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module3/exo1/analyse-syndrome-grippal.ipynb
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...@@ -9,7 +9,7 @@ ...@@ -9,7 +9,7 @@
}, },
{ {
"cell_type": "code", "cell_type": "code",
"execution_count": null, "execution_count": 1,
"metadata": {}, "metadata": {},
"outputs": [], "outputs": [],
"source": [ "source": [
...@@ -28,10 +28,8 @@ ...@@ -28,10 +28,8 @@
}, },
{ {
"cell_type": "code", "cell_type": "code",
"execution_count": null, "execution_count": 2,
"metadata": { "metadata": {},
"collapsed": true
},
"outputs": [], "outputs": [],
"source": [ "source": [
"data_url = \"http://www.sentiweb.fr/datasets/incidence-PAY-3.csv\"" "data_url = \"http://www.sentiweb.fr/datasets/incidence-PAY-3.csv\""
...@@ -61,9 +59,976 @@ ...@@ -61,9 +59,976 @@
}, },
{ {
"cell_type": "code", "cell_type": "code",
"execution_count": null, "execution_count": 3,
"metadata": {}, "metadata": {},
"outputs": [], "outputs": [
{
"data": {
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"</style>\n",
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" <th></th>\n",
" <th>week</th>\n",
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" <th>inc</th>\n",
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" <th>inc_up</th>\n",
" <th>inc100</th>\n",
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" <td>104</td>\n",
" <td>91.0</td>\n",
" <td>117.0</td>\n",
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" <th>3</th>\n",
" <td>202339</td>\n",
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" <td>72003</td>\n",
" <td>63452.0</td>\n",
" <td>80554.0</td>\n",
" <td>108</td>\n",
" <td>95.0</td>\n",
" <td>121.0</td>\n",
" <td>FR</td>\n",
" <td>France</td>\n",
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" <tr>\n",
" <th>4</th>\n",
" <td>202338</td>\n",
" <td>3</td>\n",
" <td>63218</td>\n",
" <td>55227.0</td>\n",
" <td>71209.0</td>\n",
" <td>95</td>\n",
" <td>83.0</td>\n",
" <td>107.0</td>\n",
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" <td>France</td>\n",
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" <th>5</th>\n",
" <td>202337</td>\n",
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" <td>49085</td>\n",
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" <td>63.0</td>\n",
" <td>85.0</td>\n",
" <td>FR</td>\n",
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" <th>6</th>\n",
" <td>202336</td>\n",
" <td>3</td>\n",
" <td>38247</td>\n",
" <td>32237.0</td>\n",
" <td>44257.0</td>\n",
" <td>58</td>\n",
" <td>49.0</td>\n",
" <td>67.0</td>\n",
" <td>FR</td>\n",
" <td>France</td>\n",
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" <tr>\n",
" <th>7</th>\n",
" <td>202335</td>\n",
" <td>3</td>\n",
" <td>31695</td>\n",
" <td>26013.0</td>\n",
" <td>37377.0</td>\n",
" <td>48</td>\n",
" <td>39.0</td>\n",
" <td>57.0</td>\n",
" <td>FR</td>\n",
" <td>France</td>\n",
" </tr>\n",
" <tr>\n",
" <th>8</th>\n",
" <td>202334</td>\n",
" <td>3</td>\n",
" <td>26663</td>\n",
" <td>21057.0</td>\n",
" <td>32269.0</td>\n",
" <td>40</td>\n",
" <td>32.0</td>\n",
" <td>48.0</td>\n",
" <td>FR</td>\n",
" <td>France</td>\n",
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" <tr>\n",
" <th>9</th>\n",
" <td>202333</td>\n",
" <td>3</td>\n",
" <td>19144</td>\n",
" <td>13161.0</td>\n",
" <td>25127.0</td>\n",
" <td>29</td>\n",
" <td>20.0</td>\n",
" <td>38.0</td>\n",
" <td>FR</td>\n",
" <td>France</td>\n",
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" <tr>\n",
" <th>10</th>\n",
" <td>202332</td>\n",
" <td>3</td>\n",
" <td>14641</td>\n",
" <td>10285.0</td>\n",
" <td>18997.0</td>\n",
" <td>22</td>\n",
" <td>15.0</td>\n",
" <td>29.0</td>\n",
" <td>FR</td>\n",
" <td>France</td>\n",
" </tr>\n",
" <tr>\n",
" <th>11</th>\n",
" <td>202331</td>\n",
" <td>3</td>\n",
" <td>15286</td>\n",
" <td>10705.0</td>\n",
" <td>19867.0</td>\n",
" <td>23</td>\n",
" <td>16.0</td>\n",
" <td>30.0</td>\n",
" <td>FR</td>\n",
" <td>France</td>\n",
" </tr>\n",
" <tr>\n",
" <th>12</th>\n",
" <td>202330</td>\n",
" <td>3</td>\n",
" <td>13205</td>\n",
" <td>8647.0</td>\n",
" <td>17763.0</td>\n",
" <td>20</td>\n",
" <td>13.0</td>\n",
" <td>27.0</td>\n",
" <td>FR</td>\n",
" <td>France</td>\n",
" </tr>\n",
" <tr>\n",
" <th>13</th>\n",
" <td>202329</td>\n",
" <td>3</td>\n",
" <td>11122</td>\n",
" <td>7113.0</td>\n",
" <td>15131.0</td>\n",
" <td>17</td>\n",
" <td>11.0</td>\n",
" <td>23.0</td>\n",
" <td>FR</td>\n",
" <td>France</td>\n",
" </tr>\n",
" <tr>\n",
" <th>14</th>\n",
" <td>202328</td>\n",
" <td>3</td>\n",
" <td>9179</td>\n",
" <td>5703.0</td>\n",
" <td>12655.0</td>\n",
" <td>14</td>\n",
" <td>9.0</td>\n",
" <td>19.0</td>\n",
" <td>FR</td>\n",
" <td>France</td>\n",
" </tr>\n",
" <tr>\n",
" <th>15</th>\n",
" <td>202327</td>\n",
" <td>3</td>\n",
" <td>8999</td>\n",
" <td>5763.0</td>\n",
" <td>12235.0</td>\n",
" <td>14</td>\n",
" <td>9.0</td>\n",
" <td>19.0</td>\n",
" <td>FR</td>\n",
" <td>France</td>\n",
" </tr>\n",
" <tr>\n",
" <th>16</th>\n",
" <td>202326</td>\n",
" <td>3</td>\n",
" <td>9023</td>\n",
" <td>5934.0</td>\n",
" <td>12112.0</td>\n",
" <td>14</td>\n",
" <td>9.0</td>\n",
" <td>19.0</td>\n",
" <td>FR</td>\n",
" <td>France</td>\n",
" </tr>\n",
" <tr>\n",
" <th>17</th>\n",
" <td>202325</td>\n",
" <td>3</td>\n",
" <td>10090</td>\n",
" <td>6739.0</td>\n",
" <td>13441.0</td>\n",
" <td>15</td>\n",
" <td>10.0</td>\n",
" <td>20.0</td>\n",
" <td>FR</td>\n",
" <td>France</td>\n",
" </tr>\n",
" <tr>\n",
" <th>18</th>\n",
" <td>202324</td>\n",
" <td>3</td>\n",
" <td>11308</td>\n",
" <td>7639.0</td>\n",
" <td>14977.0</td>\n",
" <td>17</td>\n",
" <td>11.0</td>\n",
" <td>23.0</td>\n",
" <td>FR</td>\n",
" <td>France</td>\n",
" </tr>\n",
" <tr>\n",
" <th>19</th>\n",
" <td>202323</td>\n",
" <td>3</td>\n",
" <td>14300</td>\n",
" <td>10661.0</td>\n",
" <td>17939.0</td>\n",
" <td>22</td>\n",
" <td>17.0</td>\n",
" <td>27.0</td>\n",
" <td>FR</td>\n",
" <td>France</td>\n",
" </tr>\n",
" <tr>\n",
" <th>20</th>\n",
" <td>202322</td>\n",
" <td>3</td>\n",
" <td>18303</td>\n",
" <td>13822.0</td>\n",
" <td>22784.0</td>\n",
" <td>28</td>\n",
" <td>21.0</td>\n",
" <td>35.0</td>\n",
" <td>FR</td>\n",
" <td>France</td>\n",
" </tr>\n",
" <tr>\n",
" <th>21</th>\n",
" <td>202321</td>\n",
" <td>3</td>\n",
" <td>16460</td>\n",
" <td>12188.0</td>\n",
" <td>20732.0</td>\n",
" <td>25</td>\n",
" <td>19.0</td>\n",
" <td>31.0</td>\n",
" <td>FR</td>\n",
" <td>France</td>\n",
" </tr>\n",
" <tr>\n",
" <th>22</th>\n",
