From 20d95e48345f86334006a4d3c1c63ba873c5c6b1 Mon Sep 17 00:00:00 2001
From: 6a057d4c0b5da227e313d46089968294
 <6a057d4c0b5da227e313d46089968294@app-learninglab.inria.fr>
Date: Sat, 3 Sep 2022 14:59:08 +0000
Subject: [PATCH] correct indexation of dataframes

---
 .../exo3/carbon_dioxyde_concentration.ipynb   | 1056 ++++++++++++++++-
 1 file changed, 1034 insertions(+), 22 deletions(-)

diff --git a/module3/exo3/carbon_dioxyde_concentration.ipynb b/module3/exo3/carbon_dioxyde_concentration.ipynb
index bfc0959..3fd3696 100644
--- a/module3/exo3/carbon_dioxyde_concentration.ipynb
+++ b/module3/exo3/carbon_dioxyde_concentration.ipynb
@@ -15,7 +15,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 4,
+   "execution_count": 118,
    "metadata": {},
    "outputs": [],
    "source": [
@@ -36,7 +36,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 2,
+   "execution_count": 119,
    "metadata": {},
    "outputs": [],
    "source": [
@@ -52,7 +52,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 7,
+   "execution_count": 120,
    "metadata": {},
    "outputs": [],
    "source": [
@@ -84,7 +84,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 49,
+   "execution_count": 121,
    "metadata": {},
    "outputs": [
     {
@@ -1049,7 +1049,7 @@
        "[780 rows x 10 columns]"
       ]
      },
-     "execution_count": 49,
+     "execution_count": 121,
      "metadata": {},
      "output_type": "execute_result"
     }
@@ -1070,7 +1070,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 66,
+   "execution_count": 122,
    "metadata": {},
    "outputs": [
     {
@@ -1222,7 +1222,7 @@
        "779       -99.99  "
       ]
      },
-     "execution_count": 66,
+     "execution_count": 122,
      "metadata": {},
      "output_type": "execute_result"
     }
@@ -1241,7 +1241,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 69,
+   "execution_count": 123,
    "metadata": {},
    "outputs": [
     {
@@ -2206,7 +2206,7 @@
        "[773 rows x 10 columns]"
       ]
      },
-     "execution_count": 69,
+     "execution_count": 123,
      "metadata": {},
      "output_type": "execute_result"
     }
@@ -2218,10 +2218,983 @@
   },
   {
    "cell_type": "code",
-   "execution_count": null,
+   "execution_count": 146,
    "metadata": {},
-   "outputs": [],
-   "source": []
+   "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",
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+       "</style>\n",
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+       "  <thead>\n",
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+       "      <th></th>\n",
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+       "      <th>DDate</th>\n",
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+       "  </thead>\n",
+       "  <tbody>\n",
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+       "      <th>1958-03</th>\n",
+       "      <td>1958</td>\n",
+       "      <td>3</td>\n",
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+       "      <td>315.71</td>\n",
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+       "      <th>1958-04</th>\n",
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+       "      <td>317.45</td>\n",
+       "      <td>315.16</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>1958-05</th>\n",
+       "      <td>1958</td>\n",
+       "      <td>5</td>\n",
+       "      <td>21320</td>\n",
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+       "      <td>317.51</td>\n",
+       "      <td>314.70</td>\n",
+       "      <td>317.88</td>\n",
+       "      <td>315.07</td>\n",
+       "      <td>317.51</td>\n",
+       "      <td>314.70</td>\n",
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+       "    <tr>\n",
+       "      <th>1958-06</th>\n",
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+       "      <td>-99.99</td>\n",
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+       "      <td>315.15</td>\n",
+       "      <td>317.26</td>\n",
+       "      <td>315.15</td>\n",
+       "    </tr>\n",
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+       "      <td>7</td>\n",
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+       "      <td>1958.5370</td>\n",
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+       "      <td>315.20</td>\n",
+       "      <td>315.86</td>\n",
+       "      <td>315.22</td>\n",
+       "      <td>315.87</td>\n",
+       "      <td>315.20</td>\n",
+       "    </tr>\n",
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+       "      <th>1958-08</th>\n",
+       "      <td>1958</td>\n",
+       "      <td>8</td>\n",
+       "      <td>21412</td>\n",
+       "      <td>1958.6219</td>\n",
+       "      <td>314.93</td>\n",
+       "      <td>316.21</td>\n",
+       "      <td>313.98</td>\n",
+       "      <td>315.29</td>\n",
