{
 "cells": [
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "# Concentration de CO2 dans l'atmosphère depuis 1958"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 1,
   "metadata": {},
   "outputs": [],
   "source": [
    "%matplotlib inline\n",
    "import numpy as np\n",
    "import matplotlib.pyplot as plt\n",
    "import pandas as pd\n",
    "import os\n",
    "import requests\n",
    "import isoweek"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## 1. Import des données\n",
    "\n",
    "Les données ont été téléchargées au format csv depuis le site Web de [l'Institut Scripps](https://scrippsco2.ucsd.edu/data/atmospheric_co2/primary_mlo_co2_record.html\\) le 01/02/2025."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 2,
   "metadata": {},
   "outputs": [],
   "source": [
    "data_url = 'https://scrippsco2.ucsd.edu/assets/data/atmospheric/stations/in_situ_co2/weekly/weekly_in_situ_co2_mlo.csv'"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 3,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Données locales déjà existantes.\n"
     ]
    },
    {
     "data": {
      "text/html": [
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       "    }\n",
       "\n",
       "    .dataframe thead th {\n",
       "        text-align: right;\n",
       "    }\n",
       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>date</th>\n",
       "      <th>concentration</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>----------------------------------------------...</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>1958-03-29</td>\n",
       "      <td>316.19</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>1958-04-05</td>\n",
       "      <td>317.31</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>1958-04-12</td>\n",
       "      <td>317.69</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>1958-04-19</td>\n",
       "      <td>317.58</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>5</th>\n",
       "      <td>1958-04-26</td>\n",
       "      <td>316.48</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>6</th>\n",
       "      <td>1958-05-03</td>\n",
       "      <td>316.95</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>7</th>\n",
       "      <td>1958-05-17</td>\n",
       "      <td>317.56</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>8</th>\n",
       "      <td>1958-05-24</td>\n",
       "      <td>317.99</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>9</th>\n",
       "      <td>1958-07-05</td>\n",
       "      <td>315.85</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>10</th>\n",
       "      <td>1958-07-12</td>\n",
       "      <td>315.85</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>11</th>\n",
       "      <td>1958-07-19</td>\n",
       "      <td>315.46</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>12</th>\n",
       "      <td>1958-07-26</td>\n",
       "      <td>315.59</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>13</th>\n",
       "      <td>1958-08-02</td>\n",
       "      <td>315.64</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>14</th>\n",
       "      <td>1958-08-09</td>\n",
       "      <td>315.10</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>15</th>\n",
       "      <td>1958-08-16</td>\n",
       "      <td>315.09</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>16</th>\n",
       "      <td>1958-08-30</td>\n",
       "      <td>314.14</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>17</th>\n",
       "      <td>1958-09-06</td>\n",
       "      <td>313.54</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>18</th>\n",
       "      <td>1958-11-08</td>\n",
       "      <td>313.05</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>19</th>\n",
       "      <td>1958-11-15</td>\n",
       "      <td>313.26</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>20</th>\n",
       "      <td>1958-11-22</td>\n",
       "      <td>313.57</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>21</th>\n",
       "      <td>1958-11-29</td>\n",
       "      <td>314.01</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>22</th>\n",
       "      <td>1958-12-06</td>\n",
       "      <td>314.56</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>23</th>\n",
       "      <td>1958-12-13</td>\n",
       "      <td>314.41</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>24</th>\n",
       "      <td>1958-12-20</td>\n",
       "      <td>314.77</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>25</th>\n",
       "      <td>1958-12-27</td>\n",
       "      <td>315.21</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>26</th>\n",
       "      <td>1959-01-03</td>\n",
       "      <td>315.24</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>27</th>\n",
       "      <td>1959-01-10</td>\n",
       "      <td>315.50</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>28</th>\n",
       "      <td>1959-01-17</td>\n",
       "      <td>315.69</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>29</th>\n",
       "      <td>1959-01-24</td>\n",
       "      <td>315.86</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>...</th>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3381</th>\n",
       "      <td>2024-06-08</td>\n",
       "      <td>427.01</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3382</th>\n",
       "      <td>2024-06-15</td>\n",
       "      <td>427.10</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3383</th>\n",
       "      <td>2024-06-22</td>\n",
       "      <td>426.54</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3384</th>\n",
       "      <td>2024-06-29</td>\n",
       "      <td>425.41</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3385</th>\n",
       "      <td>2024-07-06</td>\n",
       "      <td>425.73</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3386</th>\n",
       "      <td>2024-07-13</td>\n",
       "      <td>426.10</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3387</th>\n",
       "      <td>2024-07-20</td>\n",
       "      <td>424.36</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3388</th>\n",
       "      <td>2024-07-27</td>\n",
       "      <td>424.72</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3389</th>\n",
       "      <td>2024-08-03</td>\n",
       "      <td>424.42</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3390</th>\n",
       "      <td>2024-08-10</td>\n",
       "      <td>422.50</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3391</th>\n",
       "      <td>2024-08-17</td>\n",
       "      <td>422.80</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3392</th>\n",
       "      <td>2024-08-24</td>\n",
       "      <td>421.45</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3393</th>\n",
       "      <td>2024-08-31</td>\n",
       "      <td>421.57</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3394</th>\n",
       "      <td>2024-09-07</td>\n",
       "      <td>421.81</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3395</th>\n",
       "      <td>2024-09-14</td>\n",
       "      <td>421.39</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3396</th>\n",
       "      <td>2024-09-21</td>\n",
       "      <td>421.77</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3397</th>\n",
       "      <td>2024-09-28</td>\n",
       "      <td>421.51</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3398</th>\n",
       "      <td>2024-10-05</td>\n",
       "      <td>421.86</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3399</th>\n",
       "      <td>2024-10-12</td>\n",
