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module3/exo3/exercice.ipynb
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......@@ -55,6 +55,857 @@
"data_url = \"https://scrippsco2.ucsd.edu/assets/data/atmospheric/stations/in_situ_co2/monthly/monthly_in_situ_co2_mlo.csv\""
]
},
{
"cell_type": "markdown",
"metadata": {},
"source": [
"Les 53 premières lignes sont une présentation du jeu de données, on les passe pour ne traiter que le jeu de données à proprement parler. Voici ci-dessous un extrait de ce jeu de données."
]
},
{
"cell_type": "code",
"execution_count": 6,
"metadata": {},
"outputs": [
{
"data": {
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" <tbody>\n",
" <tr>\n",
" <th>Yr</th>\n",
" <th>Mn</th>\n",
" <th>Date</th>\n",
" <th>Date</th>\n",
" <th>CO2</th>\n",
" <th>seasonally</th>\n",
" <th>fit</th>\n",
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" <th>CO2</th>\n",
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" <th>adjusted</th>\n",
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" <th>adjusted fit</th>\n",
" <th>filled</th>\n",
" <td>adjusted filled</td>\n",
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" <tr>\n",
" <th>Excel</th>\n",
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" <th>[ppm]</th>\n",
" <th>[ppm]</th>\n",
" <th>[ppm]</th>\n",
" <th>[ppm]</th>\n",
" <th>[ppm]</th>\n",
" <td>[ppm]</td>\n",
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" <tr>\n",
" <th rowspan=\"12\" valign=\"top\">1958</th>\n",
" <th>01</th>\n",
" <th>21200</th>\n",
" <th>1958.0411</th>\n",
" <th>-99.99</th>\n",
" <th>-99.99</th>\n",
" <th>-99.99</th>\n",
" <th>-99.99</th>\n",
" <th>-99.99</th>\n",
" <td>-99.99</td>\n",
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" <th>02</th>\n",
" <th>21231</th>\n",
" <th>1958.1260</th>\n",
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" <th>-99.99</th>\n",
" <th>-99.99</th>\n",
" <th>-99.99</th>\n",
" <th>-99.99</th>\n",
" <td>-99.99</td>\n",
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" <th>03</th>\n",
" <th>21259</th>\n",
" <th>1958.2027</th>\n",
" <th>315.70</th>\n",
" <th>314.44</th>\n",
" <th>316.18</th>\n",
" <th>314.90</th>\n",
" <th>315.70</th>\n",
" <td>314.44</td>\n",
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" <tr>\n",
" <th>04</th>\n",
" <th>21290</th>\n",
" <th>1958.2877</th>\n",
" <th>317.45</th>\n",
" <th>315.16</th>\n",
" <th>317.29</th>\n",
" <th>314.98</th>\n",
" <th>317.45</th>\n",
" <td>315.16</td>\n",
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" <th>05</th>\n",
" <th>21320</th>\n",
" <th>1958.3699</th>\n",
" <th>317.51</th>\n",
" <th>314.71</th>\n",
" <th>317.86</th>\n",
" <th>315.06</th>\n",
" <th>317.51</th>\n",
" <td>314.71</td>\n",
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" <th>06</th>\n",
" <th>21351</th>\n",
" <th>1958.4548</th>\n",
" <th>-99.99</th>\n",
" <th>-99.99</th>\n",
" <th>317.24</th>\n",
" <th>315.14</th>\n",
" <th>317.24</th>\n",
" <td>315.14</td>\n",
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" <tr>\n",
" <th>07</th>\n",
" <th>21381</th>\n",
" <th>1958.5370</th>\n",
" <th>315.86</th>\n",
" <th>315.19</th>\n",
" <th>315.86</th>\n",
" <th>315.21</th>\n",
" <th>315.86</th>\n",
" <td>315.19</td>\n",
" </tr>\n",
" <tr>\n",
" <th>08</th>\n",
" <th>21412</th>\n",
" <th>1958.6219</th>\n",
" <th>314.93</th>\n",
" <th>316.19</th>\n",
" <th>313.99</th>\n",
" <th>315.28</th>\n",
" <th>314.93</th>\n",
" <td>316.19</td>\n",
" </tr>\n",
" <tr>\n",
" <th>09</th>\n",
" <th>21443</th>\n",
" <th>1958.7068</th>\n",
" <th>313.21</th>\n",
" <th>316.08</th>\n",
" <th>312.45</th>\n",
