get better

parent 877e0fdb
......@@ -40,11 +40,16 @@
},
{
"cell_type": "code",
"execution_count": 23,
"execution_count": 31,
"metadata": {},
"outputs": [],
"source": [
"data_url =\"https://app-learninglab.inria.fr/moocrr/gitlab/ef86fb54ef695a9083dc58696a4f7e7c/mooc-rr/blob/master/module3/exo1/incidence-PAY-3.csv\""
"data_file = \"incidence-PAY-3.csv\"\n",
"data_url = \"\"\n",
"import os\n",
"import urllib.request\n",
"if not os.path.exists(data_file):\n",
" urllib.request.urlretrieve(data_url, data_file)"
]
},
{
......@@ -71,32 +76,978 @@
},
{
"cell_type": "code",
"execution_count": 24,
"execution_count": 32,
"metadata": {},
"outputs": [
{
"ename": "ParserError",
"evalue": "Error tokenizing data. C error: Expected 1 fields in line 30, saw 21\n",
"output_type": "error",
"traceback": [
"\u001b[0;31m---------------------------------------------------------------------------\u001b[0m",
"\u001b[0;31mParserError\u001b[0m Traceback (most recent call last)",
"\u001b[0;32m<ipython-input-24-c6940997bed1>\u001b[0m in \u001b[0;36m<module>\u001b[0;34m\u001b[0m\n\u001b[0;32m----> 1\u001b[0;31m \u001b[0mraw_data\u001b[0m \u001b[0;34m=\u001b[0m \u001b[0mpd\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0mread_csv\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0mdata_url\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0mskiprows\u001b[0m\u001b[0;34m=\u001b[0m\u001b[0;36m1\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0m\u001b[1;32m 2\u001b[0m \u001b[0mraw_data\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n",
"\u001b[0;32m/opt/conda/lib/python3.6/site-packages/pandas/io/parsers.py\u001b[0m in \u001b[0;36mparser_f\u001b[0;34m(filepath_or_buffer, sep, delimiter, header, names, index_col, usecols, squeeze, prefix, mangle_dupe_cols, dtype, engine, converters, true_values, false_values, skipinitialspace, skiprows, nrows, na_values, keep_default_na, na_filter, verbose, skip_blank_lines, parse_dates, infer_datetime_format, keep_date_col, date_parser, dayfirst, iterator, chunksize, compression, thousands, decimal, lineterminator, quotechar, quoting, escapechar, comment, encoding, dialect, tupleize_cols, error_bad_lines, warn_bad_lines, skipfooter, skip_footer, doublequote, delim_whitespace, as_recarray, compact_ints, use_unsigned, low_memory, buffer_lines, memory_map, float_precision)\u001b[0m\n\u001b[1;32m 707\u001b[0m skip_blank_lines=skip_blank_lines)\n\u001b[1;32m 708\u001b[0m \u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0;32m--> 709\u001b[0;31m \u001b[0;32mreturn\u001b[0m \u001b[0m_read\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0mfilepath_or_buffer\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[0m\u001b[1;32m 710\u001b[0m \u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m 711\u001b[0m \u001b[0mparser_f\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0m__name__\u001b[0m \u001b[0;34m=\u001b[0m \u001b[0mname\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n",
