{
 "cells": [
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "# Concentration de CO2 dans l'atmosphère depuis 1958"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 60,
   "metadata": {},
   "outputs": [],
   "source": [
    "%matplotlib inline\n",
    "import matplotlib.pyplot as plt\n",
    "import pandas as pd\n",
    "import statsmodels.api as sm\n",
    "import isoweek"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 93,
   "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": 89,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<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>indicated by the date in the first column.</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>1958-03-29</th>\n",
       "      <td>316.19</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1958-04-05</th>\n",
       "      <td>317.31</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1958-04-12</th>\n",
       "      <td>317.69</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1958-04-19</th>\n",
       "      <td>317.58</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1958-04-26</th>\n",
       "      <td>316.48</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1958-05-03</th>\n",
       "      <td>316.95</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1958-05-17</th>\n",
       "      <td>317.56</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1958-05-24</th>\n",
       "      <td>317.99</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1958-07-05</th>\n",
       "      <td>315.85</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1958-07-12</th>\n",
       "      <td>315.85</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1958-07-19</th>\n",
       "      <td>315.46</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1958-07-26</th>\n",
       "      <td>315.59</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1958-08-02</th>\n",
       "      <td>315.64</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1958-08-09</th>\n",
       "      <td>315.10</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1958-08-16</th>\n",
       "      <td>315.09</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1958-08-30</th>\n",
       "      <td>314.14</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1958-09-06</th>\n",
       "      <td>313.54</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1958-11-08</th>\n",
       "      <td>313.05</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1958-11-15</th>\n",
       "      <td>313.26</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1958-11-22</th>\n",
       "      <td>313.57</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1958-11-29</th>\n",
       "      <td>314.01</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1958-12-06</th>\n",
       "      <td>314.56</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1958-12-13</th>\n",
       "      <td>314.41</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1958-12-20</th>\n",
       "      <td>314.77</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1958-12-27</th>\n",
       "      <td>315.21</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1959-01-03</th>\n",
       "      <td>315.24</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1959-01-10</th>\n",
       "      <td>315.50</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1959-01-17</th>\n",
       "      <td>315.69</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1959-01-24</th>\n",
       "      <td>315.86</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1959-01-31</th>\n",
       "      <td>315.42</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>...</th>\n",
       "      <td>...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2019-11-02</th>\n",
       "      <td>409.86</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2019-11-09</th>\n",
       "      <td>410.15</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2019-11-16</th>\n",
       "      <td>410.22</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2019-11-23</th>\n",
       "      <td>410.48</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2019-11-30</th>\n",
       "      <td>410.92</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2019-12-07</th>\n",
       "      <td>411.27</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2019-12-14</th>\n",
       "      <td>411.67</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2019-12-21</th>\n",
       "      <td>412.30</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2019-12-28</th>\n",
       "      <td>412.59</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2020-01-04</th>\n",
       "      <td>413.19</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2020-01-11</th>\n",
       "      <td>413.39</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2020-01-25</th>\n",
       "      <td>413.36</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2020-02-01</th>\n",
       "      <td>413.99</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2020-02-08</th>\n",
       "      <td>414.83</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2020-02-15</th>\n",
       "      <td>413.81</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2020-02-22</th>\n",
       "      <td>414.17</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2020-02-29</th>\n",
       "      <td>413.89</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2020-03-07</th>\n",
       "      <td>414.00</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2020-03-14</th>\n",
       "      <td>414.30</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2020-03-21</th>\n",
       "      <td>414.62</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2020-03-28</th>\n",
       "      <td>415.57</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2020-04-04</th>\n",
       "      <td>415.61</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2020-04-11</th>\n",
       "      <td>416.47</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2020-04-18</th>\n",
       "      <td>416.60</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2020-04-25</th>\n",
       "      <td>415.86</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2020-05-02</th>\n",
       "      <td>417.20</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2020-05-09</th>\n",
       "      <td>416.99</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2020-05-16</th>\n",
       "      <td>416.54</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2020-05-23</th>\n",
       "      <td>417.49</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2020-05-30</th>\n",
       "      <td>417.19</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "<p>3173 rows × 1 columns</p>\n",
       "</div>"
      ],
      "text/plain": [
       "             indicated by the date in the first column.                             \n",
       "1958-03-29                                             316.19                       \n",
       "1958-04-05                                             317.31                       \n",
       "1958-04-12                                             317.69                       \n",
       "1958-04-19                                             317.58                       \n",
       "1958-04-26                                             316.48                       \n",
       "1958-05-03                                             316.95                       \n",
       "1958-05-17                                             317.56                       \n",