+       "      <td>314.93</td>\n",
+       "      <td>316.21</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>1958-09</th>\n",
+       "      <td>1958</td>\n",
+       "      <td>9</td>\n",
+       "      <td>21443</td>\n",
+       "      <td>1958.7068</td>\n",
+       "      <td>313.21</td>\n",
+       "      <td>316.10</td>\n",
+       "      <td>312.45</td>\n",
+       "      <td>315.36</td>\n",
+       "      <td>313.21</td>\n",
+       "      <td>316.10</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>1958-10</th>\n",
+       "      <td>1958</td>\n",
+       "      <td>10</td>\n",
+       "      <td>21473</td>\n",
+       "      <td>1958.7890</td>\n",
+       "      <td>-99.99</td>\n",
+       "      <td>-99.99</td>\n",
+       "      <td>312.43</td>\n",
+       "      <td>315.41</td>\n",
+       "      <td>312.43</td>\n",
+       "      <td>315.41</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>1958-11</th>\n",
+       "      <td>1958</td>\n",
+       "      <td>11</td>\n",
+       "      <td>21504</td>\n",
+       "      <td>1958.8740</td>\n",
+       "      <td>313.33</td>\n",
+       "      <td>315.21</td>\n",
+       "      <td>313.61</td>\n",
+       "      <td>315.46</td>\n",
+       "      <td>313.33</td>\n",
+       "      <td>315.21</td>\n",
+       "    </tr>\n",
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+       "      <td>1958</td>\n",
+       "      <td>12</td>\n",
+       "      <td>21534</td>\n",
+       "      <td>1958.9562</td>\n",
+       "      <td>314.67</td>\n",
+       "      <td>315.43</td>\n",
+       "      <td>314.77</td>\n",
+       "      <td>315.52</td>\n",
+       "      <td>314.67</td>\n",
+       "      <td>315.43</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>1959-01</th>\n",
+       "      <td>1959</td>\n",
+       "      <td>1</td>\n",
+       "      <td>21565</td>\n",
+       "      <td>1959.0411</td>\n",
+       "      <td>315.58</td>\n",
+       "      <td>315.52</td>\n",
+       "      <td>315.64</td>\n",
+       "      <td>315.58</td>\n",
+       "      <td>315.58</td>\n",
+       "      <td>315.52</td>\n",
+       "    </tr>\n",
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+       "      <th>1959-02</th>\n",
+       "      <td>1959</td>\n",
+       "      <td>2</td>\n",
+       "      <td>21596</td>\n",
+       "      <td>1959.1260</td>\n",
+       "      <td>316.49</td>\n",
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+       "      <td>316.29</td>\n",
+       "      <td>315.64</td>\n",
+       "      <td>316.49</td>\n",
+       "      <td>315.84</td>\n",
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+       "      <th>1959-03</th>\n",
+       "      <td>1959</td>\n",
+       "      <td>3</td>\n",
+       "      <td>21624</td>\n",
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+       "      <td>316.65</td>\n",
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+       "      <td>316.99</td>\n",
+       "      <td>315.70</td>\n",
+       "      <td>316.65</td>\n",
+       "      <td>315.37</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>1959-04</th>\n",
+       "      <td>1959</td>\n",
+       "      <td>4</td>\n",
+       "      <td>21655</td>\n",
+       "      <td>1959.2877</td>\n",
+       "      <td>317.72</td>\n",
+       "      <td>315.42</td>\n",
+       "      <td>318.09</td>\n",
+       "      <td>315.77</td>\n",
+       "      <td>317.72</td>\n",
+       "      <td>315.42</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>1959-05</th>\n",
+       "      <td>1959</td>\n",
+       "      <td>5</td>\n",
+       "      <td>21685</td>\n",
+       "      <td>1959.3699</td>\n",
+       "      <td>318.29</td>\n",
+       "      <td>315.48</td>\n",
+       "      <td>318.67</td>\n",
+       "      <td>315.85</td>\n",
+       "      <td>318.29</td>\n",
+       "      <td>315.48</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>1959-06</th>\n",
+       "      <td>1959</td>\n",
+       "      <td>6</td>\n",
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+       "      <td>1959.4548</td>\n",
+       "      <td>318.15</td>\n",
+       "      <td>316.01</td>\n",
+       "      <td>318.06</td>\n",
+       "      <td>315.94</td>\n",
+       "      <td>318.15</td>\n",
+       "      <td>316.01</td>\n",
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+       "      <th>1959-07</th>\n",
+       "      <td>1959</td>\n",
+       "      <td>7</td>\n",
+       "      <td>21746</td>\n",
+       "      <td>1959.5370</td>\n",
+       "      <td>316.54</td>\n",
+       "      <td>315.87</td>\n",
+       "      <td>316.67</td>\n",
+       "      <td>316.03</td>\n",
+       "      <td>316.54</td>\n",
+       "      <td>315.87</td>\n",
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+       "      <th>1959-08</th>\n",