"\u001b[0;32m/opt/conda/lib/python3.6/site-packages/pandas/io/parsers.py\u001b[0m in \u001b[0;36m_read\u001b[0;34m(filepath_or_buffer, kwds)\u001b[0m\n\u001b[1;32m 453\u001b[0m \u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m 454\u001b[0m \u001b[0;32mtry\u001b[0m\u001b[0;34m:\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0;32m--> 455\u001b[0;31m \u001b[0mdata\u001b[0m \u001b[0;34m=\u001b[0m \u001b[0mparser\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0mread\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0mnrows\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0m\u001b[1;32m 456\u001b[0m \u001b[0;32mfinally\u001b[0m\u001b[0;34m:\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m 457\u001b[0m \u001b[0mparser\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0mclose\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/io/parsers.py\u001b[0m in \u001b[0;36mread\u001b[0;34m(self, nrows)\u001b[0m\n\u001b[1;32m 1067\u001b[0m \u001b[0;32mraise\u001b[0m \u001b[0mValueError\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0;34m'skipfooter not supported for iteration'\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m 1068\u001b[0m \u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0;32m-> 1069\u001b[0;31m \u001b[0mret\u001b[0m \u001b[0;34m=\u001b[0m \u001b[0mself\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0m_engine\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0mread\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0mnrows\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0m\u001b[1;32m 1070\u001b[0m \u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m 1071\u001b[0m \u001b[0;32mif\u001b[0m \u001b[0mself\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0moptions\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0mget\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0;34m'as_recarray'\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/io/parsers.py\u001b[0m in \u001b[0;36mread\u001b[0;34m(self, nrows)\u001b[0m\n\u001b[1;32m 1837\u001b[0m \u001b[0;32mdef\u001b[0m \u001b[0mread\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0mself\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0mnrows\u001b[0m\u001b[0;34m=\u001b[0m\u001b[0;32mNone\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m:\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m 1838\u001b[0m \u001b[0;32mtry\u001b[0m\u001b[0;34m:\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0;32m-> 1839\u001b[0;31m \u001b[0mdata\u001b[0m \u001b[0;34m=\u001b[0m \u001b[0mself\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0m_reader\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0mread\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0mnrows\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0m\u001b[1;32m 1840\u001b[0m \u001b[0;32mexcept\u001b[0m \u001b[0mStopIteration\u001b[0m\u001b[0;34m:\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m 1841\u001b[0m \u001b[0;32mif\u001b[0m \u001b[0mself\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0m_first_chunk\u001b[0m\u001b[0;34m:\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n",
"\u001b[0;32mpandas/_libs/parsers.pyx\u001b[0m in \u001b[0;36mpandas._libs.parsers.TextReader.read\u001b[0;34m()\u001b[0m\n",
"\u001b[0;32mpandas/_libs/parsers.pyx\u001b[0m in \u001b[0;36mpandas._libs.parsers.TextReader._read_low_memory\u001b[0;34m()\u001b[0m\n",
"\u001b[0;32mpandas/_libs/parsers.pyx\u001b[0m in \u001b[0;36mpandas._libs.parsers.TextReader._read_rows\u001b[0;34m()\u001b[0m\n",
"\u001b[0;32mpandas/_libs/parsers.pyx\u001b[0m in \u001b[0;36mpandas._libs.parsers.TextReader._tokenize_rows\u001b[0;34m()\u001b[0m\n",
"\u001b[0;32mpandas/_libs/parsers.pyx\u001b[0m in \u001b[0;36mpandas._libs.parsers.raise_parser_error\u001b[0;34m()\u001b[0m\n",
