{ "cells": [ { "cell_type": "markdown", "metadata": {}, "source": [ "# TP éval. par les pairs : Sujet 1 - 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 numpy as np\n", "import requests" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "Les données de mesure de la concentration de CO2 dans l'atmosphère à l'observatoire de Mauna Loa, Hawaii, États-Unis, sont disponible sur le [site Web de l'institut Scripps](https://scrippsco2.ucsd.edu/data/atmospheric_co2/primary_mlo_co2_record.html). Date de téléchargement : 18/11/2021. " ] }, { "cell_type": "code", "execution_count": 2, "metadata": { "scrolled": true }, "outputs": [ { "data": { "text/html": [ "
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YrMnDateDateCO2seasonallyfitseasonallyCO2seasonally
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
4195803212591958.2027315.71314.43316.20314.91315.71314.43
5195804212901958.2877317.45315.16317.30314.99317.45315.16
6195805213201958.3699317.51314.71317.87315.07317.51314.71
7195806213511958.4548-99.99-99.99317.25315.15317.25315.15
8195807213811958.5370315.86315.20315.86315.22315.86315.20
9195808214121958.6219314.93316.20313.99315.29314.93316.20
10195809214431958.7068313.21316.09312.46315.35313.21316.09
11195810214731958.7890-99.99-99.99312.44315.41312.44315.41
12195811215041958.8740313.33315.20313.61315.46313.33315.20
13195812215341958.9562314.67315.43314.77315.52314.67315.43
14195901215651959.0411315.58315.54315.63315.57315.58315.54
15195902215961959.1260316.49315.85316.28315.64316.49315.85
16195903216241959.2027316.65315.37316.99315.70316.65315.37
17195904216551959.2877317.72315.42318.09315.77317.72315.42
18195905216851959.3699318.29315.48318.66315.85318.29315.48
19195906217161959.4548318.15316.02318.05315.94318.15316.02
20195907217461959.5370316.54315.87316.67316.03316.54315.87
21195908217771959.6219314.80316.07314.82316.13314.80316.07
22195909218081959.7068313.84316.73313.32316.22313.84316.73
23195910218381959.7890313.33316.33313.33316.31313.33316.33
24195911218691959.8740314.81316.69314.54316.40314.81316.69
25195912218991959.9562315.58316.35315.72316.48315.58316.35
26196001219301960.0410316.43316.39316.61316.56316.43316.39
27196002219611960.1257316.98316.34317.28316.64316.98316.34
28196003219901960.2049317.58316.27318.04316.72317.58316.27
29196004220211960.2896319.03316.70319.14316.80319.03316.70
.................................
740201907436612019.5370411.78410.97412.29411.51411.78410.97
741201908436922019.6219410.01411.56410.15411.73410.01411.56
742201909437232019.7068408.48411.98408.44411.96408.48411.98
743201910437532019.7890408.40412.02408.57412.17408.40412.02
744201911437842019.8740410.16412.44410.15412.40410.16412.44
745201912438142019.9562411.81412.74411.70412.61411.81412.74
746202001438452020.0410413.30413.25412.90412.83413.30413.25
747202002438762020.1257414.05413.28413.82413.04414.05413.28
748202003439052020.2049414.45412.87414.83413.23414.45412.87
749202004439362020.2896416.11413.29416.28413.44416.11413.29
750202005439662020.3716417.15413.74417.05413.64417.15413.74
751202006439972020.4563416.29413.73416.38413.84416.29413.73
752202007440272020.5383414.42413.64414.79414.04414.42413.64
753202008440582020.6230412.52414.10412.63414.25412.52414.10
754202009440892020.7077411.18414.70410.91414.45411.18414.70
755202010441192020.7896411.12414.75411.02414.63411.12414.75
756202011441502020.8743412.88415.16412.57414.82412.88415.16
757202012441802020.9563413.89414.82414.08414.99413.89414.82
758202101442112021.0411415.15415.10415.22415.16415.15415.10
759202102442422021.1260416.47415.70416.10415.31416.47415.70
760202103442702021.2027417.16415.61417.02415.45417.16415.61
761202104443012021.2877418.24415.44418.41415.59418.24415.44
762202105443312021.3699418.95415.53419.14415.72418.95415.53
763202106443622021.4548418.70416.11418.42415.86418.70416.11
764202107443922021.5370416.65415.84416.76415.98416.65415.84
765202108444232021.6219414.34415.90414.53416.12414.34415.90
766202109444542021.7068412.90416.42-99.99-99.99412.90416.42
767202110444842021.7890-99.99-99.99-99.99-99.99-99.99-99.99
768202111445152021.8740-99.99-99.99-99.99-99.99-99.99-99.99
769202112445452021.9562-99.99-99.99-99.99-99.99-99.99-99.99
\n", "

770 rows × 10 columns

\n", "
" ], "text/plain": [ " Yr Mn Date Date CO2 seasonally fit \\\n", "0 adjusted \n", "1 Excel [ppm] [ppm] [ppm] \n", "2 1958 01 21200 1958.0411 -99.99 -99.99 -99.99 \n", "3 1958 02 21231 1958.1260 -99.99 -99.99 -99.99 \n", "4 1958 03 21259 1958.2027 315.71 314.43 316.20 \n", "5 1958 04 21290 1958.2877 317.45 315.16 317.30 \n", "6 1958 05 21320 1958.3699 317.51 314.71 317.87 \n", "7 1958 06 21351 1958.4548 -99.99 -99.99 317.25 \n", "8 1958 07 21381 1958.5370 315.86 315.20 315.86 \n", "9 1958 08 21412 1958.6219 314.93 316.20 313.99 \n", "10 1958 09 21443 1958.7068 313.21 316.09 312.46 \n", "11 1958 10 21473 1958.7890 -99.99 -99.99 312.44 \n", "12 1958 11 21504 1958.8740 313.33 315.20 313.61 \n", "13 1958 12 21534 1958.9562 314.67 315.43 314.77 \n", "14 1959 01 21565 1959.0411 315.58 315.54 