       "      <td>422.13</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3400</th>\n",
       "      <td>2024-10-19</td>\n",
       "      <td>422.16</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3401</th>\n",
       "      <td>2024-10-26</td>\n",
       "      <td>422.36</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3402</th>\n",
       "      <td>2024-11-02</td>\n",
       "      <td>423.15</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3403</th>\n",
       "      <td>2024-11-09</td>\n",
       "      <td>423.18</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3404</th>\n",
       "      <td>2024-11-16</td>\n",
       "      <td>423.51</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3405</th>\n",
       "      <td>2024-11-23</td>\n",
       "      <td>424.03</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3406</th>\n",
       "      <td>2024-11-30</td>\n",
       "      <td>424.44</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3407</th>\n",
       "      <td>2024-12-07</td>\n",
       "      <td>424.93</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3408</th>\n",
       "      <td>2024-12-14</td>\n",
       "      <td>424.79</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3409</th>\n",
       "      <td>2024-12-21</td>\n",
       "      <td>425.35</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3410</th>\n",
       "      <td>2024-12-28</td>\n",
       "      <td>425.57</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "<p>3411 rows × 2 columns</p>\n",
       "</div>"
      ],
      "text/plain": [
       "                                                   date  concentration\n",
       "0     ----------------------------------------------...            NaN\n",
       "1                                            1958-03-29         316.19\n",
       "2                                            1958-04-05         317.31\n",
       "3                                            1958-04-12         317.69\n",
       "4                                            1958-04-19         317.58\n",
       "5                                            1958-04-26         316.48\n",
       "6                                            1958-05-03         316.95\n",
       "7                                            1958-05-17         317.56\n",
       "8                                            1958-05-24         317.99\n",
       "9                                            1958-07-05         315.85\n",
       "10                                           1958-07-12         315.85\n",
       "11                                           1958-07-19         315.46\n",
       "12                                           1958-07-26         315.59\n",
       "13                                           1958-08-02         315.64\n",
       "14                                           1958-08-09         315.10\n",
       "15                                           1958-08-16         315.09\n",
       "16                                           1958-08-30         314.14\n",
       "17                                           1958-09-06         313.54\n",
       "18                                           1958-11-08         313.05\n",
       "19                                           1958-11-15         313.26\n",
       "20                                           1958-11-22         313.57\n",
       "21                                           1958-11-29         314.01\n",
       "22                                           1958-12-06         314.56\n",
       "23                                           1958-12-13         314.41\n",
       "24                                           1958-12-20         314.77\n",
       "25                                           1958-12-27         315.21\n",
       "26                                           1959-01-03         315.24\n",
       "27                                           1959-01-10         315.50\n",
       "28                                           1959-01-17         315.69\n",
       "29                                           1959-01-24         315.86\n",
       "...                                                 ...            ...\n",
       "3381                                         2024-06-08         427.01\n",
       "3382                                         2024-06-15         427.10\n",
       "3383                                         2024-06-22         426.54\n",
       "3384                                         2024-06-29         425.41\n",
       "3385                                         2024-07-06         425.73\n",
       "3386                                         2024-07-13         426.10\n",
       "3387                                         2024-07-20         424.36\n",
       "3388                                         2024-07-27         424.72\n",
       "3389                                         2024-08-03         424.42\n",
       "3390                                         2024-08-10         422.50\n",
       "3391                                         2024-08-17         422.80\n",
       "3392                                         2024-08-24         421.45\n",
       "3393                                         2024-08-31         421.57\n",
       "3394                                         2024-09-07         421.81\n",
       "3395                                         2024-09-14         421.39\n",
       "3396                                         2024-09-21         421.77\n",
       "3397                                         2024-09-28         421.51\n",
       "3398                                         2024-10-05         421.86\n",
       "3399                                         2024-10-12         422.13\n",
       "3400                                         2024-10-19         422.16\n",
       "3401                                         2024-10-26         422.36\n",
       "3402                                         2024-11-02         423.15\n",
       "3403                                         2024-11-09         423.18\n",
       "3404                                         2024-11-16         423.51\n",
       "3405                                         2024-11-23         424.03\n",
       "3406                                         2024-11-30         424.44\n",
       "3407                                         2024-12-07         424.93\n",
       "3408                                         2024-12-14         424.79\n",
       "3409                                         2024-12-21         425.35\n",
       "3410                                         2024-12-28         425.57\n",
       "\n",
       "[3411 rows x 2 columns]"
      ]
     },
     "execution_count": 3,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "file_path = r\"C:\\Users\\33612\\Downloads\\weekly_in_situ_co2_mlo.csv\"\n",
    "\n",
    "if not os.path.exists(file_path):\n",
    "    response = requests.get(data_url)\n",
    "    with open(file_path, \"wb\") as file:\n",
    "        file.write(response.content)\n",
    "    print(\"Téléchargement des données et sauvegarde locale.\")\n",
    "else:\n",
    "    print(\"Données locales déjà existantes.\")\n",
    "\n",
    "raw_data = pd.read_csv(file_path, names=[\"date\", \"concentration\"], skiprows=range(1,44)) # retrait des commentaires en haut du fichier .csv\n",
    "raw_data"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## 2. Traitement des données"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "Recherche d'éventuelles lignes vides :"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 4,
