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4dadf7f4bc5a9f128536bcac936541e3
mooc-rr
Commits
eee42b60
Commit
eee42b60
authored
Nov 20, 2022
by
4dadf7f4bc5a9f128536bcac936541e3
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eee42b60
{
"cells": [],
"cells": [
{
"cell_type": "code",
"execution_count": 73,
"metadata": {},
"outputs": [],
"source": [
"%matplotlib inline\n",
"import matplotlib.pyplot as plt\n",
"import pandas as pd\n",
"import isoweek"
]
},
{
"cell_type": "code",
"execution_count": 74,
"metadata": {},
"outputs": [],
"source": [
"data_url = \"https://scrippsco2.ucsd.edu/assets/data/atmospheric/stations/in_situ_co2/monthly/monthly_in_situ_co2_mlo.csv\""
]
},
{
"cell_type": "code",
"execution_count": 75,
"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>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",
" <th>seasonally</th>\n",
" <th>CO2</th>\n",
" <th>seasonally</th>\n",
" </tr>\n",
" </thead>\n",
" <tbody>\n",
" <tr>\n",
" <th>0</th>\n",
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" <td></td>\n",
" <td></td>\n",
" <td></td>\n",
" <td></td>\n",
" <td>adjusted</td>\n",
" <td></td>\n",
" <td>adjusted fit</td>\n",
" <td>filled</td>\n",
" <td>adjusted filled</td>\n",
" </tr>\n",
" <tr>\n",
" <th>1</th>\n",
" <td></td>\n",
" <td></td>\n",
" <td>Excel</td>\n",
" <td></td>\n",
" <td>[ppm]</td>\n",
" <td>[ppm]</td>\n",
" <td>[ppm]</td>\n",
" <td>[ppm]</td>\n",
" <td>[ppm]</td>\n",
" <td>[ppm]</td>\n",
" </tr>\n",
" <tr>\n",
" <th>2</th>\n",
" <td>1958</td>\n",
" <td>01</td>\n",
" <td>21200</td>\n",
" <td>1958.0411</td>\n",
" <td>-99.99</td>\n",
" <td>-99.99</td>\n",
" <td>-99.99</td>\n",
" <td>-99.99</td>\n",
" <td>-99.99</td>\n",
" <td>-99.99</td>\n",
" </tr>\n",
" <tr>\n",
" <th>3</th>\n",
" <td>1958</td>\n",
" <td>02</td>\n",
" <td>21231</td>\n",
" <td>1958.1260</td>\n",
" <td>-99.99</td>\n",
" <td>-99.99</td>\n",
" <td>-99.99</td>\n",
" <td>-99.99</td>\n",
" <td>-99.99</td>\n",
" <td>-99.99</td>\n",
" </tr>\n",
" <tr>\n",
" <th>4</th>\n",
" <td>1958</td>\n",
" <td>03</td>\n",
" <td>21259</td>\n",
" <td>1958.2027</td>\n",
" <td>315.71</td>\n",
" <td>314.43</td>\n",
" <td>316.20</td>\n",
" <td>314.91</td>\n",
" <td>315.71</td>\n",
" <td>314.43</td>\n",
" </tr>\n",
" <tr>\n",
" <th>5</th>\n",
" <td>1958</td>\n",
" <td>04</td>\n",
" <td>21290</td>\n",
" <td>1958.2877</td>\n",
" <td>317.45</td>\n",
" <td>315.16</td>\n",
" <td>317.30</td>\n",
" <td>314.99</td>\n",
" <td>317.45</td>\n",
" <td>315.16</td>\n",
" </tr>\n",
" <tr>\n",
" <th>6</th>\n",
" <td>1958</td>\n",
" <td>05</td>\n",
" <td>21320</td>\n",
" <td>1958.3699</td>\n",
" <td>317.51</td>\n",
" <td>314.70</td>\n",
" <td>317.88</td>\n",
" <td>315.06</td>\n",
" <td>317.51</td>\n",
" <td>314.70</td>\n",
" </tr>\n",
" <tr>\n",
" <th>7</th>\n",
" <td>1958</td>\n",
" <td>06</td>\n",
" <td>21351</td>\n",
" <td>1958.4548</td>\n",
" <td>-99.99</td>\n",
" <td>-99.99</td>\n",
" <td>317.26</td>\n",
" <td>315.14</td>\n",
" <td>317.26</td>\n",
" <td>315.14</td>\n",
" </tr>\n",
" <tr>\n",
" <th>8</th>\n",
" <td>1958</td>\n",
" <td>07</td>\n",
" <td>21381</td>\n",
" <td>1958.5370</td>\n",
" <td>315.87</td>\n",
" <td>315.20</td>\n",
" <td>315.85</td>\n",
" <td>315.22</td>\n",
" <td>315.87</td>\n",
" <td>315.20</td>\n",
" </tr>\n",
" <tr>\n",
" <th>9</th>\n",
" <td>1958</td>\n",
" <td>08</td>\n",
" <td>21412</td>\n",
" <td>1958.6219</td>\n",
" <td>314.93</td>\n",
" <td>316.21</td>\n",
" <td>313.97</td>\n",
" <td>315.29</td>\n",
" <td>314.93</td>\n",
" <td>316.21</td>\n",
" </tr>\n",
" <tr>\n",
" <th>10</th>\n",
" <td>1958</td>\n",
" <td>09</td>\n",
" <td>21443</td>\n",
" <td>1958.7068</td>\n",
" <td>313.21</td>\n",
" <td>316.11</td>\n",
" <td>312.44</td>\n",
" <td>315.35</td>\n",
" <td>313.21</td>\n",
" <td>316.11</td>\n",
" </tr>\n",
" <tr>\n",
" <th>11</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>312.42</td>\n",
" <td>315.41</td>\n",
" <td>312.42</td>\n",
" <td>315.41</td>\n",
" </tr>\n",
" <tr>\n",
" <th>12</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>313.60</td>\n",
" <td>315.46</td>\n",
" <td>313.33</td>\n",
" <td>315.21</td>\n",
" </tr>\n",
" <tr>\n",
" <th>13</th>\n",
" <td>1958</td>\n",
" <td>12</td>\n",
" <td>21534</td>\n",
" <td>1958.9562</td>\n",
" <td>314.67</td>\n",
" <td>315.44</td>\n",
" <td>314.76</td>\n",
" <td>315.51</td>\n",
" <td>314.67</td>\n",
" <td>315.44</td>\n",
" </tr>\n",
" <tr>\n",
" <th>14</th>\n",
" <td>1959</td>\n",
" <td>01</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>315.57</td>\n",
" <td>315.58</td>\n",
" <td>315.52</td>\n",
" </tr>\n",
" <tr>\n",
" <th>15</th>\n",
" <td>1959</td>\n",
" <td>02</td>\n",
" <td>21596</td>\n",
" <td>1959.1260</td>\n",
" <td>316.49</td>\n",
" <td>315.84</td>\n",
" <td>316.29</td>\n",
" <td>315.63</td>\n",
" <td>316.49</td>\n",
" <td>315.84</td>\n",
" </tr>\n",
" <tr>\n",
" <th>16</th>\n",
" <td>1959</td>\n",
" <td>03</td>\n",
" <td>21624</td>\n",
" <td>1959.2027</td>\n",
" <td>316.65</td>\n",
" <td>315.37</td>\n",
" <td>316.99</td>\n",
" <td>315.69</td>\n",
" <td>316.65</td>\n",
" <td>315.37</td>\n",
" </tr>\n",
" <tr>\n",
" <th>17</th>\n",
" <td>1959</td>\n",
" <td>04</td>\n",