" <th>315.35</th>\n",
" <th>313.21</th>\n",
" <td>316.08</td>\n",
" </tr>\n",
" <tr>\n",
" <th>10</th>\n",
" <th>21473</th>\n",
" <th>1958.7890</th>\n",
" <th>-99.99</th>\n",
" <th>-99.99</th>\n",
" <th>312.43</th>\n",
" <th>315.40</th>\n",
" <th>312.43</th>\n",
" <td>315.40</td>\n",
" </tr>\n",
" <tr>\n",
" <th>11</th>\n",
" <th>21504</th>\n",
" <th>1958.8740</th>\n",
" <th>313.33</th>\n",
" <th>315.20</th>\n",
" <th>313.61</th>\n",
" <th>315.46</th>\n",
" <th>313.33</th>\n",
" <td>315.20</td>\n",
" </tr>\n",
" <tr>\n",
" <th>12</th>\n",
" <th>21534</th>\n",
" <th>1958.9562</th>\n",
" <th>314.67</th>\n",
" <th>315.43</th>\n",
" <th>314.76</th>\n",
" <th>315.51</th>\n",
" <th>314.67</th>\n",
" <td>315.43</td>\n",
" </tr>\n",
" <tr>\n",
" <th rowspan=\"12\" valign=\"top\">1959</th>\n",
" <th>01</th>\n",
" <th>21565</th>\n",
" <th>1959.0411</th>\n",
" <th>315.58</th>\n",
" <th>315.54</th>\n",
" <th>315.62</th>\n",
" <th>315.57</th>\n",
" <th>315.58</th>\n",
" <td>315.54</td>\n",
" </tr>\n",
" <tr>\n",
" <th>02</th>\n",
" <th>21596</th>\n",
" <th>1959.1260</th>\n",
" <th>316.49</th>\n",
" <th>315.86</th>\n",
" <th>316.26</th>\n",
" <th>315.63</th>\n",
" <th>316.49</th>\n",
" <td>315.86</td>\n",
" </tr>\n",
" <tr>\n",
" <th>03</th>\n",
" <th>21624</th>\n",
" <th>1959.2027</th>\n",
" <th>316.65</th>\n",
" <th>315.38</th>\n",
" <th>316.97</th>\n",
" <th>315.69</th>\n",
" <th>316.65</th>\n",
" <td>315.38</td>\n",
" </tr>\n",
" <tr>\n",
" <th>04</th>\n",
" <th>21655</th>\n",
" <th>1959.2877</th>\n",
" <th>317.72</th>\n",
" <th>315.42</th>\n",
" <th>318.08</th>\n",
" <th>315.76</th>\n",
" <th>317.72</th>\n",
" <td>315.42</td>\n",
" </tr>\n",
" <tr>\n",
" <th>05</th>\n",
" <th>21685</th>\n",
" <th>1959.3699</th>\n",
" <th>318.29</th>\n",
" <th>315.49</th>\n",
" <th>318.65</th>\n",
" <th>315.84</th>\n",
" <th>318.29</th>\n",
" <td>315.49</td>\n",
" </tr>\n",
" <tr>\n",
" <th>06</th>\n",
" <th>21716</th>\n",
" <th>1959.4548</th>\n",
" <th>318.15</th>\n",
" <th>316.03</th>\n",
" <th>318.04</th>\n",
" <th>315.93</th>\n",
" <th>318.15</th>\n",
" <td>316.03</td>\n",
" </tr>\n",
" <tr>\n",
" <th>07</th>\n",
" <th>21746</th>\n",
" <th>1959.5370</th>\n",
" <th>316.54</th>\n",
" <th>315.86</th>\n",
" <th>316.67</th>\n",
" <th>316.02</th>\n",
" <th>316.54</th>\n",
" <td>315.86</td>\n",
" </tr>\n",
" <tr>\n",
" <th>08</th>\n",
" <th>21777</th>\n",
" <th>1959.6219</th>\n",
" <th>314.80</th>\n",
" <th>316.06</th>\n",
" <th>314.82</th>\n",
" <th>316.12</th>\n",
" <th>314.80</th>\n",
" <td>316.06</td>\n",
" </tr>\n",
" <tr>\n",
" <th>09</th>\n",
" <th>21808</th>\n",
" <th>1959.7068</th>\n",
" <th>313.84</th>\n",
" <th>316.73</th>\n",
" <th>313.31</th>\n",
" <th>316.21</th>\n",
" <th>313.84</th>\n",
" <td>316.73</td>\n",
" </tr>\n",
" <tr>\n",
" <th>10</th>\n",
" <th>21838</th>\n",
" <th>1959.7890</th>\n",
" <th>313.33</th>\n",
" <th>316.33</th>\n",
" <th>313.32</th>\n",
" <th>316.30</th>\n",
" <th>313.33</th>\n",
" <td>316.33</td>\n",
" </tr>\n",
" <tr>\n",
" <th>11</th>\n",
" <th>21869</th>\n",
" <th>1959.8740</th>\n",
" <th>314.81</th>\n",
" <th>316.68</th>\n",
" <th>314.54</th>\n",
" <th>316.39</th>\n",
" <th>314.81</th>\n",
" <td>316.68</td>\n",
" </tr>\n",
" <tr>\n",
" <th>12</th>\n",
" <th>21899</th>\n",
" <th>1959.9562</th>\n",
" <th>315.58</th>\n",
" <th>316.35</th>\n",
" <th>315.72</th>\n",
" <th>316.47</th>\n",
" <th>315.58</th>\n",
" <td>316.35</td>\n",
" </tr>\n",
" <tr>\n",
" <th rowspan=\"3\" valign=\"top\">1960</th>\n",
" <th>01</th>\n",
" <th>21930</th>\n",
" <th>1960.0410</th>\n",
" <th>316.43</th>\n",
" <th>316.39</th>\n",
" <th>316.61</th>\n",