   "metadata": {},
   "outputs": [
    {
     "data": {
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       "  <thead>\n",
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      "text/plain": [
       "                                                date  concentration\n",
       "0  ----------------------------------------------...            NaN"
      ]
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     "execution_count": 4,
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   "source": [
    "raw_data[raw_data.isnull().any(axis=1)]"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 5,
   "metadata": {},
   "outputs": [
    {
     "data": {
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       "      <th>concentration</th>\n",
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       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>1958-03-29</td>\n",
       "      <td>316.19</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>1958-04-05</td>\n",
       "      <td>317.31</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>1958-04-12</td>\n",
       "      <td>317.69</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>1958-04-19</td>\n",
       "      <td>317.58</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>5</th>\n",
       "      <td>1958-04-26</td>\n",
       "      <td>316.48</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>6</th>\n",
       "      <td>1958-05-03</td>\n",
       "      <td>316.95</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>7</th>\n",
       "      <td>1958-05-17</td>\n",
       "      <td>317.56</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>8</th>\n",
       "      <td>1958-05-24</td>\n",
       "      <td>317.99</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>9</th>\n",
       "      <td>1958-07-05</td>\n",
       "      <td>315.85</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>10</th>\n",
       "      <td>1958-07-12</td>\n",
       "      <td>315.85</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>11</th>\n",
       "      <td>1958-07-19</td>\n",
       "      <td>315.46</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>12</th>\n",
       "      <td>1958-07-26</td>\n",
       "      <td>315.59</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>13</th>\n",
       "      <td>1958-08-02</td>\n",
       "      <td>315.64</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>14</th>\n",
       "      <td>1958-08-09</td>\n",
       "      <td>315.10</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>15</th>\n",
       "      <td>1958-08-16</td>\n",
       "      <td>315.09</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>16</th>\n",
       "      <td>1958-08-30</td>\n",
       "      <td>314.14</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>17</th>\n",
       "      <td>1958-09-06</td>\n",
       "      <td>313.54</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>18</th>\n",
       "      <td>1958-11-08</td>\n",
       "      <td>313.05</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>19</th>\n",
       "      <td>1958-11-15</td>\n",
       "      <td>313.26</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>20</th>\n",
       "      <td>1958-11-22</td>\n",
       "      <td>313.57</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>21</th>\n",
       "      <td>1958-11-29</td>\n",
       "      <td>314.01</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>22</th>\n",
       "      <td>1958-12-06</td>\n",
       "      <td>314.56</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>23</th>\n",
       "      <td>1958-12-13</td>\n",
       "      <td>314.41</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>24</th>\n",
       "      <td>1958-12-20</td>\n",
       "      <td>314.77</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>25</th>\n",
       "      <td>1958-12-27</td>\n",
       "      <td>315.21</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>26</th>\n",
       "      <td>1959-01-03</td>\n",
       "      <td>315.24</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>27</th>\n",
       "      <td>1959-01-10</td>\n",
       "      <td>315.50</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>28</th>\n",
       "      <td>1959-01-17</td>\n",
       "      <td>315.69</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>29</th>\n",
       "      <td>1959-01-24</td>\n",
       "      <td>315.86</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>30</th>\n",
       "      <td>1959-01-31</td>\n",
       "      <td>315.42</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>...</th>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3381</th>\n",
       "      <td>2024-06-08</td>\n",
       "      <td>427.01</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3382</th>\n",
       "      <td>2024-06-15</td>\n",
       "      <td>427.10</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3383</th>\n",
       "      <td>2024-06-22</td>\n",
       "      <td>426.54</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3384</th>\n",
       "      <td>2024-06-29</td>\n",
       "      <td>425.41</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3385</th>\n",
       "      <td>2024-07-06</td>\n",
       "      <td>425.73</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3386</th>\n",
       "      <td>2024-07-13</td>\n",
       "      <td>426.10</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3387</th>\n",
       "      <td>2024-07-20</td>\n",
       "      <td>424.36</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3388</th>\n",
       "      <td>2024-07-27</td>\n",
       "      <td>424.72</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3389</th>\n",
       "      <td>2024-08-03</td>\n",
       "      <td>424.42</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3390</th>\n",
       "      <td>2024-08-10</td>\n",
       "      <td>422.50</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3391</th>\n",
       "      <td>2024-08-17</td>\n",
       "      <td>422.80</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3392</th>\n",
       "      <td>2024-08-24</td>\n",
       "      <td>421.45</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3393</th>\n",
       "      <td>2024-08-31</td>\n",
       "      <td>421.57</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3394</th>\n",
       "      <td>2024-09-07</td>\n",
       "      <td>421.81</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3395</th>\n",
       "      <td>2024-09-14</td>\n",
       "      <td>421.39</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3396</th>\n",
       "      <td>2024-09-21</td>\n",
       "      <td>421.77</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3397</th>\n",
       "      <td>2024-09-28</td>\n",
       "      <td>421.51</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3398</th>\n",
       "      <td>2024-10-05</td>\n",
       "      <td>421.86</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3399</th>\n",
       "      <td>2024-10-12</td>\n",
       "      <td>422.13</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3400</th>\n",
       "      <td>2024-10-19</td>\n",
       "      <td>422.16</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3401</th>\n",
       "      <td>2024-10-26</td>\n",
       "      <td>422.36</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3402</th>\n",
       "      <td>2024-11-02</td>\n",
       "      <td>423.15</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3403</th>\n",
       "      <td>2024-11-09</td>\n",