" <td>21655</td>\n",
" <td>1959.2877</td>\n",
" <td>317.72</td>\n",
" <td>315.41</td>\n",
" <td>318.09</td>\n",
" <td>315.77</td>\n",
" <td>317.72</td>\n",
" <td>315.41</td>\n",
" </tr>\n",
" <tr>\n",
" <th>18</th>\n",
" <td>1959</td>\n",
" <td>05</td>\n",
" <td>21685</td>\n",
" <td>1959.3699</td>\n",
" <td>318.29</td>\n",
" <td>315.47</td>\n",
" <td>318.67</td>\n",
" <td>315.85</td>\n",
" <td>318.29</td>\n",
" <td>315.47</td>\n",
" </tr>\n",
" <tr>\n",
" <th>19</th>\n",
" <td>1959</td>\n",
" <td>06</td>\n",
" <td>21716</td>\n",
" <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",
" </tr>\n",
" <tr>\n",
" <th>20</th>\n",
" <td>1959</td>\n",
" <td>07</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",
" </tr>\n",
" <tr>\n",
" <th>21</th>\n",
" <td>1959</td>\n",
" <td>08</td>\n",
" <td>21777</td>\n",
" <td>1959.6219</td>\n",
" <td>314.80</td>\n",
" <td>316.09</td>\n",
" <td>314.80</td>\n",
" <td>316.12</td>\n",
" <td>314.80</td>\n",
" <td>316.09</td>\n",
" </tr>\n",
" <tr>\n",
" <th>22</th>\n",
" <td>1959</td>\n",
" <td>09</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>23</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>316.34</td>\n",
" <td>313.31</td>\n",
" <td>316.31</td>\n",
" <td>313.33</td>\n",
" <td>316.34</td>\n",
" </tr>\n",
" <tr>\n",
" <th>24</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>316.70</td>\n",
" <td>314.53</td>\n",
" <td>316.39</td>\n",
" <td>314.81</td>\n",
" <td>316.70</td>\n",
" </tr>\n",
" <tr>\n",
" <th>25</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>315.72</td>\n",
" <td>316.47</td>\n",
" <td>315.58</td>\n",
" <td>316.35</td>\n",
" </tr>\n",
" <tr>\n",
" <th>26</th>\n",
" <td>1960</td>\n",
" <td>01</td>\n",
" <td>21930</td>\n",
" <td>1960.0410</td>\n",
" <td>316.43</td>\n",
" <td>316.37</td>\n",
" <td>316.62</td>\n",
" <td>316.56</td>\n",
" <td>316.43</td>\n",
" <td>316.37</td>\n",
" </tr>\n",
" <tr>\n",
" <th>27</th>\n",
" <td>1960</td>\n",
" <td>02</td>\n",
" <td>21961</td>\n",
" <td>1960.1257</td>\n",
" <td>316.98</td>\n",
" <td>316.33</td>\n",
" <td>317.29</td>\n",
" <td>316.64</td>\n",
" <td>316.98</td>\n",
" <td>316.33</td>\n",
" </tr>\n",
" <tr>\n",
" <th>28</th>\n",
" <td>1960</td>\n",
" <td>03</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>316.71</td>\n",
" <td>317.58</td>\n",
" <td>316.27</td>\n",
" </tr>\n",
" <tr>\n",
" <th>29</th>\n",
" <td>1960</td>\n",
" <td>04</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>316.79</td>\n",
" <td>319.03</td>\n",
" <td>316.70</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>752</th>\n",
" <td>2020</td>\n",
" <td>07</td>\n",
" <td>44027</td>\n",
" <td>2020.5383</td>\n",
" <td>414.42</td>\n",
" <td>413.65</td>\n",
" <td>414.75</td>\n",
" <td>414.02</td>\n",
" <td>414.42</td>\n",
" <td>413.65</td>\n",
" </tr>\n",
" <tr>\n",
" <th>753</th>\n",
" <td>2020</td>\n",
" <td>08</td>\n",
" <td>44058</td>\n",
" <td>2020.6230</td>\n",
" <td>412.52</td>\n",
" <td>414.09</td>\n",
" <td>412.60</td>\n",
" <td>414.22</td>\n",
" <td>412.52</td>\n",
" <td>414.09</td>\n",
" </tr>\n",
" <tr>\n",
" <th>754</th>\n",
" <td>2020</td>\n",
" <td>09</td>\n",
" <td>44089</td>\n",
" <td>2020.7077</td>\n",
" <td>411.18</td>\n",
" <td>414.68</td>\n",
" <td>410.91</td>\n",
" <td>414.42</td>\n",
" <td>411.18</td>\n",
" <td>414.68</td>\n",
" </tr>\n",
" <tr>\n",
" <th>755</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>414.72</td>\n",
" <td>411.02</td>\n",
" <td>414.61</td>\n",
" <td>411.12</td>\n",
" <td>414.72</td>\n",
" </tr>\n",
" <tr>\n",
" <th>756</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>415.14</td>\n",
" <td>412.56</td>\n",
" <td>414.80</td>\n",
" <td>412.88</td>\n",
" <td>415.14</td>\n",
" </tr>\n",
" <tr>\n",
" <th>757</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>414.07</td>\n",
" <td>414.97</td>\n",
" <td>413.89</td>\n",
" <td>414.81</td>\n",
" </tr>\n",
" <tr>\n",
" <th>758</th>\n",
" <td>2021</td>\n",
" <td>01</td>\n",
" <td>44211</td>\n",
" <td>2021.0411</td>\n",
" <td>415.15</td>\n",
" <td>415.08</td>\n",
" <td>415.23</td>\n",
" <td>415.15</td>\n",
" <td>415.15</td>\n",
" <td>415.08</td>\n",
" </tr>\n",
" <tr>\n",
" <th>759</th>\n",
" <td>2021</td>\n",
" <td>02</td>\n",
" <td>44242</td>\n",
" <td>2021.1260</td>\n",
" <td>416.47</td>\n",
" <td>415.69</td>\n",
" <td>416.12</td>\n",
" <td>415.33</td>\n",
" <td>416.47</td>\n",
" <td>415.69</td>\n",
" </tr>\n",
" <tr>\n",
" <th>760</th>\n",
" <td>2021</td>\n",
" <td>03</td>\n",
" <td>44270</td>\n",
" <td>2021.2027</td>\n",
" <td>417.16</td>\n",
" <td>415.62</td>\n",
" <td>417.04</td>\n",
" <td>415.48</td>\n",
" <td>417.16</td>\n",
" <td>415.62</td>\n",
" </tr>\n",
" <tr>\n",
" <th>761</th>\n",
" <td>2021</td>\n",
" <td>04</td>\n",
" <td>44301</td>\n",
" <td>2021.2877</td>\n",
" <td>418.24</td>\n",
" <td>415.47</td>\n",
" <td>418.44</td>\n",
" <td>415.65</td>\n",
" <td>418.24</td>\n",
" <td>415.47</td>\n",
" </tr>\n",
" <tr>\n",
" <th>762</th>\n",
" <td>2021</td>\n",
" <td>05</td>\n",
" <td>44331</td>\n",
" <td>2021.3699</td>\n",
" <td>418.95</td>\n",
" <td>415.56</td>\n",
" <td>419.21</td>\n",
" <td>415.82</td>\n",
" <td>418.95</td>\n",
" <td>415.56</td>\n",
" </tr>\n",
