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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": 2,
"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": 3,
"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": 4,
"metadata": {}, "metadata": {},
"outputs": [], "outputs": [
{
"data": {
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" <th>7</th>\n",
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" <td>27404</td>\n",
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" <td>32772.0</td>\n",
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" <td>33.0</td>\n",
" <td>49.0</td>\n",
" <td>FR</td>\n",
" <td>France</td>\n",
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" <th>8</th>\n",
" <td>202434</td>\n",
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" <td>26717</td>\n",
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" <th>9</th>\n",
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" <td>20623</td>\n",
" <td>15349.0</td>\n",
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" <td>23.0</td>\n",
" <td>39.0</td>\n",
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" <th>10</th>\n",
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" <td>23187</td>\n",
" <td>17532.0</td>\n",
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" <td>35</td>\n",
" <td>27.0</td>\n",
" <td>43.0</td>\n",
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" <td>France</td>\n",
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" <th>11</th>\n",
" <td>202431</td>\n",
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" <td>26035</td>\n",
" <td>20267.0</td>\n",
" <td>31803.0</td>\n",
" <td>39</td>\n",
" <td>30.0</td>\n",
" <td>48.0</td>\n",
" <td>FR</td>\n",
" <td>France</td>\n",
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" <th>12</th>\n",
" <td>202430</td>\n",
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" <td>36393</td>\n",
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" <td>55</td>\n",
" <td>43.0</td>\n",
" <td>67.0</td>\n",
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" <td>France</td>\n",
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" <th>13</th>\n",
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" <td>39560</td>\n",
" <td>32592.0</td>\n",
" <td>46528.0</td>\n",
" <td>59</td>\n",
" <td>49.0</td>\n",
" <td>69.0</td>\n",
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" <td>France</td>\n",
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" <th>14</th>\n",
" <td>202428</td>\n",
" <td>3</td>\n",
" <td>54342</td>\n",
" <td>45781.0</td>\n",
" <td>62903.0</td>\n",
" <td>81</td>\n",
" <td>68.0</td>\n",
" <td>94.0</td>\n",
" <td>FR</td>\n",
" <td>France</td>\n",
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" <th>15</th>\n",
" <td>202427</td>\n",
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" <td>47364</td>\n",
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" <td>82.0</td>\n",
" <td>FR</td>\n",
" <td>France</td>\n",
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" <th>16</th>\n",
" <td>202426</td>\n",
" <td>3</td>\n",
" <td>44219</td>\n",
" <td>36956.0</td>\n",
" <td>51482.0</td>\n",
" <td>66</td>\n",
" <td>55.0</td>\n",
" <td>77.0</td>\n",
" <td>FR</td>\n",
" <td>France</td>\n",
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" <tr>\n",
" <th>17</th>\n",
" <td>202425</td>\n",
" <td>3</td>\n",
" <td>47204</td>\n",
" <td>40300.0</td>\n",
" <td>54108.0</td>\n",
" <td>71</td>\n",
" <td>61.0</td>\n",
" <td>81.0</td>\n",
" <td>FR</td>\n",
" <td>France</td>\n",