" <td>202320</td>\n",
" <td>3</td>\n",
" <td>16162</td>\n",
" <td>11963.0</td>\n",
" <td>20361.0</td>\n",
" <td>24</td>\n",
" <td>18.0</td>\n",
" <td>30.0</td>\n",
" <td>FR</td>\n",
" <td>France</td>\n",
" </tr>\n",
" <tr>\n",
" <th>23</th>\n",
" <td>202319</td>\n",
" <td>3</td>\n",
" <td>16901</td>\n",
" <td>12577.0</td>\n",
" <td>21225.0</td>\n",
" <td>25</td>\n",
" <td>18.0</td>\n",
" <td>32.0</td>\n",
" <td>FR</td>\n",
" <td>France</td>\n",
" </tr>\n",
" <tr>\n",
" <th>24</th>\n",
" <td>202318</td>\n",
" <td>3</td>\n",
" <td>19929</td>\n",
" <td>15402.0</td>\n",
" <td>24456.0</td>\n",
" <td>30</td>\n",
" <td>23.0</td>\n",
" <td>37.0</td>\n",
" <td>FR</td>\n",
" <td>France</td>\n",
" </tr>\n",
" <tr>\n",
" <th>25</th>\n",
" <td>202317</td>\n",
" <td>3</td>\n",
" <td>27007</td>\n",
" <td>21779.0</td>\n",
" <td>32235.0</td>\n",
" <td>41</td>\n",
" <td>33.0</td>\n",
" <td>49.0</td>\n",
" <td>FR</td>\n",
" <td>France</td>\n",
" </tr>\n",
" <tr>\n",
" <th>26</th>\n",
" <td>202316</td>\n",
" <td>3</td>\n",
" <td>27875</td>\n",
" <td>22767.0</td>\n",
" <td>32983.0</td>\n",
" <td>42</td>\n",
" <td>34.0</td>\n",
" <td>50.0</td>\n",
" <td>FR</td>\n",
" <td>France</td>\n",
" </tr>\n",
" <tr>\n",
" <th>27</th>\n",
" <td>202315</td>\n",
" <td>3</td>\n",
" <td>37455</td>\n",
" <td>30993.0</td>\n",
" <td>43917.0</td>\n",
" <td>56</td>\n",
" <td>46.0</td>\n",
" <td>66.0</td>\n",
" <td>FR</td>\n",
" <td>France</td>\n",
" </tr>\n",
" <tr>\n",
" <th>28</th>\n",
" <td>202314</td>\n",
" <td>3</td>\n",
" <td>48060</td>\n",
" <td>40671.0</td>\n",
" <td>55449.0</td>\n",
" <td>72</td>\n",
" <td>61.0</td>\n",
" <td>83.0</td>\n",
" <td>FR</td>\n",
" <td>France</td>\n",
" </tr>\n",
" <tr>\n",
" <th>29</th>\n",
" <td>202313</td>\n",
" <td>3</td>\n",
" <td>64859</td>\n",
" <td>56800.0</td>\n",
" <td>72918.0</td>\n",
" <td>98</td>\n",
" <td>86.0</td>\n",
" <td>110.0</td>\n",
" <td>FR</td>\n",
" <td>France</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>2004</th>\n",
" <td>198521</td>\n",
" <td>3</td>\n",
" <td>26096</td>\n",
" <td>19621.0</td>\n",
" <td>32571.0</td>\n",
" <td>47</td>\n",
" <td>35.0</td>\n",
" <td>59.0</td>\n",
" <td>FR</td>\n",
" <td>France</td>\n",
" </tr>\n",
" <tr>\n",
" <th>2005</th>\n",
" <td>198520</td>\n",
" <td>3</td>\n",
" <td>27896</td>\n",
" <td>20885.0</td>\n",
" <td>34907.0</td>\n",
" <td>51</td>\n",
" <td>38.0</td>\n",
" <td>64.0</td>\n",
" <td>FR</td>\n",
" <td>France</td>\n",
" </tr>\n",
" <tr>\n",
" <th>2006</th>\n",
" <td>198519</td>\n",
" <td>3</td>\n",
" <td>43154</td>\n",
" <td>32821.0</td>\n",
" <td>53487.0</td>\n",
" <td>78</td>\n",
" <td>59.0</td>\n",
" <td>97.0</td>\n",
" <td>FR</td>\n",
" <td>France</td>\n",
" </tr>\n",
" <tr>\n",
" <th>2007</th>\n",
" <td>198518</td>\n",
" <td>3</td>\n",
" <td>40555</td>\n",
" <td>29935.0</td>\n",
" <td>51175.0</td>\n",
" <td>74</td>\n",
" <td>55.0</td>\n",
" <td>93.0</td>\n",
" <td>FR</td>\n",
" <td>France</td>\n",
" </tr>\n",
" <tr>\n",
" <th>2008</th>\n",
" <td>198517</td>\n",
" <td>3</td>\n",
" <td>34053</td>\n",
" <td>24366.0</td>\n",
" <td>43740.0</td>\n",
" <td>62</td>\n",
" <td>44.0</td>\n",
" <td>80.0</td>\n",
" <td>FR</td>\n",
" <td>France</td>\n",
" </tr>\n",
" <tr>\n",
" <th>2009</th>\n",
" <td>198516</td>\n",
" <td>3</td>\n",
" <td>50362</td>\n",
" <td>36451.0</td>\n",
" <td>64273.0</td>\n",
" <td>91</td>\n",
" <td>66.0</td>\n",
" <td>116.0</td>\n",
" <td>FR</td>\n",
" <td>France</td>\n",
" </tr>\n",
" <tr>\n",
" <th>2010</th>\n",
" <td>198515</td>\n",
" <td>3</td>\n",
" <td>63881</td>\n",
" <td>45538.0</td>\n",
" <td>82224.0</td>\n",
" <td>116</td>\n",
" <td>83.0</td>\n",
" <td>149.0</td>\n",
" <td>FR</td>\n",
" <td>France</td>\n",
" </tr>\n",
" <tr>\n",
" <th>2011</th>\n",
" <td>198514</td>\n",
" <td>3</td>\n",
" <td>134545</td>\n",
" <td>114400.0</td>\n",
" <td>154690.0</td>\n",
" <td>244</td>\n",
" <td>207.0</td>\n",
" <td>281.0</td>\n",
" <td>FR</td>\n",
" <td>France</td>\n",
" </tr>\n",
" <tr>\n",
" <th>2012</th>\n",
" <td>198513</td>\n",
" <td>3</td>\n",
" <td>197206</td>\n",
" <td>176080.0</td>\n",
" <td>218332.0</td>\n",
" <td>357</td>\n",
" <td>319.0</td>\n",
" <td>395.0</td>\n",
" <td>FR</td>\n",
" <td>France</td>\n",
" </tr>\n",
" <tr>\n",
" <th>2013</th>\n",
" <td>198512</td>\n",
" <td>3</td>\n",
" <td>245240</td>\n",
" <td>223304.0</td>\n",
" <td>267176.0</td>\n",
" <td>445</td>\n",
" <td>405.0</td>\n",
" <td>485.0</td>\n",
" <td>FR</td>\n",
" <td>France</td>\n",
" </tr>\n",
" <tr>\n",
" <th>2014</th>\n",
" <td>198511</td>\n",
" <td>3</td>\n",
" <td>276205</td>\n",
" <td>252399.0</td>\n",
" <td>300011.0</td>\n",
" <td>501</td>\n",
" <td>458.0</td>\n",
" <td>544.0</td>\n",
" <td>FR</td>\n",
" <td>France</td>\n",
" </tr>\n",
" <tr>\n",
" <th>2015</th>\n",
" <td>198510</td>\n",
" <td>3</td>\n",
" <td>353231</td>\n",
" <td>326279.0</td>\n",
" <td>380183.0</td>\n",
" <td>640</td>\n",
" <td>591.0</td>\n",
" <td>689.0</td>\n",
" <td>FR</td>\n",
" <td>France</td>\n",
" </tr>\n",
" <tr>\n",
" <th>2016</th>\n",
" <td>198509</td>\n",
" <td>3</td>\n",
" <td>369895</td>\n",
" <td>341109.0</td>\n",
" <td>398681.0</td>\n",
" <td>670</td>\n",
" <td>618.0</td>\n",
" <td>722.0</td>\n",
" <td>FR</td>\n",
" <td>France</td>\n",
" </tr>\n",
" <tr>\n",
" <th>2017</th>\n",
" <td>198508</td>\n",
" <td>3</td>\n",
" <td>389886</td>\n",
" <td>359529.0</td>\n",
" <td>420243.0</td>\n",
" <td>707</td>\n",
" <td>652.0</td>\n",
" <td>762.0</td>\n",
" <td>FR</td>\n",
" <td>France</td>\n",
" </tr>\n",
" <tr>\n",
" <th>2018</th>\n",
" <td>198507</td>\n",
" <td>3</td>\n",
" <td>471852</td>\n",
" <td>432599.0</td>\n",
" <td>511105.0</td>\n",
" <td>855</td>\n",
" <td>784.0</td>\n",
" <td>926.0</td>\n",
" <td>FR</td>\n",
" <td>France</td>\n",
" </tr>\n",
" <tr>\n",
" <th>2019</th>\n",
" <td>198506</td>\n",
" <td>3</td>\n",
" <td>565825</td>\n",
" <td>518011.0</td>\n",
" <td>613639.0</td>\n",
" <td>1026</td>\n",
" <td>939.0</td>\n",
" <td>1113.0</td>\n",
" <td>FR</td>\n",
" <td>France</td>\n",
" </tr>\n",
" <tr>\n",
" <th>2020</th>\n",
" <td>198505</td>\n",
" <td>3</td>\n",
" <td>637302</td>\n",
" <td>592795.0</td>\n",
" <td>681809.0</td>\n",
" <td>1155</td>\n",
" <td>1074.0</td>\n",
" <td>1236.0</td>\n",
" <td>FR</td>\n",
" <td>France</td>\n",
" </tr>\n",
" <tr>\n",
" <th>2021</th>\n",
" <td>198504</td>\n",
" <td>3</td>\n",
" <td>424937</td>\n",
" <td>390794.0</td>\n",
" <td>459080.0</td>\n",
" <td>770</td>\n",
" <td>708.0</td>\n",
" <td>832.0</td>\n",