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+       "      <td>8</td>\n",
+       "      <td>21777</td>\n",
+       "      <td>1959.6219</td>\n",
+       "      <td>314.80</td>\n",
+       "      <td>316.08</td>\n",
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+       "      <td>316.13</td>\n",
+       "      <td>314.80</td>\n",
+       "      <td>316.08</td>\n",
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+       "      <th>1959-09</th>\n",
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+       "      <td>9</td>\n",
+       "      <td>21808</td>\n",
+       "      <td>1959.7068</td>\n",
+       "      <td>313.84</td>\n",
+       "      <td>316.74</td>\n",
+       "      <td>313.30</td>\n",
+       "      <td>316.22</td>\n",
+       "      <td>313.84</td>\n",
+       "      <td>316.74</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>1959-10</th>\n",
+       "      <td>1959</td>\n",
+       "      <td>10</td>\n",
+       "      <td>21838</td>\n",
+       "      <td>1959.7890</td>\n",
+       "      <td>313.33</td>\n",
+       "      <td>316.33</td>\n",
+       "      <td>313.32</td>\n",
+       "      <td>316.31</td>\n",
+       "      <td>313.33</td>\n",
+       "      <td>316.33</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>1959-11</th>\n",
+       "      <td>1959</td>\n",
+       "      <td>11</td>\n",
+       "      <td>21869</td>\n",
+       "      <td>1959.8740</td>\n",
+       "      <td>314.81</td>\n",
+       "      <td>316.69</td>\n",
+       "      <td>314.54</td>\n",
+       "      <td>316.40</td>\n",
+       "      <td>314.81</td>\n",
+       "      <td>316.69</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>1959-12</th>\n",
+       "      <td>1959</td>\n",
+       "      <td>12</td>\n",
+       "      <td>21899</td>\n",
+       "      <td>1959.9562</td>\n",
+       "      <td>315.58</td>\n",
+       "      <td>316.35</td>\n",
+       "      <td>315.73</td>\n",
+       "      <td>316.48</td>\n",
+       "      <td>315.58</td>\n",
+       "      <td>316.35</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>1960-01</th>\n",
+       "      <td>1960</td>\n",
+       "      <td>1</td>\n",
+       "      <td>21930</td>\n",
+       "      <td>1960.0410</td>\n",
+       "      <td>316.43</td>\n",
+       "      <td>316.37</td>\n",
+       "      <td>316.63</td>\n",
+       "      <td>316.56</td>\n",
+       "      <td>316.43</td>\n",
+       "      <td>316.37</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>1960-02</th>\n",
+       "      <td>1960</td>\n",
+       "      <td>2</td>\n",
+       "      <td>21961</td>\n",
+       "      <td>1960.1257</td>\n",
+       "      <td>316.98</td>\n",
+       "      <td>316.33</td>\n",
+       "      <td>317.30</td>\n",
+       "      <td>316.64</td>\n",
+       "      <td>316.98</td>\n",
+       "      <td>316.33</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>1960-03</th>\n",
+       "      <td>1960</td>\n",
+       "      <td>3</td>\n",
+       "      <td>21990</td>\n",
+       "      <td>1960.2049</td>\n",
+       "      <td>317.58</td>\n",
+       "      <td>316.27</td>\n",
+       "      <td>318.04</td>\n",
+       "      <td>316.72</td>\n",
+       "      <td>317.58</td>\n",
+       "      <td>316.27</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>1960-04</th>\n",
+       "      <td>1960</td>\n",
+       "      <td>4</td>\n",
+       "      <td>22021</td>\n",
+       "      <td>1960.2896</td>\n",
+       "      <td>319.03</td>\n",
+       "      <td>316.70</td>\n",
+       "      <td>319.14</td>\n",
+       "      <td>316.80</td>\n",
+       "      <td>319.03</td>\n",
+       "      <td>316.70</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>1960-05</th>\n",
+       "      <td>1960</td>\n",
+       "      <td>5</td>\n",
+       "      <td>22051</td>\n",
+       "      <td>1960.3716</td>\n",
+       "      <td>320.03</td>\n",
+       "      <td>317.21</td>\n",
+       "      <td>319.69</td>\n",
+       "      <td>316.87</td>\n",
+       "      <td>320.03</td>\n",
+       "      <td>317.21</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>1960-06</th>\n",
+       "      <td>1960</td>\n",
+       "      <td>6</td>\n",
+       "      <td>22082</td>\n",
+       "      <td>1960.4563</td>\n",
+       "      <td>319.59</td>\n",
+       "      <td>317.46</td>\n",
+       "      <td>319.03</td>\n",
+       "      <td>316.93</td>\n",
+       "      <td>319.59</td>\n",
+       "      <td>317.46</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>1960-07</th>\n",
+       "      <td>1960</td>\n",
+       "      <td>7</td>\n",
+       "      <td>22112</td>\n",
+       "      <td>1960.5383</td>\n",
+       "      <td>318.18</td>\n",
+       "      <td>317.53</td>\n",
+       "      <td>317.60</td>\n",
+       "      <td>316.98</td>\n",