" <tr>\n",
" <th>763</th>\n",
" <td>2021</td>\n",
" <td>06</td>\n",
" <td>44362</td>\n",
" <td>2021.4548</td>\n",
" <td>418.70</td>\n",
" <td>416.13</td>\n",
" <td>418.55</td>\n",
" <td>415.99</td>\n",
" <td>418.70</td>\n",
" <td>416.13</td>\n",
" </tr>\n",
" <tr>\n",
" <th>764</th>\n",
" <td>2021</td>\n",
" <td>07</td>\n",
" <td>44392</td>\n",
" <td>2021.5370</td>\n",
" <td>416.65</td>\n",
" <td>415.85</td>\n",
" <td>416.94</td>\n",
" <td>416.17</td>\n",
" <td>416.65</td>\n",
" <td>415.85</td>\n",
" </tr>\n",
" <tr>\n",
" <th>765</th>\n",
" <td>2021</td>\n",
" <td>08</td>\n",
" <td>44423</td>\n",
" <td>2021.6219</td>\n",
" <td>414.34</td>\n",
" <td>415.89</td>\n",
" <td>414.76</td>\n",
" <td>416.36</td>\n",
" <td>414.34</td>\n",
" <td>415.89</td>\n",
" </tr>\n",
" <tr>\n",
" <th>766</th>\n",
" <td>2021</td>\n",
" <td>09</td>\n",
" <td>44454</td>\n",
" <td>2021.7068</td>\n",
" <td>412.91</td>\n",
" <td>416.40</td>\n",
" <td>413.03</td>\n",
" <td>416.55</td>\n",
" <td>412.91</td>\n",
" <td>416.40</td>\n",
" </tr>\n",
" <tr>\n",
" <th>767</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>417.16</td>\n",
" <td>413.13</td>\n",
" <td>416.73</td>\n",
" <td>413.55</td>\n",
" <td>417.16</td>\n",
" </tr>\n",
" <tr>\n",
" <th>768</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>414.67</td>\n",
" <td>416.92</td>\n",
" <td>414.82</td>\n",
" <td>417.09</td>\n",
" </tr>\n",
" <tr>\n",
" <th>769</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>416.18</td>\n",
" <td>417.09</td>\n",
" <td>416.43</td>\n",
" <td>417.36</td>\n",
" </tr>\n",
" <tr>\n",
" <th>770</th>\n",
" <td>2022</td>\n",
" <td>01</td>\n",
" <td>44576</td>\n",
" <td>2022.0411</td>\n",
" <td>418.01</td>\n",
" <td>417.94</td>\n",
" <td>417.34</td>\n",
" <td>417.25</td>\n",
" <td>418.01</td>\n",
" <td>417.94</td>\n",
" </tr>\n",
" <tr>\n",
" <th>771</th>\n",
" <td>2022</td>\n",
" <td>02</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>417.41</td>\n",
" <td>418.99</td>\n",
" <td>418.20</td>\n",
" </tr>\n",
" <tr>\n",
" <th>772</th>\n",
" <td>2022</td>\n",
" <td>03</td>\n",
" <td>44635</td>\n",
" <td>2022.2027</td>\n",
" <td>418.45</td>\n",
" <td>416.91</td>\n",
" <td>419.11</td>\n",
" <td>417.55</td>\n",
" <td>418.45</td>\n",
" <td>416.91</td>\n",
" </tr>\n",
" <tr>\n",
" <th>773</th>\n",
" <td>2022</td>\n",
" <td>04</td>\n",
" <td>44666</td>\n",
" <td>2022.2877</td>\n",
" <td>420.02</td>\n",
" <td>417.24</td>\n",
" <td>420.49</td>\n",
" <td>417.70</td>\n",
" <td>420.02</td>\n",
" <td>417.24</td>\n",
" </tr>\n",
" <tr>\n",
" <th>774</th>\n",
" <td>2022</td>\n",
" <td>05</td>\n",
" <td>44696</td>\n",
" <td>2022.3699</td>\n",
" <td>420.77</td>\n",
" <td>417.37</td>\n",
" <td>421.25</td>\n",
" <td>417.85</td>\n",
" <td>420.77</td>\n",
" <td>417.37</td>\n",
" </tr>\n",
" <tr>\n",
" <th>775</th>\n",
" <td>2022</td>\n",
" <td>06</td>\n",
" <td>44727</td>\n",
" <td>2022.4548</td>\n",
" <td>420.68</td>\n",
" <td>418.10</td>\n",
" <td>420.58</td>\n",
" <td>418.02</td>\n",
" <td>420.68</td>\n",
" <td>418.10</td>\n",
" </tr>\n",
" <tr>\n",
" <th>776</th>\n",
" <td>2022</td>\n",
" <td>07</td>\n",
" <td>44757</td>\n",
" <td>2022.5370</td>\n",
" <td>418.68</td>\n",
" <td>417.87</td>\n",
" <td>418.96</td>\n",
" <td>418.19</td>\n",
" <td>418.68</td>\n",
" <td>417.87</td>\n",
" </tr>\n",
" <tr>\n",
" <th>777</th>\n",
" <td>2022</td>\n",
" <td>08</td>\n",
" <td>44788</td>\n",
" <td>2022.6219</td>\n",
" <td>416.76</td>\n",
" <td>418.31</td>\n",
" <td>416.78</td>\n",
" <td>418.37</td>\n",
" <td>416.76</td>\n",
" <td>418.31</td>\n",
" </tr>\n",
" <tr>\n",
" <th>778</th>\n",
" <td>2022</td>\n",
" <td>09</td>\n",
" <td>44819</td>\n",
" <td>2022.7068</td>\n",
" <td>415.41</td>\n",
" <td>418.91</td>\n",
" <td>415.04</td>\n",
" <td>418.56</td>\n",
" <td>415.41</td>\n",
" <td>418.91</td>\n",
" </tr>\n",
" <tr>\n",
" <th>779</th>\n",
" <td>2022</td>\n",
" <td>10</td>\n",
" <td>44849</td>\n",
" <td>2022.7890</td>\n",
" <td>415.31</td>\n",
" <td>418.93</td>\n",
" <td>-99.99</td>\n",
" <td>-99.99</td>\n",
" <td>415.31</td>\n",
" <td>418.93</td>\n",
" </tr>\n",
" <tr>\n",
" <th>780</th>\n",
" <td>2022</td>\n",
" <td>11</td>\n",
" <td>44880</td>\n",
" <td>2022.8740</td>\n",
" <td>-99.99</td>\n",
" <td>-99.99</td>\n",
" <td>-99.99</td>\n",
" <td>-99.99</td>\n",
" <td>-99.99</td>\n",
" <td>-99.99</td>\n",
" </tr>\n",
" <tr>\n",
" <th>781</th>\n",
" <td>2022</td>\n",
" <td>12</td>\n",
" <td>44910</td>\n",
" <td>2022.9562</td>\n",
" <td>-99.99</td>\n",
" <td>-99.99</td>\n",
" <td>-99.99</td>\n",
" <td>-99.99</td>\n",
" <td>-99.99</td>\n",
" <td>-99.99</td>\n",
" </tr>\n",
" </tbody>\n",
"</table>\n",
"<p>782 rows × 10 columns</p>\n",
"</div>"
],
"text/plain": [
" Yr Mn Date Date CO2 seasonally fit \\\n",
"0 adjusted \n",
"1 Excel [ppm] [ppm] [ppm] \n",
"2 1958 01 21200 1958.0411 -99.99 -99.99 -99.99 \n",
"3 1958 02 21231 1958.1260 -99.99 -99.99 -99.99 \n",
"4 1958 03 21259 1958.2027 315.71 314.43 316.20 \n",
"5 1958 04 21290 1958.2877 317.45 315.16 317.30 \n",
"6 1958 05 21320 1958.3699 317.51 314.70 317.88 \n",
"7 1958 06 21351 1958.4548 -99.99 -99.99 317.26 \n",
"8 1958 07 21381 1958.5370 315.87 315.20 315.85 \n",