" <td>FR</td>\n",
" <td>France</td>\n",
" </tr>\n",
" <tr>\n",
" <th>2022</th>\n",
" <td>198503</td>\n",
" <td>3</td>\n",
" <td>213901</td>\n",
" <td>174689.0</td>\n",
" <td>253113.0</td>\n",
" <td>388</td>\n",
" <td>317.0</td>\n",
" <td>459.0</td>\n",
" <td>FR</td>\n",
" <td>France</td>\n",
" </tr>\n",
" <tr>\n",
" <th>2023</th>\n",
" <td>198502</td>\n",
" <td>3</td>\n",
" <td>97586</td>\n",
" <td>80949.0</td>\n",
" <td>114223.0</td>\n",
" <td>177</td>\n",
" <td>147.0</td>\n",
" <td>207.0</td>\n",
" <td>FR</td>\n",
" <td>France</td>\n",
" </tr>\n",
" <tr>\n",
" <th>2024</th>\n",
" <td>198501</td>\n",
" <td>3</td>\n",
" <td>85489</td>\n",
" <td>65918.0</td>\n",
" <td>105060.0</td>\n",
" <td>155</td>\n",
" <td>120.0</td>\n",
" <td>190.0</td>\n",
" <td>FR</td>\n",
" <td>France</td>\n",
" </tr>\n",
" <tr>\n",
" <th>2025</th>\n",
" <td>198452</td>\n",
" <td>3</td>\n",
" <td>84830</td>\n",
" <td>60602.0</td>\n",
" <td>109058.0</td>\n",
" <td>154</td>\n",
" <td>110.0</td>\n",
" <td>198.0</td>\n",
" <td>FR</td>\n",
" <td>France</td>\n",
" </tr>\n",
" <tr>\n",
" <th>2026</th>\n",
" <td>198451</td>\n",
" <td>3</td>\n",
" <td>101726</td>\n",
" <td>80242.0</td>\n",
" <td>123210.0</td>\n",
" <td>185</td>\n",
" <td>146.0</td>\n",
" <td>224.0</td>\n",
" <td>FR</td>\n",
" <td>France</td>\n",
" </tr>\n",
" <tr>\n",
" <th>2027</th>\n",
" <td>198450</td>\n",
" <td>3</td>\n",
" <td>123680</td>\n",
" <td>101401.0</td>\n",
" <td>145959.0</td>\n",
" <td>225</td>\n",
" <td>184.0</td>\n",
" <td>266.0</td>\n",
" <td>FR</td>\n",
" <td>France</td>\n",
" </tr>\n",
" <tr>\n",
" <th>2028</th>\n",
" <td>198449</td>\n",
" <td>3</td>\n",
" <td>101073</td>\n",
" <td>81684.0</td>\n",
" <td>120462.0</td>\n",
" <td>184</td>\n",
" <td>149.0</td>\n",
" <td>219.0</td>\n",
" <td>FR</td>\n",
" <td>France</td>\n",
" </tr>\n",
" <tr>\n",
" <th>2029</th>\n",
" <td>198448</td>\n",
" <td>3</td>\n",
" <td>78620</td>\n",
" <td>60634.0</td>\n",
" <td>96606.0</td>\n",
" <td>143</td>\n",
" <td>110.0</td>\n",
" <td>176.0</td>\n",
" <td>FR</td>\n",
" <td>France</td>\n",
" </tr>\n",
" <tr>\n",
" <th>2030</th>\n",
" <td>198447</td>\n",
" <td>3</td>\n",
" <td>72029</td>\n",
" <td>54274.0</td>\n",
" <td>89784.0</td>\n",
" <td>131</td>\n",
" <td>99.0</td>\n",
" <td>163.0</td>\n",
" <td>FR</td>\n",
" <td>France</td>\n",
" </tr>\n",
" <tr>\n",
" <th>2031</th>\n",
" <td>198446</td>\n",
" <td>3</td>\n",
" <td>87330</td>\n",
" <td>67686.0</td>\n",
" <td>106974.0</td>\n",
" <td>159</td>\n",
" <td>123.0</td>\n",
" <td>195.0</td>\n",
" <td>FR</td>\n",
" <td>France</td>\n",
" </tr>\n",
" <tr>\n",
" <th>2032</th>\n",
" <td>198445</td>\n",
" <td>3</td>\n",
" <td>135223</td>\n",
" <td>101414.0</td>\n",
" <td>169032.0</td>\n",
" <td>246</td>\n",
" <td>184.0</td>\n",
" <td>308.0</td>\n",
" <td>FR</td>\n",
" <td>France</td>\n",
" </tr>\n",
" <tr>\n",
" <th>2033</th>\n",
" <td>198444</td>\n",
" <td>3</td>\n",
" <td>68422</td>\n",
" <td>20056.0</td>\n",
" <td>116788.0</td>\n",
" <td>125</td>\n",
" <td>37.0</td>\n",
" <td>213.0</td>\n",
" <td>FR</td>\n",
" <td>France</td>\n",
" </tr>\n",
" </tbody>\n",
"</table>\n",
"<p>2034 rows × 10 columns</p>\n",
"</div>"
],
"text/plain": [
" week indicator inc inc_low inc_up inc100 inc100_low \\\n",
"0 202342 3 67331 57544.0 77118.0 101 86.0 \n",
"1 202341 3 59275 51833.0 66717.0 89 78.0 \n",
"2 202340 3 68894 60069.0 77719.0 104 91.0 \n",
"3 202339 3 72003 63452.0 80554.0 108 95.0 \n",
"4 202338 3 63218 55227.0 71209.0 95 83.0 \n",
"5 202337 3 49085 42079.0 56091.0 74 63.0 \n",
"6 202336 3 38247 32237.0 44257.0 58 49.0 \n",
"7 202335 3 31695 26013.0 37377.0 48 39.0 \n",
"8 202334 3 26663 21057.0 32269.0 40 32.0 \n",
"9 202333 3 19144 13161.0 25127.0 29 20.0 \n",
"10 202332 3 14641 10285.0 18997.0 22 15.0 \n",
"11 202331 3 15286 10705.0 19867.0 23 16.0 \n",
"12 202330 3 13205 8647.0 17763.0 20 13.0 \n",
"13 202329 3 11122 7113.0 15131.0 17 11.0 \n",
"14 202328 3 9179 5703.0 12655.0 14 9.0 \n",
"15 202327 3 8999 5763.0 12235.0 14 9.0 \n",
"16 202326 3 9023 5934.0 12112.0 14 9.0 \n",
"17 202325 3 10090 6739.0 13441.0 15 10.0 \n",
"18 202324 3 11308 7639.0 14977.0 17 11.0 \n",
"19 202323 3 14300 10661.0 17939.0 22 17.0 \n",
"20 202322 3 18303 13822.0 22784.0 28 21.0 \n",
"21 202321 3 16460 12188.0 20732.0 25 19.0 \n",
"22 202320 3 16162 11963.0 20361.0 24 18.0 \n",
"23 202319 3 16901 12577.0 21225.0 25 18.0 \n",
"24 202318 3 19929 15402.0 24456.0 30 23.0 \n",
"25 202317 3 27007 21779.0 32235.0 41 33.0 \n",
"26 202316 3 27875 22767.0 32983.0 42 34.0 \n",
"27 202315 3 37455 30993.0 43917.0 56 46.0 \n",
"28 202314 3 48060 40671.0 55449.0 72 61.0 \n",
"29 202313 3 64859 56800.0 72918.0 98 86.0 \n",
"... ... ... ... ... ... ... ... \n",
"2004 198521 3 26096 19621.0 32571.0 47 35.0 \n",
"2005 198520 3 27896 20885.0 34907.0 51 38.0 \n",
"2006 198519 3 43154 32821.0 53487.0 78 59.0 \n",
"2007 198518 3 40555 29935.0 51175.0 74 55.0 \n",
"2008 198517 3 34053 24366.0 43740.0 62 44.0 \n",
"2009 198516 3 50362 36451.0 64273.0 91 66.0 \n",
"2010 198515 3 63881 45538.0 82224.0 116 83.0 \n",
"2011 198514 3 134545 114400.0 154690.0 244 207.0 \n",
"2012 198513 3 197206 176080.0 218332.0 357 319.0 \n",
"2013 198512 3 245240 223304.0 267176.0 445 405.0 \n",
"2014 198511 3 276205 252399.0 300011.0 501 458.0 \n",
"2015 198510 3 353231 326279.0 380183.0 640 591.0 \n",
"2016 198509 3 369895 341109.0 398681.0 670 618.0 \n",
"2017 198508 3 389886 359529.0 420243.0 707 652.0 \n",
"2018 198507 3 471852 432599.0 511105.0 855 784.0 \n",
"2019 198506 3 565825 518011.0 613639.0 1026 939.0 \n",
"2020 198505 3 637302 592795.0 681809.0 1155 1074.0 \n",
"2021 198504 3 424937 390794.0 459080.0 770 708.0 \n",
"2022 198503 3 213901 174689.0 253113.0 388 317.0 \n",
"2023 198502 3 97586 80949.0 114223.0 177 147.0 \n",
"2024 198501 3 85489 65918.0 105060.0 155 120.0 \n",
"2025 198452 3 84830 60602.0 109058.0 154 110.0 \n",
"2026 198451 3 101726 80242.0 123210.0 185 146.0 \n",
"2027 198450 3 123680 101401.0 145959.0 225 184.0 \n",
"2028 198449 3 101073 81684.0 120462.0 184 149.0 \n",
"2029 198448 3 78620 60634.0 96606.0 143 110.0 \n",
"2030 198447 3 72029 54274.0 89784.0 131 99.0 \n",
"2031 198446 3 87330 67686.0 106974.0 159 123.0 \n",
"2032 198445 3 135223 101414.0 169032.0 246 184.0 \n",
"2033 198444 3 68422 20056.0 116788.0 125 37.0 \n",
"\n",
" inc100_up geo_insee geo_name \n",
"0 116.0 FR France \n",
"1 100.0 FR France \n",
"2 117.0 FR France \n",
"3 121.0 FR France \n",