"\u001b[0;31mParserError\u001b[0m: Error tokenizing data. C error: Expected 1 fields in line 30, saw 21\n"
]
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" <td>France</td>\n",
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" <td>21810</td>\n",
" <td>17894.0</td>\n",
" <td>25726.0</td>\n",
" <td>33</td>\n",
" <td>27.0</td>\n",
" <td>39.0</td>\n",
" <td>FR</td>\n",
" <td>France</td>\n",
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" <tr>\n",
" <th>18</th>\n",
" <td>202102</td>\n",
" <td>3</td>\n",
" <td>17320</td>\n",
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" <td>20734.0</td>\n",
" <td>26</td>\n",
" <td>21.0</td>\n",
" <td>31.0</td>\n",
" <td>FR</td>\n",
" <td>France</td>\n",
" </tr>\n",
" <tr>\n",
" <th>19</th>\n",
" <td>202101</td>\n",
" <td>3</td>\n",
" <td>21799</td>\n",
" <td>17778.0</td>\n",
" <td>25820.0</td>\n",
" <td>33</td>\n",
" <td>27.0</td>\n",
" <td>39.0</td>\n",
" <td>FR</td>\n",
" <td>France</td>\n",
" </tr>\n",
" <tr>\n",
" <th>20</th>\n",
" <td>202053</td>\n",
" <td>3</td>\n",
" <td>21220</td>\n",
" <td>16498.0</td>\n",
" <td>25942.0</td>\n",
" <td>32</td>\n",
" <td>25.0</td>\n",
" <td>39.0</td>\n",
" <td>FR</td>\n",
" <td>France</td>\n",
" </tr>\n",
" <tr>\n",
" <th>21</th>\n",
" <td>202052</td>\n",
" <td>3</td>\n",
" <td>16428</td>\n",
" <td>12285.0</td>\n",
" <td>20571.0</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>202051</td>\n",
" <td>3</td>\n",
" <td>21619</td>\n",
" <td>17370.0</td>\n",
" <td>25868.0</td>\n",
" <td>33</td>\n",
" <td>27.0</td>\n",
" <td>39.0</td>\n",
" <td>FR</td>\n",
" <td>France</td>\n",
" </tr>\n",
" <tr>\n",
" <th>23</th>\n",
" <td>202050</td>\n",
" <td>3</td>\n",
" <td>16845</td>\n",
" <td>13220.0</td>\n",
" <td>20470.0</td>\n",
" <td>26</td>\n",
" <td>20.0</td>\n",
" <td>32.0</td>\n",
" <td>FR</td>\n",
" <td>France</td>\n",
" </tr>\n",
" <tr>\n",
" <th>24</th>\n",
" <td>202049</td>\n",
" <td>3</td>\n",
" <td>12939</td>\n",
" <td>9923.0</td>\n",
" <td>15955.0</td>\n",
" <td>20</td>\n",
" <td>15.0</td>\n",
" <td>25.0</td>\n",
" <td>FR</td>\n",
" <td>France</td>\n",
" </tr>\n",
" <tr>\n",
" <th>25</th>\n",
" <td>202048</td>\n",
" <td>3</td>\n",
" <td>13804</td>\n",
" <td>10641.0</td>\n",
" <td>16967.0</td>\n",
" <td>21</td>\n",
" <td>16.0</td>\n",
" <td>26.0</td>\n",
" <td>FR</td>\n",
" <td>France</td>\n",
" </tr>\n",
" <tr>\n",
" <th>26</th>\n",
" <td>202047</td>\n",
" <td>3</td>\n",
" <td>19085</td>\n",
" <td>15285.0</td>\n",
" <td>22885.0</td>\n",
" <td>29</td>\n",
" <td>23.0</td>\n",
" <td>35.0</td>\n",
" <td>FR</td>\n",
" <td>France</td>\n",
" </tr>\n",
" <tr>\n",
" <th>27</th>\n",
" <td>202046</td>\n",
" <td>3</td>\n",
" <td>24801</td>\n",
" <td>20503.0</td>\n",
" <td>29099.0</td>\n",
" <td>38</td>\n",
" <td>31.0</td>\n",
" <td>45.0</td>\n",
" <td>FR</td>\n",
" <td>France</td>\n",
" </tr>\n",
" <tr>\n",
" <th>28</th>\n",
" <td>202045</td>\n",
" <td>3</td>\n",
" <td>42516</td>\n",
" <td>36857.0</td>\n",
" <td>48175.0</td>\n",
" <td>65</td>\n",
" <td>56.0</td>\n",
" <td>74.0</td>\n",
" <td>FR</td>\n",
" <td>France</td>\n",
" </tr>\n",
" <tr>\n",
" <th>29</th>\n",
" <td>202044</td>\n",
" <td>3</td>\n",
" <td>44567</td>\n",
" <td>38521.0</td>\n",
" <td>50613.0</td>\n",
" <td>68</td>\n",
" <td>59.0</td>\n",