       "1958-05-24                                             317.99                       \n",
       "1958-07-05                                             315.85                       \n",
       "1958-07-12                                             315.85                       \n",
       "1958-07-19                                             315.46                       \n",
       "1958-07-26                                             315.59                       \n",
       "1958-08-02                                             315.64                       \n",
       "1958-08-09                                             315.10                       \n",
       "1958-08-16                                             315.09                       \n",
       "1958-08-30                                             314.14                       \n",
       "1958-09-06                                             313.54                       \n",
       "1958-11-08                                             313.05                       \n",
       "1958-11-15                                             313.26                       \n",
       "1958-11-22                                             313.57                       \n",
       "1958-11-29                                             314.01                       \n",
       "1958-12-06                                             314.56                       \n",
       "1958-12-13                                             314.41                       \n",
       "1958-12-20                                             314.77                       \n",
       "1958-12-27                                             315.21                       \n",
       "1959-01-03                                             315.24                       \n",
       "1959-01-10                                             315.50                       \n",
       "1959-01-17                                             315.69                       \n",
       "1959-01-24                                             315.86                       \n",
       "1959-01-31                                             315.42                       \n",
       "...                                                       ...                       \n",
       "2019-11-02                                             409.86                       \n",
       "2019-11-09                                             410.15                       \n",
       "2019-11-16                                             410.22                       \n",
       "2019-11-23                                             410.48                       \n",
       "2019-11-30                                             410.92                       \n",
       "2019-12-07                                             411.27                       \n",
       "2019-12-14                                             411.67                       \n",
       "2019-12-21                                             412.30                       \n",
       "2019-12-28                                             412.59                       \n",
       "2020-01-04                                             413.19                       \n",
       "2020-01-11                                             413.39                       \n",
       "2020-01-25                                             413.36                       \n",
       "2020-02-01                                             413.99                       \n",
       "2020-02-08                                             414.83                       \n",
       "2020-02-15                                             413.81                       \n",
       "2020-02-22                                             414.17                       \n",
       "2020-02-29                                             413.89                       \n",
       "2020-03-07                                             414.00                       \n",
       "2020-03-14                                             414.30                       \n",
       "2020-03-21                                             414.62                       \n",
       "2020-03-28                                             415.57                       \n",
       "2020-04-04                                             415.61                       \n",
       "2020-04-11                                             416.47                       \n",
       "2020-04-18                                             416.60                       \n",
       "2020-04-25                                             415.86                       \n",
       "2020-05-02                                             417.20                       \n",
       "2020-05-09                                             416.99                       \n",
       "2020-05-16                                             416.54                       \n",
       "2020-05-23                                             417.49                       \n",
       "2020-05-30                                             417.19                       \n",
       "\n",
       "[3173 rows x 1 columns]"
      ]
     },
     "execution_count": 89,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "data = pd.read_csv(data_url, skiprows=43)\n",
    "data"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 90,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "Index(['1958-03-29', '1958-04-05', '1958-04-12', '1958-04-19', '1958-04-26',\n",
       "       '1958-05-03', '1958-05-17', '1958-05-24', '1958-07-05', '1958-07-12',\n",
       "       ...\n",
       "       '2020-03-28', '2020-04-04', '2020-04-11', '2020-04-18', '2020-04-25',\n",
       "       '2020-05-02', '2020-05-09', '2020-05-16', '2020-05-23', '2020-05-30'],\n",
       "      dtype='object', length=3173)"
      ]
     },
     "execution_count": 90,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "data.index"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 97,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 720x432 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "data.plot(figsize=(10, 6))\n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 101,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "<matplotlib.axes._subplots.AxesSubplot at 0x7f9dd5df0c18>"
      ]
     },
     "execution_count": 101,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 720x432 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "data[-200:].plot(figsize=(10,6))"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 107,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "<matplotlib.axes._subplots.AxesSubplot at 0x7f9dd5a77668>"
      ]
     },
     "execution_count": 107,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 720x432 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "data[-200:].plot(style='*',figsize=(10,6))"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 114,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "array([[<matplotlib.axes._subplots.AxesSubplot object at 0x7f9dd5803ac8>]],\n",
       "      dtype=object)"
      ]
     },
     "execution_count": 114,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 720x432 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "data.hist(figsize=(10,6))"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": []
  }
 ],
 "metadata": {
  "kernelspec": {
   "display_name": "Python 3",
   "language": "python",
   "name": "python3"
  },
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