"4 107.0 FR France \n",
"5 85.0 FR France \n",
"6 67.0 FR France \n",
"7 57.0 FR France \n",
"8 48.0 FR France \n",
"9 38.0 FR France \n",
"10 29.0 FR France \n",
"11 30.0 FR France \n",
"12 27.0 FR France \n",
"13 23.0 FR France \n",
"14 19.0 FR France \n",
"15 19.0 FR France \n",
"16 19.0 FR France \n",
"17 20.0 FR France \n",
"18 23.0 FR France \n",
"19 27.0 FR France \n",
"20 35.0 FR France \n",
"21 31.0 FR France \n",
"22 30.0 FR France \n",
"23 32.0 FR France \n",
"24 37.0 FR France \n",
"25 49.0 FR France \n",
"26 50.0 FR France \n",
"27 66.0 FR France \n",
"28 83.0 FR France \n",
"29 110.0 FR France \n",
"... ... ... ... \n",
"2004 59.0 FR France \n",
"2005 64.0 FR France \n",
"2006 97.0 FR France \n",
"2007 93.0 FR France \n",
"2008 80.0 FR France \n",
"2009 116.0 FR France \n",
"2010 149.0 FR France \n",
"2011 281.0 FR France \n",
"2012 395.0 FR France \n",
"2013 485.0 FR France \n",
"2014 544.0 FR France \n",
"2015 689.0 FR France \n",
"2016 722.0 FR France \n",
"2017 762.0 FR France \n",
"2018 926.0 FR France \n",
"2019 1113.0 FR France \n",
"2020 1236.0 FR France \n",
"2021 832.0 FR France \n",
"2022 459.0 FR France \n",
"2023 207.0 FR France \n",
"2024 190.0 FR France \n",
"2025 198.0 FR France \n",
"2026 224.0 FR France \n",
"2027 266.0 FR France \n",
"2028 219.0 FR France \n",
"2029 176.0 FR France \n",
"2030 163.0 FR France \n",
"2031 195.0 FR France \n",
"2032 308.0 FR France \n",
"2033 213.0 FR France \n",
"\n",
"[2034 rows x 10 columns]"
]
},
"execution_count": 3,
"metadata": {},
"output_type": "execute_result"
}
],
"source": [ "source": [
"raw_data = pd.read_csv(data_url, skiprows=1)\n", "raw_data = pd.read_csv(data_url, skiprows=1)\n",
"raw_data" "raw_data"
...@@ -78,9 +1043,73 @@ ...@@ -78,9 +1043,73 @@
}, },
{ {
"cell_type": "code", "cell_type": "code",
"execution_count": null, "execution_count": 4,
"metadata": {}, "metadata": {},
"outputs": [], "outputs": [
{
"data": {
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" <thead>\n",
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" <th></th>\n",
" <th>week</th>\n",
" <th>indicator</th>\n",
" <th>inc</th>\n",
" <th>inc_low</th>\n",
" <th>inc_up</th>\n",
" <th>inc100</th>\n",
" <th>inc100_low</th>\n",
" <th>inc100_up</th>\n",
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" <th>geo_name</th>\n",
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" <tr>\n",
" <th>1797</th>\n",
" <td>198919</td>\n",
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" <td>NaN</td>\n",
" <td>-</td>\n",
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],
"text/plain": [
" week indicator inc inc_low inc_up inc100 inc100_low inc100_up \\\n",
"1797 198919 3 - NaN NaN - NaN NaN \n",
"\n",
" geo_insee geo_name \n",
"1797 FR France "
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},
"execution_count": 4,
"metadata": {},
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"source": [ "source": [
"raw_data[raw_data.isnull().any(axis=1)]" "raw_data[raw_data.isnull().any(axis=1)]"
] ]
...@@ -94,9 +1123,976 @@ ...@@ -94,9 +1123,976 @@
}, },
{ {
"cell_type": "code", "cell_type": "code",
"execution_count": null, "execution_count": 5,
"metadata": {}, "metadata": {},
"outputs": [], "outputs": [
{
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" <thead>\n",
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" <th></th>\n",
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" <th>indicator</th>\n",
" <th>inc</th>\n",
" <th>inc_low</th>\n",
" <th>inc_up</th>\n",
" <th>inc100</th>\n",
" <th>inc100_low</th>\n",
" <th>inc100_up</th>\n",
" <th>geo_insee</th>\n",
" <th>geo_name</th>\n",
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" <tbody>\n",
" <tr>\n",
" <th>0</th>\n",
" <td>202342</td>\n",
" <td>3</td>\n",
" <td>67331</td>\n",
" <td>57544.0</td>\n",
" <td>77118.0</td>\n",
" <td>101</td>\n",
" <td>86.0</td>\n",
" <td>116.0</td>\n",
" <td>FR</td>\n",
" <td>France</td>\n",
" </tr>\n",
" <tr>\n",
" <th>1</th>\n",
" <td>202341</td>\n",
" <td>3</td>\n",
" <td>59275</td>\n",
" <td>51833.0</td>\n",
" <td>66717.0</td>\n",
" <td>89</td>\n",
" <td>78.0</td>\n",
" <td>100.0</td>\n",
" <td>FR</td>\n",
" <td>France</td>\n",
" </tr>\n",
" <tr>\n",
" <th>2</th>\n",
" <td>202340</td>\n",
" <td>3</td>\n",
" <td>68894</td>\n",
" <td>60069.0</td>\n",
" <td>77719.0</td>\n",
" <td>104</td>\n",
" <td>91.0</td>\n",
" <td>117.0</td>\n",
" <td>FR</td>\n",
" <td>France</td>\n",
" </tr>\n",
" <tr>\n",
" <th>3</th>\n",
" <td>202339</td>\n",
" <td>3</td>\n",
" <td>72003</td>\n",
" <td>63452.0</td>\n",
" <td>80554.0</td>\n",
" <td>108</td>\n",
" <td>95.0</td>\n",
" <td>121.0</td>\n",
" <td>FR</td>\n",
" <td>France</td>\n",
" </tr>\n",
" <tr>\n",
" <th>4</th>\n",
" <td>202338</td>\n",
" <td>3</td>\n",
" <td>63218</td>\n",
" <td>55227.0</td>\n",
" <td>71209.0</td>\n",
" <td>95</td>\n",
" <td>83.0</td>\n",
" <td>107.0</td>\n",
" <td>FR</td>\n",
" <td>France</td>\n",
" </tr>\n",
" <tr>\n",
" <th>5</th>\n",
" <td>202337</td>\n",
" <td>3</td>\n",
" <td>49085</td>\n",
" <td>42079.0</td>\n",
" <td>56091.0</td>\n",
" <td>74</td>\n",
" <td>63.0</td>\n",
" <td>85.0</td>\n",
" <td>FR</td>\n",
" <td>France</td>\n",
" </tr>\n",
" <tr>\n",
" <th>6</th>\n",
" <td>202336</td>\n",
" <td>3</td>\n",
" <td>38247</td>\n",
" <td>32237.0</td>\n",
" <td>44257.0</td>\n",
" <td>58</td>\n",
" <td>49.0</td>\n",
" <td>67.0</td>\n",
" <td>FR</td>\n",
" <td>France</td>\n",
" </tr>\n",
" <tr>\n",
" <th>7</th>\n",
" <td>202335</td>\n",
" <td>3</td>\n",
" <td>31695</td>\n",
" <td>26013.0</td>\n",
" <td>37377.0</td>\n",
" <td>48</td>\n",
" <td>39.0</td>\n",
" <td>57.0</td>\n",
" <td>FR</td>\n",
" <td>France</td>\n",
" </tr>\n",
" <tr>\n",
" <th>8</th>\n",
" <td>202334</td>\n",
" <td>3</td>\n",
" <td>26663</td>\n",
" <td>21057.0</td>\n",
" <td>32269.0</td>\n",
" <td>40</td>\n",
" <td>32.0</td>\n",
" <td>48.0</td>\n",
" <td>FR</td>\n",
" <td>France</td>\n",
" </tr>\n",
" <tr>\n",
" <th>9</th>\n",
" <td>202333</td>\n",
" <td>3</td>\n",
" <td>19144</td>\n",
" <td>13161.0</td>\n",
" <td>25127.0</td>\n",
" <td>29</td>\n",
" <td>20.0</td>\n",
" <td>38.0</td>\n",
" <td>FR</td>\n",
" <td>France</td>\n",
" </tr>\n",
" <tr>\n",
" <th>10</th>\n",
" <td>202332</td>\n",
" <td>3</td>\n",
" <td>14641</td>\n",
" <td>10285.0</td>\n",
" <td>18997.0</td>\n",
" <td>22</td>\n",
" <td>15.0</td>\n",
" <td>29.0</td>\n",
" <td>FR</td>\n",
" <td>France</td>\n",
" </tr>\n",
" <tr>\n",
" <th>11</th>\n",
" <td>202331</td>\n",
