{ "cells": [ { "cell_type": "markdown", "metadata": {}, "source": [ "# Sujet 1 : Concentration de CO2 dans l'atmosphère depuis 1958" ] }, { "cell_type": "code", "execution_count": 1, "metadata": {}, "outputs": [], "source": [ "%matplotlib inline\n", "\n", "import numpy as np\n", "import pandas as pd\n", "import matplotlib.pyplot as plt\n", "import os.path\n", "import pandas as pd\n", "import datetime\n", "import scipy.signal as sps\n", "import scipy.optimize as spo" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "# Récupération des données" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "On va commencer par mettre les données dans un dataframe pandas. " ] }, { "cell_type": "code", "execution_count": 2, "metadata": {}, "outputs": [], "source": [ "data_url = r'https://scrippsco2.ucsd.edu/assets/data/atmospheric/stations/in_situ_co2/weekly/weekly_in_situ_co2_mlo.csv'\n", "data_file = r'weekly_in_situ_co2_mlo.csv'\n", "\n", "if not os.path.exists(data_file):\n", " print('please downlad the csv file of the following url', data_url, '\\n', 'and put it in the jupyter repository, at:', \n", " 'https://app-learninglab.inria.fr/moocrr/jupyter/user/your_unique_identifier/edit/work/module3/exo3/weekly_in_situ_co2_mlo.csv')\n", "else: \n", " data = pd.read_csv(data_file, skiprows=44, names=['week', 'CO2'])" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "J'ai eu des problèmes pour télécharger automatiquement les données (problème de certificat: cf [ce post sur StackOverflow](https://stackoverflow.com/questions/32400867/pandas-read-csv-from-url)), et puis ensuite pour y accéder depuis Jupyter. \n", "La solution la plus simple que j'ai trouvée est de télécharger à la main les données, puis de les réenvoyer dans le dossier Jupyter en ligne (cf [ce post](https://stackoverflow.com/questions/46972225/how-to-open-local-file-on-jupyter))" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "# Nettoyage et mise en forme des données" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "On visualise ensuite rapidement les données:" ] }, { "cell_type": "code", "execution_count": 3, "metadata": {}, "outputs": [ { "data": { "text/html": [ "
\n", " | week | \n", "CO2 | \n", "
---|---|---|
0 | \n", "1958-03-29 | \n", "316.19 | \n", "
1 | \n", "1958-04-05 | \n", "317.31 | \n", "
2 | \n", "1958-04-12 | \n", "317.69 | \n", "
3 | \n", "1958-04-19 | \n", "317.58 | \n", "
4 | \n", "1958-04-26 | \n", "316.48 | \n", "
\n", " | CO2 | \n", "
---|---|
week | \n", "\n", " |
1958-03-30 | \n", "316.19 | \n", "
1958-04-06 | \n", "317.31 | \n", "
1958-04-13 | \n", "317.69 | \n", "
1958-04-20 | \n", "317.58 | \n", "
1958-04-27 | \n", "316.48 | \n", "
1958-05-04 | \n", "316.95 | \n", "
1958-05-11 | \n", "NaN | \n", "
1958-05-18 | \n", "317.56 | \n", "
1958-05-25 | \n", "317.99 | \n", "
1958-06-01 | \n", "NaN | \n", "
1958-06-08 | \n", "NaN | \n", "
1958-06-15 | \n", "NaN | \n", "
1958-06-22 | \n", "NaN | \n", "
1958-06-29 | \n", "NaN | \n", "
1958-07-06 | \n", "315.85 | \n", "
1958-07-13 | \n", "315.85 | \n", "
1958-07-20 | \n", "315.46 | \n", "
1958-07-27 | \n", "315.59 | \n", "
1958-08-03 | \n", "315.64 | \n", "
1958-08-10 | \n", "315.10 | \n", "
1958-08-17 | \n", "315.09 | \n", "
1958-08-24 | \n", "NaN | \n", "
1958-08-31 | \n", "314.14 | \n", "
1958-09-07 | \n", "313.54 | \n", "
1958-09-14 | \n", "NaN | \n", "
1958-09-21 | \n", "NaN | \n", "
1958-09-28 | \n", "NaN | \n", "
1958-10-05 | \n", "NaN | \n", "
1958-10-12 | \n", "NaN | \n", "
1958-10-19 | \n", "NaN | \n", "
... | \n", "... | \n", "
2020-12-06 | \n", "413.00 | \n", "
2020-12-13 | \n", "413.60 | \n", "
2020-12-20 | \n", "414.34 | \n", "
2020-12-27 | \n", "414.64 | \n", "
2021-01-03 | \n", "415.19 | \n", "
2021-01-10 | \n", "414.83 | \n", "
2021-01-17 | \n", "414.84 | \n", "
2021-01-24 | \n", "415.46 | \n", "
2021-01-31 | \n", "415.68 | \n", "
2021-02-07 | \n", "416.91 | \n", "
2021-02-14 | \n", "416.46 | \n", "
2021-02-21 | \n", "416.16 | \n", "
2021-02-28 | \n", "416.43 | \n", "
2021-03-07 | \n", "417.56 | \n", "
2021-03-14 | \n", "416.54 | \n", "
2021-03-21 | \n", "417.93 | \n", "
2021-03-28 | \n", "416.43 | \n", "
2021-04-04 | \n", "417.69 | \n", "
2021-04-11 | \n", "419.02 | \n", "
2021-04-18 | \n", "417.66 | \n", "
2021-04-25 | \n", "418.54 | \n", "
2021-05-02 | \n", "419.65 | \n", "
2021-05-09 | \n", "418.16 | \n", "
2021-05-16 | \n", "418.90 | \n", "
2021-05-23 | \n", "417.94 | \n", "
2021-05-30 | \n", "419.49 | \n", "
2021-06-06 | \n", "419.54 | \n", "
2021-06-13 | \n", "418.93 | \n", "
2021-06-20 | \n", "418.49 | \n", "
2021-06-27 | \n", "417.82 | \n", "
3301 rows × 1 columns
\n", "