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" <tr>\n",
" <th>18</th>\n",
" <td>202424</td>\n",
" <td>3</td>\n",
" <td>41110</td>\n",
" <td>34671.0</td>\n",
" <td>47549.0</td>\n",
" <td>62</td>\n",
" <td>52.0</td>\n",
" <td>72.0</td>\n",
" <td>FR</td>\n",
" <td>France</td>\n",
" </tr>\n",
" <tr>\n",
" <th>19</th>\n",
" <td>202423</td>\n",
" <td>3</td>\n",
" <td>35875</td>\n",
" <td>30610.0</td>\n",
" <td>41140.0</td>\n",
" <td>54</td>\n",
" <td>46.0</td>\n",
" <td>62.0</td>\n",
" <td>FR</td>\n",
" <td>France</td>\n",
" </tr>\n",
" <tr>\n",
" <th>20</th>\n",
" <td>202422</td>\n",
" <td>3</td>\n",
" <td>33772</td>\n",
" <td>28274.0</td>\n",
" <td>39270.0</td>\n",
" <td>51</td>\n",
" <td>43.0</td>\n",
" <td>59.0</td>\n",
" <td>FR</td>\n",
" <td>France</td>\n",
" </tr>\n",
" <tr>\n",
" <th>21</th>\n",
" <td>202421</td>\n",
" <td>3</td>\n",
" <td>21963</td>\n",
" <td>17556.0</td>\n",
" <td>26370.0</td>\n",
" <td>33</td>\n",
" <td>26.0</td>\n",
" <td>40.0</td>\n",
" <td>FR</td>\n",
" <td>France</td>\n",
" </tr>\n",
" <tr>\n",
" <th>22</th>\n",
" <td>202420</td>\n",
" <td>3</td>\n",
" <td>20057</td>\n",
" <td>15780.0</td>\n",
" <td>24334.0</td>\n",
" <td>30</td>\n",
" <td>24.0</td>\n",
" <td>36.0</td>\n",
" <td>FR</td>\n",
" <td>France</td>\n",
" </tr>\n",
" <tr>\n",
" <th>23</th>\n",
" <td>202419</td>\n",
" <td>3</td>\n",
" <td>15375</td>\n",
" <td>11274.0</td>\n",
" <td>19476.0</td>\n",
" <td>23</td>\n",
" <td>17.0</td>\n",
" <td>29.0</td>\n",
" <td>FR</td>\n",
" <td>France</td>\n",
" </tr>\n",
" <tr>\n",
" <th>24</th>\n",
" <td>202418</td>\n",
" <td>3</td>\n",
" <td>22409</td>\n",
" <td>17653.0</td>\n",
" <td>27165.0</td>\n",
" <td>34</td>\n",
" <td>27.0</td>\n",
" <td>41.0</td>\n",
" <td>FR</td>\n",
" <td>France</td>\n",
" </tr>\n",
" <tr>\n",
" <th>25</th>\n",
" <td>202417</td>\n",
" <td>3</td>\n",
" <td>27042</td>\n",
" <td>21410.0</td>\n",
" <td>32674.0</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>202416</td>\n",
" <td>3</td>\n",
" <td>28882</td>\n",
" <td>23305.0</td>\n",
" <td>34459.0</td>\n",
" <td>43</td>\n",
" <td>35.0</td>\n",
" <td>51.0</td>\n",
" <td>FR</td>\n",
" <td>France</td>\n",
" </tr>\n",
" <tr>\n",
" <th>27</th>\n",
" <td>202415</td>\n",
" <td>3</td>\n",
" <td>30229</td>\n",
" <td>24648.0</td>\n",
" <td>35810.0</td>\n",
" <td>45</td>\n",
" <td>37.0</td>\n",
" <td>53.0</td>\n",
" <td>FR</td>\n",
" <td>France</td>\n",
" </tr>\n",
" <tr>\n",
" <th>28</th>\n",
" <td>202414</td>\n",
" <td>3</td>\n",
" <td>31813</td>\n",
" <td>26529.0</td>\n",
" <td>37097.0</td>\n",
" <td>48</td>\n",
" <td>40.0</td>\n",
" <td>56.0</td>\n",
" <td>FR</td>\n",
" <td>France</td>\n",
" </tr>\n",
" <tr>\n",
" <th>29</th>\n",
" <td>202413</td>\n",
" <td>3</td>\n",
" <td>35090</td>\n",
" <td>29607.0</td>\n",
" <td>40573.0</td>\n",
" <td>53</td>\n",
" <td>45.0</td>\n",
" <td>61.0</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>2056</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>2057</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>2058</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>2059</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>2060</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>2061</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>2062</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>2063</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>2064</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>2065</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>2066</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>2067</