" <th>316.55</th>\n",
" <th>316.43</th>\n",
" <td>316.39</td>\n",
" </tr>\n",
" <tr>\n",
" <th>02</th>\n",
" <th>21961</th>\n",
" <th>1960.1257</th>\n",
" <th>316.98</th>\n",
" <th>316.35</th>\n",
" <th>317.27</th>\n",
" <th>316.64</th>\n",
" <th>316.98</th>\n",
" <td>316.35</td>\n",
" </tr>\n",
" <tr>\n",
" <th>03</th>\n",
" <th>21990</th>\n",
" <th>1960.2049</th>\n",
" <th>317.58</th>\n",
" <th>316.28</th>\n",
" <th>318.02</th>\n",
" <th>316.71</th>\n",
" <th>317.58</th>\n",
" <td>316.28</td>\n",
" </tr>\n",
" <tr>\n",
" <th>...</th>\n",
" <th>...</th>\n",
" <th>...</th>\n",
" <th>...</th>\n",
" <th>...</th>\n",
" <th>...</th>\n",
" <th>...</th>\n",
" <th>...</th>\n",
" <th>...</th>\n",
" <td>...</td>\n",
" </tr>\n",
" <tr>\n",
" <th rowspan=\"6\" valign=\"top\">2018</th>\n",
" <th>07</th>\n",
" <th>43296</th>\n",
" <th>2018.5370</th>\n",
" <th>408.90</th>\n",
" <th>408.08</th>\n",
" <th>409.43</th>\n",
" <th>408.65</th>\n",
" <th>408.90</th>\n",
" <td>408.08</td>\n",
" </tr>\n",
" <tr>\n",
" <th>08</th>\n",
" <th>43327</th>\n",
" <th>2018.6219</th>\n",
" <th>407.10</th>\n",
" <th>408.63</th>\n",
" <th>407.33</th>\n",
" <th>408.90</th>\n",
" <th>407.10</th>\n",
" <td>408.63</td>\n",
" </tr>\n",
" <tr>\n",
" <th>09</th>\n",
" <th>43358</th>\n",
" <th>2018.7068</th>\n",
" <th>405.59</th>\n",
" <th>409.08</th>\n",
" <th>405.66</th>\n",
" <th>409.18</th>\n",
" <th>405.59</th>\n",
" <td>409.08</td>\n",
" </tr>\n",
" <tr>\n",
" <th>10</th>\n",
" <th>43388</th>\n",
" <th>2018.7890</th>\n",
" <th>405.99</th>\n",
" <th>409.61</th>\n",
" <th>405.84</th>\n",
" <th>409.44</th>\n",
" <th>405.99</th>\n",
" <td>409.61</td>\n",
" </tr>\n",
" <tr>\n",
" <th>11</th>\n",
" <th>43419</th>\n",
" <th>2018.8740</th>\n",
" <th>408.12</th>\n",
" <th>410.38</th>\n",
" <th>407.48</th>\n",
" <th>409.72</th>\n",
" <th>408.12</th>\n",
" <td>410.38</td>\n",
" </tr>\n",
" <tr>\n",
" <th>12</th>\n",
" <th>43449</th>\n",
" <th>2018.9562</th>\n",
" <th>409.23</th>\n",
" <th>410.15</th>\n",
" <th>409.07</th>\n",
" <th>409.98</th>\n",
" <th>409.23</th>\n",
" <td>410.15</td>\n",
" </tr>\n",
" <tr>\n",
" <th rowspan=\"12\" valign=\"top\">2019</th>\n",
" <th>01</th>\n",
" <th>43480</th>\n",
" <th>2019.0411</th>\n",
" <th>410.92</th>\n",
" <th>410.87</th>\n",
" <th>410.30</th>\n",
" <th>410.24</th>\n",
" <th>410.92</th>\n",
" <td>410.87</td>\n",
" </tr>\n",
" <tr>\n",
" <th>02</th>\n",
" <th>43511</th>\n",
" <th>2019.1260</th>\n",
" <th>411.66</th>\n",
" <th>410.90</th>\n",
" <th>411.25</th>\n",
" <th>410.48</th>\n",
" <th>411.66</th>\n",
" <td>410.90</td>\n",
" </tr>\n",
" <tr>\n",
" <th>03</th>\n",
" <th>43539</th>\n",
" <th>2019.2027</th>\n",
" <th>412.00</th>\n",
" <th>410.46</th>\n",
" <th>412.25</th>\n",
" <th>410.69</th>\n",
" <th>412.00</th>\n",
" <td>410.46</td>\n",
" </tr>\n",
" <tr>\n",
" <th>04</th>\n",
" <th>43570</th>\n",
" <th>2019.2877</th>\n",
" <th>413.52</th>\n",
" <th>410.72</th>\n",
" <th>413.73</th>\n",
" <th>410.92</th>\n",
" <th>413.52</th>\n",
" <td>410.72</td>\n",
" </tr>\n",
" <tr>\n",
" <th>05</th>\n",
" <th>43600</th>\n",
" <th>2019.3699</th>\n",
" <th>414.83</th>\n",
" <th>411.42</th>\n",
" <th>414.54</th>\n",
" <th>411.14</th>\n",
" <th>414.83</th>\n",
" <td>411.42</td>\n",
" </tr>\n",
" <tr>\n",
" <th>06</th>\n",
" <th>43631</th>\n",
" <th>2019.4548</th>\n",
" <th>413.96</th>\n",
" <th>411.38</th>\n",
" <th>413.91</th>\n",
" <th>411.36</th>\n",
" <th>413.96</th>\n",
" <td>411.38</td>\n",
" </tr>\n",
" <tr>\n",
" <th>07</th>\n",
" <th>43661</th>\n",
" <th>2019.5370</th>\n",
" <th>411.85</th>\n",
" <th>411.03</th>\n",
" <th>412.36</th>\n",
" <th>411.57</th>\n",
