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[covid19.git] / excess_death_accuracy.ipynb
1 {
2 "cells": [
3 {
4 "cell_type": "code",
5 "execution_count": 23,
6 "metadata": {
7 "Collapsed": "false"
8 },
9 "outputs": [],
10 "source": [
11 "import itertools\n",
12 "import collections\n",
13 "import json\n",
14 "import pandas as pd\n",
15 "import numpy as np\n",
16 "from scipy.stats import gmean\n",
17 "import datetime\n",
18 "\n",
19 "import matplotlib as mpl\n",
20 "import matplotlib.pyplot as plt\n",
21 "%matplotlib inline"
22 ]
23 },
24 {
25 "cell_type": "code",
26 "execution_count": 66,
27 "metadata": {
28 "Collapsed": "false"
29 },
30 "outputs": [
31 {
32 "data": {
33 "text/html": [
34 "<div>\n",
35 "<style scoped>\n",
36 " .dataframe tbody tr th:only-of-type {\n",
37 " vertical-align: middle;\n",
38 " }\n",
39 "\n",
40 " .dataframe tbody tr th {\n",
41 " vertical-align: top;\n",
42 " }\n",
43 "\n",
44 " .dataframe thead th {\n",
45 " text-align: right;\n",
46 " }\n",
47 "</style>\n",
48 "<table border=\"1\" class=\"dataframe\">\n",
49 " <thead>\n",
50 " <tr style=\"text-align: right;\">\n",
51 " <th></th>\n",
52 " <th>cases</th>\n",
53 " <th>deaths</th>\n",
54 " <th>cases_culm</th>\n",
55 " <th>deaths_culm</th>\n",
56 " <th>cases_diff</th>\n",
57 " <th>deaths_diff</th>\n",
58 " <th>cases_m7</th>\n",
59 " <th>deaths_m7</th>\n",
60 " <th>deaths_g4</th>\n",
61 " <th>deaths_g7</th>\n",
62 " <th>doubling_time</th>\n",
63 " <th>doubling_time_7</th>\n",
64 " </tr>\n",
65 " <tr>\n",
66 " <th>dateRep</th>\n",
67 " <th></th>\n",
68 " <th></th>\n",
69 " <th></th>\n",
70 " <th></th>\n",
71 " <th></th>\n",
72 " <th></th>\n",
73 " <th></th>\n",
74 " <th></th>\n",
75 " <th></th>\n",
76 " <th></th>\n",
77 " <th></th>\n",
78 " <th></th>\n",
79 " </tr>\n",
80 " </thead>\n",
81 " <tbody>\n",
82 " <tr>\n",
83 " <td>2019-12-31</td>\n",
84 " <td>0</td>\n",
85 " <td>0</td>\n",
86 " <td>0</td>\n",
87 " <td>0</td>\n",
88 " <td>NaN</td>\n",
89 " <td>NaN</td>\n",
90 " <td>0.000000</td>\n",
91 " <td>0.000000</td>\n",
92 " <td>0.000000</td>\n",
93 " <td>0.000000</td>\n",
94 " <td>NaN</td>\n",
95 " <td>NaN</td>\n",
96 " </tr>\n",
97 " <tr>\n",
98 " <td>2020-01-01</td>\n",
99 " <td>0</td>\n",
100 " <td>0</td>\n",
101 " <td>0</td>\n",
102 " <td>0</td>\n",
103 " <td>0.0</td>\n",
104 " <td>0.0</td>\n",
105 " <td>0.000000</td>\n",
106 " <td>0.000000</td>\n",
107 " <td>0.000000</td>\n",
108 " <td>0.000000</td>\n",
109 " <td>NaN</td>\n",
110 " <td>NaN</td>\n",
111 " </tr>\n",
112 " <tr>\n",
113 " <td>2020-01-02</td>\n",
114 " <td>0</td>\n",
115 " <td>0</td>\n",
116 " <td>0</td>\n",
117 " <td>0</td>\n",
118 " <td>0.0</td>\n",