"9 1958 08 21412 1958.6219 314.93 316.21 313.97 \n",
"10 1958 09 21443 1958.7068 313.21 316.11 312.44 \n",
"11 1958 10 21473 1958.7890 -99.99 -99.99 312.42 \n",
"12 1958 11 21504 1958.8740 313.33 315.21 313.60 \n",
"13 1958 12 21534 1958.9562 314.67 315.44 314.76 \n",
"14 1959 01 21565 1959.0411 315.58 315.52 315.64 \n",
"15 1959 02 21596 1959.1260 316.49 315.84 316.29 \n",
"16 1959 03 21624 1959.2027 316.65 315.37 316.99 \n",
"17 1959 04 21655 1959.2877 317.72 315.41 318.09 \n",
"18 1959 05 21685 1959.3699 318.29 315.47 318.67 \n",
"19 1959 06 21716 1959.4548 318.15 316.01 318.06 \n",
"20 1959 07 21746 1959.5370 316.54 315.87 316.67 \n",
"21 1959 08 21777 1959.6219 314.80 316.09 314.80 \n",
"22 1959 09 21808 1959.7068 313.84 316.74 313.30 \n",
"23 1959 10 21838 1959.7890 313.33 316.34 313.31 \n",
"24 1959 11 21869 1959.8740 314.81 316.70 314.53 \n",
"25 1959 12 21899 1959.9562 315.58 316.35 315.72 \n",
"26 1960 01 21930 1960.0410 316.43 316.37 316.62 \n",
"27 1960 02 21961 1960.1257 316.98 316.33 317.29 \n",
"28 1960 03 21990 1960.2049 317.58 316.27 318.04 \n",
"29 1960 04 22021 1960.2896 319.03 316.70 319.14 \n",
".. ... ... ... ... ... ... ... \n",
"752 2020 07 44027 2020.5383 414.42 413.65 414.75 \n",
"753 2020 08 44058 2020.6230 412.52 414.09 412.60 \n",
"754 2020 09 44089 2020.7077 411.18 414.68 410.91 \n",
"755 2020 10 44119 2020.7896 411.12 414.72 411.02 \n",
"756 2020 11 44150 2020.8743 412.88 415.14 412.56 \n",
"757 2020 12 44180 2020.9563 413.89 414.81 414.07 \n",
"758 2021 01 44211 2021.0411 415.15 415.08 415.23 \n",
"759 2021 02 44242 2021.1260 416.47 415.69 416.12 \n",
"760 2021 03 44270 2021.2027 417.16 415.62 417.04 \n",
"761 2021 04 44301 2021.2877 418.24 415.47 418.44 \n",
"762 2021 05 44331 2021.3699 418.95 415.56 419.21 \n",
"763 2021 06 44362 2021.4548 418.70 416.13 418.55 \n",
"764 2021 07 44392 2021.5370 416.65 415.85 416.94 \n",
"765 2021 08 44423 2021.6219 414.34 415.89 414.76 \n",
"766 2021 09 44454 2021.7068 412.91 416.40 413.03 \n",
"767 2021 10 44484 2021.7890 413.55 417.16 413.13 \n",
"768 2021 11 44515 2021.8740 414.82 417.09 414.67 \n",
"769 2021 12 44545 2021.9562 416.43 417.36 416.18 \n",
"770 2022 01 44576 2022.0411 418.01 417.94 417.34 \n",
"771 2022 02 44607 2022.1260 418.99 418.20 418.20 \n",
"772 2022 03 44635 2022.2027 418.45 416.91 419.11 \n",
"773 2022 04 44666 2022.2877 420.02 417.24 420.49 \n",
"774 2022 05 44696 2022.3699 420.77 417.37 421.25 \n",
"775 2022 06 44727 2022.4548 420.68 418.10 420.58 \n",
"776 2022 07 44757 2022.5370 418.68 417.87 418.96 \n",
"777 2022 08 44788 2022.6219 416.76 418.31 416.78 \n",
"778 2022 09 44819 2022.7068 415.41 418.91 415.04 \n",
"779 2022 10 44849 2022.7890 415.31 418.93 -99.99 \n",
"780 2022 11 44880 2022.8740 -99.99 -99.99 -99.99 \n",
"781 2022 12 44910 2022.9562 -99.99 -99.99 -99.99 \n",
"\n",
" seasonally CO2 seasonally \n",
"0 adjusted fit filled adjusted filled \n",
"1 [ppm] [ppm] [ppm] \n",
"2 -99.99 -99.99 -99.99 \n",
"3 -99.99 -99.99 -99.99 \n",
"4 314.91 315.71 314.43 \n",
"5 314.99 317.45 315.16 \n",
"6 315.06 317.51 314.70 \n",
"7 315.14 317.26 315.14 \n",
"8 315.22 315.87 315.20 \n",
"9 315.29 314.93 316.21 \n",
"10 315.35 313.21 316.11 \n",
"11 315.41 312.42 315.41 \n",
"12 315.46 313.33 315.21 \n",
"13 315.51 314.67 315.44 \n",
"14 315.57 315.58 315.52 \n",
"15 315.63 316.49 315.84 \n",
"16 315.69 316.65 315.37 \n",
"17 315.77 317.72 315.41 \n",
"18 315.85 318.29 315.47 \n",
"19 315.94 318.15 316.01 \n",
"20 316.03 316.54 315.87 \n",
"21 316.12 314.80 316.09 \n",
"22 316.22 313.84 316.74 \n",
"23 316.31 313.33 316.34 \n",
"24 316.39 314.81 316.70 \n",
"25 316.47 315.58 316.35 \n",
"26 316.56 316.43 316.37 \n",
"27 316.64 316.98 316.33 \n",
"28 316.71 317.58 316.27 \n",
"29 316.79 319.03 316.70 \n",
".. ... ... ... \n",
"752 414.02 414.42 413.65 \n",
"753 414.22 412.52 414.09 \n",
"754 414.42 411.18 414.68 \n",
"755 414.61 411.12 414.72 \n",
"756 414.80 412.88 415.14 \n",
"757 414.97 413.89 414.81 \n",
"758 415.15 415.15 415.08 \n",
"759 415.33 416.47 415.69 \n",
"760 415.48 417.16 415.62 \n",
"761 415.65 418.24 415.47 \n",
"762 415.82 418.95 415.56 \n",
"763 415.99 418.70 416.13 \n",
"764 416.17 416.65 415.85 \n",
"765 416.36 414.34 415.89 \n",
"766 416.55 412.91 416.40 \n",
"767 416.73 413.55 417.16 \n",
"768 416.92 414.82 417.09 \n",
"769 417.09 416.43 417.36 \n",
"770 417.25 418.01 417.94 \n",
"771 417.41 418.99 418.20 \n",
"772 417.55 418.45 416.91 \n",
"773 417.70 420.02 417.24 \n",
"774 417.85 420.77 417.37 \n",
"775 418.02 420.68 418.10 \n",
"776 418.19 418.68 417.87 \n",
"777 418.37 416.76 418.31 \n",
"778 418.56 415.41 418.91 \n",
"779 -99.99 415.31 418.93 \n",
"780 -99.99 -99.99 -99.99 \n",
"781 -99.99 -99.99 -99.99 \n",
"\n",
"[782 rows x 10 columns]"
]
},
"execution_count": 75,
"metadata": {},
"output_type": "execute_result"
}
],
"source": [
"raw_data = pd.read_csv(data_url, encoding = 'iso-8859-1', skiprows=54)\n",
"raw_data"
]
},
{
"cell_type": "code",
"execution_count": 76,
"metadata": {
"scrolled": true
},
"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>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",
" <th>seasonally</th>\n",