" <td>77.0</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>1878</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>1879</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>1880</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>1881</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>1882</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>1883</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>1884</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>1885</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>1886</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>1887</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>1888</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>1889</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>1890</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>1891</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>1892</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>1893</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>1894</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>1895</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>1896</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>1897</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>1898</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>1899</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>1900</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>1901</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>1902</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>1903</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>1904</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>1905</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>1906</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>1907</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>1908 rows × 10 columns</p>\n",
"</div>"
],
"text/plain": [
" week indicator inc inc_low inc_up inc100 inc100_low \\\n",
"0 202120 3 13803 9830.0 17776.0 21 15.0 \n",
"1 202119 3 9774 7030.0 12518.0 15 11.0 \n",
"2 202118 3 12135 9165.0 15105.0 18 14.0 \n",
"3 202117 3 12058 8891.0 15225.0 18 13.0 \n",
"4 202116 3 16505 12735.0 20275.0 25 19.0 \n",
"5 202115 3 19306 15398.0 23214.0 29 23.0 \n",
"6 202114 3 21073 17099.0 25047.0 32 26.0 \n",
"7 202113 3 26413 22094.0 30732.0 40 33.0 \n",
"8 202112 3 30658 25919.0 35397.0 46 39.0 \n",
"9 202111 3 24988 20718.0 29258.0 38 32.0 \n",
"10 202110 3 19539 15951.0 23127.0 30 25.0 \n",
"11 202109 3 17572 13926.0 21218.0 27 21.0 \n",
"12 202108 3 20882 16907.0 24857.0 32 26.0 \n",
"13 202107 3 22393 18303.0 26483.0 34 28.0 \n",
"14 202106 3 23183 19134.0 27232.0 35 29.0 \n",
"15 202105 3 22426 18445.0 26407.0 34 28.0 \n",
"16 202104 3 25804 21491.0 30117.0 39 32.0 \n",
"17 202103 3 21810 17894.0 25726.0 33 27.0 \n",
"18 202102 3 17320 13906.0 20734.0 26 21.0 \n",
"19 202101 3 21799 17778.0 25820.0 33 27.0 \n",
"20 202053 3 21220 16498.0 25942.0 32 25.0 \n",
"21 202052 3 16428 12285.0 20571.0 25 19.0 \n",
"22 202051 3 21619 17370.0 25868.0 33 27.0 \n",
"23 202050 3 16845 13220.0 20470.0 26 20.0 \n",
"24 202049 3 12939 9923.0 15955.0 20 15.0 \n",
"25 202048 3 13804 10641.0 16967.0 21 16.0 \n",
"26 202047 3 19085 15285.0 22885.0 29 23.0 \n",
"27 202046 3 24801 20503.0 29099.0 38 31.0 \n",
"28 202045 3 42516 36857.0 48175.0 65 56.0 \n",
"29 202044 3 44567 38521.0 50613.0 68 59.0 \n",
"... ... ... ... ... ... ... ... \n",
"1878 198521 3 26096 19621.0 32571.0 47 35.0 \n",
"1879 198520 3 27896 20885.0 34907.0 51 38.0 \n",