" <td>3</td>\n",
" <td>15286</td>\n",
" <td>10705.0</td>\n",
" <td>19867.0</td>\n",
" <td>23</td>\n",
" <td>16.0</td>\n",
" <td>30.0</td>\n",
" <td>FR</td>\n",
" <td>France</td>\n",
" </tr>\n",
" <tr>\n",
" <th>12</th>\n",
" <td>202330</td>\n",
" <td>3</td>\n",
" <td>13205</td>\n",
" <td>8647.0</td>\n",
" <td>17763.0</td>\n",
" <td>20</td>\n",
" <td>13.0</td>\n",
" <td>27.0</td>\n",
" <td>FR</td>\n",
" <td>France</td>\n",
" </tr>\n",
" <tr>\n",
" <th>13</th>\n",
" <td>202329</td>\n",
" <td>3</td>\n",
" <td>11122</td>\n",
" <td>7113.0</td>\n",
" <td>15131.0</td>\n",
" <td>17</td>\n",
" <td>11.0</td>\n",
" <td>23.0</td>\n",
" <td>FR</td>\n",
" <td>France</td>\n",
" </tr>\n",
" <tr>\n",
" <th>14</th>\n",
" <td>202328</td>\n",
" <td>3</td>\n",
" <td>9179</td>\n",
" <td>5703.0</td>\n",
" <td>12655.0</td>\n",
" <td>14</td>\n",
" <td>9.0</td>\n",
" <td>19.0</td>\n",
" <td>FR</td>\n",
" <td>France</td>\n",
" </tr>\n",
" <tr>\n",
" <th>15</th>\n",
" <td>202327</td>\n",
" <td>3</td>\n",
" <td>8999</td>\n",
" <td>5763.0</td>\n",
" <td>12235.0</td>\n",
" <td>14</td>\n",
" <td>9.0</td>\n",
" <td>19.0</td>\n",
" <td>FR</td>\n",
" <td>France</td>\n",
" </tr>\n",
" <tr>\n",
" <th>16</th>\n",
" <td>202326</td>\n",
" <td>3</td>\n",
" <td>9023</td>\n",
" <td>5934.0</td>\n",
" <td>12112.0</td>\n",
" <td>14</td>\n",
" <td>9.0</td>\n",
" <td>19.0</td>\n",
" <td>FR</td>\n",
" <td>France</td>\n",
" </tr>\n",
" <tr>\n",
" <th>17</th>\n",
" <td>202325</td>\n",
" <td>3</td>\n",
" <td>10090</td>\n",
" <td>6739.0</td>\n",
" <td>13441.0</td>\n",
" <td>15</td>\n",
" <td>10.0</td>\n",
" <td>20.0</td>\n",
" <td>FR</td>\n",
" <td>France</td>\n",
" </tr>\n",
" <tr>\n",
" <th>18</th>\n",
" <td>202324</td>\n",
" <td>3</td>\n",
" <td>11308</td>\n",
" <td>7639.0</td>\n",
" <td>14977.0</td>\n",
" <td>17</td>\n",
" <td>11.0</td>\n",
" <td>23.0</td>\n",
" <td>FR</td>\n",
" <td>France</td>\n",
" </tr>\n",
" <tr>\n",
" <th>19</th>\n",
" <td>202323</td>\n",
" <td>3</td>\n",
" <td>14300</td>\n",
" <td>10661.0</td>\n",
" <td>17939.0</td>\n",
" <td>22</td>\n",
" <td>17.0</td>\n",
" <td>27.0</td>\n",
" <td>FR</td>\n",
" <td>France</td>\n",
" </tr>\n",
" <tr>\n",
" <th>20</th>\n",
" <td>202322</td>\n",
" <td>3</td>\n",
" <td>18303</td>\n",
" <td>13822.0</td>\n",
" <td>22784.0</td>\n",
" <td>28</td>\n",
" <td>21.0</td>\n",
" <td>35.0</td>\n",
" <td>FR</td>\n",
" <td>France</td>\n",
" </tr>\n",
" <tr>\n",
" <th>21</th>\n",
" <td>202321</td>\n",
" <td>3</td>\n",
" <td>16460</td>\n",
" <td>12188.0</td>\n",
" <td>20732.0</td>\n",
" <td>25</td>\n",
" <td>19.0</td>\n",
" <td>31.0</td>\n",
" <td>FR</td>\n",
" <td>France</td>\n",
" </tr>\n",
" <tr>\n",
" <th>22</th>\n",
" <td>202320</td>\n",
" <td>3</td>\n",
" <td>16162</td>\n",
" <td>11963.0</td>\n",
" <td>20361.0</td>\n",
" <td>24</td>\n",
" <td>18.0</td>\n",
" <td>30.0</td>\n",
" <td>FR</td>\n",
" <td>France</td>\n",
" </tr>\n",
" <tr>\n",
" <th>23</th>\n",
" <td>202319</td>\n",
" <td>3</td>\n",
" <td>16901</td>\n",
" <td>12577.0</td>\n",
" <td>21225.0</td>\n",
" <td>25</td>\n",
" <td>18.0</td>\n",
" <td>32.0</td>\n",
" <td>FR</td>\n",
" <td>France</td>\n",
" </tr>\n",
" <tr>\n",
" <th>24</th>\n",
" <td>202318</td>\n",
" <td>3</td>\n",
" <td>19929</td>\n",
" <td>15402.0</td>\n",
" <td>24456.0</td>\n",
" <td>30</td>\n",
" <td>23.0</td>\n",
" <td>37.0</td>\n",
" <td>FR</td>\n",
" <td>France</td>\n",
" </tr>\n",
" <tr>\n",
" <th>25</th>\n",
" <td>202317</td>\n",
" <td>3</td>\n",
" <td>27007</td>\n",
" <td>21779.0</td>\n",
" <td>32235.0</td>\n",
" <td>41</td>\n",
" <td>33.0</td>\n",
" <td>49.0</td>\n",
" <td>FR</td>\n",
" <td>France</td>\n",
" </tr>\n",
" <tr>\n",
" <th>26</th>\n",
" <td>202316</td>\n",
" <td>3</td>\n",
" <td>27875</td>\n",
" <td>22767.0</td>\n",
" <td>32983.0</td>\n",
" <td>42</td>\n",
" <td>34.0</td>\n",
" <td>50.0</td>\n",
" <td>FR</td>\n",
" <td>France</td>\n",
" </tr>\n",
" <tr>\n",
" <th>27</th>\n",
" <td>202315</td>\n",
" <td>3</td>\n",
" <td>37455</td>\n",
" <td>30993.0</td>\n",
" <td>43917.0</td>\n",
" <td>56</td>\n",
" <td>46.0</td>\n",
" <td>66.0</td>\n",
" <td>FR</td>\n",
" <td>France</td>\n",
" </tr>\n",
" <tr>\n",
" <th>28</th>\n",
" <td>202314</td>\n",
" <td>3</td>\n",
" <td>48060</td>\n",
" <td>40671.0</td>\n",
" <td>55449.0</td>\n",
" <td>72</td>\n",
" <td>61.0</td>\n",
" <td>83.0</td>\n",
" <td>FR</td>\n",
" <td>France</td>\n",
" </tr>\n",
" <tr>\n",
" <th>29</th>\n",
" <td>202313</td>\n",
" <td>3</td>\n",
" <td>64859</td>\n",
" <td>56800.0</td>\n",
" <td>72918.0</td>\n",
" <td>98</td>\n",
" <td>86.0</td>\n",
" <td>110.0</td>\n",
" <td>FR</td>\n",
" <td>France</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>2004</th>\n",
" <td>198521</td>\n",
" <td>3</td>\n",
" <td>26096</td>\n",
" <td>19621.0</td>\n",
" <td>32571.0</td>\n",
" <td>47</td>\n",
" <td>35.0</td>\n",
" <td>59.0</td>\n",
" <td>FR</td>\n",
" <td>France</td>\n",
" </tr>\n",
" <tr>\n",
" <th>2005</th>\n",
" <td>198520</td>\n",
" <td>3</td>\n",
" <td>27896</td>\n",
" <td>20885.0</td>\n",
" <td>34907.0</td>\n",
" <td>51</td>\n",
" <td>38.0</td>\n",
" <td>64.0</td>\n",
" <td>FR</td>\n",
" <td>France</td>\n",
" </tr>\n",
" <tr>\n",
" <th>2006</th>\n",
" <td>198519</td>\n",
" <td>3</td>\n",
" <td>43154</td>\n",
" <td>32821.0</td>\n",
" <td>53487.0</td>\n",
" <td>78</td>\n",
" <td>59.0</td>\n",
" <td>97.0</td>\n",
" <td>FR</td>\n",
" <td>France</td>\n",
" </tr>\n",
" <tr>\n",
" <th>2007</th>\n",
" <td>198518</td>\n",
" <td>3</td>\n",
" <td>40555</td>\n",
" <td>29935.0</td>\n",
" <td>51175.0</td>\n",
" <td>74</td>\n",
" <td>55.0</td>\n",
" <td>93.0</td>\n",
" <td>FR</td>\n",
" <td>France</td>\n",
" </tr>\n",
" <tr>\n",
" <th>2008</th>\n",
" <td>198517</td>\n",
" <td>3</td>\n",
" <td>34053</td>\n",
" <td>24366.0</td>\n",
" <td>43740.0</td>\n",
" <td>62</td>\n",
" <td>44.0</td>\n",
" <td>80.0</td>\n",
" <td>FR</td>\n",
" <td>France</td>\n",
" </tr>\n",
" <tr>\n",
" <th>2009</th>\n",
" <td>198516</td>\n",
" <td>3</td>\n",
" <td>50362</td>\n",
" <td>36451.0</td>\n",
" <td>64273.0</td>\n",
" <td>91</td>\n",
" <td>66.0</td>\n",
" <td>116.0</td>\n",
" <td>FR</td>\n",
" <td>France</td>\n",
" </tr>\n",
" <tr>\n",
" <th>2010</th>\n",
" <td>198515</td>\n",
" <td>3</td>\n",
" <td>63881</td>\n",
" <td>45538.0</td>\n",
" <td>82224.0</td>\n",
" <td>116</td>\n",
" <td>83.0</td>\n",
" <td>149.0</td>\n",
" <td>FR</td>\n",
" <td>France</td>\n",
" </tr>\n",
" <tr>\n",
" <th>2011</th>\n",
" <td>198514</td>\n",
" <td>3</td>\n",