" <th>CO2</th>\n",
" <th>seasonally</th>\n",
" </tr>\n",
" </thead>\n",
" <tbody>\n",
" <tr>\n",
" <th>2</th>\n",
" <td>1958</td>\n",
" <td>01</td>\n",
" <td>21200</td>\n",
" <td>1958.0411</td>\n",
" <td>-99.99</td>\n",
" <td>-99.99</td>\n",
" <td>-99.99</td>\n",
" <td>-99.99</td>\n",
" <td>-99.99</td>\n",
" <td>-99.99</td>\n",
" </tr>\n",
" <tr>\n",
" <th>3</th>\n",
" <td>1958</td>\n",
" <td>02</td>\n",
" <td>21231</td>\n",
" <td>1958.1260</td>\n",
" <td>-99.99</td>\n",
" <td>-99.99</td>\n",
" <td>-99.99</td>\n",
" <td>-99.99</td>\n",
" <td>-99.99</td>\n",
" <td>-99.99</td>\n",
" </tr>\n",
" <tr>\n",
" <th>4</th>\n",
" <td>1958</td>\n",
" <td>03</td>\n",
" <td>21259</td>\n",
" <td>1958.2027</td>\n",
" <td>315.71</td>\n",
" <td>314.43</td>\n",
" <td>316.20</td>\n",
" <td>314.91</td>\n",
" <td>315.71</td>\n",
" <td>314.43</td>\n",
" </tr>\n",
" <tr>\n",
" <th>5</th>\n",
" <td>1958</td>\n",
" <td>04</td>\n",
" <td>21290</td>\n",
" <td>1958.2877</td>\n",
" <td>317.45</td>\n",
" <td>315.16</td>\n",
" <td>317.30</td>\n",
" <td>314.99</td>\n",
" <td>317.45</td>\n",
" <td>315.16</td>\n",
" </tr>\n",
" <tr>\n",
" <th>6</th>\n",
" <td>1958</td>\n",
" <td>05</td>\n",
" <td>21320</td>\n",
" <td>1958.3699</td>\n",
" <td>317.51</td>\n",
" <td>314.70</td>\n",
" <td>317.88</td>\n",
" <td>315.06</td>\n",
" <td>317.51</td>\n",
" <td>314.70</td>\n",
" </tr>\n",
" <tr>\n",
" <th>7</th>\n",
" <td>1958</td>\n",
" <td>06</td>\n",
" <td>21351</td>\n",
" <td>1958.4548</td>\n",
" <td>-99.99</td>\n",
" <td>-99.99</td>\n",
" <td>317.26</td>\n",
" <td>315.14</td>\n",
" <td>317.26</td>\n",
" <td>315.14</td>\n",
" </tr>\n",
" <tr>\n",
" <th>8</th>\n",
" <td>1958</td>\n",
" <td>07</td>\n",
" <td>21381</td>\n",
" <td>1958.5370</td>\n",
" <td>315.87</td>\n",
" <td>315.20</td>\n",
" <td>315.85</td>\n",
" <td>315.22</td>\n",
" <td>315.87</td>\n",
" <td>315.20</td>\n",
" </tr>\n",
" <tr>\n",
" <th>9</th>\n",
" <td>1958</td>\n",
" <td>08</td>\n",
" <td>21412</td>\n",
" <td>1958.6219</td>\n",
" <td>314.93</td>\n",
" <td>316.21</td>\n",
" <td>313.97</td>\n",
" <td>315.29</td>\n",
" <td>314.93</td>\n",
" <td>316.21</td>\n",
" </tr>\n",
" <tr>\n",
" <th>10</th>\n",
" <td>1958</td>\n",
" <td>09</td>\n",
" <td>21443</td>\n",
" <td>1958.7068</td>\n",
" <td>313.21</td>\n",
" <td>316.11</td>\n",
" <td>312.44</td>\n",
" <td>315.35</td>\n",
" <td>313.21</td>\n",
" <td>316.11</td>\n",
" </tr>\n",
" <tr>\n",
" <th>11</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>312.42</td>\n",
" <td>315.41</td>\n",
" <td>312.42</td>\n",
" <td>315.41</td>\n",
" </tr>\n",
" <tr>\n",
" <th>12</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>313.60</td>\n",
" <td>315.46</td>\n",
" <td>313.33</td>\n",
" <td>315.21</td>\n",
" </tr>\n",
" <tr>\n",
" <th>13</th>\n",
" <td>1958</td>\n",
" <td>12</td>\n",
" <td>21534</td>\n",
" <td>1958.9562</td>\n",
" <td>314.67</td>\n",
" <td>315.44</td>\n",
" <td>314.76</td>\n",
" <td>315.51</td>\n",
" <td>314.67</td>\n",
" <td>315.44</td>\n",
" </tr>\n",
" <tr>\n",
" <th>14</th>\n",
" <td>1959</td>\n",
" <td>01</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>315.57</td>\n",
" <td>315.58</td>\n",
" <td>315.52</td>\n",
" </tr>\n",
" <tr>\n",
" <th>15</th>\n",
" <td>1959</td>\n",
" <td>02</td>\n",
" <td>21596</td>\n",
" <td>1959.1260</td>\n",
" <td>316.49</td>\n",
" <td>315.84</td>\n",
" <td>316.29</td>\n",
" <td>315.63</td>\n",
" <td>316.49</td>\n",
" <td>315.84</td>\n",
" </tr>\n",
" <tr>\n",
" <th>16</th>\n",
" <td>1959</td>\n",
" <td>03</td>\n",
" <td>21624</td>\n",
" <td>1959.2027</td>\n",
" <td>316.65</td>\n",
" <td>315.37</td>\n",
" <td>316.99</td>\n",
" <td>315.69</td>\n",
" <td>316.65</td>\n",
" <td>315.37</td>\n",
" </tr>\n",
" <tr>\n",
" <th>17</th>\n",
" <td>1959</td>\n",
" <td>04</td>\n",
" <td>21655</td>\n",
" <td>1959.2877</td>\n",
" <td>317.72</td>\n",
" <td>315.41</td>\n",
" <td>318.09</td>\n",
" <td>315.77</td>\n",
" <td>317.72</td>\n",
" <td>315.41</td>\n",
" </tr>\n",
" <tr>\n",
" <th>18</th>\n",
" <td>1959</td>\n",
" <td>05</td>\n",
" <td>21685</td>\n",
" <td>1959.3699</td>\n",
" <td>318.29</td>\n",
" <td>315.47</td>\n",
" <td>318.67</td>\n",
" <td>315.85</td>\n",
" <td>318.29</td>\n",
" <td>315.47</td>\n",
" </tr>\n",
" <tr>\n",
" <th>19</th>\n",
" <td>1959</td>\n",
" <td>06</td>\n",
" <td>21716</td>\n",
" <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",
" </tr>\n",
" <tr>\n",
" <th>20</th>\n",
" <td>1959</td>\n",
" <td>07</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",
" </tr>\n",
" <tr>\n",
" <th>21</th>\n",
" <td>1959</td>\n",
" <td>08</td>\n",
" <td>21777</td>\n",
" <td>1959.6219</td>\n",
" <td>314.80</td>\n",
" <td>316.09</td>\n",
" <td>314.80</td>\n",
" <td>316.12</td>\n",
" <td>314.80</td>\n",
" <td>316.09</td>\n",
" </tr>\n",
" <tr>\n",
" <th>22</th>\n",
" <td>1959</td>\n",
" <td>09</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>23</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>316.34</td>\n",
" <td>313.31</td>\n",
" <td>316.31</td>\n",
" <td>313.33</td>\n",
" <td>316.34</td>\n",
" </tr>\n",
" <tr>\n",
" <th>24</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>316.70</td>\n",
" <td>314.53</td>\n",