315.63 \n", "15 1959 02 21596 1959.1260 316.49 315.85 316.28 \n", "16 1959 03 21624 1959.2027 316.65 315.37 316.99 \n", "17 1959 04 21655 1959.2877 317.72 315.42 318.09 \n", "18 1959 05 21685 1959.3699 318.29 315.48 318.66 \n", "19 1959 06 21716 1959.4548 318.15 316.02 318.05 \n", "20 1959 07 21746 1959.5370 316.54 315.87 316.67 \n", "21 1959 08 21777 1959.6219 314.80 316.07 314.82 \n", "22 1959 09 21808 1959.7068 313.84 316.73 313.32 \n", "23 1959 10 21838 1959.7890 313.33 316.33 313.33 \n", "24 1959 11 21869 1959.8740 314.81 316.69 314.54 \n", "25 1959 12 21899 1959.9562 315.58 316.35 315.72 \n", "26 1960 01 21930 1960.0410 316.43 316.39 316.61 \n", "27 1960 02 21961 1960.1257 316.98 316.34 317.28 \n", "28 1960 03 21990 1960.2049 317.58 316.27 318.04 \n", "29 1960 04 22021 1960.2896 319.03 316.70 319.14 \n", ".. ... ... ... ... ... ... ... \n", "740 2019 07 43661 2019.5370 411.78 410.97 412.29 \n", "741 2019 08 43692 2019.6219 410.01 411.56 410.15 \n", "742 2019 09 43723 2019.7068 408.48 411.98 408.44 \n", "743 2019 10 43753 2019.7890 408.40 412.02 408.57 \n", "744 2019 11 43784 2019.8740 410.16 412.44 410.15 \n", "745 2019 12 43814 2019.9562 411.81 412.74 411.70 \n", "746 2020 01 43845 2020.0410 413.30 413.25 412.90 \n", "747 2020 02 43876 2020.1257 414.05 413.28 413.82 \n", "748 2020 03 43905 2020.2049 414.45 412.87 414.83 \n", "749 2020 04 43936 2020.2896 416.11 413.29 416.28 \n", "750 2020 05 43966 2020.3716 417.15 413.74 417.05 \n", "751 2020 06 43997 2020.4563 416.29 413.73 416.38 \n", "752 2020 07 44027 2020.5383 414.42 413.64 414.79 \n", "753 2020 08 44058 2020.6230 412.52 414.10 412.63 \n", "754 2020 09 44089 2020.7077 411.18 414.70 410.91 \n", "755 2020 10 44119 2020.7896 411.12 414.75 411.02 \n", "756 2020 11 44150 2020.8743 412.88 415.16 412.57 \n", "757 2020 12 44180 2020.9563 413.89 414.82 414.08 \n", "758 2021 01 44211 2021.0411 415.15 415.10 415.22 \n", "759 2021 02 44242 2021.1260 416.47 415.70 416.10 \n", "760 2021 03 44270 2021.2027 417.16 415.61 417.02 \n", "761 2021 04 44301 2021.2877 418.24 415.44 418.41 \n", "762 2021 05 44331 2021.3699 418.95 415.53 419.14 \n", "763 2021 06 44362 2021.4548 418.70 416.11 418.42 \n", "764 2021 07 44392 2021.5370 416.65 415.84 416.76 \n", "765 2021 08 44423 2021.6219 414.34 415.90 414.53 \n", "766 2021 09 44454 2021.7068 412.90 416.42 -99.99 \n", "767 2021 10 44484 2021.7890 -99.99 -99.99 -99.99 \n", "768 2021 11 44515 2021.8740 -99.99 -99.99 -99.99 \n", "769 2021 12 44545 2021.9562 -99.99 -99.99 -99.99 \n", "\n", " seasonally CO2 seasonally \n", "0 adjusted fit filled adjusted filled \n", "1 [ppm] [ppm] [ppm] \n", "2 -99.99 -99.99 -99.99 \n", "3 -99.99 -99.99 -99.99 \n", "4 314.91 315.71 314.43 \n", "5 314.99 317.45 315.16 \n", "6 315.07 317.51 314.71 \n", "7 315.15 317.25 315.15 \n", "8 315.22 315.86 315.20 \n", "9 315.29 314.93 316.20 \n", "10 315.35 313.21 316.09 \n", "11 315.41 312.44 315.41 \n", "12 315.46 313.33 315.20 \n", "13 315.52 314.67 315.43 \n", "14 315.57 315.58 315.54 \n", "15 315.64 316.49 315.85 \n", "16 315.70 316.65 315.37 \n", "17 315.77 317.72 315.42 \n", "18 315.85 318.29 315.48 \n", "19 315.94 318.15 316.02 \n", "20 316.03 316.54 315.87 \n", "21 316.13 314.80 316.07 \n", "22 316.22 313.84 316.73 \n", "23 316.31 313.33 316.33 \n", "24 316.40 314.81 316.69 \n", "25 316.48 315.58 316.35 \n", "26 316.56 316.43 316.39 \n", "27 316.64 316.98 316.34 \n", "28 316.72 317.58 316.27 \n", "29 316.80 319.03 316.70 \n", ".. ... ... ... \n", "740 411.51 411.78 410.97 \n", "741 411.73 410.01 411.56 \n", "742 411.96 408.48 411.98 \n", "743 412.17 408.40 412.02 \n", "744 412.40 410.16 412.44 \n", "745 412.61 411.81 412.74 \n", "746 412.83 413.30 413.25 \n", "747 413.04 414.05 413.28 \n", "748 413.23 414.45 412.87 \n", "749 413.44 416.11 413.29 \n", "750 413.64 417.15 413.74 \n", "751 413.84 416.29 413.73 \n", "752 414.04 414.42 413.64 \n", "753 414.25 412.52 414.10 \n", "754 414.45 411.18 414.70 \n", "755 414.63 411.12 414.75 \n", "756 414.82 412.88 415.16 \n", "757 414.99 413.89 414.82 \n", "758 415.16 415.15 415.10 \n", "759 415.31 416.47 415.70 \n", "760 415.45 417.16 415.61 \n", "761 415.59 418.24 415.44 \n", "762 415.72 418.95 415.53 \n", "763 415.86 418.70 416.11 \n", "764 415.98 416.65 415.84 \n", "765 416.12 414.34 415.90 \n", "766 -99.99 412.90 416.42 \n", "767 -99.99 -99.99 -99.99 \n", "768 -99.99 -99.99 -99.99 \n", "769 -99.99 -99.99 -99.99 \n", "\n", "[770 rows x 10 columns]" ] }, "execution_count": 2, "metadata": {}, "output_type": "execute_result" } ], "source": [ "data_url = \"https://scrippsco2.ucsd.edu/assets/data/atmospheric/stations/in_situ_co2/monthly/monthly_in_situ_co2_mlo.csv\"\n", "data_filename = 'monthly_in_situ_co2_mlo.csv'\n", "\n", "# On essaie de lire le fichier csv local si il existe, sinon on le telecharge\n", "# de maniere a avoir une copie locale.