" <td>134545</td>\n",
" <td>114400.0</td>\n",
" <td>154690.0</td>\n",
" <td>244</td>\n",
" <td>207.0</td>\n",
" <td>281.0</td>\n",
" <td>FR</td>\n",
" <td>France</td>\n",
" </tr>\n",
" <tr>\n",
" <th>2012</th>\n",
" <td>198513</td>\n",
" <td>3</td>\n",
" <td>197206</td>\n",
" <td>176080.0</td>\n",
" <td>218332.0</td>\n",
" <td>357</td>\n",
" <td>319.0</td>\n",
" <td>395.0</td>\n",
" <td>FR</td>\n",
" <td>France</td>\n",
" </tr>\n",
" <tr>\n",
" <th>2013</th>\n",
" <td>198512</td>\n",
" <td>3</td>\n",
" <td>245240</td>\n",
" <td>223304.0</td>\n",
" <td>267176.0</td>\n",
" <td>445</td>\n",
" <td>405.0</td>\n",
" <td>485.0</td>\n",
" <td>FR</td>\n",
" <td>France</td>\n",
" </tr>\n",
" <tr>\n",
" <th>2014</th>\n",
" <td>198511</td>\n",
" <td>3</td>\n",
" <td>276205</td>\n",
" <td>252399.0</td>\n",
" <td>300011.0</td>\n",
" <td>501</td>\n",
" <td>458.0</td>\n",
" <td>544.0</td>\n",
" <td>FR</td>\n",
" <td>France</td>\n",
" </tr>\n",
" <tr>\n",
" <th>2015</th>\n",
" <td>198510</td>\n",
" <td>3</td>\n",
" <td>353231</td>\n",
" <td>326279.0</td>\n",
" <td>380183.0</td>\n",
" <td>640</td>\n",
" <td>591.0</td>\n",
" <td>689.0</td>\n",
" <td>FR</td>\n",
" <td>France</td>\n",
" </tr>\n",
" <tr>\n",
" <th>2016</th>\n",
" <td>198509</td>\n",
" <td>3</td>\n",
" <td>369895</td>\n",
" <td>341109.0</td>\n",
" <td>398681.0</td>\n",
" <td>670</td>\n",
" <td>618.0</td>\n",
" <td>722.0</td>\n",
" <td>FR</td>\n",
" <td>France</td>\n",
" </tr>\n",
" <tr>\n",
" <th>2017</th>\n",
" <td>198508</td>\n",
" <td>3</td>\n",
" <td>389886</td>\n",
" <td>359529.0</td>\n",
" <td>420243.0</td>\n",
" <td>707</td>\n",
" <td>652.0</td>\n",
" <td>762.0</td>\n",
" <td>FR</td>\n",
" <td>France</td>\n",
" </tr>\n",
" <tr>\n",
" <th>2018</th>\n",
" <td>198507</td>\n",
" <td>3</td>\n",
" <td>471852</td>\n",
" <td>432599.0</td>\n",
" <td>511105.0</td>\n",
" <td>855</td>\n",
" <td>784.0</td>\n",
" <td>926.0</td>\n",
" <td>FR</td>\n",
" <td>France</td>\n",
" </tr>\n",
" <tr>\n",
" <th>2019</th>\n",
" <td>198506</td>\n",
" <td>3</td>\n",
" <td>565825</td>\n",
" <td>518011.0</td>\n",
" <td>613639.0</td>\n",
" <td>1026</td>\n",
" <td>939.0</td>\n",
" <td>1113.0</td>\n",
" <td>FR</td>\n",
" <td>France</td>\n",
" </tr>\n",
" <tr>\n",
" <th>2020</th>\n",
" <td>198505</td>\n",
" <td>3</td>\n",
" <td>637302</td>\n",
" <td>592795.0</td>\n",
" <td>681809.0</td>\n",
" <td>1155</td>\n",
" <td>1074.0</td>\n",
" <td>1236.0</td>\n",
" <td>FR</td>\n",
" <td>France</td>\n",
" </tr>\n",
" <tr>\n",
" <th>2021</th>\n",
" <td>198504</td>\n",
" <td>3</td>\n",
" <td>424937</td>\n",
" <td>390794.0</td>\n",
" <td>459080.0</td>\n",
" <td>770</td>\n",
" <td>708.0</td>\n",
" <td>832.0</td>\n",
" <td>FR</td>\n",
" <td>France</td>\n",
" </tr>\n",
" <tr>\n",
" <th>2022</th>\n",
" <td>198503</td>\n",
" <td>3</td>\n",
" <td>213901</td>\n",
" <td>174689.0</td>\n",
" <td>253113.0</td>\n",
" <td>388</td>\n",
" <td>317.0</td>\n",
" <td>459.0</td>\n",
" <td>FR</td>\n",
" <td>France</td>\n",
" </tr>\n",
" <tr>\n",
" <th>2023</th>\n",
" <td>198502</td>\n",
" <td>3</td>\n",
" <td>97586</td>\n",
" <td>80949.0</td>\n",
" <td>114223.0</td>\n",
" <td>177</td>\n",
" <td>147.0</td>\n",
" <td>207.0</td>\n",
" <td>FR</td>\n",
" <td>France</td>\n",
" </tr>\n",
" <tr>\n",
" <th>2024</th>\n",
" <td>198501</td>\n",
" <td>3</td>\n",
" <td>85489</td>\n",
" <td>65918.0</td>\n",
" <td>105060.0</td>\n",
" <td>155</td>\n",
" <td>120.0</td>\n",
" <td>190.0</td>\n",
" <td>FR</td>\n",
" <td>France</td>\n",
" </tr>\n",
" <tr>\n",
" <th>2025</th>\n",
" <td>198452</td>\n",
" <td>3</td>\n",
" <td>84830</td>\n",
" <td>60602.0</td>\n",
" <td>109058.0</td>\n",
" <td>154</td>\n",
" <td>110.0</td>\n",
" <td>198.0</td>\n",
" <td>FR</td>\n",
" <td>France</td>\n",
" </tr>\n",
" <tr>\n",
" <th>2026</th>\n",
" <td>198451</td>\n",
" <td>3</td>\n",
" <td>101726</td>\n",
" <td>80242.0</td>\n",
" <td>123210.0</td>\n",
" <td>185</td>\n",
" <td>146.0</td>\n",
" <td>224.0</td>\n",
" <td>FR</td>\n",
" <td>France</td>\n",
" </tr>\n",
" <tr>\n",
" <th>2027</th>\n",
" <td>198450</td>\n",
" <td>3</td>\n",
" <td>123680</td>\n",
" <td>101401.0</td>\n",
" <td>145959.0</td>\n",
" <td>225</td>\n",
" <td>184.0</td>\n",
" <td>266.0</td>\n",
" <td>FR</td>\n",
" <td>France</td>\n",
" </tr>\n",
" <tr>\n",
" <th>2028</th>\n",
" <td>198449</td>\n",
" <td>3</td>\n",
" <td>101073</td>\n",
" <td>81684.0</td>\n",
" <td>120462.0</td>\n",
" <td>184</td>\n",
" <td>149.0</td>\n",
" <td>219.0</td>\n",
" <td>FR</td>\n",
" <td>France</td>\n",
" </tr>\n",
" <tr>\n",
" <th>2029</th>\n",
" <td>198448</td>\n",
" <td>3</td>\n",
" <td>78620</td>\n",
" <td>60634.0</td>\n",
" <td>96606.0</td>\n",
" <td>143</td>\n",
" <td>110.0</td>\n",
" <td>176.0</td>\n",
" <td>FR</td>\n",
" <td>France</td>\n",
" </tr>\n",
" <tr>\n",
" <th>2030</th>\n",
" <td>198447</td>\n",
" <td>3</td>\n",
" <td>72029</td>\n",
" <td>54274.0</td>\n",
" <td>89784.0</td>\n",
" <td>131</td>\n",
" <td>99.0</td>\n",
" <td>163.0</td>\n",
" <td>FR</td>\n",
" <td>France</td>\n",
" </tr>\n",
" <tr>\n",
" <th>2031</th>\n",
" <td>198446</td>\n",
" <td>3</td>\n",
" <td>87330</td>\n",
" <td>67686.0</td>\n",
" <td>106974.0</td>\n",
" <td>159</td>\n",
" <td>123.0</td>\n",
" <td>195.0</td>\n",
" <td>FR</td>\n",
" <td>France</td>\n",
" </tr>\n",
" <tr>\n",
" <th>2032</th>\n",
" <td>198445</td>\n",
" <td>3</td>\n",
" <td>135223</td>\n",
" <td>101414.0</td>\n",
" <td>169032.0</td>\n",
" <td>246</td>\n",
" <td>184.0</td>\n",
" <td>308.0</td>\n",
" <td>FR</td>\n",
" <td>France</td>\n",
" </tr>\n",
" <tr>\n",
" <th>2033</th>\n",
" <td>198444</td>\n",
" <td>3</td>\n",
" <td>68422</td>\n",
" <td>20056.0</td>\n",
" <td>116788.0</td>\n",
" <td>125</td>\n",
" <td>37.0</td>\n",
" <td>213.0</td>\n",
" <td>FR</td>\n",
" <td>France</td>\n",
" </tr>\n",
" </tbody>\n",
"</table>\n",
"<p>2033 rows × 10 columns</p>\n",
"</div>"
],
"text/plain": [
" week indicator inc inc_low inc_up inc100 inc100_low \\\n",
"0 202342 3 67331 57544.0 77118.0 101 86.0 \n",
"1 202341 3 59275 51833.0 66717.0 89 78.0 \n",
"2 202340 3 68894 60069.0 77719.0 104 91.0 \n",
"3 202339 3 72003 63452.0 80554.0 108 95.0 \n",
"4 202338 3 63218 55227.0 71209.0 95 83.0 \n",
"5 202337 3 49085 42079.0 56091.0 74 63.0 \n",
"6 202336 3 38247 32237.0 44257.0 58 49.0 \n",
"7 202335 3 31695 26013.0 37377.0 48 39.0 \n",
"8 202334 3 26663 21057.0 32269.0 40 32.0 \n",
"9 202333 3 19144 13161.0 25127.0 29 20.0 \n",
"10 202332 3 14641 10285.0 18997.0 22 15.0 \n",