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>2068</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>2069</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>2070</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>2071</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>2072</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>2073</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>2074</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>2075</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>2076</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>2077</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>2078</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>2079</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>2080</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>2081</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>2082</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>2083</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>2084</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>2085</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>2086 rows × 10 columns</p>\n",
"</div>"
],
"text/plain": [
" week indicator inc inc_low inc_up inc100 inc100_low \\\n",
"0 202442 3 78153 68586.0 87720.0 117 103.0 \n",
"1 202441 3 79515 71427.0 87603.0 119 107.0 \n",
"2 202440 3 84965 76555.0 93375.0 127 114.0 \n",
"3 202439 3 91660 82937.0 100383.0 137 124.0 \n",
"4 202438 3 91786 82903.0 100669.0 138 125.0 \n",
"5 202437 3 56460 49319.0 63601.0 85 74.0 \n",
"6 202436 3 33657 27906.0 39408.0 50 41.0 \n",
"7 202435 3 27404 22036.0 32772.0 41 33.0 \n",
"8 202434 3 26717 21003.0 32431.0 40 31.0 \n",
"9 202433 3 20623 15349.0 25897.0 31 23.0 \n",
"10 202432 3 23187 17532.0 28842.0 35 27.0 \n",
"11 202431 3 26035 20267.0 31803.0 39 30.0 \n",
"12 202430 3 36393 28593.0 44193.0 55 43.0 \n",
"13 202429 3 39560 32592.0 46528.0 59 49.0 \n",
"14 202428 3 54342 45781.0 62903.0 81 68.0 \n",
"15 202427 3 47364 40234.0 54494.0 71 60.0 \n",
"16 202426 3 44219 36956.0 51482.0 66 55.0 \n",
"17 202425 3 47204 40300.0 54108.0 71 61.0 \n",
"18 202424 3 41110 34671.0 47549.0 62 52.0 \n",
"19 202423 3 35875 30610.0 41140.0 54 46.0 \n",
"20 202422 3 33772 28274.0 39270.0 51 43.0 \n",
"21 202421 3 21963 17556.0 26370.0 33 26.0 \n",
"22 202420 3 20057 15780.0 24334.0 30 24.0 \n",
"23 202419 3 15375 11274.0 19476.0 23 17.0 \n",
"24 202418 3 22409 17653.0 27165.0 34 27.0 \n",
"25 202417 3 27042 21410.0 32674.0 41 33.0 \n",
"26 202416 3 28882 23305.0 34459.0 43 35.0 \n",
"27 202415 3 30229 24648.0 35810.0 45 37.0 \n",
"28 202414 3 31813 26529.0 37097.0 48 40.0 \n",
"29 202413 3 35090 29607.0 40573.0 53 45.0 \n",
"... ... ... ... ... ... ... ... \n",
"2056 198521 3 26096 19621.0 32571.0 47 35.0 \n",
"2057 198520 3 27896 20885.0 34907.0 51 38.0 \n",
"2058 198519 3 43154 32821.0 53487.0 78 59.0 \n",
"2059 198518 3 40555 29935.0 51175.0 74 55.0 \n",
"2060 198517 3 34053 24366.0 43740.0 62 44.0 \n",
"2061 198516 3 50362 36451.0 64273.0 91 66.0 \n",
"2062 198515 3 63881 45538.0 82224.0 116 83.0 \n",
"2063 198514 3 134545 114400.0 154690.0 244 207.0 \n",
"2064 198513 3 197206 176080.0 218332.0 357 319.0 \n",
"2065 198512 3 245240 223304.0 267176.0 445 405.0 \n",
"2066 198511 3 276205 252399.0 300011.0 501 458.0 \n",
"2067 198510 3 353231 326279.0 380183.0 640 591.0 \n",
"2068 198509 3 369895 341109.0 398681.0 670 618.0 \n",
"2069 198508 3 389886 359529.0 420243.0 707 652.0 \n",
"2070 198507 3 471852 432599.0 511105.0 855 784.0 \n",
"2071 198506 3 565825 518011.0 613639.0 1026 939.0 \n",