+       "      <td>318.18</td>\n",
+       "      <td>317.53</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>1960-08</th>\n",
+       "      <td>1960</td>\n",
+       "      <td>8</td>\n",
+       "      <td>22143</td>\n",
+       "      <td>1960.6230</td>\n",
+       "      <td>315.90</td>\n",
+       "      <td>317.22</td>\n",
+       "      <td>315.67</td>\n",
+       "      <td>317.02</td>\n",
+       "      <td>315.90</td>\n",
+       "      <td>317.22</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",
+       "      <td>...</td>\n",
+       "      <td>...</td>\n",
+       "      <td>...</td>\n",
+       "      <td>...</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>2020-02</th>\n",
+       "      <td>2020</td>\n",
+       "      <td>2</td>\n",
+       "      <td>43876</td>\n",
+       "      <td>2020.1257</td>\n",
+       "      <td>414.05</td>\n",
+       "      <td>413.27</td>\n",
+       "      <td>413.83</td>\n",
+       "      <td>413.04</td>\n",
+       "      <td>414.05</td>\n",
+       "      <td>413.27</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>2020-03</th>\n",
+       "      <td>2020</td>\n",
+       "      <td>3</td>\n",
+       "      <td>43905</td>\n",
+       "      <td>2020.2049</td>\n",
+       "      <td>414.45</td>\n",
+       "      <td>412.88</td>\n",
+       "      <td>414.82</td>\n",
+       "      <td>413.23</td>\n",
+       "      <td>414.45</td>\n",
+       "      <td>412.88</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>2020-04</th>\n",
+       "      <td>2020</td>\n",
+       "      <td>4</td>\n",
+       "      <td>43936</td>\n",
+       "      <td>2020.2896</td>\n",
+       "      <td>416.11</td>\n",
+       "      <td>413.31</td>\n",
+       "      <td>416.25</td>\n",
+       "      <td>413.43</td>\n",
+       "      <td>416.11</td>\n",
+       "      <td>413.31</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>2020-05</th>\n",
+       "      <td>2020</td>\n",
+       "      <td>5</td>\n",
+       "      <td>43966</td>\n",
+       "      <td>2020.3716</td>\n",
+       "      <td>417.15</td>\n",
+       "      <td>413.76</td>\n",
+       "      <td>417.02</td>\n",
+       "      <td>413.63</td>\n",
+       "      <td>417.15</td>\n",
+       "      <td>413.76</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>2020-06</th>\n",
+       "      <td>2020</td>\n",
+       "      <td>6</td>\n",
+       "      <td>43997</td>\n",
+       "      <td>2020.4563</td>\n",
+       "      <td>416.29</td>\n",
+       "      <td>413.74</td>\n",
+       "      <td>416.36</td>\n",
+       "      <td>413.83</td>\n",
+       "      <td>416.29</td>\n",
+       "      <td>413.74</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>2020-07</th>\n",
+       "      <td>2020</td>\n",
+       "      <td>7</td>\n",
+       "      <td>44027</td>\n",
+       "      <td>2020.5383</td>\n",
+       "      <td>414.42</td>\n",
+       "      <td>413.64</td>\n",
+       "      <td>414.77</td>\n",
+       "      <td>414.03</td>\n",
+       "      <td>414.42</td>\n",
+       "      <td>413.64</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>2020-08</th>\n",
+       "      <td>2020</td>\n",
+       "      <td>8</td>\n",
+       "      <td>44058</td>\n",
+       "      <td>2020.6230</td>\n",
+       "      <td>412.52</td>\n",
+       "      <td>414.10</td>\n",
+       "      <td>412.61</td>\n",
+       "      <td>414.23</td>\n",
+       "      <td>412.52</td>\n",
+       "      <td>414.10</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>2020-09</th>\n",
+       "      <td>2020</td>\n",
+       "      <td>9</td>\n",
+       "      <td>44089</td>\n",
+       "      <td>2020.7077</td>\n",
+       "      <td>411.18</td>\n",
+       "      <td>414.69</td>\n",
+       "      <td>410.90</td>\n",
+       "      <td>414.43</td>\n",
+       "      <td>411.18</td>\n",
+       "      <td>414.69</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>2020-10</th>\n",
+       "      <td>2020</td>\n",
+       "      <td>10</td>\n",
+       "      <td>44119</td>\n",
+       "      <td>2020.7896</td>\n",
+       "      <td>411.12</td>\n",
+       "      <td>414.73</td>\n",
+       "      <td>411.02</td>\n",
+       "      <td>414.62</td>\n",
+       "      <td>411.12</td>\n",
+       "      <td>414.73</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>2020-11</th>\n",
+       "      <td>2020</td>\n",
+       "      <td>11</td>\n",
+       "      <td>44150</td>\n",
+       "      <td>2020.8743</td>\n",
+       "      <td>412.88</td>\n",
+       "      <td>415.15</td>\n",
+       "      <td>412.57</td>\n",
+       "      <td>414.81</td>\n",
+       "      <td>412.88</td>\n",
+       "      <td>415.15</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>2020-12</th>\n",
+       "      <td>2020</td>\n",