\n", "# Les 54 premieres lignes décrivent les données\n", "\n", "try:\n", " raw_data = pd.read_csv(data_filename, skiprows=54)\n", "except FileNotFoundError:\n", " req = requests.get(data_url)\n", " url_content = req.content\n", " csv_file = open(data_filename, 'wb')\n", " csv_file.write(url_content)\n", " raw_data = pd.read_csv(data_filename, skiprows=54)\n", "\n", "raw_data" ] }, { "cell_type": "code", "execution_count": 3, "metadata": {}, "outputs": [ { "data": { "text/plain": [ "Index([' Yr', ' Mn', ' Date', ' Date', ' CO2', 'seasonally',\n", " ' fit', ' seasonally', ' CO2', ' seasonally'],\n", " dtype='object')" ] }, "execution_count": 3, "metadata": {}, "output_type": "execute_result" } ], "source": [ "# On retire les 2 premiere lignes qui contiennent des commentaires et des unites\n", "raw_data = raw_data[2:]\n", "# On regarde les noms des colonnes\n", "raw_data.columns" ] }, { "cell_type": "code", "execution_count": 4, "metadata": { "scrolled": true }, "outputs": [], "source": [ "# Remplacement des noms des colonnes par des noms plus pratiques et surtout uniques\n", "cols = raw_data.columns\n", "data = raw_data.rename(columns= {cols[0]:'Yr', cols[1]:'Mn', cols[2]:'Date_Excel', cols[3]:'Date', cols[4]:'CO2', cols[5]:'seasonally_adjusted',\n", " cols[6]:'fit', cols[7]:'seasonally_adjusted_fit', cols[8]:'CO2_filled', cols[9]:'seasonally_adjusted_filled'})" ] }, { "cell_type": "code", "execution_count": 5, "metadata": {}, "outputs": [ { "data": { "text/html": [ "
\n", "\n", "\n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", "
YrMnDate_ExcelDateCO2seasonally_adjustedfitseasonally_adjusted_fitCO2_filledseasonally_adjusted_filled
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" ], "text/plain": [ "Empty DataFrame\n", "Columns: [Yr, Mn, Date_Excel, Date, CO2, seasonally_adjusted, fit, seasonally_adjusted_fit, CO2_filled, seasonally_adjusted_filled]\n", "Index: []" ] }, "execution_count": 5, "metadata": {}, "output_type": "execute_result" } ], "source": [ "# On teste si certaines lignes ne sont pas complètes\n", "# -> pas le cas, cependant une inspection visuelle, confirmée par le header du document,\n", "# montre que des données sont manquantes et sont dénotées par -99.99\n", "\n", "data[data.isnull().any(axis=1)]" ] }, { "cell_type": "code", "execution_count": 9, "metadata": { "scrolled": true }, "outputs": [], "source": [ "# On transforme les valeurs manquante de -99.99 en NaN\n", "# On transforme d abord les valeurs en float\n", "\n", "data.iloc[:, 3:] = data.iloc[:, 3:].astype(float)\n", "\n", "data = data.replace(-99.99, np.nan)\n" ] }, { "cell_type": "code", "execution_count": 135, "metadata": { "scrolled": true }, "outputs": [ { "ename": "KeyError", "evalue": "'Date'", "output_type": "error", "traceback": [ "\u001b[0;31m---------------------------------------------------------------------------\u001b[0m", "\u001b[0;31mKeyError\u001b[0m Traceback (most recent call last)", "\u001b[0;32m/opt/conda/lib/python3.6/site-packages/pandas/core/indexes/base.py\u001b[0m in \u001b[0;36mget_loc\u001b[0;34m(self, key, method, tolerance)\u001b[0m\n\u001b[1;32m 2524\u001b[0m \u001b[0;32mtry\u001b[0m\u001b[0;34m:\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0;32m-> 2525\u001b[0;31m \u001b[0;32mreturn\u001b[0m \u001b[0mself\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0m_engine\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0mget_loc\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0mkey\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0m\u001b[1;32m 2526\u001b[0m \u001b[0;32mexcept\u001b[0m \u001b[0mKeyError\u001b[0m\u001b[0;34m:\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n", "\u001b[0;32mpandas/_libs/index.pyx\u001b[0m in \u001b[0;36mpandas._libs.index.IndexEngine.get_loc\u001b[0;34m()\u001b[0m\n", "\u001b[0;32mpandas/_libs/index.pyx\u001b[0m in \u001b[0;36mpandas._libs.index.IndexEngine.get_loc\u001b[0;34m()\u001b[0m\n", "\u001b[0;32mpandas/_libs/hashtable_class_helper.pxi\u001b[0m in \u001b[0;36mpandas._libs.hashtable.PyObjectHashTable.get_item\u001b[0;34m()\u001b[0m\n", "\u001b[0;32mpandas/_libs/hashtable_class_helper.pxi\u001b[0m in \u001b[0;36mpandas._libs.hashtable.PyObjectHashTable.get_item\u001b[0;34m()\u001b[0m\n", "\u001b[0;31mKeyError\u001b[0m: 'Date'", "\nDuring handling of the above exception, another exception occurred:\n", "\u001b[0;31mKeyError\u001b[0m Traceback (most recent call last)", "\u001b[0;32m\u001b[0m in \u001b[0;36m\u001b[0;34m\u001b[0m\n\u001b[1;32m 1\u001b[0m \u001b[0;31m# Finalement on termine le pre traitement en re assignant les indices\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0;32m----> 2\u001b[0;31m \u001b[0mdata\u001b[0m \u001b[0;34m=\u001b[0m \u001b[0mdata\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0mset_index\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0;34m'Date'\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0m\u001b[1;32m 3\u001b[0m \u001b[0mdata\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n", "\u001b[0;32m/opt/conda/lib/python3.6/site-packages/pandas/core/frame.py\u001b[0m in \u001b[0;36mset_index\u001b[0;34m(self, keys, drop, append, inplace, verify_integrity)\u001b[0m\n\u001b[1;32m 