"2072 198505 3 637302 592795.0 681809.0 1155 1074.0 \n",
"2073 198504 3 424937 390794.0 459080.0 770 708.0 \n",
"2074 198503 3 213901 174689.0 253113.0 388 317.0 \n",
"2075 198502 3 97586 80949.0 114223.0 177 147.0 \n",
"2076 198501 3 85489 65918.0 105060.0 155 120.0 \n",
"2077 198452 3 84830 60602.0 109058.0 154 110.0 \n",
"2078 198451 3 101726 80242.0 123210.0 185 146.0 \n",
"2079 198450 3 123680 101401.0 145959.0 225 184.0 \n",
"2080 198449 3 101073 81684.0 120462.0 184 149.0 \n",
"2081 198448 3 78620 60634.0 96606.0 143 110.0 \n",
"2082 198447 3 72029 54274.0 89784.0 131 99.0 \n",
"2083 198446 3 87330 67686.0 106974.0 159 123.0 \n",
"2084 198445 3 135223 101414.0 169032.0 246 184.0 \n",
"2085 198444 3 68422 20056.0 116788.0 125 37.0 \n",
"\n",
" inc100_up geo_insee geo_name \n",
"0 131.0 FR France \n",
"1 131.0 FR France \n",
"2 140.0 FR France \n",
"3 150.0 FR France \n",
"4 151.0 FR France \n",
"5 96.0 FR France \n",
"6 59.0 FR France \n",
"7 49.0 FR France \n",
"8 49.0 FR France \n",
"9 39.0 FR France \n",
"10 43.0 FR France \n",
"11 48.0 FR France \n",
"12 67.0 FR France \n",
"13 69.0 FR France \n",
"14 94.0 FR France \n",
"15 82.0 FR France \n",
"16 77.0 FR France \n",
"17 81.0 FR France \n",
"18 72.0 FR France \n",
"19 62.0 FR France \n",
"20 59.0 FR France \n",
"21 40.0 FR France \n",
"22 36.0 FR France \n",
"23 29.0 FR France \n",
"24 41.0 FR France \n",
"25 49.0 FR France \n",
"26 51.0 FR France \n",
"27 53.0 FR France \n",
"28 56.0 FR France \n",
"29 61.0 FR France \n",
"... ... ... ... \n",
"2056 59.0 FR France \n",
"2057 64.0 FR France \n",
"2058 97.0 FR France \n",
"2059 93.0 FR France \n",
"2060 80.0 FR France \n",
"2061 116.0 FR France \n",
"2062 149.0 FR France \n",
"2063 281.0 FR France \n",
"2064 395.0 FR France \n",
"2065 485.0 FR France \n",
"2066 544.0 FR France \n",
"2067 689.0 FR France \n",
"2068 722.0 FR France \n",
"2069 762.0 FR France \n",
"2070 926.0 FR France \n",
"2071 1113.0 FR France \n",
"2072 1236.0 FR France \n",
"2073 832.0 FR France \n",
"2074 459.0 FR France \n",
"2075 207.0 FR France \n",
"2076 190.0 FR France \n",
"2077 198.0 FR France \n",
"2078 224.0 FR France \n",
"2079 266.0 FR France \n",
"2080 219.0 FR France \n",
"2081 176.0 FR France \n",
"2082 163.0 FR France \n",
"2083 195.0 FR France \n",
"2084 308.0 FR France \n",
"2085 213.0 FR France \n",
"\n",
"[2086 rows x 10 columns]"
]
},
"execution_count": 4,
"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": 5,
"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",
" <th>geo_insee</th>\n",
" <th>geo_name</th>\n",
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" <tr>\n",
" <th>1849</th>\n",
" <td>198919</td>\n",
" <td>3</td>\n",
" <td>-</td>\n",
" <td>NaN</td>\n",
" <td>NaN</td>\n",
" <td>-</td>\n",
" <td>NaN</td>\n",
" <td>NaN</td>\n",
" <td>FR</td>\n",
" <td>France</td>\n",
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],
"text/plain": [
" week indicator inc inc_low inc_up inc100 inc100_low inc100_up \\\n",
"1849 198919 3 - NaN NaN - NaN NaN \n",
"\n",
" geo_insee geo_name \n",
"1849 FR France "
]
},
"execution_count": 5,
"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": 6,
"metadata": {}, "metadata": {},
"outputs": [], "outputs": [
{
"data": {
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" <thead>\n",
" <tr style=\"text-align: right;\">\n",
" <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",
" <th>geo_insee</th>\n",
" <th>geo_name</th>\n",
" </tr>\n",
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" <tbody>\n",
" <tr>\n",
" <th>0</th>\n",