       "      <td>423.18</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3404</th>\n",
       "      <td>2024-11-16</td>\n",
       "      <td>423.51</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3405</th>\n",
       "      <td>2024-11-23</td>\n",
       "      <td>424.03</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3406</th>\n",
       "      <td>2024-11-30</td>\n",
       "      <td>424.44</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3407</th>\n",
       "      <td>2024-12-07</td>\n",
       "      <td>424.93</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3408</th>\n",
       "      <td>2024-12-14</td>\n",
       "      <td>424.79</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3409</th>\n",
       "      <td>2024-12-21</td>\n",
       "      <td>425.35</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3410</th>\n",
       "      <td>2024-12-28</td>\n",
       "      <td>425.57</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "<p>3410 rows × 2 columns</p>\n",
       "</div>"
      ],
      "text/plain": [
       "            date  concentration\n",
       "1     1958-03-29         316.19\n",
       "2     1958-04-05         317.31\n",
       "3     1958-04-12         317.69\n",
       "4     1958-04-19         317.58\n",
       "5     1958-04-26         316.48\n",
       "6     1958-05-03         316.95\n",
       "7     1958-05-17         317.56\n",
       "8     1958-05-24         317.99\n",
       "9     1958-07-05         315.85\n",
       "10    1958-07-12         315.85\n",
       "11    1958-07-19         315.46\n",
       "12    1958-07-26         315.59\n",
       "13    1958-08-02         315.64\n",
       "14    1958-08-09         315.10\n",
       "15    1958-08-16         315.09\n",
       "16    1958-08-30         314.14\n",
       "17    1958-09-06         313.54\n",
       "18    1958-11-08         313.05\n",
       "19    1958-11-15         313.26\n",
       "20    1958-11-22         313.57\n",
       "21    1958-11-29         314.01\n",
       "22    1958-12-06         314.56\n",
       "23    1958-12-13         314.41\n",
       "24    1958-12-20         314.77\n",
       "25    1958-12-27         315.21\n",
       "26    1959-01-03         315.24\n",
       "27    1959-01-10         315.50\n",
       "28    1959-01-17         315.69\n",
       "29    1959-01-24         315.86\n",
       "30    1959-01-31         315.42\n",
       "...          ...            ...\n",
       "3381  2024-06-08         427.01\n",
       "3382  2024-06-15         427.10\n",
       "3383  2024-06-22         426.54\n",
       "3384  2024-06-29         425.41\n",
       "3385  2024-07-06         425.73\n",
       "3386  2024-07-13         426.10\n",
       "3387  2024-07-20         424.36\n",
       "3388  2024-07-27         424.72\n",
       "3389  2024-08-03         424.42\n",
       "3390  2024-08-10         422.50\n",
       "3391  2024-08-17         422.80\n",
       "3392  2024-08-24         421.45\n",
       "3393  2024-08-31         421.57\n",
       "3394  2024-09-07         421.81\n",
       "3395  2024-09-14         421.39\n",
       "3396  2024-09-21         421.77\n",
       "3397  2024-09-28         421.51\n",
       "3398  2024-10-05         421.86\n",
       "3399  2024-10-12         422.13\n",
       "3400  2024-10-19         422.16\n",
       "3401  2024-10-26         422.36\n",
       "3402  2024-11-02         423.15\n",
       "3403  2024-11-09         423.18\n",
       "3404  2024-11-16         423.51\n",
       "3405  2024-11-23         424.03\n",
       "3406  2024-11-30         424.44\n",
       "3407  2024-12-07         424.93\n",
       "3408  2024-12-14         424.79\n",
       "3409  2024-12-21         425.35\n",
       "3410  2024-12-28         425.57\n",
       "\n",
       "[3410 rows x 2 columns]"
      ]
     },
     "execution_count": 5,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "data = raw_data.dropna().copy()\n",
    "data"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "Conversion de la première colonne au format `datetime` :"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 6,
   "metadata": {},
   "outputs": [],
   "source": [
    "data[\"date\"] = pd.to_datetime(data[\"date\"], format=\"%Y-%m-%d\") # Conversion de la première colonne en dates"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "Premier aperçu des données :"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 7,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 864x432 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "plt.figure(figsize=(12, 6))\n",
    "plt.plot(data[\"date\"], data[\"concentration\"], marker=\".\")\n",
    "plt.xlabel(\"Temps\")\n",
    "plt.ylabel(\"Concentration en CO2 (ppm)\")\n",
    "plt.xticks(rotation=45)\n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### 2.1. Une oscillation périodique superposée à une évolution systématique plus lente :"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "Afin de séparer la composante oscillante de la tendance générale de cette série temporelle, nous allons utilisier `seasonal_decompose` issue de `statsmodels.tsa.seasonal`. La bibliothèque `statsmodels` permet de réaliser des analyses statistiques sur des séries temporelles."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 8,
   "metadata": {},
   "outputs": [],
   "source": [
    "from statsmodels.tsa.seasonal import seasonal_decompose"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "La variation de concentration en CO2 évoluant de manière saisonnière, on estime *a priori* sa période d'oscillation à 52 semaines, c'est-à-dire un an."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 9,
   "metadata": {},
   "outputs": [],
   "source": [
    "decomposed_data = seasonal_decompose(data['concentration'], model=\"additive\", period=52)\n",
    "\n",
    "data['tendance'] = decomposed_data.trend #Extraction de la tendance\n",
    "data['oscillations'] = decomposed_data.seasonal #Extraction des oscillations"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 10,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 720x360 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "fig1, ax1 = plt.subplots(figsize=(10, 5))\n",
    "ax1.plot(data['date'], data['concentration'], label=\"Données brutes\")\n",
    "ax1.plot(data['date'], data['tendance'], color=\"red\", label=\"Tendance\")\n",
    "ax1.set_xlabel('Temps', fontsize=16)\n",
    "ax1.set_ylabel('Concentration en CO2 (ppm)', fontsize=16)\n",
    "ax1.legend()\n",
    "plt.xticks(fontsize=16)\n",
    "plt.yticks(fontsize=16)\n",
    "plt.grid()\n",
    "plt.legend(fontsize=16)\n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "Traçons les deux composantes (lente et rapide) sur des graphes séparés afin de les visualiser : "
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 11,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 1296x432 with 2 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "fig2, ax2 = plt.subplots(1,2, figsize=(18, 6))\n",
    "\n",
    "ax2[0].plot(data['date'], data['tendance'], c='r', label=\"Tendance\")\n",
    "ax2[0].set_xlabel('Temps', fontsize=16)\n",
    "ax2[0].set_ylabel('[CO2] (ppm)', fontsize=16)\n",
    "ax2[0].legend(fontsize=16)\n",
    "ax2[0].tick_params(axis='both', labelsize=16)\n",
    "ax2[0].grid()\n",
    "\n",
    "ax2[1].plot(data['date'], data['oscillations'], label=\"Oscillations\")\n",
    "ax2[1].set_xlabel('Temps', fontsize=16)\n",
    "ax2[1].set_ylabel('$\\Delta$ [CO2] (ppm)', fontsize=16)\n",
    "ax2[1].legend(fontsize=16)\n",
    "ax2[1].tick_params(axis='both', labelsize=16)\n",