" <td>316.39</td>\n",
" <td>314.81</td>\n",
" <td>316.70</td>\n",
" </tr>\n",
" <tr>\n",
" <th>25</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>315.72</td>\n",
" <td>316.47</td>\n",
" <td>315.58</td>\n",
" <td>316.35</td>\n",
" </tr>\n",
" <tr>\n",
" <th>26</th>\n",
" <td>1960</td>\n",
" <td>01</td>\n",
" <td>21930</td>\n",
" <td>1960.0410</td>\n",
" <td>316.43</td>\n",
" <td>316.37</td>\n",
" <td>316.62</td>\n",
" <td>316.56</td>\n",
" <td>316.43</td>\n",
" <td>316.37</td>\n",
" </tr>\n",
" <tr>\n",
" <th>27</th>\n",
" <td>1960</td>\n",
" <td>02</td>\n",
" <td>21961</td>\n",
" <td>1960.1257</td>\n",
" <td>316.98</td>\n",
" <td>316.33</td>\n",
" <td>317.29</td>\n",
" <td>316.64</td>\n",
" <td>316.98</td>\n",
" <td>316.33</td>\n",
" </tr>\n",
" <tr>\n",
" <th>28</th>\n",
" <td>1960</td>\n",
" <td>03</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>316.71</td>\n",
" <td>317.58</td>\n",
" <td>316.27</td>\n",
" </tr>\n",
" <tr>\n",
" <th>29</th>\n",
" <td>1960</td>\n",
" <td>04</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>316.79</td>\n",
" <td>319.03</td>\n",
" <td>316.70</td>\n",
" </tr>\n",
" <tr>\n",
" <th>30</th>\n",
" <td>1960</td>\n",
" <td>05</td>\n",
" <td>22051</td>\n",
" <td>1960.3716</td>\n",
" <td>320.03</td>\n",
" <td>317.20</td>\n",
" <td>319.69</td>\n",
" <td>316.86</td>\n",
" <td>320.03</td>\n",
" <td>317.20</td>\n",
" </tr>\n",
" <tr>\n",
" <th>31</th>\n",
" <td>1960</td>\n",
" <td>06</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>...</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>752</th>\n",
" <td>2020</td>\n",
" <td>07</td>\n",
" <td>44027</td>\n",
" <td>2020.5383</td>\n",
" <td>414.42</td>\n",
" <td>413.65</td>\n",
" <td>414.75</td>\n",
" <td>414.02</td>\n",
" <td>414.42</td>\n",
" <td>413.65</td>\n",
" </tr>\n",
" <tr>\n",
" <th>753</th>\n",
" <td>2020</td>\n",
" <td>08</td>\n",
" <td>44058</td>\n",
" <td>2020.6230</td>\n",
" <td>412.52</td>\n",
" <td>414.09</td>\n",
" <td>412.60</td>\n",
" <td>414.22</td>\n",
" <td>412.52</td>\n",
" <td>414.09</td>\n",
" </tr>\n",
" <tr>\n",
" <th>754</th>\n",
" <td>2020</td>\n",
" <td>09</td>\n",
" <td>44089</td>\n",
" <td>2020.7077</td>\n",
" <td>411.18</td>\n",
" <td>414.68</td>\n",
" <td>410.91</td>\n",
" <td>414.42</td>\n",
" <td>411.18</td>\n",
" <td>414.68</td>\n",
" </tr>\n",
" <tr>\n",
" <th>755</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>414.72</td>\n",
" <td>411.02</td>\n",
" <td>414.61</td>\n",
" <td>411.12</td>\n",
" <td>414.72</td>\n",
" </tr>\n",
" <tr>\n",
" <th>756</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>415.14</td>\n",
" <td>412.56</td>\n",
" <td>414.80</td>\n",
" <td>412.88</td>\n",
" <td>415.14</td>\n",
" </tr>\n",
" <tr>\n",
" <th>757</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>414.07</td>\n",
" <td>414.97</td>\n",
" <td>413.89</td>\n",
" <td>414.81</td>\n",
" </tr>\n",
" <tr>\n",
" <th>758</th>\n",
" <td>2021</td>\n",
" <td>01</td>\n",
" <td>44211</td>\n",
" <td>2021.0411</td>\n",
" <td>415.15</td>\n",
" <td>415.08</td>\n",
" <td>415.23</td>\n",
" <td>415.15</td>\n",
" <td>415.15</td>\n",
" <td>415.08</td>\n",
" </tr>\n",
" <tr>\n",
" <th>759</th>\n",
" <td>2021</td>\n",
" <td>02</td>\n",
" <td>44242</td>\n",
" <td>2021.1260</td>\n",
" <td>416.47</td>\n",
" <td>415.69</td>\n",
" <td>416.12</td>\n",
" <td>415.33</td>\n",
" <td>416.47</td>\n",
" <td>415.69</td>\n",
" </tr>\n",
" <tr>\n",
" <th>760</th>\n",
" <td>2021</td>\n",
" <td>03</td>\n",
" <td>44270</td>\n",
" <td>2021.2027</td>\n",
" <td>417.16</td>\n",
" <td>415.62</td>\n",
" <td>417.04</td>\n",
" <td>415.48</td>\n",
" <td>417.16</td>\n",
" <td>415.62</td>\n",
" </tr>\n",
" <tr>\n",
" <th>761</th>\n",
" <td>2021</td>\n",
" <td>04</td>\n",
" <td>44301</td>\n",
" <td>2021.2877</td>\n",
" <td>418.24</td>\n",
" <td>415.47</td>\n",
" <td>418.44</td>\n",
" <td>415.65</td>\n",
" <td>418.24</td>\n",
" <td>415.47</td>\n",
" </tr>\n",
" <tr>\n",
" <th>762</th>\n",
" <td>2021</td>\n",
" <td>05</td>\n",
" <td>44331</td>\n",
" <td>2021.3699</td>\n",
" <td>418.95</td>\n",
" <td>415.56</td>\n",
" <td>419.21</td>\n",
" <td>415.82</td>\n",
" <td>418.95</td>\n",
" <td>415.56</td>\n",
" </tr>\n",
" <tr>\n",
" <th>763</th>\n",
" <td>2021</td>\n",
" <td>06</td>\n",
" <td>44362</td>\n",
" <td>2021.4548</td>\n",
" <td>418.70</td>\n",
" <td>416.13</td>\n",
" <td>418.55</td>\n",
" <td>415.99</td>\n",
" <td>418.70</td>\n",
" <td>416.13</td>\n",
" </tr>\n",
" <tr>\n",
" <th>764</th>\n",
" <td>2021</td>\n",
" <td>07</td>\n",
" <td>44392</td>\n",
" <td>2021.5370</td>\n",
" <td>416.65</td>\n",
" <td>415.85</td>\n",
" <td>416.94</td>\n",
" <td>416.17</td>\n",
" <td>416.65</td>\n",
" <td>415.85</td>\n",
" </tr>\n",
" <tr>\n",
" <th>765</th>\n",
" <td>2021</td>\n",
" <td>08</td>\n",
" <td>44423</td>\n",
" <td>2021.6219</td>\n",
" <td>414.34</td>\n",
" <td>415.89</td>\n",
" <td>414.76</td>\n",
" <td>416.36</td>\n",
" <td>414.34</td>\n",
" <td>415.89</td>\n",
" </tr>\n",
" <tr>\n",
" <th>766</th>\n",
" <td>2021</td>\n",
" <td>09</td>\n",
" <td>44454</td>\n",
" <td>2021.7068</td>\n",
" <td>412.91</td>\n",
" <td>416.40</td>\n",
" <td>413.03</td>\n",
" <td>416.55</td>\n",
" <td>412.91</td>\n",