" <td>202442</td>\n",
" <td>3</td>\n",
" <td>78153</td>\n",
" <td>68586.0</td>\n",
" <td>87720.0</td>\n",
" <td>117</td>\n",
" <td>103.0</td>\n",
" <td>131.0</td>\n",
" <td>FR</td>\n",
" <td>France</td>\n",
" </tr>\n",
" <tr>\n",
" <th>1</th>\n",
" <td>202441</td>\n",
" <td>3</td>\n",
" <td>79515</td>\n",
" <td>71427.0</td>\n",
" <td>87603.0</td>\n",
" <td>119</td>\n",
" <td>107.0</td>\n",
" <td>131.0</td>\n",
" <td>FR</td>\n",
" <td>France</td>\n",
" </tr>\n",
" <tr>\n",
" <th>2</th>\n",
" <td>202440</td>\n",
" <td>3</td>\n",
" <td>84965</td>\n",
" <td>76555.0</td>\n",
" <td>93375.0</td>\n",
" <td>127</td>\n",
" <td>114.0</td>\n",
" <td>140.0</td>\n",
" <td>FR</td>\n",
" <td>France</td>\n",
" </tr>\n",
" <tr>\n",
" <th>3</th>\n",
" <td>202439</td>\n",
" <td>3</td>\n",
" <td>91660</td>\n",
" <td>82937.0</td>\n",
" <td>100383.0</td>\n",
" <td>137</td>\n",
" <td>124.0</td>\n",
" <td>150.0</td>\n",
" <td>FR</td>\n",
" <td>France</td>\n",
" </tr>\n",
" <tr>\n",
" <th>4</th>\n",
" <td>202438</td>\n",
" <td>3</td>\n",
" <td>91786</td>\n",
" <td>82903.0</td>\n",
" <td>100669.0</td>\n",
" <td>138</td>\n",
" <td>125.0</td>\n",
" <td>151.0</td>\n",
" <td>FR</td>\n",
" <td>France</td>\n",
" </tr>\n",
" <tr>\n",
" <th>5</th>\n",
" <td>202437</td>\n",
" <td>3</td>\n",
" <td>56460</td>\n",
" <td>49319.0</td>\n",
" <td>63601.0</td>\n",
" <td>85</td>\n",
" <td>74.0</td>\n",
" <td>96.0</td>\n",
" <td>FR</td>\n",
" <td>France</td>\n",
" </tr>\n",
" <tr>\n",
" <th>6</th>\n",
" <td>202436</td>\n",
" <td>3</td>\n",
" <td>33657</td>\n",
" <td>27906.0</td>\n",
" <td>39408.0</td>\n",
" <td>50</td>\n",
" <td>41.0</td>\n",
" <td>59.0</td>\n",
" <td>FR</td>\n",
" <td>France</td>\n",
" </tr>\n",
" <tr>\n",
" <th>7</th>\n",
" <td>202435</td>\n",
" <td>3</td>\n",
" <td>27404</td>\n",
" <td>22036.0</td>\n",
" <td>32772.0</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>8</th>\n",
" <td>202434</td>\n",
" <td>3</td>\n",
" <td>26717</td>\n",
" <td>21003.0</td>\n",
" <td>32431.0</td>\n",
" <td>40</td>\n",
" <td>31.0</td>\n",
" <td>49.0</td>\n",
" <td>FR</td>\n",
" <td>France</td>\n",
" </tr>\n",
" <tr>\n",
" <th>9</th>\n",
" <td>202433</td>\n",
" <td>3</td>\n",
" <td>20623</td>\n",
" <td>15349.0</td>\n",
" <td>25897.0</td>\n",
" <td>31</td>\n",
" <td>23.0</td>\n",
" <td>39.0</td>\n",
" <td>FR</td>\n",
" <td>France</td>\n",
" </tr>\n",
" <tr>\n",
" <th>10</th>\n",
" <td>202432</td>\n",
" <td>3</td>\n",
" <td>23187</td>\n",
" <td>17532.0</td>\n",
" <td>28842.0</td>\n",
" <td>35</td>\n",
" <td>27.0</td>\n",
" <td>43.0</td>\n",
" <td>FR</td>\n",
" <td>France</td>\n",
" </tr>\n",
" <tr>\n",
" <th>11</th>\n",
" <td>202431</td>\n",
" <td>3</td>\n",
" <td>26035</td>\n",
" <td>20267.0</td>\n",
" <td>31803.0</td>\n",
" <td>39</td>\n",
" <td>30.0</td>\n",
" <td>48.0</td>\n",
" <td>FR</td>\n",
" <td>France</td>\n",
" </tr>\n",
" <tr>\n",
" <th>12</th>\n",
" <td>202430</td>\n",
" <td>3</td>\n",
" <td>36393</td>\n",
" <td>28593.0</td>\n",
" <td>44193.0</td>\n",
" <td>55</td>\n",
" <td>43.0</td>\n",
" <td>67.0</td>\n",
" <td>FR</td>\n",
" <td>France</td>\n",
" </tr>\n",
" <tr>\n",
" <th>13</th>\n",
" <td>202429</td>\n",
" <td>3</td>\n",
" <td>39560</td>\n",
" <td>32592.0</td>\n",
" <td>46528.0</td>\n",
" <td>59</td>\n",
" <td>49.0</td>\n",
" <td>69.0</td>\n",
" <td>FR</td>\n",
" <td>France</td>\n",
" </tr>\n",
" <tr>\n",
" <th>14</th>\n",
" <td>202428</td>\n",
" <td>3</td>\n",
" <td>54342</td>\n",
" <td>45781.0</td>\n",
" <td>62903.0</td>\n",
" <td>81</td>\n",
" <td>68.0</td>\n",
" <td>94.0</td>\n",
" <td>FR</td>\n",
" <td>France</td>\n",