    "ax2[1].grid()"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### 2.2. Caractérisation des oscillations périodiques"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "Nous nous concentrons désormais sur la composante rapide afin de la caractériser. Nous allons ajuster cette composante oscillante avec une fonction de la forme $f(t) = A sin(2\\pi f t + \\phi)$, de cette manière nous pourrons extraire l'amplitude des oscillations $A$ et leur fréquence $f$.  \n",
    "\n",
    "Cet ajustement par un sinus fait l'hypothèse qu'il n'existe qu'une seule fréquence caractéristique dans ces oscillations. Cette hypothèse est raisonable dans le cadre de l'étude d'une variation saisonnière de la concentration en CO2 dans l'atmosphère. "
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 12,
   "metadata": {},
   "outputs": [],
   "source": [
    "import scipy.optimize as spo"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "Pour que l'ajustement avec `scipy.optimize.curve_fit` fonctionne, il faut d'abord convertir les dates contenues dans notre série de données du type `datetime64[ns]` vers un type numérique comme le `float64`. La ligne de code ci-dessous convertit les dates en numéro de semaine."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 13,
   "metadata": {},
   "outputs": [],
   "source": [
    "data['date_num'] = (data['date'] - data['date'].min())  / np.timedelta64(1, 'W')"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "Les données peuvent désormais être ajustées :"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 14,
   "metadata": {},
   "outputs": [],
   "source": [
    "def sin_fit(t,A,f,phi):\n",
    "    return A*np.sin(2*np.pi*f*t + phi)\n",
    "\n",
    "guess = [2,1/52,0] #dans l'ordre : amplitude, fréquence, phase\n",
    "popt, _ = spo.curve_fit(sin_fit, data['date_num'], data['oscillations'], p0=guess) #ajustement des données par un sinus"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "Revenons au format `datetime64[ns]` pour tracer les données proprement : "
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 15,
   "metadata": {},
   "outputs": [],
   "source": [
    "data['date_bis'] = data['date'].min() + pd.to_timedelta(data['date_num'], unit='W')"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 23,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 720x360 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "fig3, ax3 = plt.subplots(figsize=(10, 5))\n",
    "ax3.plot(data['date'], data['oscillations'], marker = '+', label=\"Composante oscillante\")\n",
    "ax3.plot(data['date_bis'], sin_fit(data['date_num'],*popt), label=f\"Fit $f(t) = A sin(2\\pi f t + \\phi)$ \\n $A$ = {popt[0]:.2f} ppm, $f$ = {popt[1]:.3f} /semaine, $\\phi$ = {popt[2]:.2f} rad\")\n",
    "ax3.set_xlabel('Temps', fontsize=16)\n",
    "ax3.set_ylabel('[CO2] (ppm)', fontsize=16)\n",
    "ax3.legend(fontsize=14,bbox_to_anchor=(1, 1.03))\n",
    "ax3.tick_params(axis='both', labelsize=16)\n",
    "ax3.grid()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 17,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "L'amplitude des oscillations est de 1.800 ppm, leur fréquence est de 0.019 /semaine. Cela correspond à une période de 52.388 semaines, soit une année, comme attendu.\n"
     ]
    }
   ],
   "source": [
    "print(f\"L'amplitude des oscillations est de {popt[0]:.3f} ppm, leur fréquence est de {popt[1]:.3f} /semaine. Cela correspond à une période de {1/popt[1]:.3f} semaines, soit une année, comme attendu.\")"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### 2.3. Caractérisation de la composante lente et extrapolation jusqu'à 2050"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "D'après les derniers [rapports du GIEC](https://www.ipcc.ch/), la concentration en CO2 dans l'atmosphère augmente avec une tendance principalement exponentielle. \n",
    "\n",
    "La composante lente de notre série temporelle sera donc ajustée par une courbe exponentielle de la forme $f(t) = y_0 + A e^{t/\\tau}$. Cela permettra d'extrapoler les données jusqu'en 2050.\n",
    "\n",
    "Par construction, la tendance extraite des données brutes avec `statsmodels.tsa.seasonal.seasonal_decompose` comporte des NaN pour les 26 premières semaines et les 26 dernières semaines. L'ajustement avec `scipy.optimize.curve_fit` ne supporte pas le type NaN. Nous choisissons de supprimer les lignes correspondant à des NaN afin de pouvoir utiliser `scipy.optimize.curve_fit`."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 18,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
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       "<style scoped>\n",
       "    .dataframe tbody tr th:only-of-type {\n",
       "        vertical-align: middle;\n",
       "    }\n",
       "\n",
       "    .dataframe tbody tr th {\n",
       "        vertical-align: top;\n",
       "    }\n",
       "\n",
       "    .dataframe thead th {\n",
       "        text-align: right;\n",
       "    }\n",
       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>date</th>\n",
       "      <th>concentration</th>\n",
       "      <th>tendance</th>\n",
       "      <th>oscillations</th>\n",
       "      <th>date_num</th>\n",
       "      <th>date_bis</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>27</th>\n",
       "      <td>1959-01-10</td>\n",
       "      <td>315.50</td>\n",
       "      <td>316.300673</td>\n",
       "      <td>-2.459605</td>\n",
       "      <td>41.0</td>\n",
       "      <td>1959-01-10</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>28</th>\n",
       "      <td>1959-01-17</td>\n",
       "      <td>315.69</td>\n",
       "      <td>316.272115</td>\n",
       "      <td>-2.483316</td>\n",
       "      <td>42.0</td>\n",
       "      <td>1959-01-17</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>29</th>\n",
       "      <td>1959-01-24</td>\n",
       "      <td>315.86</td>\n",
       "      <td>316.223173</td>\n",
       "      <td>-2.297352</td>\n",
       "      <td>43.0</td>\n",
       "      <td>1959-01-24</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>30</th>\n",
       "      <td>1959-01-31</td>\n",
       "      <td>315.42</td>\n",
       "      <td>316.164327</td>\n",
       "      <td>-2.161713</td>\n",
       "      <td>44.0</td>\n",
       "      <td>1959-01-31</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>31</th>\n",
       "      <td>1959-02-14</td>\n",
       "      <td>316.94</td>\n",
       "      <td>316.111827</td>\n",
       "      <td>-1.966287</td>\n",
       "      <td>46.0</td>\n",
       "      <td>1959-02-14</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>32</th>\n",
       "      <td>1959-02-21</td>\n",
       "      <td>316.61</td>\n",
       "      <td>316.063269</td>\n",
       "      <td>-1.740902</td>\n",
       "      <td>47.0</td>\n",
       "      <td>1959-02-21</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>33</th>\n",
       "      <td>1959-02-28</td>\n",
       "      <td>316.62</td>\n",
       "      <td>315.995865</td>\n",
       "      <td>-1.488386</td>\n",
       "      <td>48.0</td>\n",
       "      <td>1959-02-28</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>34</th>\n",
       "      <td>1959-03-07</td>\n",
       "      <td>316.81</td>\n",
       "      <td>315.914712</td>\n",
       "      <td>-1.262435</td>\n",
       "      <td>49.0</td>\n",
       "      <td>1959-03-07</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>35</th>\n",
       "      <td>1959-03-21</td>\n",
       "      <td>316.73</td>\n",
       "      <td>315.844904</td>\n",
       "      <td>-0.990745</td>\n",
       "      <td>51.0</td>\n",