" <td>416.40</td>\n",
" </tr>\n",
" <tr>\n",
" <th>767</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>417.16</td>\n",
" <td>413.13</td>\n",
" <td>416.73</td>\n",
" <td>413.55</td>\n",
" <td>417.16</td>\n",
" </tr>\n",
" <tr>\n",
" <th>768</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>414.67</td>\n",
" <td>416.92</td>\n",
" <td>414.82</td>\n",
" <td>417.09</td>\n",
" </tr>\n",
" <tr>\n",
" <th>769</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>416.18</td>\n",
" <td>417.09</td>\n",
" <td>416.43</td>\n",
" <td>417.36</td>\n",
" </tr>\n",
" <tr>\n",
" <th>770</th>\n",
" <td>2022</td>\n",
" <td>01</td>\n",
" <td>44576</td>\n",
" <td>2022.0411</td>\n",
" <td>418.01</td>\n",
" <td>417.94</td>\n",
" <td>417.34</td>\n",
" <td>417.25</td>\n",
" <td>418.01</td>\n",
" <td>417.94</td>\n",
" </tr>\n",
" <tr>\n",
" <th>771</th>\n",
" <td>2022</td>\n",
" <td>02</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>417.41</td>\n",
" <td>418.99</td>\n",
" <td>418.20</td>\n",
" </tr>\n",
" <tr>\n",
" <th>772</th>\n",
" <td>2022</td>\n",
" <td>03</td>\n",
" <td>44635</td>\n",
" <td>2022.2027</td>\n",
" <td>418.45</td>\n",
" <td>416.91</td>\n",
" <td>419.11</td>\n",
" <td>417.55</td>\n",
" <td>418.45</td>\n",
" <td>416.91</td>\n",
" </tr>\n",
" <tr>\n",
" <th>773</th>\n",
" <td>2022</td>\n",
" <td>04</td>\n",
" <td>44666</td>\n",
" <td>2022.2877</td>\n",
" <td>420.02</td>\n",
" <td>417.24</td>\n",
" <td>420.49</td>\n",
" <td>417.70</td>\n",
" <td>420.02</td>\n",
" <td>417.24</td>\n",
" </tr>\n",
" <tr>\n",
" <th>774</th>\n",
" <td>2022</td>\n",
" <td>05</td>\n",
" <td>44696</td>\n",
" <td>2022.3699</td>\n",
" <td>420.77</td>\n",
" <td>417.37</td>\n",
" <td>421.25</td>\n",
" <td>417.85</td>\n",
" <td>420.77</td>\n",
" <td>417.37</td>\n",
" </tr>\n",
" <tr>\n",
" <th>775</th>\n",
" <td>2022</td>\n",
" <td>06</td>\n",
" <td>44727</td>\n",
" <td>2022.4548</td>\n",
" <td>420.68</td>\n",
" <td>418.10</td>\n",
" <td>420.58</td>\n",
" <td>418.02</td>\n",
" <td>420.68</td>\n",
" <td>418.10</td>\n",
" </tr>\n",
" <tr>\n",
" <th>776</th>\n",
" <td>2022</td>\n",
" <td>07</td>\n",
" <td>44757</td>\n",
" <td>2022.5370</td>\n",
" <td>418.68</td>\n",
" <td>417.87</td>\n",
" <td>418.96</td>\n",
" <td>418.19</td>\n",
" <td>418.68</td>\n",
" <td>417.87</td>\n",
" </tr>\n",
" <tr>\n",
" <th>777</th>\n",
" <td>2022</td>\n",
" <td>08</td>\n",
" <td>44788</td>\n",
" <td>2022.6219</td>\n",
" <td>416.76</td>\n",
" <td>418.31</td>\n",
" <td>416.78</td>\n",
" <td>418.37</td>\n",
" <td>416.76</td>\n",
" <td>418.31</td>\n",
" </tr>\n",
" <tr>\n",
" <th>778</th>\n",
" <td>2022</td>\n",
" <td>09</td>\n",
" <td>44819</td>\n",
" <td>2022.7068</td>\n",
" <td>415.41</td>\n",
" <td>418.91</td>\n",
" <td>415.04</td>\n",
" <td>418.56</td>\n",
" <td>415.41</td>\n",
" <td>418.91</td>\n",
" </tr>\n",
" <tr>\n",
" <th>779</th>\n",
" <td>2022</td>\n",
" <td>10</td>\n",
" <td>44849</td>\n",
" <td>2022.7890</td>\n",
" <td>415.31</td>\n",
" <td>418.93</td>\n",
" <td>-99.99</td>\n",
" <td>-99.99</td>\n",
" <td>415.31</td>\n",
" <td>418.93</td>\n",
" </tr>\n",
" <tr>\n",
" <th>780</th>\n",
" <td>2022</td>\n",
" <td>11</td>\n",
" <td>44880</td>\n",
" <td>2022.8740</td>\n",
" <td>-99.99</td>\n",
" <td>-99.99</td>\n",
" <td>-99.99</td>\n",
" <td>-99.99</td>\n",
" <td>-99.99</td>\n",
" <td>-99.99</td>\n",
" </tr>\n",
" <tr>\n",
" <th>781</th>\n",
" <td>2022</td>\n",
" <td>12</td>\n",
" <td>44910</td>\n",
" <td>2022.9562</td>\n",
" <td>-99.99</td>\n",
" <td>-99.99</td>\n",
" <td>-99.99</td>\n",
" <td>-99.99</td>\n",
" <td>-99.99</td>\n",
" <td>-99.99</td>\n",
" </tr>\n",
" </tbody>\n",
"</table>\n",
"<p>780 rows × 10 columns</p>\n",
"</div>"
],
"text/plain": [
" Yr Mn Date Date CO2 seasonally fit \\\n",
"2 1958 01 21200 1958.0411 -99.99 -99.99 -99.99 \n",
"3 1958 02 21231 1958.1260 -99.99 -99.99 -99.99 \n",
"4 1958 03 21259 1958.2027 315.71 314.43 316.20 \n",
"5 1958 04 21290 1958.2877 317.45 315.16 317.30 \n",
"6 1958 05 21320 1958.3699 317.51 314.70 317.88 \n",
"7 1958 06 21351 1958.4548 -99.99 -99.99 317.26 \n",
"8 1958 07 21381 1958.5370 315.87 315.20 315.85 \n",
"9 1958 08 21412 1958.6219 314.93 316.21 313.97 \n",
"10 1958 09 21443 1958.7068 313.21 316.11 312.44 \n",
"11 1958 10 21473 1958.7890 -99.99 -99.99 312.42 \n",
"12 1958 11 21504 1958.8740 313.33 315.21 313.60 \n",
"13 1958 12 21534 1958.9562 314.67 315.44 314.76 \n",
"14 1959 01 21565 1959.0411 315.58 315.52 315.64 \n",
"15 1959 02 21596 1959.1260 316.49 315.84 316.29 \n",
"16 1959 03 21624 1959.2027 316.65 315.37 316.99 \n",
"17 1959 04 21655 1959.2877 317.72 315.41 318.09 \n",
"18 1959 05 21685 1959.3699 318.29 315.47 318.67 \n",
"19 1959 06 21716 1959.4548 318.15 316.01 318.06 \n",
"20 1959 07 21746 1959.5370 316.54 315.87 316.67 \n",
"21 1959 08 21777 1959.6219 314.80 316.09 314.80 \n",
"22 1959 09 21808 1959.7068 313.84 316.74 313.30 \n",
"23 1959 10 21838 1959.7890 313.33 316.34 313.31 \n",
"24 1959 11 21869 1959.8740 314.81 316.70 314.53 \n",
"25 1959 12 21899 1959.9562 315.58 316.35 315.72 \n",
"26 1960 01 21930 1960.0410 316.43 316.37 316.62 \n",
"27 1960 02 21961 1960.1257 316.98 316.33 317.29 \n",