" </tr>\n",
" <tr>\n",
" <th>15</th>\n",
" <td>202427</td>\n",
" <td>3</td>\n",
" <td>47364</td>\n",
" <td>40234.0</td>\n",
" <td>54494.0</td>\n",
" <td>71</td>\n",
" <td>60.0</td>\n",
" <td>82.0</td>\n",
" <td>FR</td>\n",
" <td>France</td>\n",
" </tr>\n",
" <tr>\n",
" <th>16</th>\n",
" <td>202426</td>\n",
" <td>3</td>\n",
" <td>44219</td>\n",
" <td>36956.0</td>\n",
" <td>51482.0</td>\n",
" <td>66</td>\n",
" <td>55.0</td>\n",
" <td>77.0</td>\n",
" <td>FR</td>\n",
" <td>France</td>\n",
" </tr>\n",
" <tr>\n",
" <th>17</th>\n",
" <td>202425</td>\n",
" <td>3</td>\n",
" <td>47204</td>\n",
" <td>40300.0</td>\n",
" <td>54108.0</td>\n",
" <td>71</td>\n",
" <td>61.0</td>\n",
" <td>81.0</td>\n",
" <td>FR</td>\n",
" <td>France</td>\n",
" </tr>\n",
" <tr>\n",
" <th>18</th>\n",
" <td>202424</td>\n",
" <td>3</td>\n",
" <td>41110</td>\n",
" <td>34671.0</td>\n",
" <td>47549.0</td>\n",
" <td>62</td>\n",
" <td>52.0</td>\n",
" <td>72.0</td>\n",
" <td>FR</td>\n",
" <td>France</td>\n",
" </tr>\n",
" <tr>\n",
" <th>19</th>\n",
" <td>202423</td>\n",
" <td>3</td>\n",
" <td>35875</td>\n",
" <td>30610.0</td>\n",
" <td>41140.0</td>\n",
" <td>54</td>\n",
" <td>46.0</td>\n",
" <td>62.0</td>\n",
" <td>FR</td>\n",
" <td>France</td>\n",
" </tr>\n",
" <tr>\n",
" <th>20</th>\n",
" <td>202422</td>\n",
" <td>3</td>\n",
" <td>33772</td>\n",
" <td>28274.0</td>\n",
" <td>39270.0</td>\n",
" <td>51</td>\n",
" <td>43.0</td>\n",
" <td>59.0</td>\n",
" <td>FR</td>\n",
" <td>France</td>\n",
" </tr>\n",
" <tr>\n",
" <th>21</th>\n",
" <td>202421</td>\n",
" <td>3</td>\n",
" <td>21963</td>\n",
" <td>17556.0</td>\n",
" <td>26370.0</td>\n",
" <td>33</td>\n",
" <td>26.0</td>\n",
" <td>40.0</td>\n",
" <td>FR</td>\n",
" <td>France</td>\n",
" </tr>\n",
" <tr>\n",
" <th>22</th>\n",
" <td>202420</td>\n",
" <td>3</td>\n",
" <td>20057</td>\n",
" <td>15780.0</td>\n",
" <td>24334.0</td>\n",
" <td>30</td>\n",
" <td>24.0</td>\n",
" <td>36.0</td>\n",
" <td>FR</td>\n",
" <td>France</td>\n",
" </tr>\n",
" <tr>\n",
" <th>23</th>\n",
" <td>202419</td>\n",
" <td>3</td>\n",
" <td>15375</td>\n",
" <td>11274.0</td>\n",
" <td>19476.0</td>\n",
" <td>23</td>\n",
" <td>17.0</td>\n",
" <td>29.0</td>\n",
" <td>FR</td>\n",
" <td>France</td>\n",
" </tr>\n",
" <tr>\n",
" <th>24</th>\n",
" <td>202418</td>\n",
" <td>3</td>\n",
" <td>22409</td>\n",
" <td>17653.0</td>\n",
" <td>27165.0</td>\n",
" <td>34</td>\n",
" <td>27.0</td>\n",
" <td>41.0</td>\n",
" <td>FR</td>\n",
" <td>France</td>\n",
" </tr>\n",
" <tr>\n",
" <th>25</th>\n",
" <td>202417</td>\n",
" <td>3</td>\n",
" <td>27042</td>\n",
" <td>21410.0</td>\n",
" <td>32674.0</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>202416</td>\n",
" <td>3</td>\n",
" <td>28882</td>\n",
" <td>23305.0</td>\n",
" <td>34459.0</td>\n",
" <td>43</td>\n",
" <td>35.0</td>\n",
" <td>51.0</td>\n",
" <td>FR</td>\n",
" <td>France</td>\n",
" </tr>\n",
" <tr>\n",
" <th>27</th>\n",
" <td>202415</td>\n",
" <td>3</td>\n",
" <td>30229</td>\n",
" <td>24648.0</td>\n",
" <td>35810.0</td>\n",
" <td>45</td>\n",
" <td>37.0</td>\n",
" <td>53.0</td>\n",
" <td>FR</td>\n",
" <td>France</td>\n",
" </tr>\n",
" <tr>\n",
" <th>28</th>\n",
" <td>202414</td>\n",
" <td>3</td>\n",
" <td>31813</td>\n",
" <td>26529.0</td>\n",
" <td>37097.0</td>\n",
" <td>48</td>\n",
" <td>40.0</td>\n",
" <td>56.0</td>\n",
" <td>FR</td>\n",
" <td>France</td>\n",
" </tr>\n",
" <tr>\n",
" <th>29</th>\n",
" <td>202413</td>\n",
" <td>3</td>\n",
" <td>35090</td>\n",
" <td>29607.0</td>\n",
" <td>40573.0</td>\n",
" <td>53</td>\n",
" <td>45.0</td>\n",