" <th>411.85</th>\n",
" <td>411.03</td>\n",
" </tr>\n",
" <tr>\n",
" <th>08</th>\n",
" <th>43692</th>\n",
" <th>2019.6219</th>\n",
" <th>410.08</th>\n",
" <th>411.62</th>\n",
" <th>410.22</th>\n",
" <th>411.79</th>\n",
" <th>410.08</th>\n",
" <td>411.62</td>\n",
" </tr>\n",
" <tr>\n",
" <th>09</th>\n",
" <th>43723</th>\n",
" <th>2019.7068</th>\n",
" <th>408.55</th>\n",
" <th>412.06</th>\n",
" <th>408.49</th>\n",
" <th>412.02</th>\n",
" <th>408.55</th>\n",
" <td>412.06</td>\n",
" </tr>\n",
" <tr>\n",
" <th>10</th>\n",
" <th>43753</th>\n",
" <th>2019.7890</th>\n",
" <th>408.43</th>\n",
" <th>412.06</th>\n",
" <th>408.62</th>\n",
" <th>412.23</th>\n",
" <th>408.43</th>\n",
" <td>412.06</td>\n",
" </tr>\n",
" <tr>\n",
" <th>11</th>\n",
" <th>43784</th>\n",
" <th>2019.8740</th>\n",
" <th>410.29</th>\n",
" <th>412.56</th>\n",
" <th>410.21</th>\n",
" <th>412.46</th>\n",
" <th>410.29</th>\n",
" <td>412.56</td>\n",
" </tr>\n",
" <tr>\n",
" <th>12</th>\n",
" <th>43814</th>\n",
" <th>2019.9562</th>\n",
" <th>411.85</th>\n",
" <th>412.78</th>\n",
" <th>411.76</th>\n",
" <th>412.67</th>\n",
" <th>411.85</th>\n",
" <td>412.78</td>\n",
" </tr>\n",
" <tr>\n",
" <th rowspan=\"12\" valign=\"top\">2020</th>\n",
" <th>01</th>\n",
" <th>43845</th>\n",
" <th>2020.0410</th>\n",
" <th>413.37</th>\n",
" <th>413.32</th>\n",
" <th>412.95</th>\n",
" <th>412.89</th>\n",
" <th>413.37</th>\n",
" <td>413.32</td>\n",
" </tr>\n",
" <tr>\n",
" <th>02</th>\n",
" <th>43876</th>\n",
" <th>2020.1257</th>\n",
" <th>414.09</th>\n",
" <th>413.33</th>\n",
" <th>413.87</th>\n",
" <th>413.10</th>\n",
" <th>414.09</th>\n",
" <td>413.33</td>\n",
" </tr>\n",
" <tr>\n",
" <th>03</th>\n",
" <th>43905</th>\n",
" <th>2020.2049</th>\n",
" <th>414.51</th>\n",
" <th>412.94</th>\n",
" <th>414.89</th>\n",
" <th>413.30</th>\n",
" <th>414.51</th>\n",
" <td>412.94</td>\n",
" </tr>\n",
" <tr>\n",
" <th>04</th>\n",
" <th>43936</th>\n",
" <th>2020.2896</th>\n",
" <th>416.18</th>\n",
" <th>413.35</th>\n",
" <th>416.35</th>\n",
" <th>413.50</th>\n",
" <th>416.18</th>\n",
" <td>413.35</td>\n",
" </tr>\n",
" <tr>\n",
" <th>05</th>\n",
" <th>43966</th>\n",
" <th>2020.3716</th>\n",
" <th>417.16</th>\n",
" <th>413.75</th>\n",
" <th>-99.99</th>\n",
" <th>-99.99</th>\n",
" <th>417.16</th>\n",
" <td>413.75</td>\n",
" </tr>\n",
" <tr>\n",
" <th>06</th>\n",
" <th>43997</th>\n",
" <th>2020.4563</th>\n",
" <th>-99.99</th>\n",
" <th>-99.99</th>\n",
" <th>-99.99</th>\n",
" <th>-99.99</th>\n",
" <th>-99.99</th>\n",
" <td>-99.99</td>\n",
" </tr>\n",
" <tr>\n",
" <th>07</th>\n",
" <th>44027</th>\n",
" <th>2020.5383</th>\n",
" <th>-99.99</th>\n",
" <th>-99.99</th>\n",
" <th>-99.99</th>\n",
" <th>-99.99</th>\n",
" <th>-99.99</th>\n",
" <td>-99.99</td>\n",
" </tr>\n",
" <tr>\n",
" <th>08</th>\n",
" <th>44058</th>\n",
" <th>2020.6230</th>\n",
" <th>-99.99</th>\n",
" <th>-99.99</th>\n",
" <th>-99.99</th>\n",
" <th>-99.99</th>\n",
" <th>-99.99</th>\n",
" <td>-99.99</td>\n",
" </tr>\n",
" <tr>\n",
" <th>09</th>\n",
" <th>44089</th>\n",
" <th>2020.7077</th>\n",
" <th>-99.99</th>\n",
" <th>-99.99</th>\n",
" <th>-99.99</th>\n",
" <th>-99.99</th>\n",
" <th>-99.99</th>\n",
" <td>-99.99</td>\n",
" </tr>\n",
" <tr>\n",
" <th>10</th>\n",
" <th>44119</th>\n",
" <th>2020.7896</th>\n",
" <th>-99.99</th>\n",
" <th>-99.99</th>\n",
" <th>-99.99</th>\n",
" <th>-99.99</th>\n",
" <th>-99.99</th>\n",
" <td>-99.99</td>\n",
" </tr>\n",
" <tr>\n",
" <th>11</th>\n",
" <th>44150</th>\n",
" <th>2020.8743</th>\n",
" <th>-99.99</th>\n",
" <th>-99.99</th>\n",
" <th>-99.99</th>\n",
" <th>-99.99</th>\n",
" <th>-99.99</th>\n",
" <td>-99.99</td>\n",
" </tr>\n",
" <tr>\n",