3144\u001b[0m \u001b[0mnames\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0mappend\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0;32mNone\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m 3145\u001b[0m \u001b[0;32melse\u001b[0m\u001b[0;34m:\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0;32m-> 3146\u001b[0;31m \u001b[0mlevel\u001b[0m \u001b[0;34m=\u001b[0m \u001b[0mframe\u001b[0m\u001b[0;34m[\u001b[0m\u001b[0mcol\u001b[0m\u001b[0;34m]\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0m_values\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0m\u001b[1;32m 3147\u001b[0m \u001b[0mnames\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0mappend\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0mcol\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m 3148\u001b[0m \u001b[0;32mif\u001b[0m \u001b[0mdrop\u001b[0m\u001b[0;34m:\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n", "\u001b[0;32m/opt/conda/lib/python3.6/site-packages/pandas/core/frame.py\u001b[0m in \u001b[0;36m__getitem__\u001b[0;34m(self, key)\u001b[0m\n\u001b[1;32m 2137\u001b[0m \u001b[0;32mreturn\u001b[0m \u001b[0mself\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0m_getitem_multilevel\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0mkey\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m 2138\u001b[0m \u001b[0;32melse\u001b[0m\u001b[0;34m:\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0;32m-> 2139\u001b[0;31m \u001b[0;32mreturn\u001b[0m \u001b[0mself\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0m_getitem_column\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0mkey\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0m\u001b[1;32m 2140\u001b[0m \u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m 2141\u001b[0m \u001b[0;32mdef\u001b[0m \u001b[0m_getitem_column\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0mself\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0mkey\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m:\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n", "\u001b[0;32m/opt/conda/lib/python3.6/site-packages/pandas/core/frame.py\u001b[0m in \u001b[0;36m_getitem_column\u001b[0;34m(self, key)\u001b[0m\n\u001b[1;32m 2144\u001b[0m \u001b[0;31m# get column\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m 2145\u001b[0m \u001b[0;32mif\u001b[0m \u001b[0mself\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0mcolumns\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0mis_unique\u001b[0m\u001b[0;34m:\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0;32m-> 2146\u001b[0;31m \u001b[0;32mreturn\u001b[0m \u001b[0mself\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0m_get_item_cache\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0mkey\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0m\u001b[1;32m 2147\u001b[0m \u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m 2148\u001b[0m \u001b[0;31m# duplicate columns & possible reduce dimensionality\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n", "\u001b[0;32m/opt/conda/lib/python3.6/site-packages/pandas/core/generic.py\u001b[0m in \u001b[0;36m_get_item_cache\u001b[0;34m(self, item)\u001b[0m\n\u001b[1;32m 1840\u001b[0m \u001b[0mres\u001b[0m \u001b[0;34m=\u001b[0m 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'Date'" ] } ], "source": [ "# Finalement on termine le pre traitement en re assignant les indices\n", "data = data.set_index('Date')\n", "data" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "On va maitenant examiner la colonne 'CO2'\n", "On constate une variation lente superposé à une oscillation périodique, annuelle.\n", "\n", "On va décomposer ces 2 variations à l'aide d'un polynome de degré 3 pour la variation \n", "lente et d'un modèle sinusoidale pour la variation annuelle." ] }, { "cell_type": "code", "execution_count": 109, "metadata": {}, "outputs": [ { "name": "stdout", "output_type": "stream", "text": [ "[ 4.14866741e-05 -2.34324344e-01 4.41306168e+02 -2.76839348e+05]\n" ] }, { "data": { "text/plain": [ "" ] }, "execution_count": 109, "metadata": {}, "output_type": "execute_result" }, { "data": { "image/png": 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\n", 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\n", 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" ] }, "metadata": { "needs_background": "light" }, "output_type": "display_data" } ], "source": [ "from scipy import optimize\n", "\n", "# on enleve les lignes ne contenant pour de mesure\n", "data_cln = data[data['CO2'] > 1]\n", "x, y = data_cln.index, data_cln['CO2']\n", "\n", "# fit par un polynome degré 3\n", "z = np.polyfit(x, y, 3)\n", "p = np.poly1d(z)\n", "pfit = p(x)\n", "print(z)\n", "\n", "# plot des données de base + le fit\n", "plt.figure(figsize=(6, 4))\n", "plt.plot(x, y, label='Data')\n", "plt.plot(x, pfit, label='Fitted function')\n", "plt.legend()\n", "\n", "# on soustrait aux données la fit polynomial pour isoler la variation annuelle\n", "plt.figure(figsize=(6, 