" <td>61.0</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>2056</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>2057</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>2058</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>2059</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>2060</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>2061</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>2062</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>2063</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>2064</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>2065</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>2066</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>2067</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>2068</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>2069</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>2070</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>2071</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>2072</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>2073</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>2074</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>2075</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>2076</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>2077</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>2078</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>2079</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>2080</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>2081</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>2082</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>2083</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>2084</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>2085</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>2085 rows × 10 columns</p>\n",
"</div>"
],
"text/plain": [
" week indicator inc inc_low inc_up inc100 inc100_low \\\n",
"0 202442 3 78153 68586.0 87720.0 117 103.0 \n",
"1 202441 3 79515 71427.0 87603.0 119 107.0 \n",
"2 202440 3 84965 76555.0 93375.0 127 114.0 \n",
"3 202439 3 91660 82937.0 100383.0 137 124.0 \n",
"4 202438 3 91786 82903.0 100669.0 138 125.0 \n",
"5 202437 3 56460 49319.0 63601.0 85 74.0 \n",
"6 202436 3 33657 27906.0 39408.0 50 41.0 \n",
"7 202435 3 27404 22036.0 32772.0 41 33.0 \n",
"8 202434 3 26717 21003.0 32431.0 40 31.0 \n",
"9 202433 3 20623 15349.0 25897.0 31 23.0 \n",
"10 202432 3 23187 17532.0 28842.0 35 27.0 \n",
"11 202431 3 26035 20267.0 31803.0 39 30.0 \n",
"12 202430 3 36393 28593.0 44193.0 55 43.0 \n",
"13 202429 3 39560 32592.0 46528.0 59 49.0 \n",
"14 202428 3 54342 45781.0 62903.0 81 68.0 \n",
"15 202427 3 47364 40234.0 54494.0 71 60.0 \n",
"16 202426 3 44219 36956.0 51482.0 66 55.0 \n",
"17 202425 3 47204 40300.0 54108.0 71 61.0 \n",
"18 202424 3 41110 34671.0 47549.0 62 52.0 \n",
"19 202423 3 35875 30610.0 41140.0 54 46.0 \n",
"20 202422 3 33772 28274.0 39270.0 51 43.0 \n",
"21 202421 3 21963 17556.0 26370.0 33 26.0 \n",
"22 202420 3 20057 15780.0 24334.0 30 24.0 \n",
"23 202419 3 15375 11274.0 19476.0 23 17.0 \n",
"24 202418 3 22409 17653.0 27165.0 34 27.0 \n",
"25 202417 3 27042 21410.0 32674.0 41 33.0 \n",
"26 202416 3 28882 23305.0 34459.0 43 35.0 \n",
"27 202415 3 30229 24648.0 35810.0 45 37.0 \n",
"28 202414 3 31813 26529.0 37097.0 48 40.0 \n",
"29 202413 3 35090 29607.0 40573.0 53 45.0 \n",
"... ... ... ... ... ... ... ... \n",
"2056 198521 3 26096 19621.0 32571.0 47 35.0 \n",
"2057 198520 3 27896 20885.0 34907.0 51 38.0 \n",