"11 202331 3 15286 10705.0 19867.0 23 16.0 \n",
"12 202330 3 13205 8647.0 17763.0 20 13.0 \n",
"13 202329 3 11122 7113.0 15131.0 17 11.0 \n",
"14 202328 3 9179 5703.0 12655.0 14 9.0 \n",
"15 202327 3 8999 5763.0 12235.0 14 9.0 \n",
"16 202326 3 9023 5934.0 12112.0 14 9.0 \n",
"17 202325 3 10090 6739.0 13441.0 15 10.0 \n",
"18 202324 3 11308 7639.0 14977.0 17 11.0 \n",
"19 202323 3 14300 10661.0 17939.0 22 17.0 \n",
"20 202322 3 18303 13822.0 22784.0 28 21.0 \n",
"21 202321 3 16460 12188.0 20732.0 25 19.0 \n",
"22 202320 3 16162 11963.0 20361.0 24 18.0 \n",
"23 202319 3 16901 12577.0 21225.0 25 18.0 \n",
"24 202318 3 19929 15402.0 24456.0 30 23.0 \n",
"25 202317 3 27007 21779.0 32235.0 41 33.0 \n",
"26 202316 3 27875 22767.0 32983.0 42 34.0 \n",
"27 202315 3 37455 30993.0 43917.0 56 46.0 \n",
"28 202314 3 48060 40671.0 55449.0 72 61.0 \n",
"29 202313 3 64859 56800.0 72918.0 98 86.0 \n",
"... ... ... ... ... ... ... ... \n",
"2004 198521 3 26096 19621.0 32571.0 47 35.0 \n",
"2005 198520 3 27896 20885.0 34907.0 51 38.0 \n",
"2006 198519 3 43154 32821.0 53487.0 78 59.0 \n",
"2007 198518 3 40555 29935.0 51175.0 74 55.0 \n",
"2008 198517 3 34053 24366.0 43740.0 62 44.0 \n",
"2009 198516 3 50362 36451.0 64273.0 91 66.0 \n",
"2010 198515 3 63881 45538.0 82224.0 116 83.0 \n",
"2011 198514 3 134545 114400.0 154690.0 244 207.0 \n",
"2012 198513 3 197206 176080.0 218332.0 357 319.0 \n",
"2013 198512 3 245240 223304.0 267176.0 445 405.0 \n",
"2014 198511 3 276205 252399.0 300011.0 501 458.0 \n",
"2015 198510 3 353231 326279.0 380183.0 640 591.0 \n",
"2016 198509 3 369895 341109.0 398681.0 670 618.0 \n",
"2017 198508 3 389886 359529.0 420243.0 707 652.0 \n",
"2018 198507 3 471852 432599.0 511105.0 855 784.0 \n",
"2019 198506 3 565825 518011.0 613639.0 1026 939.0 \n",
"2020 198505 3 637302 592795.0 681809.0 1155 1074.0 \n",
"2021 198504 3 424937 390794.0 459080.0 770 708.0 \n",
"2022 198503 3 213901 174689.0 253113.0 388 317.0 \n",
"2023 198502 3 97586 80949.0 114223.0 177 147.0 \n",
"2024 198501 3 85489 65918.0 105060.0 155 120.0 \n",
"2025 198452 3 84830 60602.0 109058.0 154 110.0 \n",
"2026 198451 3 101726 80242.0 123210.0 185 146.0 \n",
"2027 198450 3 123680 101401.0 145959.0 225 184.0 \n",
"2028 198449 3 101073 81684.0 120462.0 184 149.0 \n",
"2029 198448 3 78620 60634.0 96606.0 143 110.0 \n",
"2030 198447 3 72029 54274.0 89784.0 131 99.0 \n",
"2031 198446 3 87330 67686.0 106974.0 159 123.0 \n",
"2032 198445 3 135223 101414.0 169032.0 246 184.0 \n",
"2033 198444 3 68422 20056.0 116788.0 125 37.0 \n",
"\n",
" inc100_up geo_insee geo_name \n",
"0 116.0 FR France \n",
"1 100.0 FR France \n",
"2 117.0 FR France \n",
"3 121.0 FR France \n",
"4 107.0 FR France \n",
"5 85.0 FR France \n",
"6 67.0 FR France \n",
"7 57.0 FR France \n",
"8 48.0 FR France \n",
"9 38.0 FR France \n",
"10 29.0 FR France \n",
"11 30.0 FR France \n",
"12 27.0 FR France \n",
"13 23.0 FR France \n",
"14 19.0 FR France \n",
"15 19.0 FR France \n",
"16 19.0 FR France \n",
"17 20.0 FR France \n",
"18 23.0 FR France \n",
"19 27.0 FR France \n",
"20 35.0 FR France \n",
"21 31.0 FR France \n",
"22 30.0 FR France \n",
"23 32.0 FR France \n",
"24 37.0 FR France \n",
"25 49.0 FR France \n",
"26 50.0 FR France \n",
"27 66.0 FR France \n",
"28 83.0 FR France \n",
"29 110.0 FR France \n",
"... ... ... ... \n",
"2004 59.0 FR France \n",
"2005 64.0 FR France \n",
"2006 97.0 FR France \n",
"2007 93.0 FR France \n",
"2008 80.0 FR France \n",
"2009 116.0 FR France \n",
"2010 149.0 FR France \n",
"2011 281.0 FR France \n",
"2012 395.0 FR France \n",
"2013 485.0 FR France \n",
"2014 544.0 FR France \n",
"2015 689.0 FR France \n",
"2016 722.0 FR France \n",
"2017 762.0 FR France \n",
"2018 926.0 FR France \n",
"2019 1113.0 FR France \n",
"2020 1236.0 FR France \n",
"2021 832.0 FR France \n",
"2022 459.0 FR France \n",
"2023 207.0 FR France \n",
"2024 190.0 FR France \n",
"2025 198.0 FR France \n",
"2026 224.0 FR France \n",
"2027 266.0 FR France \n",
"2028 219.0 FR France \n",
"2029 176.0 FR France \n",
"2030 163.0 FR France \n",
"2031 195.0 FR France \n",
"2032 308.0 FR France \n",
"2033 213.0 FR France \n",
"\n",
"[2033 rows x 10 columns]"
]
},
"execution_count": 5,
"metadata": {},
"output_type": "execute_result"
}
],
"source": [ "source": [
"data = raw_data.dropna().copy()\n", "data = raw_data.dropna().copy()\n",
"data" "data"
...@@ -122,7 +2118,7 @@ ...@@ -122,7 +2118,7 @@
}, },
{ {
"cell_type": "code", "cell_type": "code",
"execution_count": null, "execution_count": 6,
"metadata": {}, "metadata": {},
"outputs": [], "outputs": [],
"source": [ "source": [
...@@ -152,10 +2148,8 @@ ...@@ -152,10 +2148,8 @@
}, },
{ {
"cell_type": "code", "cell_type": "code",
"execution_count": null, "execution_count": 7,
"metadata": { "metadata": {},
"collapsed": true
},
"outputs": [], "outputs": [],
"source": [ "source": [
"sorted_data = data.set_index('period').sort_index()" "sorted_data = data.set_index('period').sort_index()"
...@@ -179,9 +2173,17 @@ ...@@ -179,9 +2173,17 @@
}, },
{ {
"cell_type": "code", "cell_type": "code",
"execution_count": null, "execution_count": 8,
"metadata": {}, "metadata": {},
"outputs": [], "outputs": [
{
"name": "stdout",
"output_type": "stream",
"text": [
"1989-05-01/1989-05-07 1989-05-15/1989-05-21\n"
]
}
],
"source": [ "source": [
"periods = sorted_data.index\n", "periods = sorted_data.index\n",
"for p1, p2 in zip(periods[:-1], periods[1:]):\n", "for p1, p2 in zip(periods[:-1], periods[1:]):\n",
...@@ -199,9 +2201,26 @@ ...@@ -199,9 +2201,26 @@
}, },
{ {
"cell_type": "code", "cell_type": "code",
"execution_count": null, "execution_count": 9,
"metadata": {}, "metadata": {},
"outputs": [], "outputs": [
{
"ename": "TypeError",
"evalue": "Empty 'DataFrame': no numeric data to plot",
"output_type": "error",
"traceback": [
"\u001b[0;31m---------------------------------------------------------------------------\u001b[0m",
"\u001b[0;31mTypeError\u001b[0m Traceback (most recent call last)",