       "      <td>1959-03-21</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>36</th>\n",
       "      <td>1959-03-28</td>\n",
       "      <td>316.71</td>\n",
       "      <td>315.791923</td>\n",
       "      <td>-0.710275</td>\n",
       "      <td>52.0</td>\n",
       "      <td>1959-03-28</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>37</th>\n",
       "      <td>1959-04-04</td>\n",
       "      <td>317.72</td>\n",
       "      <td>315.746442</td>\n",
       "      <td>-0.493469</td>\n",
       "      <td>53.0</td>\n",
       "      <td>1959-04-04</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>38</th>\n",
       "      <td>1959-04-11</td>\n",
       "      <td>317.12</td>\n",
       "      <td>315.706442</td>\n",
       "      <td>-0.276853</td>\n",
       "      <td>54.0</td>\n",
       "      <td>1959-04-11</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>39</th>\n",
       "      <td>1959-04-18</td>\n",
       "      <td>317.64</td>\n",
       "      <td>315.671346</td>\n",
       "      <td>-0.096491</td>\n",
       "      <td>55.0</td>\n",
       "      <td>1959-04-18</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>40</th>\n",
       "      <td>1959-04-25</td>\n",
       "      <td>318.32</td>\n",
       "      <td>315.650192</td>\n",
       "      <td>0.149438</td>\n",
       "      <td>56.0</td>\n",
       "      <td>1959-04-25</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>41</th>\n",
       "      <td>1959-05-02</td>\n",
       "      <td>318.27</td>\n",
       "      <td>315.641635</td>\n",
       "      <td>0.223774</td>\n",
       "      <td>57.0</td>\n",
       "      <td>1959-05-02</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>42</th>\n",
       "      <td>1959-05-09</td>\n",
       "      <td>318.78</td>\n",
       "      <td>315.649808</td>\n",
       "      <td>0.443974</td>\n",
       "      <td>58.0</td>\n",
       "      <td>1959-05-09</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>43</th>\n",
       "      <td>1959-05-16</td>\n",
       "      <td>318.05</td>\n",
       "      <td>315.675096</td>\n",
       "      <td>0.468542</td>\n",
       "      <td>59.0</td>\n",
       "      <td>1959-05-16</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>44</th>\n",
       "      <td>1959-05-23</td>\n",
       "      <td>318.43</td>\n",
       "      <td>315.709519</td>\n",
       "      <td>0.733705</td>\n",
       "      <td>60.0</td>\n",
       "      <td>1959-05-23</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>45</th>\n",
       "      <td>1959-06-06</td>\n",
       "      <td>318.53</td>\n",
       "      <td>315.751731</td>\n",
       "      <td>0.952119</td>\n",
       "      <td>62.0</td>\n",
       "      <td>1959-06-06</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>46</th>\n",
       "      <td>1959-06-13</td>\n",
       "      <td>318.14</td>\n",
       "      <td>315.796635</td>\n",
       "      <td>1.158873</td>\n",
       "      <td>63.0</td>\n",
       "      <td>1959-06-13</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>47</th>\n",
       "      <td>1959-06-20</td>\n",
       "      <td>317.88</td>\n",
       "      <td>315.835577</td>\n",
       "      <td>1.278166</td>\n",
       "      <td>64.0</td>\n",
       "      <td>1959-06-20</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>48</th>\n",
       "      <td>1959-06-27</td>\n",
       "      <td>317.76</td>\n",
       "      <td>315.863654</td>\n",
       "      <td>1.476997</td>\n",
       "      <td>65.0</td>\n",
       "      <td>1959-06-27</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>49</th>\n",
       "      <td>1959-07-04</td>\n",
       "      <td>316.86</td>\n",
       "      <td>315.893942</td>\n",
       "      <td>1.599921</td>\n",
       "      <td>66.0</td>\n",
       "      <td>1959-07-04</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>50</th>\n",
       "      <td>1959-07-11</td>\n",
       "      <td>316.83</td>\n",
       "      <td>315.931923</td>\n",
       "      <td>1.540975</td>\n",
       "      <td>67.0</td>\n",
       "      <td>1959-07-11</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>51</th>\n",
       "      <td>1959-07-18</td>\n",
       "      <td>316.45</td>\n",
       "      <td>315.963846</td>\n",
       "      <td>1.781099</td>\n",
       "      <td>68.0</td>\n",
       "      <td>1959-07-18</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>52</th>\n",
       "      <td>1959-07-25</td>\n",
       "      <td>316.16</td>\n",
       "      <td>315.990769</td>\n",
       "      <td>1.943156</td>\n",
       "      <td>69.0</td>\n",
       "      <td>1959-07-25</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>53</th>\n",
       "      <td>1959-08-01</td>\n",
       "      <td>315.62</td>\n",
       "      <td>316.015288</td>\n",
       "      <td>2.117891</td>\n",
       "      <td>70.0</td>\n",
       "      <td>1959-08-01</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>54</th>\n",
       "      <td>1959-08-08</td>\n",
       "      <td>314.91</td>\n",
       "      <td>316.038365</td>\n",
       "      <td>2.074795</td>\n",
       "      <td>71.0</td>\n",
       "      <td>1959-08-08</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>55</th>\n",
       "      <td>1959-08-22</td>\n",
       "      <td>315.00</td>\n",
       "      <td>316.065769</td>\n",
       "      <td>2.168921</td>\n",
       "      <td>73.0</td>\n",
       "      <td>1959-08-22</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>56</th>\n",
       "      <td>1959-08-29</td>\n",
       "      <td>314.15</td>\n",
       "      <td>316.095962</td>\n",
       "      <td>2.075506</td>\n",
       "      <td>74.0</td>\n",
       "      <td>1959-08-29</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>...</th>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3355</th>\n",
       "      <td>2023-12-09</td>\n",
       "      <td>421.23</td>\n",
       "      <td>422.399231</td>\n",
       "      <td>-2.459605</td>\n",
       "      <td>3428.0</td>\n",
       "      <td>2023-12-09</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3356</th>\n",
       "      <td>2023-12-16</td>\n",
       "      <td>422.57</td>\n",
       "      <td>422.468173</td>\n",
       "      <td>-2.483316</td>\n",
       "      <td>3429.0</td>\n",
       "      <td>2023-12-16</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3357</th>\n",
       "      <td>2023-12-23</td>\n",
       "      <td>422.06</td>\n",
       "      <td>422.549904</td>\n",
       "      <td>-2.297352</td>\n",
       "      <td>3430.0</td>\n",
       "      <td>2023-12-23</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3358</th>\n",
       "      <td>2023-12-30</td>\n",
       "      <td>421.76</td>\n",
       "      <td>422.616635</td>\n",
       "      <td>-2.161713</td>\n",
       "      <td>3431.0</td>\n",
       "      <td>2023-12-30</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3359</th>\n",
       "      <td>2024-01-06</td>\n",
       "      <td>422.85</td>\n",
       "      <td>422.674519</td>\n",
       "      <td>-1.966287</td>\n",
       "      <td>3432.0</td>\n",
       "      <td>2024-01-06</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3360</th>\n",
       "      <td>2024-01-13</td>\n",
       "      <td>423.13</td>\n",
       "      <td>422.752212</td>\n",
       "      <td>-1.740902</td>\n",
       "      <td>3433.0</td>\n",
       "      <td>2024-01-13</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3361</th>\n",
       "      <td>2024-01-20</td>\n",
       "      <td>422.65</td>\n",
       "      <td>422.831923</td>\n",