4))\n", "detrend_y = y - pfit\n", "plt.plot(x, detrend_y, label='oscillation')\n", "plt.legend()\n" ] }, { "cell_type": "code", "execution_count": 126, "metadata": {}, "outputs": [ { "name": "stdout", "output_type": "stream", "text": [ "[-0.0121165 2.86744008 6.28571768 -5.40388516]\n" ] }, { "data": { "text/plain": [ "" ] }, "execution_count": 126, "metadata": {}, "output_type": "execute_result" }, { "data": { "image/png": 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\n", 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\n", 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" ] }, "metadata": { "needs_background": "light" }, "output_type": "display_data" } ], "source": [ "# on fit maintenant les données auxquelles on a soustrait la variation lente\n", "# avec un modèle sinusoidal\n", "# on prend comme pulsation : 2 * pi / 1, et on estime l'amplitude initiale a ~ 3\n", "\n", "def sin(x, a1,a2,a3,a4):\n", " return a1 + a2 * np.sin(a3*x + a4)\n", "\n", "params, params_covariance = optimize.curve_fit(sin, x,detrend_y, p0=[0,3,2*np.pi/1,0])\n", "print(params)\n", "\n", "sfit = sin(x, *params)\n", "\n", "# plot du fit sinusoidale, on zoom pour mieux visualiser\n", "plt.figure(figsize=(6, 4))\n", "plt.plot(x, detrend_y, label='Data')\n", "plt.plot(x, sfit, label='Fitted function')\n", "plt.legend()\n", "plt.xlim((1960,1970))\n", "\n", "# on plot les résidus\n", "plt.figure(figsize=(6, 4))\n", "plt.plot(x, detrend_y - sfit, label='osc')\n", "plt.legend()" ] }, { "cell_type": "code", "execution_count": 144, "metadata": {}, "outputs": [ { "data": { "text/plain": [ "(380, 440)" ] }, "execution_count": 144, "metadata": {}, "output_type": "execute_result" }, { "data": { "image/png": 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CuLQBTil13YiKitK7g38JR3sZfQqMAMpk3WiMeRe4HzgDdLFvrgGsy5Is2r5NFXMikuceHUqp3DnTC80Zud4hGGN6AydFZNPl+0TkVRGpCUwGnrp4SDanuaI2xphhxpgwY0xYbGxsHoutihpvb2/i4+Ov2S+uUtcLESE+Pt6hsSn55cgdQjugrzHmNsAbKGuM+VlE7s2S5hdgHvAm1h1BzSz7/IFjl59URMYD48F6qOxc8VVR4e/vT3R0NBrclXI9b2/vHMeDuFKuAUFERgIjAYwxnYEXReReY0xdEdlvT9YX2GN/PQf4xRjzCVAdqAtscHXBVdHi6elJ7dq1C7sYSql8yM9I5feNMfWxup0eAoYDiEi4MWY6sAtIB54UkYx8l1QppVSBcngcQkHScQhKKZV3hTkOQSmlVDGmAUEppRSgAUEppZSdBgSllFKABgSllFJ2GhCUUkoBGhCUUkrZaUBQSikF6JrKSqnrgQjEbIV9iyApDto8CRUCCrtURY4GBKVU8SYCc56GLZMAA+4lYNNEaP8cdB4JOmV7Jg0ISqnibeXHVjBo/SR0eAEyUmHRa7D8A/AsaQUGBWhAUEoVZ7v/gKVvQ5OB0OPdf+4GBnwHYoMlo6FGM6jdsXDLWUToQ2WlVPGUngJ/joRqTaDfF5c2DRkDff8HlW6CXx+CpFOFV84iRAOCUqp4CvsezhyB7m+Bh9eV+73KwMAfISkelr13zYtXFGlAUEoVPymJsOIjqynoxi45p6vaGJo/CBu/g9i9zuV1bCvYbM4dW8RoQFBKFT/rv7a6l3Z7M/deRF3+D0qUth4059WZaJjQDVZ+5Fw5ixgNCEqp4iUjDTZMgJtuBn8H1o4pVRk6vgj7F0HEX3nLa/3XVrfWoLudK2sRowFBKXVtiUBcBKSnFsz5d/8B545Dy2GOH9PqMahQGxa+Chnpjh2TfAbCfoTGt0OFWk4VtajRgKCUujZsGbDqU/hfM/i8ufU97AfHL8CO2vCtNQr5ppsdP8bDC255G2L3wKYfHDtm00RITYS2TztVzKJIA4JS6tpY8hb89SaUqQ49/gulq8Lc52DOU9Zdgysc3wmH10Dow+DmnrdjG/SGWu3h7//m3g01PQXWfQUBHaB6U+fLW8RoQFBKFbydM2H1p1aPngfnWXMJPfIXdBwB26ZYF1dX2PgteHhD03vzfqwx0PM9qylo4f9dPe3qzyDxGHT4j3PlLKI0ICilCtapSPj9SajZGm798J/txlhzCTXobfXwiVqVv3wuJMD26dDkTihZ0blz+AVZ01tsmwJ7/8w+zamDsGIMNLod6lylS+u/kAYEpVTBWv4BIDDwB/Aocek+Nze442sofwP88Vz+HjRvmwJpSdDi0XwVl44vgW8jqzkr8cSl+0Rg/kvg7mndTRQzGhCUUgUndi9snwYtHoGy1bNP41UGbv0A4vfDhm+cy8dmsx4m+7eE6iHOlxesB8y3f2U1HX3X3eoRBZB2AWY9anVN7fpazvX5F9OAoJQqOMveAw8faP/81dPV6wF1e8CyDyDxeN7zOfg3nDqQt66mV1M9BB6YC6nnYEJX+Ol2GN8ZdsyAbm9Aq+GuyaeI0YCglCoYJ3dD+G/Q+nFr8Fduer4H6cnW7KR5tf4bKFUFGvXN+7E58W8ODy+2pr9ISbTuHAb9Yj1ILqZrKOj010qpgrFhPLh7QesnHEtfqY41QGztF9DqcagW6NhxJ3bB/oXQ5dXsJ7HLj0p14O6fXXvOIkzvEJS63ohAxBL4+U74sTfsnGVN9+BKyWdg2zSrx0+pSo4f1+E/4F0WFr/h+DFrPrMWumnxSN7LqS7hcEAwxrgbY7YYY+ba348xxuwxxmw3xvxmjCmfJe1IY0yEMWavMaZHQRRcKeUEWwZMGQw/94fjO6zpoX99EL7tajWLuMrWKZB2Pu8X6ZIVrV4+B5ZYQSs3CUesdv1mDzjf1VRlyssdwrPA7izvFwOBIhIE7ANGAhhjGgGDgMZAT+BLY0wehwwqpQrE8g9h3wLo+jo8tx2e3gz9J8CJcPj1YStg5JcIbJwANZpbq5HlVcth1tQTC0ZAWvLV06793Pre5sm856Ou4FBAMMb4A72ACRe3icgiEbk4Cck6wN/+uh8wVURSRCQSiABauq7ISimnRCyxxgQED7aaZjy8rOkdggbCbWOsdvi8NNXk5OAyqwupsz1+PLyg96cQH2Efw5CDY1utrqYh90D5ms7lpS7h6B3Cp8AIIKdVIB4CFthf1wCOZNkXbd92CWPMMGNMmDEmLDY21sFiKKWckp4Cc56BKvWh18dX9pJp8bDVvLP2cziyMX95bZwAJStZI3mdVacLhNwLq8dBzLYr92ekw5ynrXy6j3Y+H3WJXAOCMaY3cFJENuWw/1UgHZh8cVM2ya6YuUpExotIqIiEVqlSJQ9FVkrl2ZZJcDba6tpZolT2aW4eBWX8YP6LzjcdJRyBvfOh2f3g6e1saS093rG6q/4y6J/BYWA1Sa0YA8e3W3c2PhXyl4/K5MgdQjugrzEmCpgKdDXG/AxgjHkA6A3cI5I5XWE0kPX+zR845rISK1UM2WzChVQXtN9nJz0FVn4CNVtdfTlJrzJwyzsQsxU2T3Qur7Dvre+hDzl3fFY+FeDeWZCRCj/caq1zcHIPzHwElr8PgQOgUb/856My5RoQRGSkiPiLSADWw+KlInKvMaYn8DLQV0SSshwyBxhkjPEyxtQG6gIbCqDsShULaRk2hv+8iaDRC3lk4kZmbz1KWoYL1+jd/BOcPWpNJJfbgKrAAdaUzkvesiaLy4v0FCuverdacxO5QrVAeHCB9axj2r3wZSsIn2VNHdH/22I7QKyw5Gdg2ueAF7DYWB/KOhEZLiLhxpjpwC6spqQnRaSA/vVR6t8tPcPGs1O3sGjXCXoF+bEp6jR/7T7JnuOJvNyzQf4zyEi32uFrtoYbO+ee3hhrrYJvOsKqsXlrn98xw1rHuKWLxwNUqQdPhcGJnRC33woSxWgNgqLEiKsWpsiH0NBQCQsLK+xiKHVNic3GN9+Pp3TUIvxCbqFb3/uxefjw8MSN7I5JZM0rXXFzy+d/wLvnwrR7rNG2Dfs4ftxvw60Ba09vcqwHjy0DvmhlrUUwfKX+536NGGM2iYgDC0c7RkcqK1UYzhzl5Bc9GB79MoM9l9Nt58vwSQPcjqzj9qY1OH42mc2HT+c/n43fQll/qxknL7q8an1f+o5j6ffMtbqadnhBg8G/mAYEpa61jHRSp95P6bjt/FDuCczIaHjgD2tytimDuLlKAiU83Ji7PSZ/+cTus8YEhD4I7nlsHS5f05qUbvtUOLT26mlFYOXHULGOPuT9l9OAoNQ1Jsvfp0RMGG/IMLrd/zpuJXysGTXvnQnuJSg1/W763OTJ/B0x2Gz5aNLdOAHcS1jTOjij0wgoV9NaKOZqC9fsXWCNFWj/XN7XMVZFigYEpbKYvvEIO6LPFFwGh9fDio+Ykd6RwB4PcUOlkv/sqxAA90yHxOM8Z5vEycQUNkblsth7TlLOWSuINbodSjs5zqdEKWsQW+weWDMu+zRJp2Du89YKY0GDnMtHFRkaEJSyWxR+nBEzt3Pvd+uJijtfIHmcnvs6J6Q88/xf4IE2AVcmqN4U2j5NzcO/085zL/N2ONlstH0apJyFlvlcTrJeDyuoLPsA9v915f4FL1s9i+74+srlMdW/jgYEpYCEpFRe/X0ndX1LYww88lMYZ5NdOyX07vV/UuHkemaXupPPhrbPuQdRxxehXE0+9PmJhdujychrs9HFyeX8gsG/Rf4L3udT8G1g9VY6uNzalp5ijVXYMR06jrDyUv96GhCUAt6au4vT51MZe3cIX97TjKi48zw7ZUv+2vCzOH0+lYQF73LKlGfAo69S1tsz58QlSkHP96mRGkmP5PlsyWtvo0Or4eQua7F5V/T48akA9/1uNWn91Be+bGN9rfzYPlHeC/nPQxUJGhDUdW/FvlhmbT7K453rEFijHG3rVObVXg35e28sqyLiXJLHzDm/0YbtpLd+msoVHJh7p0Ev0m9oz3Mes1i+42DeMtvwLXiXt0Ydu0qpyjB0vjVtdhk/a5qLe2ZaTUXuVwlu6l9FA4K67n23bDdPlf6bZyqstSZnAwa3vIFyPp7M3Byd7/NHxZ2n+u7vSHIvg2+Xxx07yBg8erxNRZNI1e1fO57ZqYPWnD/N7oMSJXNPnxelKlnNWffNgseWQ92bXXt+Veg0IKjr2pFNf/Jm9KO8mP4tnvOehU8DYc7TeLsb+gT7sTD8eL6fJXwzbyXdTRgScl/OM41mp0YzIqvdyoDU2UQe3OfYMavGgpsHtHnKucKq65oGBHX9OrqZ6n8Mwc3A2TunwxProOVj1gRtf77CgKY1SE6zMT8fA8Q2HTpNtf3T8DA2SrXL+4IxpW4bhRtC+oJXc0+ccMRaurLZ/VCmmhOlVdc7DQjq+pR2gYyZw4iVcvzY6HvKBvYA34Zw6wfWf9cbviHk8I/cWKWU081GIsKH87Zzj8dSMup0h4q183wO3xsa8GvJu6gbuwgOLL164tWfWt/bP+dEaZXSgKCKoL/3nuT2L1ZzNOFCwWXy12jcT+3nxbTHuKtDk3+2G2OtCdCoH2bZezzUIIONUac5FJ/3cQl/7jyOb/QiKpOAR2snl5MEEpo9QaStKulz/2N198xOzDbYNBFChkA5/+zTKJULDQiqSElNt/Hm7HC2Hkng0YlhJKWm535QXp3cg6z/mhlut5JaqxONqpe9dL8xcOsY8PBh4PFPMEaYuflonrJITbfxwZ97GOazFKlQG+p0c7q4XQNv4I30B/E4fRDmvWCNM7gksyRr0ZhSla1Vz5RykgYEVaRMCzvC4VNJPNy+NruPn+WlGdtx5RTt51LS2TrlDS5ICb5mIC/3rJ99wjJV4eY38TqyihHVtjFrc3SexiRMXn8In1O7aZKxC9PiEXBz/k+tQbUyHKnQmuklB8GWny+dgTQjHRa8ZK0TcMfXULKi0/kopQFBFRlJqel8tmQ/LQMq8lqvhoy8tQHzdsTw3apIl5z/QmoGr3w7h8BTi9nqewezXupL81pXuYA2fxCqN2PohYnEnU5gg4PzCiUkpfLZkv28VHEF4uEDTe/JV7mNMQzrWIcRp/oQU+cuWPkRTOxj9Sj6up0VJNo/59gCOEpdhQYEVWT8uCaK2MQURvSsjzGGRzvcSNs6lZi4Nirfdwkp6RkMmxRG2xOTMO7utL1vFOV8chlQ5eYGPd7FJ/kEj5VYyMxNjj1cfn12OCY5gc7Jf2OCBrpkEfg7m/tTvZwPT5+9D+n8f3DmKPw1ylpv+O7J0O3NfOehlAYEVSScS0ln3bJ5fFztL0JT1sP5eIwx3B5SgyOnLhB+7KzT5xYRnp+2lT37I7jbcyXuze6Dsn6OHVyrLdTvxeMec1i7Y2+uzzTmbj/GH9uOMa5+OG4Zydb0ES5QwsONx7vcRNiRRFbXeNhayey5HfDEemjYWxelUS6hAUEVvvQUDvzyH36UNxmQ8D1MGQTjguHwOro3qoq7m2G+s7N+AmsOxDN/x3E+b7Add1ta3gdt3TwKL0nhEdsMFoYfzzHZycRkXvt9Jy1qeNM+doq1WL1fkNPlvtxdof74lfNm3JJ9CFgL2esMo8qFNCCoQmebOYzgQz+ytFRP+M8+eHCB9VD35wFUiN9M2zqVmL8jxulmoy/+jsCvtDst42ZbvX0q1cnbCarUg+ZDuc/jLzasXZljsg8W7OVCagZfNtiOOXcCOr/iVHlz4uXhzuOd67Ax6jTrDjq5ToJSV6EBQRWu8N9w2/07Y9Luwr3vZ1YgqNUWHphrjbadPJABdQxR8UnsOZ6Y59NvPnyaNQfieafBIcy5GGjp3HgA0/U1Uj3KcMfxTzmSzZiE0+dT+WP7Me5p7kuVbV9ZdwcB7Z3K62ruCq3JxwODCQ3I/3MJpS6nAUEVnvNxyLwX2et+E0srDaFz/Swre5X1g3t+hYw0bj3yMW5GWOBEs9GXf0dQvqQnnc/OhvK1oG5358pasiIpnV6npdseVv321RW7Z26OJjXdxnDvv+DcCeg80rl8cuHt6c6A5v54uuufrnI9/a1ShUb+Go3tQgJPJz3Qg9RnAAAfgElEQVTKI53qYi5/MFqxNnT5P7wO/MmT1XYzf2fO7ffZ2R1zlr92n+TF4AzcD6+GFg/na83f8u0eJrpkI3od+ZhDe7b8Uw8Rfll/mLuqn8R34xio3wsC2jmdj1KFRQOCKhRrtu0mbcsvTE7rQonqjekTXD37hK2fgGpNeDzpG2JOxrI7xvHeRt+uPEipEu4MtC0AD29oel/+Cu3mRsl7JpGKJ6V+HQznrbUS1h6MJy7uBG9eGGM1c/X7PH/5KFVINCCoHCWnZZCeYXP5eedtj2HDjDGUIB2/Hs/x+xPtKOGRw6+iuwf0/pSSKbEM95zP1A2HHcrj1PlU5m6PYUhQObx2zYAmd7pkFG/FGjexOPhTSqfFkfJ1F1j7JYcWfs4879cpmXISBv6oo4XVv5YGBJWts8lp3DJ2BV0/Xs7iXSdcNn3EX7tO8NLUDQwtsYSMm26he4f2eOTWHu4fCo1uZ5jHPFZs2cmF1Ixc85kRdoTUdBuPlF0HaUkuGw8A0Pu2Pjzr/n/sPusFC0cy+ORY3EpWxAyZZpVVqX8pj8IugCpizh6D1eMI259Ap7Ml2VyuO4/+FEaX+lX44p5mlCzh/K/M5sOneWLyZp6ouIXy5xKgzROOH9ztDTx3z+XR9Gn8sb0dd4XWzDGpzSZMXn+YVrXKU3XPJPBvCdVDnC735cp4e/Lo/UOZvqU7c+J2IWlJPDzoLqiYh8VvlCqCHP7rNsa4A2HAURHpbYwZCIwCGgItRSQsS9qRwMNABvCMiCx0aalVwTi4HH59iIzkM7TLELp6pGMru4WJwR8xeukJZm89xuCWNzh9+v8t2U9Zbw+eKrkYfBrmbe6dSnUwLR7i7g0TeH71Cu4KzXl+oBX7Yzl8KomPAw/BhgPQ5f+cLnNOQgMqEhpQEWiSa1ql/i3y0mT0LLA7y/udQH9gRdZExphGwCCgMdAT+NIeTFRRFrUKJt1OundF7pQPubvK76TfNRm32N0M3fcEzSumMmfrMedPH3eeZftieblhHB4nd0Lrx/M83YLpPJJ0j9LcHfcF4UcTckz387rD+JZyp3nkV1C5HjS+w+lyK3U9cSggGGP8gV7AhIvbRGS3iOzNJnk/YKqIpIhIJBABtHRFYa9XaQXwYPfSDJLhj2eR8jfwRMkP2Z3uxyd3N8WjUW+4dyYm4TBjvCawLjKOE2eTncpi0rpDuBtD3wu/g09FCLor7ycpWRFb51dp5x7O1kU/Z5vkaMIFlu45wRu19+IWu8caLZyPrqZKXU8cvUP4FBgBOHJlqgEcyfI+2r7tEsaYYcaYMGNMWGxsrIPFuP7M2XaMoFGLmJePdX1ztfJjiI9gyY2vsCgiiVd7NeLGKqWtfQHtodvr3Hh6FX3MWv7Ylve7hPMp6UwPO8L99W14HVgIoQ+Bp49TRfVp8wgxXjfSOWos8afir9g/Zf1h3MigR9yP4NsYGundgVKOyjUgGGN6AydFZJOD58yuHeCKLioiMl5EQkUktEqVKtkcog7HJ/F/s3aQmmHj+WlbWXMgzvWZxEXAqrEk1uvPUxvK06leFe5tddlzglbDoUYob3v9xPItu7M/z1X8tuUoicnpPObzF7h5QItHnC+vuwcZt31ENeKJn/zIJauHpabbmLrxMF9UmY1nwkHo9nq+FqZR6nrjyF9LO6CvMSYKmAp0NcZkf79uiQaydgHxB5xvfL5OpWXYeGbqFoyBOU+1I6BySYb9tInwY2dcm9G6LxDjxpNx/fH2dOfDO4OuHDHs5g79Pqc0Sdx28lui4hxfX9hmE35aG0ULPw98I36FwP6OTz2dA//gbsys9Bj14peS+vcHmdsXhh+nXdJSepz9FVo+BvVvzVc+Sl1vcg0IIjJSRPxFJADrYfFSEbn3KofMAQYZY7yMMbWBusAGl5T2OvK/pRFsPZLAe/2b0Lh6OSY+1JIy3h78Z/o21y0pmXQKtk5hS/lbWHHMjff7N6FqWe/s0/o25ELIQ9zlvozVa1ZknyYb08KOsO/EOd6osRmTmmg9THaBOn1fZlZGe0qseA+m3gP7FsGiV/mwxASkVjvo8a5L8lHqeuL0/bQx5g5jTDTQBphnjFkIICLhwHRgF/An8KSI5D6SSGVKSk3n+1WR9GriR+8ga0oHv3I+PNnlJvYcT8zXYjGX2DwR0i8w8lg7HmwXQM/Aq//nXrr7SC64laLe1vcQW+6Pk+LPpfD+gj20CihHYPQUuKENVG/qkqI3D6jIzOojmOB+NxK5An4ZSI9zs4mu0hFz10/gnstqaEqpK+QpIIjIMhHpbX/9m/3OwUtEqopIjyzp3hWROiJSX0QWuLrQxd3irQcYbfsfY2Ifg286wZK3wJZB7yA/PN0Nv285mu88JD2VC6u/Zp00wds/iJG3Nsz9oJIVOdDoSVrYtrFn1W+5Jn9/wR7Op6TzSUgMJuGQy+4OLnqka0PeOd+P4DMfMzztBTqkf0X5B36BUpVdmo9S1wt94lbUnD1G0OIh3O6+Gh/f2lCitNULaOo9lPdIo0t9X2ZvO5avOYY2Hz7NR+M+wufCceaW7McXQ5rmPJfQZer1fp5DVKP8qrcgI+flJMOiTjFjUzSPtK9NjfBvodwN1iygLtSlvi+TH2nF07eFUq3Vnfzn9rZUKu3l0jyUup5oQChK0pJJ+743VVKjmdv4E8yQ6fDgPLjtI9i/EH65m/5N/YhNTGH1gSu7XDoi7lwK93+3gZ7nfiOxZE1G/ed5/CuUdPh4Hx8f1tR+Br/UKJLWfZ9juu9XR1KpVAmeC4iEI+uh/bPWRHUu1u6myjza8UZG9W3MXS1yns5CKZU7DQhXkZKewag54Qwev472Hyxl6A8bSEhKLbgMV3+KZ8IBnkh7jtDug/7Z3vJR6DMOolZyc+Jsynp7ON1s9NmS/dRP30MT2UeZTk/j4ZH3i3Twzfey3tYAs+y/kHzl84zzKeks3XOSXoFV8V72DlSoDc0ecKq8SqlrRwPCVazaH8ePa6JITEkjuGZ51kTEc9c3a4k5c8H1mZ06iKz8hL/c22O7sSs1yl82cKvpfVC3Bx5L3+L++jb+3Hmc8yk5N9lk52DsOX5Zf5g3qywHr7IQMsSpojaqUY5pFYbjk3Ya+WvUFfuX7DlJcpqN+8tshJPh0PU1fcir1L+ABoSrWB0Rj5eHG78Ob8sXQ5rx40MtOJaQzJ1freVogmuDgvz5Cum48+r5QdzZ3P/KBMZAn0/BvQTDEsZyIS2dheF5W0FszMK91PQ4TZMzy6DZ/eBVxunyhrbtxvj0Xpiw72DHr5fsm7vtGIGlE6mz9UOo1gQa93c6H6XUtaMB4SrWHIijRUBFvD2tuXDa1qnM1GGtOX42mSnrHVuoxRHx+zdg9i1kbHJvatxwIz0Dq2WfsGx1uPkNyp5Yz+CyO/gtD81Gmw6dZsHO43x4wwYMYjVD5UO/kOp843Ev+70DYc4zELMdgMTkNDbuO8R3Hh9i0pLgjvE6Wlipfwn9S81BbGIKe44n0vamSpdsD6xRjqY1y7Nyv2vmX1p7IJ4Nv4zmvHhTtetTzBjeNjMAZavZUKhcn5fcJrMh4jgnHZxs7uvlB6heUgiNnw0NekGFgHyVu5SXB/e2u4l7Eh4n3bMUfNsFFr5K1B8fMNltNL4pUdbqYVUb5SsfpdS1owEhB9a8QUKXymchehOc2JW5r0PdKmw/eobT551/wCwi/LA6khHfzeUWWUNqyP080C0Yd7dcpoR294Bb3qZi8hEGu/3FHAcmmzsUf56/dp9gVMBOzIXT1jrFLjC0bQDnSlRmdI3x1vOItV/QJHwMXu6C9P8WburmknyUUteGBoQcrN93nK+8v6Dhr11gQlf4qg38ORIy0ulYrzIisDofk83N2xHD6D928Xrl5bi5uVGh67OOH1z3FqjdiRdK/MbCsOxmIL/Uj2ui8HCDrgkzwS/YGjHsAhVKlWBIyxv4JfwCh9q9z5/dFtAx7X9MaT4NtyYDXJKHUura0YCQDUk9T589L3Ira6DDizBkBrQcBuu+hEm3E1S1BGW9PVixz7lmIxHhi78PEFjZ0D15IaZxfyiXzYPknBgDt7xDGTnHzfGT2Hs8McekiclpzAiL5sUbj+Bxah+0yvvCNFfzSIcbcTeGPv9bxfB5p6hYvQ6PdLjRZedXSl07GhCycW7OK7TK2MLaRm9YUyjXuwVuGwO3fwVRK3FfMpr2dSuzcn+cUxPNLd8Xy+6Ys7wVEI5JPWdNL51XfkGkNL6boe4LWbp2Y47JpodFcz4llfuTfrJGCwe6tsdPtXLe3NemFiU83PhwQBCzHm9LtXI5TJCnlCrSNCBcLmY7pXdOYmLGLVTp/Nil+0KGWO3vG77hzgoRxJxJ5kDsuTxn8dWyA/iV9SLkxK/gFwI1mjlVVO8eb4KbO/V2jMFmuzIwpWfY+HFNJM/7bsUnPtwKbh6un9rhtV4N2fjqzdzVoiZuuT0DUUoVWRoQshJBFowg0a0sk32GUKdKqSvTdHsDKtej465RlCGJFfvy9hxh06HTrI88xWtNEqwlHls84nwTTtnqRDYYRjfbGiKWXDmNxIKdxzl56gyPpk22nh0E3ulcPrkwxly5hoJS6l9HA0IWEv4b5vBa/psykDvaBmZ/kfP0gdu/xuPcMUaWXcCKPHQ/tZ4dRFC+pCc9kuaCdzkIzN/D14DbX2ez1OeGta9C/IFL8vrq7wg+KDMNnwsxcMs7Oh5AKXVV/7orREY2TSMuIULc/P+yz1YDn5YP8ETnOjmn9W8OQYO4K+0Pog7sJSnVsSkkpm08wtI9J/lP6zJ47P0DQu6FEo5PLJcdby8vFtR7h5QMN2xThkDsPgBW7o/jlrgfuD1tAbR5Cmp3zFc+Sqni718TEGw24ZvlB2j85p/8udP1C87vXj2HKkn72ep/L6/3aZJ7E0jX1zBuhmfMVIeajXYdO8ubc8LpULcy95hFILZ8jxa+qEurZjyZ9gzpZ2Lg6/bw2+P4/tqP5zxmkRE8xLo7UEqpXBT9gJCRTtJf77NlTC9aLbmTh80fvDVnJxdSXbsIW+qq/xFHefre95xjD0bL18S0foL+7qvYFbb8qkkTk9N48pfNlC/pydg76uK26XtrtHDF2i4pe+sbK3GgTAtGVP0W6vUgY9ccziensilgGO59/+fSbqZKqeKraAeEjHSY9SglV71HuaQo/CuU5CW3yXxwYRQTF7tumeb9OzcSnLyRiIDBePs43oTj1uEFEt3L0yHqU9LScw5Qv6w/TGTcef43uBmVD8yC5ARo/aQrim6Vw83QN6Q6fxzM4A3vl2mYNIFhnu9Rf/B7BbIGgVKqeCq6AUEEfh8O4bP4b/oQfms7i8rPrYI+n9HKYz8tNjxLdLxr1hY+sfhTksWTxn2fy9uB3mU5EvwsLdhFxMoZOSabtyOGYP9ytKxVDtZ9BdWbwQ2t81nqS/Vv6k+GTfh53SFub1qdP55uT2kvDQZKKccV3YCw41fYMYOw2k8wPr03/Zv5W00fzR/gfI9PaG72smXyG/nO5vDRYzRLWMxe31spUzGHWUavonb3Jzgg1am87l3ISLti/5FTSWyPPsNtTfxg808QHwHtn3N5M079amX4+t7mLHyuIx/eGUz1y9dTUEqpXBTNgJB2Af4ahVQL4vVTPQipWZ46VUpn7q7Q+l72VOnBrfET2bNxidPZiAgbZn9JSZNCzR5PO3UOHx9v/vR7nCoph7GtHHvF/vk7rAfgveqVgqXvwA1toWFfp8t8NT0Dq1G3qvNrHCilrm9FMyCs/RzORhMZ+hq7T5xnQDYLxtS892viTEW8Fr6I2Jx7wPzxwr00Pf4rMaUDqXhTS6eLWy30DuZktMEs/wCObrpk3/wdMQT5l8N/xxeQFA89/6sPeZVSRVLRCwjn42DlWGjQm59jalLC3Y0+QX5XJCtVriIRQf+hdvpBwv/8Ns/ZfLP8AJtWzKGOWwzVbs7fA95ujaoyyvYwCR4VYeajmesMHzmVxLboMwz3i7CeHYQMgepN85WXUkoVlKIXEDZ+B2nnSev8KrO3HqVbQ1/KlyyRbdJWfYexx+0mfDeOIT35vMNZrNofx3sL9vBKhWWIT0VrttF8KF+yBHe2C+Tx848hp6NgfGeI2c6C7dHc4raRW8NfhKqNoce7+cpHKaUKUtEKCGnJsPFbuKk784+XI/58KgOa5TwttKeHB2c6vImvxLF39ocOZzNh1UFCS8cTdH4NpsXD4Jn/2Tmf6noTESWDeaP8e0haEjK+Mw8ta834EmMx1ZrA/bPBp0K+81FKqYJStALCzl/hfCxpLZ/g40X7aFCtDF0b+F71kJad+7DctODGvePhXO7zCkXFnWf5vljeqLwM4+5prXPgAmW9PRnRowGTYvz5puFEpnnezlfpfdgUNMoeDMq7JB+llCooRScgiMDaL8G3MVPjb+TwqSRe7tkg11HDxhjW3PgMnrZkZNn7uWbz87pDVDGJNImdB0F3Q+mrB5y8uLO5P01qlOP9FXF8LEMIuv8jmvd/HrzLuiwPpZQqKA4HBGOMuzFmizFmrv19RWPMYmPMfvv3ClnSjjTGRBhj9hpjejiUQdRKOBlOSovH+GxpBC0DKtK5fhWHDm0Y2JzJ6d1g0w+Zk7tl50JqBtPDjvBmtTWYjGRr0jcXcnMzfDQwmEc71ObPZzvQqZ5j5VdKqaIgL3cIzwK7s7x/BVgiInWBJfb3GGMaAYOAxkBP4EtjjHuuZ984AfGuwBsRDYhNTOHlW+s7PMd+u5sqMy59AGlu3rBghHW3kY05245SKvkEPc9Oh4Z9wLeBQ+fPi/rVyvBqr0ZUKu36hWiUUqogORQQjDH+QC9gQpbN/YCJ9tcTgduzbJ8qIikiEglEAFfv5J+Rhm33XH5J68j07XE80bkOzWtVdLgSVcp4Uc3Pn0mlh8LBv607hWz8vO4w75WZjhsCt2iPH6WUysrRO4RPgRGALcu2qiISA2D/frExvgZwJEu6aPu2SxhjhhljwowxYWdjj4DNxmKfXsx8vC0jeub9P/cO9SrzQVxbMgI6wcLX4FTkJfv3nUikdMwaOqetxLR/ASrUynMeSilVnOUaEIwxvYGTIrIpt7QXD8lm2xVtOCIyXkRCRSS0pO08mzyb8c1zd9LsBue6ZnasW4XUDMO6JqPBzR2mDLokKKxdsYgvPMeRUe4GaPeMU3kopVRx5sh0mO2AvsaY2wBvoKwx5mfghDHGT0RijDF+wEl7+migZpbj/YFjVy9EOtW6P42XR+6PGnLSvFYFvD3dWHy0BO0GTYZp98G3XaDtM9jSUxgY/innPcvjfv/v1jKYSimlLpHrHYKIjBQRfxEJwHpYvFRE7gXmAA/Ykz0AzLa/ngMMMsZ4GWNqA3WBqy5ekO7mRc0W/ZysgsXb051WtStZaxzX7giPLoXS1WDJaNyWv0+EzY8t3adBpassjamUUtex/EyY/z4w3RjzMHAYGAggIuHGmOnALiAdeFJErjr7nEfZqi5ZAP7mhr68PjucsKhThAbUgcfXQMoZ/m/OXv7YlcDGZk3ynYdSShVXeboKi8gyEeltfx0vIt1EpK79+6ks6d4VkToiUl9EFuR6Yh/HexRdzYDm/lQo6cmXyw5YG9zcuOBeltnhCdzaxA9vT+ebpJRSqrgrGiOVXTQddMkSHjzYrjZL95xk1zFrxtFfNhzmfGqGtcCOUkqpHBWNgOBCD7QJoFQJd75afoAlu0/w7rxddK5fhZYBrrkLUUqp4qrYLbpbrqQn97apxbcrDrJ413EaVy/HF0Oa5TonklJKXe+K3R0CwMPta+Ph7kaVMl58P7QFpXSxeaWUylWxvFL6lvHm9yfaUaWMF1XK6JxCSinliGIZEAAaVdcpp5VSKi+KZZORUkqpvNOAoJRSCtCAoJRSyk4DglJKKUADglJKKTsNCEoppQANCEoppew0ICillAI0ICillLLTgKCUUgrQgKCUUspOA4JSSilAA4JSSik7DQhKKaUADQhKKaXsNCAopZQCNCAopZSy04CglFIK0ICglFLKTgOCUkopQAOCUkopu1wDgjHG2xizwRizzRgTbowZbd8ebIxZa4zZYYz5wxhTNssxI40xEcaYvcaYHgVZAaWUUq7hyB1CCtBVRIKBEKCnMaY1MAF4RUSaAL8BLwEYYxoBg4DGQE/gS2OMe0EUXimllOvkGhDEcs7+1tP+JUB9YIV9+2JggP11P2CqiKSISCQQAbR0aamVUkq5nEPPEIwx7saYrcBJYLGIrAd2An3tSQYCNe2vawBHshwebd+mlFKqCHMoIIhIhoiEAP5AS2NMIPAQ8KQxZhNQBki1JzfZneLyDcaYYcaYMGNMWGxsrHOlV0op5TJ56mUkIgnAMqCniOwRkVtEpDkwBThgTxbNP3cLYAWRY9mca7yIhIpIaJUqVZwqvFJKKddxpJdRFWNMeftrH+BmYI8xxte+zQ14DfjafsgcYJAxxssYUxuoC2woiMIrpZRyHQ8H0vgBE+09hdyA6SIy1xjzrDHmSXuaWcAPACISboyZDuwC0oEnRSSjAMqulFLKhYzIFc3711xoaKiEhYUVdjGUUupfxRizSURCXXU+HamslFIK0ICglFLKTgOCUkopQAOCUkopOw0ISimlAA0ISiml7DQgKKWUAjQgKKWUstOAoJRSCtCAoJRSyk4DglJKKUADglJKKTsNCEoppQANCEoppew0ICillAI0ICillLLTgKCUUgrQgKCUUspOA4JSSilAA4JSSik7DQhKKaUADQhKKaXsNCAopZQCNCAopZSy04CglFIK0ICglFLKTgOCUkopQAOCUkopu1wDgjHG2xizwRizzRgTbowZbd8eYoxZZ4zZaowJM8a0zHLMSGNMhDFmrzGmR0FWQCmllGt4OJAmBegqIueMMZ7AKmPMAuAtYLSILDDG3AZ8CHQ2xjQCBgGNgerAX8aYeiKSUUB1UEop5QK53iGI5Zz9raf9S+xfZe3bywHH7K/7AVNFJEVEIoEIoCVKKaWKNEfuEDDGuAObgJuAL0RkvTHmOWChMeYjrMDS1p68BrAuy+HR9m2Xn3MYMMz+9pwxZq9zVci3ykBcIeVdWLTOxd/1Vl+4Putc35Uncygg2Jt7Qowx5YHfjDGBWBfz50VkpjHmLuA74GbAZHeKbM45HhjvdMldxBgTJiKhhV2Oa0nrXPxdb/WF67fOrjxfnnoZiUgCsAzoCTwAzLLvmsE/zULRQM0sh/nzT3OSUkqpIsqRXkZV7HcGGGN8sO4C9mBd5DvZk3UF9ttfzwEGGWO8jDG1gbrABlcXXCmllGs50mTkB0y0P0dwA6aLyFxjTAIwzhjjASRjfx4gIuHGmOnALiAdeLKI9zAq9GarQqB1Lv6ut/qC1jnfjMgVzftKKaWuQzpSWSmlFKABQSmllF2xCwjGmJrGmL+NMbvtU208a99e0Riz2Biz3/69gn17JXv6c8aYzy87VwljzHhjzD5jzB5jzIDCqFNuXFznwcaYHcaY7caYP40xlQujTrlxos7djTGb7HXbZIzpmuVcze3bI4wxnxljsus6XahcVV9jTEljzDz773O4Meb9wqzX1bjyM85yzjnGmJ3Xui6OcvHvdd6vXyJSrL6wHoI3s78uA+wDGmFNrfGKffsrwAf216WA9sBw4PPLzjUaeMf+2g2oXNj1K8g6Y3UyOHmxnvbjRxV2/VxU56ZAdfvrQOBolnNtANpgjaFZANxa2PUrqPoCJYEu9tclgJVFsb6u/ozt2/oDvwA7C7tu16LOzly/Cv0HcA1+wLOB7sBewC/LD33vZemGcmVAOAKUKuw6XKs6Y01LEgvUsl8cvwaGFXZ9XFln+3YDxANe9jR7suwbDHxT2PUpqPpms28c8Ghh16eg6wyUBlbZL65FNiC4uM55vn4VuyajrIwxAVgRdD1QVURiAOzffXM5trz95dvGmM3GmBnGmKoFWFyXyE+dRSQNeBzYgTXOpBHWCPQizYk6DwC2iEgK1rQq0Vn2ZTvVSlGSz/pmPU95oA+wpCDL6wouqPPbwMdAUoEX1kXyU2dnr1/FNiAYY0oDM4HnROSsE6fwwBplvVpEmgFrgY9cWESXy2+djTWb7ePYb0OB7cBIlxbSxfJaZ2NMY+AD4LGLm7JJVmT7Yrugvhe3ewBTgM9E5GBBlNVV8ltnY0wIcJOI/FagBXUhF3zOTl2/imVAsF/YZgKTReTi9BonjDF+9v1+WG3lVxOP9d/ExV+iGUCzAiiuS7ioziEAInJArHvO6fwzaWGRk9c6G2P8sT7P+0XkgH1zNNYfzkVFdqoVF9X3ovHAfhH5tOBL7jwX1bkN0NwYE4XVbFTPGLPs2tQg71xUZ6euX8UuINh7iHwH7BaRT7LsmoM1/xL277Ovdh77BfEPoLN9Uzes0ddFjqvqDBwFGhljqtjfdwd2u7KsrpLXOttvoecBI0Vk9cXE9tvvRGNMa/s57yf3n9M156r62ve9gzVl/XMFXe78cOFn/JWIVBeRAKzOFPtEpHPB1yDvXFhn565fhf3QxNVfWB+4YDV3bLV/3QZUwmor3W//XjHLMVHAKeAc1n+MjezbawEr7OdaAtxQ2PW7BnUejhUEttt/oSoVdv1cUWfgNeB8lrRbAV/7vlBgJ3AA+Bz7CP6i9OWq+mLdAYn9M764/ZHCrl9Bf8ZZzhlAEX6o7OLf6zxfv3TqCqWUUkAxbDJSSin1/+3VMQEAAAzDoPhXvacKdoMJfoQAQCUEAEYIAFRCAGCEAEAlBADmAO0UEnfnT1+9AAAAAElFTkSuQmCC\n", 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" ] }, "metadata": { "needs_background": "light" }, "output_type": "display_data" } ], "source": [ "# on somme les 2 fits et on extrapole jusqu'en 2025\n", "\n", "time_sample = np.linspace(1958, 2025, 1000)\n", "fit_2025 = p(time_sample) + sin(time_sample, *params)\n", "\n", "plt.figure(figsize=(6, 4))\n", "plt.plot(x, y, label='Data')\n", "plt.plot(time_sample, fit_2025, label='Fitted function extrapolated to 2025')\n", "plt.legend()\n", "plt.xlim((2015,2026))\n", "plt.ylim((380,440))" ] }, { "cell_type": "code", "execution_count": 149, "metadata": {}, "outputs": [ { "data": { "text/plain": [ "(380, 440)" ] }, "execution_count": 149, "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": [ "# On peut comparer notre résultat avec le fit fournit dans le fichier de données\n", "\n", "plt.figure(figsize=(6, 4))\n", "plt.plot(x, y, label='Data')\n", "plt.plot(data.index, data['fit'], label='Fit fournit')\n", "plt.plot(time_sample, fit_2025, label='Fitted function extrapolated to 2025')\n", "plt.legend()\n", "plt.xlim((2015,2026))\n", "plt.ylim((380,440))" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "On constate que notre modèle mériterait plus de raffinement mais devrait permettre tout de même de prédire relativement précisément la variation future du taux de CO2" ] } ], "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 }