"\u001b[0;32m<ipython-input-9-0966cd984262>\u001b[0m in \u001b[0;36m<module>\u001b[0;34m\u001b[0m\n\u001b[0;32m----> 1\u001b[0;31m \u001b[0msorted_data\u001b[0m\u001b[0;34m[\u001b[0m\u001b[0;34m'inc'\u001b[0m\u001b[0;34m]\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0mplot\u001b[0m\u001b[0;34m(\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/plotting/_core.py\u001b[0m in \u001b[0;36m__call__\u001b[0;34m(self, kind, ax, figsize, use_index, title, grid, legend, style, logx, logy, loglog, xticks, yticks, xlim, ylim, rot, fontsize, colormap, table, yerr, xerr, label, secondary_y, **kwds)\u001b[0m\n\u001b[1;32m 2501\u001b[0m \u001b[0mcolormap\u001b[0m\u001b[0;34m=\u001b[0m\u001b[0mcolormap\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0mtable\u001b[0m\u001b[0;34m=\u001b[0m\u001b[0mtable\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0myerr\u001b[0m\u001b[0;34m=\u001b[0m\u001b[0myerr\u001b[0m\u001b[0;34m,\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m 2502\u001b[0m \u001b[0mxerr\u001b[0m\u001b[0;34m=\u001b[0m\u001b[0mxerr\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0mlabel\u001b[0m\u001b[0;34m=\u001b[0m\u001b[0mlabel\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0msecondary_y\u001b[0m\u001b[0;34m=\u001b[0m\u001b[0msecondary_y\u001b[0m\u001b[0;34m,\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0;32m-> 2503\u001b[0;31m **kwds)\n\u001b[0m\u001b[1;32m 2504\u001b[0m \u001b[0m__call__\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0m__doc__\u001b[0m \u001b[0;34m=\u001b[0m \u001b[0mplot_series\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0m__doc__\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m 2505\u001b[0m \u001b[0;34m\u001b[0m\u001b[0m\n",
"\u001b[0;32m/opt/conda/lib/python3.6/site-packages/pandas/plotting/_core.py\u001b[0m in \u001b[0;36mplot_series\u001b[0;34m(data, kind, ax, figsize, use_index, title, grid, legend, style, logx, logy, loglog, xticks, yticks, xlim, ylim, rot, fontsize, colormap, table, yerr, xerr, label, secondary_y, **kwds)\u001b[0m\n\u001b[1;32m 1925\u001b[0m \u001b[0myerr\u001b[0m\u001b[0;34m=\u001b[0m\u001b[0myerr\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0mxerr\u001b[0m\u001b[0;34m=\u001b[0m\u001b[0mxerr\u001b[0m\u001b[0;34m,\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m 1926\u001b[0m \u001b[0mlabel\u001b[0m\u001b[0;34m=\u001b[0m\u001b[0mlabel\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0msecondary_y\u001b[0m\u001b[0;34m=\u001b[0m\u001b[0msecondary_y\u001b[0m\u001b[0;34m,\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0;32m-> 1927\u001b[0;31m **kwds)\n\u001b[0m\u001b[1;32m 1928\u001b[0m \u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m 1929\u001b[0m \u001b[0;34m\u001b[0m\u001b[0m\n",
"\u001b[0;32m/opt/conda/lib/python3.6/site-packages/pandas/plotting/_core.py\u001b[0m in \u001b[0;36m_plot\u001b[0;34m(data, x, y, subplots, ax, kind, **kwds)\u001b[0m\n\u001b[1;32m 1727\u001b[0m \u001b[0mplot_obj\u001b[0m \u001b[0;34m=\u001b[0m \u001b[0mklass\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0mdata\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0msubplots\u001b[0m\u001b[0;34m=\u001b[0m\u001b[0msubplots\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0max\u001b[0m\u001b[0;34m=\u001b[0m\u001b[0max\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0mkind\u001b[0m\u001b[0;34m=\u001b[0m\u001b[0mkind\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0;34m**\u001b[0m\u001b[0mkwds\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m 1728\u001b[0m \u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0;32m-> 1729\u001b[0;31m \u001b[0mplot_obj\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0mgenerate\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 1730\u001b[0m \u001b[0mplot_obj\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0mdraw\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m 1731\u001b[0m \u001b[0;32mreturn\u001b[0m \u001b[0mplot_obj\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0mresult\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n",
"\u001b[0;32m/opt/conda/lib/python3.6/site-packages/pandas/plotting/_core.py\u001b[0m in \u001b[0;36mgenerate\u001b[0;34m(self)\u001b[0m\n\u001b[1;32m 248\u001b[0m \u001b[0;32mdef\u001b[0m \u001b[0mgenerate\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0mself\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m:\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m 249\u001b[0m \u001b[0mself\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0m_args_adjust\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0;32m--> 250\u001b[0;31m \u001b[0mself\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0m_compute_plot_data\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 251\u001b[0m \u001b[0mself\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0m_setup_subplots\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m 252\u001b[0m \u001b[0mself\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0m_make_plot\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/plotting/_core.py\u001b[0m in \u001b[0;36m_compute_plot_data\u001b[0;34m(self)\u001b[0m\n\u001b[1;32m 363\u001b[0m \u001b[0;32mif\u001b[0m \u001b[0mis_empty\u001b[0m\u001b[0;34m:\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m 364\u001b[0m raise TypeError('Empty {0!r}: no numeric data to '\n\u001b[0;32m--> 365\u001b[0;31m 'plot'.format(numeric_data.__class__.__name__))\n\u001b[0m\u001b[1;32m 366\u001b[0m \u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m 367\u001b[0m \u001b[0mself\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0mdata\u001b[0m \u001b[0;34m=\u001b[0m \u001b[0mnumeric_data\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n",
"\u001b[0;31mTypeError\u001b[0m: Empty 'DataFrame': no numeric data to plot"
]
}
],
"source": [ "source": [
"sorted_data['inc'].plot()" "sorted_data['inc'].plot()"
] ]
...@@ -253,9 +2272,7 @@ ...@@ -253,9 +2272,7 @@
{ {
"cell_type": "code", "cell_type": "code",
"execution_count": null, "execution_count": null,
"metadata": { "metadata": {},
"collapsed": true
},
"outputs": [], "outputs": [],
"source": [ "source": [
"first_august_week = [pd.Period(pd.Timestamp(y, 8, 1), 'W')\n", "first_august_week = [pd.Period(pd.Timestamp(y, 8, 1), 'W')\n",
...@@ -341,9 +2358,7 @@ ...@@ -341,9 +2358,7 @@
{ {
"cell_type": "code", "cell_type": "code",
"execution_count": null, "execution_count": null,
"metadata": { "metadata": {},
"collapsed": true
},
"outputs": [], "outputs": [],
"source": [] "source": []
} }
...@@ -364,7 +2379,7 @@ ...@@ -364,7 +2379,7 @@
"name": "python", "name": "python",
"nbconvert_exporter": "python", "nbconvert_exporter": "python",
"pygments_lexer": "ipython3", "pygments_lexer": "ipython3",
"version": "3.6.1" "version": "3.6.4"
} }
}, },
"nbformat": 4, "nbformat": 4,
......
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