+       "      <td>12</td>\n",
+       "      <td>44180</td>\n",
+       "      <td>2020.9563</td>\n",
+       "      <td>413.89</td>\n",
+       "      <td>414.81</td>\n",
+       "      <td>414.08</td>\n",
+       "      <td>414.99</td>\n",
+       "      <td>413.89</td>\n",
+       "      <td>414.81</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>2021-01</th>\n",
+       "      <td>2021</td>\n",
+       "      <td>1</td>\n",
+       "      <td>44211</td>\n",
+       "      <td>2021.0411</td>\n",
+       "      <td>415.15</td>\n",
+       "      <td>415.08</td>\n",
+       "      <td>415.25</td>\n",
+       "      <td>415.16</td>\n",
+       "      <td>415.15</td>\n",
+       "      <td>415.08</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>2021-02</th>\n",
+       "      <td>2021</td>\n",
+       "      <td>2</td>\n",
+       "      <td>44242</td>\n",
+       "      <td>2021.1260</td>\n",
+       "      <td>416.47</td>\n",
+       "      <td>415.69</td>\n",
+       "      <td>416.13</td>\n",
+       "      <td>415.34</td>\n",
+       "      <td>416.47</td>\n",
+       "      <td>415.69</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>2021-03</th>\n",
+       "      <td>2021</td>\n",
+       "      <td>3</td>\n",
+       "      <td>44270</td>\n",
+       "      <td>2021.2027</td>\n",
+       "      <td>417.16</td>\n",
+       "      <td>415.62</td>\n",
+       "      <td>417.06</td>\n",
+       "      <td>415.50</td>\n",
+       "      <td>417.16</td>\n",
+       "      <td>415.62</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>2021-04</th>\n",
+       "      <td>2021</td>\n",
+       "      <td>4</td>\n",
+       "      <td>44301</td>\n",
+       "      <td>2021.2877</td>\n",
+       "      <td>418.24</td>\n",
+       "      <td>415.46</td>\n",
+       "      <td>418.47</td>\n",
+       "      <td>415.67</td>\n",
+       "      <td>418.24</td>\n",
+       "      <td>415.46</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>2021-05</th>\n",
+       "      <td>2021</td>\n",
+       "      <td>5</td>\n",
+       "      <td>44331</td>\n",
+       "      <td>2021.3699</td>\n",
+       "      <td>418.95</td>\n",
+       "      <td>415.55</td>\n",
+       "      <td>419.24</td>\n",
+       "      <td>415.84</td>\n",
+       "      <td>418.95</td>\n",
+       "      <td>415.55</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>2021-06</th>\n",
+       "      <td>2021</td>\n",
+       "      <td>6</td>\n",
+       "      <td>44362</td>\n",
+       "      <td>2021.4548</td>\n",
+       "      <td>418.70</td>\n",
+       "      <td>416.12</td>\n",
+       "      <td>418.58</td>\n",
+       "      <td>416.02</td>\n",
+       "      <td>418.70</td>\n",
+       "      <td>416.12</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>2021-07</th>\n",
+       "      <td>2021</td>\n",
+       "      <td>7</td>\n",
+       "      <td>44392</td>\n",
+       "      <td>2021.5370</td>\n",
+       "      <td>416.65</td>\n",
+       "      <td>415.84</td>\n",
+       "      <td>416.97</td>\n",
+       "      <td>416.20</td>\n",
+       "      <td>416.65</td>\n",
+       "      <td>415.84</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>2021-08</th>\n",
+       "      <td>2021</td>\n",
+       "      <td>8</td>\n",
+       "      <td>44423</td>\n",
+       "      <td>2021.6219</td>\n",
+       "      <td>414.34</td>\n",
+       "      <td>415.89</td>\n",
+       "      <td>414.79</td>\n",
+       "      <td>416.39</td>\n",
+       "      <td>414.34</td>\n",
+       "      <td>415.89</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>2021-09</th>\n",
+       "      <td>2021</td>\n",
+       "      <td>9</td>\n",
+       "      <td>44454</td>\n",
+       "      <td>2021.7068</td>\n",
+       "      <td>412.90</td>\n",
+       "      <td>416.41</td>\n",
+       "      <td>413.05</td>\n",
+       "      <td>416.58</td>\n",
+       "      <td>412.90</td>\n",
+       "      <td>416.41</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>2021-10</th>\n",
+       "      <td>2021</td>\n",
+       "      <td>10</td>\n",
+       "      <td>44484</td>\n",
+       "      <td>2021.7890</td>\n",
+       "      <td>413.55</td>\n",
+       "      <td>417.17</td>\n",
+       "      <td>413.15</td>\n",
+       "      <td>416.76</td>\n",
+       "      <td>413.55</td>\n",
+       "      <td>417.17</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>2021-11</th>\n",
+       "      <td>2021</td>\n",
+       "      <td>11</td>\n",
+       "      <td>44515</td>\n",
+       "      <td>2021.8740</td>\n",
+       "      <td>414.82</td>\n",
+       "      <td>417.09</td>\n",
+       "      <td>414.70</td>\n",
+       "      <td>416.94</td>\n",
+       "      <td>414.82</td>\n",
+       "      <td>417.09</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>2021-12</th>\n",