"1880 198519 3 43154 32821.0 53487.0 78 59.0 \n",
"1881 198518 3 40555 29935.0 51175.0 74 55.0 \n",
"1882 198517 3 34053 24366.0 43740.0 62 44.0 \n",
"1883 198516 3 50362 36451.0 64273.0 91 66.0 \n",
"1884 198515 3 63881 45538.0 82224.0 116 83.0 \n",
"1885 198514 3 134545 114400.0 154690.0 244 207.0 \n",
"1886 198513 3 197206 176080.0 218332.0 357 319.0 \n",
"1887 198512 3 245240 223304.0 267176.0 445 405.0 \n",
"1888 198511 3 276205 252399.0 300011.0 501 458.0 \n",
"1889 198510 3 353231 326279.0 380183.0 640 591.0 \n",
"1890 198509 3 369895 341109.0 398681.0 670 618.0 \n",
"1891 198508 3 389886 359529.0 420243.0 707 652.0 \n",
"1892 198507 3 471852 432599.0 511105.0 855 784.0 \n",
"1893 198506 3 565825 518011.0 613639.0 1026 939.0 \n",
"1894 198505 3 637302 592795.0 681809.0 1155 1074.0 \n",
"1895 198504 3 424937 390794.0 459080.0 770 708.0 \n",
"1896 198503 3 213901 174689.0 253113.0 388 317.0 \n",
"1897 198502 3 97586 80949.0 114223.0 177 147.0 \n",
"1898 198501 3 85489 65918.0 105060.0 155 120.0 \n",
"1899 198452 3 84830 60602.0 109058.0 154 110.0 \n",
"1900 198451 3 101726 80242.0 123210.0 185 146.0 \n",
"1901 198450 3 123680 101401.0 145959.0 225 184.0 \n",
"1902 198449 3 101073 81684.0 120462.0 184 149.0 \n",
"1903 198448 3 78620 60634.0 96606.0 143 110.0 \n",
"1904 198447 3 72029 54274.0 89784.0 131 99.0 \n",
"1905 198446 3 87330 67686.0 106974.0 159 123.0 \n",
"1906 198445 3 135223 101414.0 169032.0 246 184.0 \n",
"1907 198444 3 68422 20056.0 116788.0 125 37.0 \n",
"\n",
" inc100_up geo_insee geo_name \n",
"0 27.0 FR France \n",
"1 19.0 FR France \n",
"2 22.0 FR France \n",
"3 23.0 FR France \n",
"4 31.0 FR France \n",
"5 35.0 FR France \n",
"6 38.0 FR France \n",
"7 47.0 FR France \n",
"8 53.0 FR France \n",
"9 44.0 FR France \n",
"10 35.0 FR France \n",
"11 33.0 FR France \n",
"12 38.0 FR France \n",
"13 40.0 FR France \n",
"14 41.0 FR France \n",
"15 40.0 FR France \n",
"16 46.0 FR France \n",
"17 39.0 FR France \n",
"18 31.0 FR France \n",
"19 39.0 FR France \n",
"20 39.0 FR France \n",
"21 31.0 FR France \n",
"22 39.0 FR France \n",
"23 32.0 FR France \n",
"24 25.0 FR France \n",
"25 26.0 FR France \n",
"26 35.0 FR France \n",
"27 45.0 FR France \n",
"28 74.0 FR France \n",
"29 77.0 FR France \n",
"... ... ... ... \n",
"1878 59.0 FR France \n",
"1879 64.0 FR France \n",
"1880 97.0 FR France \n",
"1881 93.0 FR France \n",
"1882 80.0 FR France \n",
"1883 116.0 FR France \n",
"1884 149.0 FR France \n",
"1885 281.0 FR France \n",
"1886 395.0 FR France \n",
"1887 485.0 FR France \n",
"1888 544.0 FR France \n",
"1889 689.0 FR France \n",
"1890 722.0 FR France \n",
"1891 762.0 FR France \n",
"1892 926.0 FR France \n",
"1893 1113.0 FR France \n",
"1894 1236.0 FR France \n",
"1895 832.0 FR France \n",
"1896 459.0 FR France \n",
"1897 207.0 FR France \n",
"1898 190.0 FR France \n",
"1899 198.0 FR France \n",
"1900 224.0 FR France \n",
"1901 266.0 FR France \n",
"1902 219.0 FR France \n",
"1903 176.0 FR France \n",
"1904 163.0 FR France \n",
"1905 195.0 FR France \n",
"1906 308.0 FR France \n",
"1907 213.0 FR France \n",
"\n",
"[1908 rows x 10 columns]"
]
},
"execution_count": 32,
"metadata": {},
"output_type": "execute_result"
}
],
"source": [
"raw_data = pd.read_csv(data_url, skiprows=1)\n",
"raw_data = pd.read_csv(data_file, skiprows=1)\n",
"raw_data"
]
},
......
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