       "      <td>-1.488386</td>\n",
       "      <td>3434.0</td>\n",
       "      <td>2024-01-20</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3362</th>\n",
       "      <td>2024-01-27</td>\n",
       "      <td>422.27</td>\n",
       "      <td>422.903654</td>\n",
       "      <td>-1.262435</td>\n",
       "      <td>3435.0</td>\n",
       "      <td>2024-01-27</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3363</th>\n",
       "      <td>2024-02-03</td>\n",
       "      <td>423.97</td>\n",
       "      <td>422.979327</td>\n",
       "      <td>-0.990745</td>\n",
       "      <td>3436.0</td>\n",
       "      <td>2024-02-03</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3364</th>\n",
       "      <td>2024-02-10</td>\n",
       "      <td>424.62</td>\n",
       "      <td>423.039231</td>\n",
       "      <td>-0.710275</td>\n",
       "      <td>3437.0</td>\n",
       "      <td>2024-02-10</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3365</th>\n",
       "      <td>2024-02-17</td>\n",
       "      <td>423.58</td>\n",
       "      <td>423.097308</td>\n",
       "      <td>-0.493469</td>\n",
       "      <td>3438.0</td>\n",
       "      <td>2024-02-17</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3366</th>\n",
       "      <td>2024-02-24</td>\n",
       "      <td>425.10</td>\n",
       "      <td>423.159327</td>\n",
       "      <td>-0.276853</td>\n",
       "      <td>3439.0</td>\n",
       "      <td>2024-02-24</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3367</th>\n",
       "      <td>2024-03-02</td>\n",
       "      <td>424.50</td>\n",
       "      <td>423.213942</td>\n",
       "      <td>-0.096491</td>\n",
       "      <td>3440.0</td>\n",
       "      <td>2024-03-02</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3368</th>\n",
       "      <td>2024-03-09</td>\n",
       "      <td>425.09</td>\n",
       "      <td>423.277404</td>\n",
       "      <td>0.149438</td>\n",
       "      <td>3441.0</td>\n",
       "      <td>2024-03-09</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3369</th>\n",
       "      <td>2024-03-16</td>\n",
       "      <td>425.71</td>\n",
       "      <td>423.338942</td>\n",
       "      <td>0.223774</td>\n",
       "      <td>3442.0</td>\n",
       "      <td>2024-03-16</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3370</th>\n",
       "      <td>2024-03-23</td>\n",
       "      <td>425.94</td>\n",
       "      <td>423.405000</td>\n",
       "      <td>0.443974</td>\n",
       "      <td>3443.0</td>\n",
       "      <td>2024-03-23</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3371</th>\n",
       "      <td>2024-03-30</td>\n",
       "      <td>425.02</td>\n",
       "      <td>423.478269</td>\n",
       "      <td>0.468542</td>\n",
       "      <td>3444.0</td>\n",
       "      <td>2024-03-30</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3372</th>\n",
       "      <td>2024-04-06</td>\n",
       "      <td>425.99</td>\n",
       "      <td>423.549231</td>\n",
       "      <td>0.733705</td>\n",
       "      <td>3445.0</td>\n",
       "      <td>2024-04-06</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3373</th>\n",
       "      <td>2024-04-13</td>\n",
       "      <td>425.43</td>\n",
       "      <td>423.617212</td>\n",
       "      <td>0.952119</td>\n",
       "      <td>3446.0</td>\n",
       "      <td>2024-04-13</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3374</th>\n",
       "      <td>2024-04-20</td>\n",
       "      <td>426.91</td>\n",
       "      <td>423.680865</td>\n",
       "      <td>1.158873</td>\n",
       "      <td>3447.0</td>\n",
       "      <td>2024-04-20</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3375</th>\n",
       "      <td>2024-04-27</td>\n",
       "      <td>427.13</td>\n",
       "      <td>423.748654</td>\n",
       "      <td>1.278166</td>\n",
       "      <td>3448.0</td>\n",
       "      <td>2024-04-27</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3376</th>\n",
       "      <td>2024-05-04</td>\n",
       "      <td>426.51</td>\n",
       "      <td>423.823846</td>\n",
       "      <td>1.476997</td>\n",
       "      <td>3449.0</td>\n",
       "      <td>2024-05-04</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3377</th>\n",
       "      <td>2024-05-11</td>\n",
       "      <td>427.20</td>\n",
       "      <td>423.899327</td>\n",
       "      <td>1.599921</td>\n",
       "      <td>3450.0</td>\n",
       "      <td>2024-05-11</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3378</th>\n",
       "      <td>2024-05-18</td>\n",
       "      <td>426.26</td>\n",
       "      <td>423.957981</td>\n",
       "      <td>1.540975</td>\n",
       "      <td>3451.0</td>\n",
       "      <td>2024-05-18</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3379</th>\n",
       "      <td>2024-05-25</td>\n",
       "      <td>426.68</td>\n",
       "      <td>424.007404</td>\n",
       "      <td>1.781099</td>\n",
       "      <td>3452.0</td>\n",
       "      <td>2024-05-25</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3380</th>\n",
       "      <td>2024-06-01</td>\n",
       "      <td>426.78</td>\n",
       "      <td>424.074423</td>\n",
       "      <td>1.943156</td>\n",
       "      <td>3453.0</td>\n",
       "      <td>2024-06-01</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3381</th>\n",
       "      <td>2024-06-08</td>\n",
       "      <td>427.01</td>\n",
       "      <td>424.150000</td>\n",
       "      <td>2.117891</td>\n",
       "      <td>3454.0</td>\n",
       "      <td>2024-06-08</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3382</th>\n",
       "      <td>2024-06-15</td>\n",
       "      <td>427.10</td>\n",
       "      <td>424.206923</td>\n",
       "      <td>2.074795</td>\n",
       "      <td>3455.0</td>\n",
       "      <td>2024-06-15</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3383</th>\n",
       "      <td>2024-06-22</td>\n",
       "      <td>426.54</td>\n",
       "      <td>424.259904</td>\n",
       "      <td>2.168921</td>\n",
       "      <td>3456.0</td>\n",
       "      <td>2024-06-22</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3384</th>\n",
       "      <td>2024-06-29</td>\n",
       "      <td>425.41</td>\n",
       "      <td>424.328173</td>\n",
       "      <td>2.075506</td>\n",
       "      <td>3457.0</td>\n",
       "      <td>2024-06-29</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "<p>3358 rows × 6 columns</p>\n",
       "</div>"
      ],
      "text/plain": [
       "           date  concentration    tendance  oscillations  date_num   date_bis\n",
       "27   1959-01-10         315.50  316.300673     -2.459605      41.0 1959-01-10\n",
       "28   1959-01-17         315.69  316.272115     -2.483316      42.0 1959-01-17\n",
       "29   1959-01-24         315.86  316.223173     -2.297352      43.0 1959-01-24\n",
       "30   1959-01-31         315.42  316.164327     -2.161713      44.0 1959-01-31\n",
       "31   1959-02-14         316.94  316.111827     -1.966287      46.0 1959-02-14\n",
       "32   1959-02-21         316.61  316.063269     -1.740902      47.0 1959-02-21\n",
       "33   1959-02-28         316.62  315.995865     -1.488386      48.0 1959-02-28\n",
       "34   1959-03-07         316.81  315.914712     -1.262435      49.0 1959-03-07\n",
       "35   1959-03-21         316.73  315.844904     -0.990745      51.0 1959-03-21\n",
       "36   1959-03-28         316.71  315.791923     -0.710275      52.0 1959-03-28\n",
       "37   1959-04-04         317.72  315.746442     -0.493469      53.0 1959-04-04\n",