+       "      <td>2021</td>\n",
+       "      <td>12</td>\n",
+       "      <td>44545</td>\n",
+       "      <td>2021.9562</td>\n",
+       "      <td>416.43</td>\n",
+       "      <td>417.36</td>\n",
+       "      <td>416.20</td>\n",
+       "      <td>417.11</td>\n",
+       "      <td>416.43</td>\n",
+       "      <td>417.36</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>2022-01</th>\n",
+       "      <td>2022</td>\n",
+       "      <td>1</td>\n",
+       "      <td>44576</td>\n",
+       "      <td>2022.0411</td>\n",
+       "      <td>418.01</td>\n",
+       "      <td>417.94</td>\n",
+       "      <td>417.35</td>\n",
+       "      <td>417.26</td>\n",
+       "      <td>418.01</td>\n",
+       "      <td>417.94</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>2022-02</th>\n",
+       "      <td>2022</td>\n",
+       "      <td>2</td>\n",
+       "      <td>44607</td>\n",
+       "      <td>2022.1260</td>\n",
+       "      <td>418.99</td>\n",
+       "      <td>418.20</td>\n",
+       "      <td>418.20</td>\n",
+       "      <td>417.40</td>\n",
+       "      <td>418.99</td>\n",
+       "      <td>418.20</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>2022-03</th>\n",
+       "      <td>2022</td>\n",
+       "      <td>3</td>\n",
+       "      <td>44635</td>\n",
+       "      <td>2022.2027</td>\n",
+       "      <td>418.45</td>\n",
+       "      <td>416.90</td>\n",
+       "      <td>419.08</td>\n",
+       "      <td>417.51</td>\n",
+       "      <td>418.45</td>\n",
+       "      <td>416.90</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>2022-04</th>\n",
+       "      <td>2022</td>\n",
+       "      <td>4</td>\n",
+       "      <td>44666</td>\n",
+       "      <td>2022.2877</td>\n",
+       "      <td>420.02</td>\n",
+       "      <td>417.23</td>\n",
+       "      <td>420.44</td>\n",
+       "      <td>417.63</td>\n",
+       "      <td>420.02</td>\n",
+       "      <td>417.23</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>2022-05</th>\n",
+       "      <td>2022</td>\n",
+       "      <td>5</td>\n",
+       "      <td>44696</td>\n",
+       "      <td>2022.3699</td>\n",
+       "      <td>420.78</td>\n",
+       "      <td>417.36</td>\n",
+       "      <td>421.16</td>\n",
+       "      <td>417.75</td>\n",
+       "      <td>420.78</td>\n",
+       "      <td>417.36</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>2022-06</th>\n",
+       "      <td>2022</td>\n",
+       "      <td>6</td>\n",
+       "      <td>44727</td>\n",
+       "      <td>2022.4548</td>\n",
+       "      <td>420.68</td>\n",
+       "      <td>418.09</td>\n",
+       "      <td>420.43</td>\n",
+       "      <td>417.86</td>\n",
+       "      <td>420.68</td>\n",
+       "      <td>418.09</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>2022-07</th>\n",
+       "      <td>2022</td>\n",
+       "      <td>7</td>\n",
+       "      <td>44757</td>\n",
+       "      <td>2022.5370</td>\n",
+       "      <td>418.66</td>\n",
+       "      <td>417.85</td>\n",
+       "      <td>418.75</td>\n",
+       "      <td>417.98</td>\n",
+       "      <td>418.66</td>\n",
+       "      <td>417.85</td>\n",
+       "    </tr>\n",
+       "  </tbody>\n",
+       "</table>\n",
+       "<p>773 rows × 10 columns</p>\n",
+       "</div>"
+      ],
+      "text/plain": [
+       "           Yr  Mn  EDate      DDate     C02      SA     Fit   SAFit  Filled  \\\n",
+       "1958-03  1958   3  21259  1958.2027  315.71  314.44  316.20  314.91  315.71   \n",
+       "1958-04  1958   4  21290  1958.2877  317.45  315.16  317.30  314.99  317.45   \n",
+       "1958-05  1958   5  21320  1958.3699  317.51  314.70  317.88  315.07  317.51   \n",
+       "1958-06  1958   6  21351  1958.4548  -99.99  -99.99  317.26  315.15  317.26   \n",
+       "1958-07  1958   7  21381  1958.5370  315.87  315.20  315.86  315.22  315.87   \n",
+       "1958-08  1958   8  21412  1958.6219  314.93  316.21  313.98  315.29  314.93   \n",
+       "1958-09  1958   9  21443  1958.7068  313.21  316.10  312.45  315.36  313.21   \n",
+       "1958-10  1958  10  21473  1958.7890  -99.99  -99.99  312.43  315.41  312.43   \n",
+       "1958-11  1958  11  21504  1958.8740  313.33  315.21  313.61  315.46  313.33   \n",
+       "1958-12  1958  12  21534  1958.9562  314.67  315.43  314.77  315.52  314.67   \n",
+       "1959-01  1959   1  21565  1959.0411  315.58  315.52  315.64  315.58  315.58   \n",
+       "1959-02  1959   2  21596  1959.1260  316.49  315.84  316.29  315.64  316.49   \n",
+       "1959-03  1959   3  21624  1959.2027  316.65  315.37  316.99  315.70  316.65   \n",
+       "1959-04  1959   4  21655  1959.2877  317.72  315.42  318.09  315.77  317.72   \n",