" <th>12</th>\n",
" <th>44180</th>\n",
" <th>2020.9563</th>\n",
" <th>-99.99</th>\n",
" <th>-99.99</th>\n",
" <th>-99.99</th>\n",
" <th>-99.99</th>\n",
" <th>-99.99</th>\n",
" <td>-99.99</td>\n",
" </tr>\n",
" </tbody>\n",
"</table>\n",
"<p>759 rows × 1 columns</p>\n",
"</div>"
],
"text/plain": [
" \n",
" Yr Mn Date Date CO2 seasonally fit seasonally CO2 seasonally \n",
" adjusted adjusted fit filled adjusted filled \n",
" Excel [ppm] [ppm] [ppm] [ppm] [ppm] [ppm] \n",
"1958 01 21200 1958.0411 -99.99 -99.99 -99.99 -99.99 -99.99 -99.99 \n",
" 02 21231 1958.1260 -99.99 -99.99 -99.99 -99.99 -99.99 -99.99 \n",
" 03 21259 1958.2027 315.70 314.44 316.18 314.90 315.70 314.44 \n",
" 04 21290 1958.2877 317.45 315.16 317.29 314.98 317.45 315.16 \n",
" 05 21320 1958.3699 317.51 314.71 317.86 315.06 317.51 314.71 \n",
" 06 21351 1958.4548 -99.99 -99.99 317.24 315.14 317.24 315.14 \n",
" 07 21381 1958.5370 315.86 315.19 315.86 315.21 315.86 315.19 \n",
" 08 21412 1958.6219 314.93 316.19 313.99 315.28 314.93 316.19 \n",
" 09 21443 1958.7068 313.21 316.08 312.45 315.35 313.21 316.08 \n",
" 10 21473 1958.7890 -99.99 -99.99 312.43 315.40 312.43 315.40 \n",
" 11 21504 1958.8740 313.33 315.20 313.61 315.46 313.33 315.20 \n",
" 12 21534 1958.9562 314.67 315.43 314.76 315.51 314.67 315.43 \n",
"1959 01 21565 1959.0411 315.58 315.54 315.62 315.57 315.58 315.54 \n",
" 02 21596 1959.1260 316.49 315.86 316.26 315.63 316.49 315.86 \n",
" 03 21624 1959.2027 316.65 315.38 316.97 315.69 316.65 315.38 \n",
" 04 21655 1959.2877 317.72 315.42 318.08 315.76 317.72 315.42 \n",
" 05 21685 1959.3699 318.29 315.49 318.65 315.84 318.29 315.49 \n",
" 06 21716 1959.4548 318.15 316.03 318.04 315.93 318.15 316.03 \n",
" 07 21746 1959.5370 316.54 315.86 316.67 316.02 316.54 315.86 \n",
" 08 21777 1959.6219 314.80 316.06 314.82 316.12 314.80 316.06 \n",
" 09 21808 1959.7068 313.84 316.73 313.31 316.21 313.84 316.73 \n",
" 10 21838 1959.7890 313.33 316.33 313.32 316.30 313.33 316.33 \n",
" 11 21869 1959.8740 314.81 316.68 314.54 316.39 314.81 316.68 \n",
" 12 21899 1959.9562 315.58 316.35 315.72 316.47 315.58 316.35 \n",
"1960 01 21930 1960.0410 316.43 316.39 316.61 316.55 316.43 316.39 \n",
" 02 21961 1960.1257 316.98 316.35 317.27 316.64 316.98 316.35 \n",
" 03 21990 1960.2049 317.58 316.28 318.02 316.71 317.58 316.28 \n",
"... ... \n",
"2018 07 43296 2018.5370 408.90 408.08 409.43 408.65 408.90 408.08 \n",
" 08 43327 2018.6219 407.10 408.63 407.33 408.90 407.10 408.63 \n",
" 09 43358 2018.7068 405.59 409.08 405.66 409.18 405.59 409.08 \n",
" 10 43388 2018.7890 405.99 409.61 405.84 409.44 405.99 409.61 \n",
" 11 43419 2018.8740 408.12 410.38 407.48 409.72 408.12 410.38 \n",
" 12 43449 2018.9562 409.23 410.15 409.07 409.98 409.23 410.15 \n",
"2019 01 43480 2019.0411 410.92 410.87 410.30 410.24 410.92 410.87 \n",
" 02 43511 2019.1260 411.66 410.90 411.25 410.48 411.66 410.90 \n",
" 03 43539 2019.2027 412.00 410.46 412.25 410.69 412.00 410.46 \n",
" 04 43570 2019.2877 413.52 410.72 413.73 410.92 413.52 410.72 \n",
" 05 43600 2019.3699 414.83 411.42 414.54 411.14 414.83 411.42 \n",
" 06 43631 2019.4548 413.96 411.38 413.91 411.36 413.96 411.38 \n",
" 07 43661 2019.5370 411.85 411.03 412.36 411.57 411.85 411.03 \n",
" 08 43692 2019.6219 410.08 411.62 410.22 411.79 410.08 411.62 \n",
" 09 43723 2019.7068 408.55 412.06 408.49 412.02 408.55 412.06 \n",
" 10 43753 2019.7890 408.43 412.06 408.62 412.23 408.43 412.06 \n",
" 11 43784 2019.8740 410.29 412.56 410.21 412.46 410.29 412.56 \n",
" 12 43814 2019.9562 411.85 412.78 411.76 412.67 411.85 412.78 \n",
"2020 01 43845 2020.0410 413.37 413.32 412.95 412.89 413.37 413.32 \n",
