", "2025-09-01 426.960411\n", "2025-10-01 427.186092\n", "2025-11-01 427.405423\n", "2025-12-01 427.627688\n", "Length: 815, dtype: float64" ] }, "execution_count": 33, "metadata": {}, "output_type": "execute_result" } ], "source": [ "historical_trend = result.trend\n", "historical_trend_color = ['blue' for _ in historical_trend]\n", "forecast_trend_color = ['red' for _ in forecast_trend]\n", "all_colors = [*historical_trend_color, *forecast_trend_color]\n", "all_points = pd.concat([historical_trend, forecast_trend], axis = 0)\n", "all_points" ] }, { "cell_type": "code", "execution_count": 34, "metadata": {}, "outputs": [ { "data": { "text/plain": [ "" ] }, "execution_count": 34, "metadata": {}, "output_type": "execute_result" }, { "data": { "image/png": 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\n", 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" ] }, "metadata": { "needs_background": "light" }, "output_type": "display_data" } ], "source": [ "plt.scatter(all_points.index, all_points.values, c=all_colors,s=1)" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "On peut voir la prédiction en rouge jusqu'à fin 2025." ] } ], "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": "3.6.4" } }, "nbformat": 4, "nbformat_minor": 2 }