       "38   1959-04-11         317.12  315.706442     -0.276853      54.0 1959-04-11\n",
       "39   1959-04-18         317.64  315.671346     -0.096491      55.0 1959-04-18\n",
       "40   1959-04-25         318.32  315.650192      0.149438      56.0 1959-04-25\n",
       "41   1959-05-02         318.27  315.641635      0.223774      57.0 1959-05-02\n",
       "42   1959-05-09         318.78  315.649808      0.443974      58.0 1959-05-09\n",
       "43   1959-05-16         318.05  315.675096      0.468542      59.0 1959-05-16\n",
       "44   1959-05-23         318.43  315.709519      0.733705      60.0 1959-05-23\n",
       "45   1959-06-06         318.53  315.751731      0.952119      62.0 1959-06-06\n",
       "46   1959-06-13         318.14  315.796635      1.158873      63.0 1959-06-13\n",
       "47   1959-06-20         317.88  315.835577      1.278166      64.0 1959-06-20\n",
       "48   1959-06-27         317.76  315.863654      1.476997      65.0 1959-06-27\n",
       "49   1959-07-04         316.86  315.893942      1.599921      66.0 1959-07-04\n",
       "50   1959-07-11         316.83  315.931923      1.540975      67.0 1959-07-11\n",
       "51   1959-07-18         316.45  315.963846      1.781099      68.0 1959-07-18\n",
       "52   1959-07-25         316.16  315.990769      1.943156      69.0 1959-07-25\n",
       "53   1959-08-01         315.62  316.015288      2.117891      70.0 1959-08-01\n",
       "54   1959-08-08         314.91  316.038365      2.074795      71.0 1959-08-08\n",
       "55   1959-08-22         315.00  316.065769      2.168921      73.0 1959-08-22\n",
       "56   1959-08-29         314.15  316.095962      2.075506      74.0 1959-08-29\n",
       "...         ...            ...         ...           ...       ...        ...\n",
       "3355 2023-12-09         421.23  422.399231     -2.459605    3428.0 2023-12-09\n",
       "3356 2023-12-16         422.57  422.468173     -2.483316    3429.0 2023-12-16\n",
       "3357 2023-12-23         422.06  422.549904     -2.297352    3430.0 2023-12-23\n",
       "3358 2023-12-30         421.76  422.616635     -2.161713    3431.0 2023-12-30\n",
       "3359 2024-01-06         422.85  422.674519     -1.966287    3432.0 2024-01-06\n",
       "3360 2024-01-13         423.13  422.752212     -1.740902    3433.0 2024-01-13\n",
       "3361 2024-01-20         422.65  422.831923     -1.488386    3434.0 2024-01-20\n",
       "3362 2024-01-27         422.27  422.903654     -1.262435    3435.0 2024-01-27\n",
       "3363 2024-02-03         423.97  422.979327     -0.990745    3436.0 2024-02-03\n",
       "3364 2024-02-10         424.62  423.039231     -0.710275    3437.0 2024-02-10\n",
       "3365 2024-02-17         423.58  423.097308     -0.493469    3438.0 2024-02-17\n",
       "3366 2024-02-24         425.10  423.159327     -0.276853    3439.0 2024-02-24\n",
       "3367 2024-03-02         424.50  423.213942     -0.096491    3440.0 2024-03-02\n",
       "3368 2024-03-09         425.09  423.277404      0.149438    3441.0 2024-03-09\n",
       "3369 2024-03-16         425.71  423.338942      0.223774    3442.0 2024-03-16\n",
       "3370 2024-03-23         425.94  423.405000      0.443974    3443.0 2024-03-23\n",
       "3371 2024-03-30         425.02  423.478269      0.468542    3444.0 2024-03-30\n",
       "3372 2024-04-06         425.99  423.549231      0.733705    3445.0 2024-04-06\n",
       "3373 2024-04-13         425.43  423.617212      0.952119    3446.0 2024-04-13\n",
       "3374 2024-04-20         426.91  423.680865      1.158873    3447.0 2024-04-20\n",
       "3375 2024-04-27         427.13  423.748654      1.278166    3448.0 2024-04-27\n",
       "3376 2024-05-04         426.51  423.823846      1.476997    3449.0 2024-05-04\n",
       "3377 2024-05-11         427.20  423.899327      1.599921    3450.0 2024-05-11\n",
       "3378 2024-05-18         426.26  423.957981      1.540975    3451.0 2024-05-18\n",
       "3379 2024-05-25         426.68  424.007404      1.781099    3452.0 2024-05-25\n",
       "3380 2024-06-01         426.78  424.074423      1.943156    3453.0 2024-06-01\n",
       "3381 2024-06-08         427.01  424.150000      2.117891    3454.0 2024-06-08\n",
       "3382 2024-06-15         427.10  424.206923      2.074795    3455.0 2024-06-15\n",
       "3383 2024-06-22         426.54  424.259904      2.168921    3456.0 2024-06-22\n",
       "3384 2024-06-29         425.41  424.328173      2.075506    3457.0 2024-06-29\n",
       "\n",
       "[3358 rows x 6 columns]"
      ]
     },
     "execution_count": 18,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "data_sans_NaN = data.dropna(subset=['tendance'])\n",
    "data_sans_NaN"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 19,
   "metadata": {},
   "outputs": [],
   "source": [
    "def exp_fit(t,y0,A,tau):\n",
    "    return y0 + A*np.exp(t/tau)\n",
    "\n",
    "guess = [300,100,25e3] #dans l'ordre : offset, amplitude, temps caractéristique\n",
    "popt, _ = spo.curve_fit(exp_fit, data_sans_NaN['date_num'], data_sans_NaN['tendance'], p0=guess) #ajustement des données par une exponentielle"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "Construisons un axe temporel qui s'étend jusqu'au 1er janvier 2050 afin d'extrapoler nos données :"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 20,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Dernier jour de l'axe temporel : 2050-01-01 00:00:00\n"
     ]
    }
   ],
   "source": [
    "temps_2050 = np.linspace(data['date_num'].iloc[0], data['date_num'].iloc[-1]+1305,len(data['date_num']+1305)) #axe temporel jusqu'à 2050, type = float64\n",
    "temps_2050_datetime = pd.to_datetime(data['date'].iloc[0]) + pd.to_timedelta(temps_2050, unit='W') #conversion vers le type = datetime64[ns]\n",
    "\n",
    "print(f\"Dernier jour de l'axe temporel : {temps_2050_datetime[-1]}\")"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "Nous pouvons désormais tracer la tendance des données recueillies jusqu'en 2024 et leur ajustement extrapolé jusqu'en 2050 : "
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 21,
   "metadata": {
    "scrolled": true
   },
   "outputs": [
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 720x360 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "fig4, ax4 = plt.subplots(figsize=(10, 5))\n",
    "ax4.plot(data['date'], data['tendance'], marker = '+', label=\"Tendance\")\n",
    "ax4.plot(temps_2050_datetime, exp_fit(temps_2050,*popt), label=f\"Modèle exponentiel \\n y0 = {popt[0]:.2f} ppm, A = {popt[1]:.2f} ppm, tau = {popt[2]:.2f} /semaine.\")\n",
    "ax4.set_xlabel('Temps', fontsize=16)\n",
    "ax4.set_ylabel('[CO2] (ppm)', fontsize=16)\n",
    "ax4.legend(fontsize=14,bbox_to_anchor=(1, 1.03))\n",
    "ax4.tick_params(axis='both', labelsize=16)\n",
    "ax4.grid()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 22,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Le modèle prédit une concentration en CO2 de 510.70 ppm au 1er janvier 2050.\n"
     ]
    }
   ],
   "source": [
    "print(f\"Le modèle prédit une concentration en CO2 de {exp_fit(temps_2050[-1],*popt):.2f} ppm au 1er janvier 2050.\")"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": []
  }
 ],
 "metadata": {
  "kernelspec": {
   "display_name": "Python 3",
   "language": "python",
   "name": "python3"
  },
  "language_info": {
   "codemirror_mode": {
    "name": "ipython",
    "version": 3
   },
   "file_extension": ".py",
   "mimetype": "text/x-python",
   "name": "python",
   "nbconvert_exporter": "python",
   "pygments_lexer": "ipython3",
   "version": "3.6.4"
  }
 },
 "nbformat": 4,
 "nbformat_minor": 2
}