" 02 43876 2020.1257 414.09 413.33 413.87 413.10 414.09 413.33 \n",
" 03 43905 2020.2049 414.51 412.94 414.89 413.30 414.51 412.94 \n",
" 04 43936 2020.2896 416.18 413.35 416.35 413.50 416.18 413.35 \n",
" 05 43966 2020.3716 417.16 413.75 -99.99 -99.99 417.16 413.75 \n",
" 06 43997 2020.4563 -99.99 -99.99 -99.99 -99.99 -99.99 -99.99 \n",
" 07 44027 2020.5383 -99.99 -99.99 -99.99 -99.99 -99.99 -99.99 \n",
" 08 44058 2020.6230 -99.99 -99.99 -99.99 -99.99 -99.99 -99.99 \n",
" 09 44089 2020.7077 -99.99 -99.99 -99.99 -99.99 -99.99 -99.99 \n",
" 10 44119 2020.7896 -99.99 -99.99 -99.99 -99.99 -99.99 -99.99 \n",
" 11 44150 2020.8743 -99.99 -99.99 -99.99 -99.99 -99.99 -99.99 \n",
" 12 44180 2020.9563 -99.99 -99.99 -99.99 -99.99 -99.99 -99.99 \n",
"\n",
"[759 rows x 1 columns]"
]
},
"execution_count": 6,
"metadata": {},
"output_type": "execute_result"
}
],
"source": [
"raw_data = pd.read_csv(data_url, skiprows=53)\n",
"raw_data"
]
},
{
"cell_type": "markdown",
"metadata": {},
"source": [
"On vérifie qu'il n'y a pas de données manquantes"
]
},
{
"cell_type": "code",
"execution_count": 15,
"metadata": {},
"outputs": [
{
"ename": "KeyError",
"evalue": "'CO2'",
"output_type": "error",
"traceback": [
"\u001b[0;31m---------------------------------------------------------------------------\u001b[0m",
"\u001b[0;31mKeyError\u001b[0m Traceback (most recent call last)",
"\u001b[0;32m/opt/conda/lib/python3.6/site-packages/pandas/core/indexes/base.py\u001b[0m in \u001b[0;36mget_loc\u001b[0;34m(self, key, method, tolerance)\u001b[0m\n\u001b[1;32m 2524\u001b[0m \u001b[0;32mtry\u001b[0m\u001b[0;34m:\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0;32m-> 2525\u001b[0;31m \u001b[0;32mreturn\u001b[0m \u001b[0mself\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0m_engine\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0mget_loc\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0mkey\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0m\u001b[1;32m 2526\u001b[0m \u001b[0;32mexcept\u001b[0m \u001b[0mKeyError\u001b[0m\u001b[0;34m:\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n",
"\u001b[0;32mpandas/_libs/index.pyx\u001b[0m in \u001b[0;36mpandas._libs.index.IndexEngine.get_loc\u001b[0;34m()\u001b[0m\n",
"\u001b[0;32mpandas/_libs/index.pyx\u001b[0m in \u001b[0;36mpandas._libs.index.IndexEngine.get_loc\u001b[0;34m()\u001b[0m\n",
"\u001b[0;32mpandas/_libs/hashtable_class_helper.pxi\u001b[0m in \u001b[0;36mpandas._libs.hashtable.PyObjectHashTable.get_item\u001b[0;34m()\u001b[0m\n",
"\u001b[0;32mpandas/_libs/hashtable_class_helper.pxi\u001b[0m in \u001b[0;36mpandas._libs.hashtable.PyObjectHashTable.get_item\u001b[0;34m()\u001b[0m\n",
"\u001b[0;31mKeyError\u001b[0m: 'CO2'",
"\nDuring handling of the above exception, another exception occurred:\n",
"\u001b[0;31mKeyError\u001b[0m Traceback (most recent call last)",
"\u001b[0;32m<ipython-input-15-95dc9971d4ce>\u001b[0m in \u001b[0;36m<module>\u001b[0;34m\u001b[0m\n\u001b[0;32m----> 1\u001b[0;31m \u001b[0mraw_data\u001b[0m\u001b[0;34m[\u001b[0m\u001b[0mraw_data\u001b[0m\u001b[0;34m[\u001b[0m\u001b[0;34m'CO2'\u001b[0m\u001b[0;34m]\u001b[0m \u001b[0;34m==\u001b[0m \u001b[0;34m-\u001b[0m\u001b[0;36m99.99\u001b[0m\u001b[0;34m]\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0m",