+       "1959-05  1959   5  21685  1959.3699  318.29  315.48  318.67  315.85  318.29   \n",
+       "1959-06  1959   6  21716  1959.4548  318.15  316.01  318.06  315.94  318.15   \n",
+       "1959-07  1959   7  21746  1959.5370  316.54  315.87  316.67  316.03  316.54   \n",
+       "1959-08  1959   8  21777  1959.6219  314.80  316.08  314.81  316.13  314.80   \n",
+       "1959-09  1959   9  21808  1959.7068  313.84  316.74  313.30  316.22  313.84   \n",
+       "1959-10  1959  10  21838  1959.7890  313.33  316.33  313.32  316.31  313.33   \n",
+       "1959-11  1959  11  21869  1959.8740  314.81  316.69  314.54  316.40  314.81   \n",
+       "1959-12  1959  12  21899  1959.9562  315.58  316.35  315.73  316.48  315.58   \n",
+       "1960-01  1960   1  21930  1960.0410  316.43  316.37  316.63  316.56  316.43   \n",
+       "1960-02  1960   2  21961  1960.1257  316.98  316.33  317.30  316.64  316.98   \n",
+       "1960-03  1960   3  21990  1960.2049  317.58  316.27  318.04  316.72  317.58   \n",
+       "1960-04  1960   4  22021  1960.2896  319.03  316.70  319.14  316.80  319.03   \n",
+       "1960-05  1960   5  22051  1960.3716  320.03  317.21  319.69  316.87  320.03   \n",
+       "1960-06  1960   6  22082  1960.4563  319.59  317.46  319.03  316.93  319.59   \n",
+       "1960-07  1960   7  22112  1960.5383  318.18  317.53  317.60  316.98  318.18   \n",
+       "1960-08  1960   8  22143  1960.6230  315.90  317.22  315.67  317.02  315.90   \n",
+       "...       ...  ..    ...        ...     ...     ...     ...     ...     ...   \n",
+       "2020-02  2020   2  43876  2020.1257  414.05  413.27  413.83  413.04  414.05   \n",
+       "2020-03  2020   3  43905  2020.2049  414.45  412.88  414.82  413.23  414.45   \n",
+       "2020-04  2020   4  43936  2020.2896  416.11  413.31  416.25  413.43  416.11   \n",
+       "2020-05  2020   5  43966  2020.3716  417.15  413.76  417.02  413.63  417.15   \n",
+       "2020-06  2020   6  43997  2020.4563  416.29  413.74  416.36  413.83  416.29   \n",
+       "2020-07  2020   7  44027  2020.5383  414.42  413.64  414.77  414.03  414.42   \n",
+       "2020-08  2020   8  44058  2020.6230  412.52  414.10  412.61  414.23  412.52   \n",
+       "2020-09  2020   9  44089  2020.7077  411.18  414.69  410.90  414.43  411.18   \n",
+       "2020-10  2020  10  44119  2020.7896  411.12  414.73  411.02  414.62  411.12   \n",
+       "2020-11  2020  11  44150  2020.8743  412.88  415.15  412.57  414.81  412.88   \n",
+       "2020-12  2020  12  44180  2020.9563  413.89  414.81  414.08  414.99  413.89   \n",
+       "2021-01  2021   1  44211  2021.0411  415.15  415.08  415.25  415.16  415.15   \n",
+       "2021-02  2021   2  44242  2021.1260  416.47  415.69  416.13  415.34  416.47   \n",
+       "2021-03  2021   3  44270  2021.2027  417.16  415.62  417.06  415.50  417.16   \n",
+       "2021-04  2021   4  44301  2021.2877  418.24  415.46  418.47  415.67  418.24   \n",
+       "2021-05  2021   5  44331  2021.3699  418.95  415.55  419.24  415.84  418.95   \n",
+       "2021-06  2021   6  44362  2021.4548  418.70  416.12  418.58  416.02  418.70   \n",
+       "2021-07  2021   7  44392  2021.5370  416.65  415.84  416.97  416.20  416.65   \n",
+       "2021-08  2021   8  44423  2021.6219  414.34  415.89  414.79  416.39  414.34   \n",
+       "2021-09  2021   9  44454  2021.7068  412.90  416.41  413.05  416.58  412.90   \n",
+       "2021-10  2021  10  44484  2021.7890  413.55  417.17  413.15  416.76  413.55   \n",
+       "2021-11  2021  11  44515  2021.8740  414.82  417.09  414.70  416.94  414.82   \n",
+       "2021-12  2021  12  44545  2021.9562  416.43  417.36  416.20  417.11  416.43   \n",
+       "2022-01  2022   1  44576  2022.0411  418.01  417.94  417.35  417.26  418.01   \n",
+       "2022-02  2022   2  44607  2022.1260  418.99  418.20  418.20  417.40  418.99   \n",
+       "2022-03  2022   3  44635  2022.2027  418.45  416.90  419.08  417.51  418.45   \n",
+       "2022-04  2022   4  44666  2022.2877  420.02  417.23  420.44  417.63  420.02   \n",
+       "2022-05  2022   5  44696  2022.3699  420.78  417.36  421.16  417.75  420.78   \n",
+       "2022-06  2022   6  44727  2022.4548  420.68  418.09  420.43  417.86  420.68   \n",
+       "2022-07  2022   7  44757  2022.5370  418.66  417.85  418.75  417.98  418.66   \n",
+       "\n",
+       "         SAFitFilled  \n",
+       "1958-03       314.44  \n",
+       "1958-04       315.16  \n",
+       "1958-05       314.70  \n",
+       "1958-06       315.15  \n",
+       "1958-07       315.20  \n",
+       "1958-08       316.21  \n",
+       "1958-09       316.10  \n",
+       "1958-10       315.41  \n",
+       "1958-11       315.21  \n",
+       "1958-12       315.43  \n",
+       "1959-01       315.52  \n",
+       "1959-02       315.84  \n",
+       "1959-03       315.37  \n",
+       "1959-04       315.42  \n",