"2058 198519 3 43154 32821.0 53487.0 78 59.0 \n",
"2059 198518 3 40555 29935.0 51175.0 74 55.0 \n",
"2060 198517 3 34053 24366.0 43740.0 62 44.0 \n",
"2061 198516 3 50362 36451.0 64273.0 91 66.0 \n",
"2062 198515 3 63881 45538.0 82224.0 116 83.0 \n",
"2063 198514 3 134545 114400.0 154690.0 244 207.0 \n",
"2064 198513 3 197206 176080.0 218332.0 357 319.0 \n",
"2065 198512 3 245240 223304.0 267176.0 445 405.0 \n",
"2066 198511 3 276205 252399.0 300011.0 501 458.0 \n",
"2067 198510 3 353231 326279.0 380183.0 640 591.0 \n",
"2068 198509 3 369895 341109.0 398681.0 670 618.0 \n",
"2069 198508 3 389886 359529.0 420243.0 707 652.0 \n",
"2070 198507 3 471852 432599.0 511105.0 855 784.0 \n",
"2071 198506 3 565825 518011.0 613639.0 1026 939.0 \n",
"2072 198505 3 637302 592795.0 681809.0 1155 1074.0 \n",
"2073 198504 3 424937 390794.0 459080.0 770 708.0 \n",
"2074 198503 3 213901 174689.0 253113.0 388 317.0 \n",
"2075 198502 3 97586 80949.0 114223.0 177 147.0 \n",
"2076 198501 3 85489 65918.0 105060.0 155 120.0 \n",
"2077 198452 3 84830 60602.0 109058.0 154 110.0 \n",
"2078 198451 3 101726 80242.0 123210.0 185 146.0 \n",
"2079 198450 3 123680 101401.0 145959.0 225 184.0 \n",
"2080 198449 3 101073 81684.0 120462.0 184 149.0 \n",
"2081 198448 3 78620 60634.0 96606.0 143 110.0 \n",
"2082 198447 3 72029 54274.0 89784.0 131 99.0 \n",
"2083 198446 3 87330 67686.0 106974.0 159 123.0 \n",
"2084 198445 3 135223 101414.0 169032.0 246 184.0 \n",
"2085 198444 3 68422 20056.0 116788.0 125 37.0 \n",
"\n",
" inc100_up geo_insee geo_name \n",
"0 131.0 FR France \n",
"1 131.0 FR France \n",
"2 140.0 FR France \n",
"3 150.0 FR France \n",
"4 151.0 FR France \n",
"5 96.0 FR France \n",
"6 59.0 FR France \n",
"7 49.0 FR France \n",
"8 49.0 FR France \n",
"9 39.0 FR France \n",
"10 43.0 FR France \n",
"11 48.0 FR France \n",
"12 67.0 FR France \n",
"13 69.0 FR France \n",
"14 94.0 FR France \n",
"15 82.0 FR France \n",
"16 77.0 FR France \n",
"17 81.0 FR France \n",
"18 72.0 FR France \n",
"19 62.0 FR France \n",
"20 59.0 FR France \n",
"21 40.0 FR France \n",
"22 36.0 FR France \n",
"23 29.0 FR France \n",
"24 41.0 FR France \n",
"25 49.0 FR France \n",
"26 51.0 FR France \n",
"27 53.0 FR France \n",
"28 56.0 FR France \n",
"29 61.0 FR France \n",
"... ... ... ... \n",
"2056 59.0 FR France \n",
"2057 64.0 FR France \n",
"2058 97.0 FR France \n",
"2059 93.0 FR France \n",
"2060 80.0 FR France \n",
"2061 116.0 FR France \n",
"2062 149.0 FR France \n",
"2063 281.0 FR France \n",
"2064 395.0 FR France \n",
"2065 485.0 FR France \n",
"2066 544.0 FR France \n",
"2067 689.0 FR France \n",
"2068 722.0 FR France \n",
"2069 762.0 FR France \n",
"2070 926.0 FR France \n",
"2071 1113.0 FR France \n",
"2072 1236.0 FR France \n",
"2073 832.0 FR France \n",
"2074 459.0 FR France \n",
"2075 207.0 FR France \n",
"2076 190.0 FR France \n",
"2077 198.0 FR France \n",
"2078 224.0 FR France \n",
"2079 266.0 FR France \n",
"2080 219.0 FR France \n",
"2081 176.0 FR France \n",
"2082 163.0 FR France \n",
"2083 195.0 FR France \n",
"2084 308.0 FR France \n",
"2085 213.0 FR France \n",
"\n",
"[2085 rows x 10 columns]"
]
},
"execution_count": 6,
"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": 7,
"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": 8,
"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": 9,
"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": 10,
"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-10-0966cd984262>\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": []
} }
......
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