"\u001b[0;32m/opt/conda/lib/python3.6/site-packages/pandas/core/frame.py\u001b[0m in \u001b[0;36m__getitem__\u001b[0;34m(self, key)\u001b[0m\n\u001b[1;32m 2137\u001b[0m \u001b[0;32mreturn\u001b[0m \u001b[0mself\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0m_getitem_multilevel\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0mkey\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m 2138\u001b[0m \u001b[0;32melse\u001b[0m\u001b[0;34m:\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0;32m-> 2139\u001b[0;31m \u001b[0;32mreturn\u001b[0m \u001b[0mself\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0m_getitem_column\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0mkey\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0m\u001b[1;32m 2140\u001b[0m \u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m 2141\u001b[0m \u001b[0;32mdef\u001b[0m \u001b[0m_getitem_column\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0mself\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0mkey\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m:\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n",
"\u001b[0;32m/opt/conda/lib/python3.6/site-packages/pandas/core/frame.py\u001b[0m in \u001b[0;36m_getitem_column\u001b[0;34m(self, key)\u001b[0m\n\u001b[1;32m 2144\u001b[0m \u001b[0;31m# get column\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m 2145\u001b[0m \u001b[0;32mif\u001b[0m \u001b[0mself\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0mcolumns\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0mis_unique\u001b[0m\u001b[0;34m:\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0;32m-> 2146\u001b[0;31m \u001b[0;32mreturn\u001b[0m \u001b[0mself\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0m_get_item_cache\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0mkey\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0m\u001b[1;32m 2147\u001b[0m \u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m 2148\u001b[0m \u001b[0;31m# duplicate columns & possible reduce dimensionality\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n",
"\u001b[0;32m/opt/conda/lib/python3.6/site-packages/pandas/core/generic.py\u001b[0m in \u001b[0;36m_get_item_cache\u001b[0;34m(self, item)\u001b[0m\n\u001b[1;32m 1840\u001b[0m \u001b[0mres\u001b[0m \u001b[0;34m=\u001b[0m \u001b[0mcache\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0mget\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0mitem\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m 1841\u001b[0m \u001b[0;32mif\u001b[0m \u001b[0mres\u001b[0m \u001b[0;32mis\u001b[0m \u001b[0;32mNone\u001b[0m\u001b[0;34m:\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0;32m-> 1842\u001b[0;31m \u001b[0mvalues\u001b[0m \u001b[0;34m=\u001b[0m \u001b[0mself\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0m_data\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0mget\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0mitem\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0m\u001b[1;32m 1843\u001b[0m \u001b[0mres\u001b[0m \u001b[0;34m=\u001b[0m \u001b[0mself\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0m_box_item_values\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0mitem\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0mvalues\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m 1844\u001b[0m \u001b[0mcache\u001b[0m\u001b[0;34m[\u001b[0m\u001b[0mitem\u001b[0m\u001b[0;34m]\u001b[0m \u001b[0;34m=\u001b[0m \u001b[0mres\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n",