+       "1959-05       315.48  \n",
+       "1959-06       316.01  \n",
+       "1959-07       315.87  \n",
+       "1959-08       316.08  \n",
+       "1959-09       316.74  \n",
+       "1959-10       316.33  \n",
+       "1959-11       316.69  \n",
+       "1959-12       316.35  \n",
+       "1960-01       316.37  \n",
+       "1960-02       316.33  \n",
+       "1960-03       316.27  \n",
+       "1960-04       316.70  \n",
+       "1960-05       317.21  \n",
+       "1960-06       317.46  \n",
+       "1960-07       317.53  \n",
+       "1960-08       317.22  \n",
+       "...              ...  \n",
+       "2020-02       413.27  \n",
+       "2020-03       412.88  \n",
+       "2020-04       413.31  \n",
+       "2020-05       413.76  \n",
+       "2020-06       413.74  \n",
+       "2020-07       413.64  \n",
+       "2020-08       414.10  \n",
+       "2020-09       414.69  \n",
+       "2020-10       414.73  \n",
+       "2020-11       415.15  \n",
+       "2020-12       414.81  \n",
+       "2021-01       415.08  \n",
+       "2021-02       415.69  \n",
+       "2021-03       415.62  \n",
+       "2021-04       415.46  \n",
+       "2021-05       415.55  \n",
+       "2021-06       416.12  \n",
+       "2021-07       415.84  \n",
+       "2021-08       415.89  \n",
+       "2021-09       416.41  \n",
+       "2021-10       417.17  \n",
+       "2021-11       417.09  \n",
+       "2021-12       417.36  \n",
+       "2022-01       417.94  \n",
+       "2022-02       418.20  \n",
+       "2022-03       416.90  \n",
+       "2022-04       417.23  \n",
+       "2022-05       417.36  \n",
+       "2022-06       418.09  \n",
+       "2022-07       417.85  \n",
+       "\n",
+       "[773 rows x 10 columns]"
+      ]
+     },
+     "execution_count": 146,
+     "metadata": {},
+     "output_type": "execute_result"
+    }
+   ],
+   "source": [
+    "def generate_period(yr,mn):\n",
+    "    return pd.Period(year = yr, month = mn, freq='M')\n",
+    "periods = pd.PeriodIndex(data = [generate_period(data.at[index,'Yr'],data.at[index,'Mn']) for index in data.index])\n",
+    "indexed_data = data.set_index(periods).copy()\n",
+    "indexed_data"
+   ]
   },
   {
    "cell_type": "markdown",
@@ -2236,22 +3209,22 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 70,
+   "execution_count": 150,
    "metadata": {},
    "outputs": [
     {
      "data": {
       "text/plain": [
-       "<matplotlib.axes._subplots.AxesSubplot at 0x7f393b35d320>"
+       "<matplotlib.axes._subplots.AxesSubplot at 0x7f393a5feda0>"
       ]
      },
-     "execution_count": 70,
+     "execution_count": 150,
      "metadata": {},
      "output_type": "execute_result"
     },
     {
      "data": {
-      "image/png": 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\n",
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\n",
       "text/plain": [
        "<Figure size 432x288 with 1 Axes>"
       ]
@@ -2263,7 +3236,7 @@
     }
    ],
    "source": [
-    "data[\"Filled\"].plot()"
+    "indexed_data['Filled'].plot()"
    ]
   },
   {
@@ -2275,22 +3248,61 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 71,
+   "execution_count": 152,
+   "metadata": {},
+   "outputs": [
+    {
+     "data": {
+      "text/plain": [
+       "<matplotlib.axes._subplots.AxesSubplot at 0x7f393a4a1898>"
+      ]
+     },
+     "execution_count": 152,
+     "metadata": {},
+     "output_type": "execute_result"
+    },
+    {
+     "data": {
+      "image/png": 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\n",
+      "text/plain": [
+       "<Figure size 432x288 with 1 Axes>"
+      ]
+     },
+     "metadata": {
+      "needs_background": "light"
+     },
+     "output_type": "display_data"
+    }
+   ],
+   "source": [
+    "indexed_data[\"Filled\"][-30:].plot()"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "We observe seasonal fluctuations of the C02 concentration. When adjusting for these fluctuations (column `SAFitFilled`), we have the following graphs."
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 154,
    "metadata": {},
    "outputs": [
     {
      "data": {
       "text/plain": [
-       "<matplotlib.axes._subplots.AxesSubplot at 0x7f393b35d898>"
+       "<matplotlib.axes._subplots.AxesSubplot at 0x7f393a365b00>"
       ]
      },
-     "execution_count": 71,
+     "execution_count": 154,
      "metadata": {},
      "output_type": "execute_result"
     },
     {
      "data": {
-      "image/png": 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\n",
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\n",
       "text/plain": [
        "<Figure size 432x288 with 1 Axes>"
       ]
@@ -2302,7 +3314,7 @@
     }
    ],
    "source": [
-    "data[\"Filled\"][-30:].plot()"
+    "indexed_data['SAFitFilled'].plot()"
    ]
   }
  ],
-- 
2.18.1