"28 1960 03 21990 1960.2049 317.58 316.27 318.04 \n",
"29 1960 04 22021 1960.2896 319.03 316.70 319.14 \n",
"30 1960 05 22051 1960.3716 320.03 317.20 319.69 \n",
"31 1960 06 22082 1960.4563 319.59 317.46 319.03 \n",
".. ... ... ... ... ... ... ... \n",
"752 2020 07 44027 2020.5383 414.42 413.65 414.75 \n",
"753 2020 08 44058 2020.6230 412.52 414.09 412.60 \n",
"754 2020 09 44089 2020.7077 411.18 414.68 410.91 \n",
"755 2020 10 44119 2020.7896 411.12 414.72 411.02 \n",
"756 2020 11 44150 2020.8743 412.88 415.14 412.56 \n",
"757 2020 12 44180 2020.9563 413.89 414.81 414.07 \n",
"758 2021 01 44211 2021.0411 415.15 415.08 415.23 \n",
"759 2021 02 44242 2021.1260 416.47 415.69 416.12 \n",
"760 2021 03 44270 2021.2027 417.16 415.62 417.04 \n",
"761 2021 04 44301 2021.2877 418.24 415.47 418.44 \n",
"762 2021 05 44331 2021.3699 418.95 415.56 419.21 \n",
"763 2021 06 44362 2021.4548 418.70 416.13 418.55 \n",
"764 2021 07 44392 2021.5370 416.65 415.85 416.94 \n",
"765 2021 08 44423 2021.6219 414.34 415.89 414.76 \n",
"766 2021 09 44454 2021.7068 412.91 416.40 413.03 \n",
"767 2021 10 44484 2021.7890 413.55 417.16 413.13 \n",
"768 2021 11 44515 2021.8740 414.82 417.09 414.67 \n",
"769 2021 12 44545 2021.9562 416.43 417.36 416.18 \n",
"770 2022 01 44576 2022.0411 418.01 417.94 417.34 \n",
"771 2022 02 44607 2022.1260 418.99 418.20 418.20 \n",
"772 2022 03 44635 2022.2027 418.45 416.91 419.11 \n",
"773 2022 04 44666 2022.2877 420.02 417.24 420.49 \n",
"774 2022 05 44696 2022.3699 420.77 417.37 421.25 \n",
"775 2022 06 44727 2022.4548 420.68 418.10 420.58 \n",
"776 2022 07 44757 2022.5370 418.68 417.87 418.96 \n",
"777 2022 08 44788 2022.6219 416.76 418.31 416.78 \n",
"778 2022 09 44819 2022.7068 415.41 418.91 415.04 \n",
"779 2022 10 44849 2022.7890 415.31 418.93 -99.99 \n",
"780 2022 11 44880 2022.8740 -99.99 -99.99 -99.99 \n",
"781 2022 12 44910 2022.9562 -99.99 -99.99 -99.99 \n",
"\n",
" seasonally CO2 seasonally \n",
"2 -99.99 -99.99 -99.99 \n",
"3 -99.99 -99.99 -99.99 \n",
"4 314.91 315.71 314.43 \n",
"5 314.99 317.45 315.16 \n",
"6 315.06 317.51 314.70 \n",
"7 315.14 317.26 315.14 \n",
"8 315.22 315.87 315.20 \n",
"9 315.29 314.93 316.21 \n",
"10 315.35 313.21 316.11 \n",
"11 315.41 312.42 315.41 \n",
"12 315.46 313.33 315.21 \n",
"13 315.51 314.67 315.44 \n",
"14 315.57 315.58 315.52 \n",
"15 315.63 316.49 315.84 \n",
"16 315.69 316.65 315.37 \n",
"17 315.77 317.72 315.41 \n",
"18 315.85 318.29 315.47 \n",
"19 315.94 318.15 316.01 \n",
"20 316.03 316.54 315.87 \n",
"21 316.12 314.80 316.09 \n",
"22 316.22 313.84 316.74 \n",
"23 316.31 313.33 316.34 \n",
"24 316.39 314.81 316.70 \n",
"25 316.47 315.58 316.35 \n",
"26 316.56 316.43 316.37 \n",
"27 316.64 316.98 316.33 \n",
"28 316.71 317.58 316.27 \n",
"29 316.79 319.03 316.70 \n",
"30 316.86 320.03 317.20 \n",
"31 316.93 319.59 317.46 \n",
".. ... ... ... \n",
"752 414.02 414.42 413.65 \n",
"753 414.22 412.52 414.09 \n",
"754 414.42 411.18 414.68 \n",
"755 414.61 411.12 414.72 \n",
"756 414.80 412.88 415.14 \n",
"757 414.97 413.89 414.81 \n",
"758 415.15 415.15 415.08 \n",
"759 415.33 416.47 415.69 \n",
"760 415.48 417.16 415.62 \n",
"761 415.65 418.24 415.47 \n",
"762 415.82 418.95 415.56 \n",
"763 415.99 418.70 416.13 \n",
"764 416.17 416.65 415.85 \n",
"765 416.36 414.34 415.89 \n",
"766 416.55 412.91 416.40 \n",
"767 416.73 413.55 417.16 \n",
"768 416.92 414.82 417.09 \n",
"769 417.09 416.43 417.36 \n",
"770 417.25 418.01 417.94 \n",
"771 417.41 418.99 418.20 \n",
"772 417.55 418.45 416.91 \n",
"773 417.70 420.02 417.24 \n",
"774 417.85 420.77 417.37 \n",
"775 418.02 420.68 418.10 \n",
"776 418.19 418.68 417.87 \n",
"777 418.37 416.76 418.31 \n",
"778 418.56 415.41 418.91 \n",
"779 -99.99 415.31 418.93 \n",
"780 -99.99 -99.99 -99.99 \n",
"781 -99.99 -99.99 -99.99 \n",
"\n",
"[780 rows x 10 columns]"
]
},
"execution_count": 76,
"metadata": {},
"output_type": "execute_result"
}
],
"source": [
"data = raw_data.dropna().copy()\n",
"data = data.iloc[2:]\n",
"data"
]
},
{
"cell_type": "code",
"execution_count": 77,
"metadata": {
"scrolled": false
},
"outputs": [],
"source": [
"data[' CO2'] = data[' CO2'].astype(float)\n",
"data['seasonally'] = data['seasonally'].astype(float)"
]
},
{
"cell_type": "code",
"execution_count": 82,
"metadata": {
"scrolled": true
},
"outputs": [
{
"data": {
"text/plain": [
"<matplotlib.axes._subplots.AxesSubplot at 0x7f0c7b5ef588>"
]
},
"execution_count": 82,
"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": [
"indexNames = data[ data[' CO2'] == (-99.99) ].index\n",
"data.drop(indexNames , inplace=True)\n",
"#sorted_data = data.set_index(' Date').sort_index()\n",
"#sorted_data[' CO2'].plot()\n",
"data[' CO2'].plot(color='b', label='CO2')\n",
"data['seasonally'].plot(color='r', label='seasonally')"
]
},
{
"cell_type": "code",
"execution_count": null,
"metadata": {},
"outputs": [],
"source": []
}
],
"metadata": {
"kernelspec": {
"display_name": "Python 3",
...
...
@@ -16,10 +2053,9 @@
"name": "python",
"nbconvert_exporter": "python",
"pygments_lexer": "ipython3",
"version": "3.6.
3
"
"version": "3.6.
4
"
}
},
"nbformat": 4,
"nbformat_minor": 2
}
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