"\u001b[0;32m/opt/conda/lib/python3.6/site-packages/pandas/core/internals.py\u001b[0m in \u001b[0;36mget\u001b[0;34m(self, item, fastpath)\u001b[0m\n\u001b[1;32m 3841\u001b[0m \u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m 3842\u001b[0m \u001b[0;32mif\u001b[0m \u001b[0;32mnot\u001b[0m \u001b[0misna\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0mitem\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m:\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0;32m-> 3843\u001b[0;31m \u001b[0mloc\u001b[0m \u001b[0;34m=\u001b[0m \u001b[0mself\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0mitems\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0mget_loc\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0mitem\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0m\u001b[1;32m 3844\u001b[0m \u001b[0;32melse\u001b[0m\u001b[0;34m:\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m 3845\u001b[0m \u001b[0mindexer\u001b[0m \u001b[0;34m=\u001b[0m \u001b[0mnp\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0marange\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0mlen\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0mself\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0mitems\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m[\u001b[0m\u001b[0misna\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0mself\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0mitems\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m]\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n",
"\u001b[0;32m/opt/conda/lib/python3.6/site-packages/pandas/core/indexes/base.py\u001b[0m in \u001b[0;36mget_loc\u001b[0;34m(self, key, method, tolerance)\u001b[0m\n\u001b[1;32m 2525\u001b[0m \u001b[0;32mreturn\u001b[0m \u001b[0mself\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0m_engine\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0mget_loc\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0mkey\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m 2526\u001b[0m \u001b[0;32mexcept\u001b[0m \u001b[0mKeyError\u001b[0m\u001b[0;34m:\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0;32m-> 2527\u001b[0;31m \u001b[0;32mreturn\u001b[0m \u001b[0mself\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0m_engine\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0mget_loc\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0mself\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0m_maybe_cast_indexer\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0mkey\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0m\u001b[1;32m 2528\u001b[0m \u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m 2529\u001b[0m \u001b[0mindexer\u001b[0m \u001b[0;34m=\u001b[0m \u001b[0mself\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0mget_indexer\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0;34m[\u001b[0m\u001b[0mkey\u001b[0m\u001b[0;34m]\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0mmethod\u001b[0m\u001b[0;34m=\u001b[0m\u001b[0mmethod\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0mtolerance\u001b[0m\u001b[0;34m=\u001b[0m\u001b[0mtolerance\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n",
"\u001b[0;32mpandas/_libs/index.pyx\u001b[0m in \u001b[0;36mpandas._libs.index.IndexEngine.get_loc\u001b[0;34m()\u001b[0m\n",
"\u001b[0;32mpandas/_libs/index.pyx\u001b[0m in \u001b[0;36mpandas._libs.index.IndexEngine.get_loc\u001b[0;34m()\u001b[0m\n",
"\u001b[0;32mpandas/_libs/hashtable_class_helper.pxi\u001b[0m in \u001b[0;36mpandas._libs.hashtable.PyObjectHashTable.get_item\u001b[0;34m()\u001b[0m\n",
"\u001b[0;32mpandas/_libs/hashtable_class_helper.pxi\u001b[0m in \u001b[0;36mpandas._libs.hashtable.PyObjectHashTable.get_item\u001b[0;34m()\u001b[0m\n",
"\u001b[0;31mKeyError\u001b[0m: 'CO2'"
]
}
],
"source": [
"raw_data[raw_data['CO2'] == -99.99]"
]
},
{
"cell_type": "code",
"execution_count": null,
......
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