119 " <td>0.0</td>\n",
120 " <td>0.000000</td>\n",
121 " <td>0.000000</td>\n",
122 " <td>0.000000</td>\n",
123 " <td>0.000000</td>\n",
124 " <td>NaN</td>\n",
125 " <td>NaN</td>\n",
126 " </tr>\n",
127 " <tr>\n",
128 " <td>2020-01-03</td>\n",
129 " <td>0</td>\n",
130 " <td>0</td>\n",
131 " <td>0</td>\n",
132 " <td>0</td>\n",
133 " <td>0.0</td>\n",
134 " <td>0.0</td>\n",
135 " <td>0.000000</td>\n",
136 " <td>0.000000</td>\n",
137 " <td>0.000000</td>\n",
138 " <td>0.000000</td>\n",
139 " <td>NaN</td>\n",
140 " <td>NaN</td>\n",
141 " </tr>\n",
142 " <tr>\n",
143 " <td>2020-01-04</td>\n",
144 " <td>0</td>\n",
145 " <td>0</td>\n",
146 " <td>0</td>\n",
147 " <td>0</td>\n",
148 " <td>0.0</td>\n",
149 " <td>0.0</td>\n",
150 " <td>0.000000</td>\n",
151 " <td>0.000000</td>\n",
152 " <td>0.000000</td>\n",
153 " <td>0.000000</td>\n",
154 " <td>NaN</td>\n",
155 " <td>NaN</td>\n",
156 " </tr>\n",
157 " <tr>\n",
158 " <td>...</td>\n",
159 " <td>...</td>\n",
160 " <td>...</td>\n",
161 " <td>...</td>\n",
162 " <td>...</td>\n",
163 " <td>...</td>\n",
164 " <td>...</td>\n",
165 " <td>...</td>\n",
166 " <td>...</td>\n",
167 " <td>...</td>\n",
168 " <td>...</td>\n",
169 " <td>...</td>\n",
170 " <td>...</td>\n",
171 " </tr>\n",
172 " <tr>\n",
173 " <td>2020-12-06</td>\n",
174 " <td>15539</td>\n",
175 " <td>397</td>\n",
176 " <td>1705971</td>\n",
177 " <td>61014</td>\n",
178 " <td>-759.0</td>\n",
179 " <td>-107.0</td>\n",
180 " <td>14399.857143</td>\n",
181 " <td>426.285714</td>\n",
182 " <td>481.336835</td>\n",
183 " <td>391.619248</td>\n",
184 " <td>88.209086</td>\n",
185 " <td>108.338041</td>\n",
186 " </tr>\n",
187 " <tr>\n",
188 " <td>2020-12-07</td>\n",
189 " <td>17271</td>\n",
190 " <td>231</td>\n",
191 " <td>1723242</td>\n",
192 " <td>61245</td>\n",
193 " <td>1732.0</td>\n",
194 " <td>-166.0</td>\n",
195 " <td>15130.714286</td>\n",
196 " <td>428.571429</td>\n",
197 " <td>371.927543</td>\n",
198 " <td>395.655665</td>\n",
199 " <td>114.486195</td>\n",
200 " <td>107.641011</td>\n",
201 " </tr>\n",
202 " <tr>\n",
203 " <td>2020-12-08</td>\n",
204 " <td>14718</td>\n",
205 " <td>189</td>\n",
206 " <td>1737960</td>\n",
207 " <td>61434</td>\n",
208 " <td>-2553.0</td>\n",
209 " <td>-42.0</td>\n",
210 " <td>15471.857143</td>\n",
211 " <td>426.571429</td>\n",
212 " <td>305.719899</td>\n",
213 " <td>391.637191</td>\n",
214 " <td>139.633275</td>\n",
215 " <td>109.076442</td>\n",
216 " </tr>\n",
217 " <tr>\n",
218 " <td>2020-12-09</td>\n",
219 " <td>12281</td>\n",
220 " <td>599</td>\n",
221 " <td>1750241</td>\n",
222 " <td>62033</td>\n",
223 " <td>-2437.0</td>\n",
224 " <td>410.0</td>\n",
225 " <td>15307.857143</td>\n",
226 " <td>426.000000</td>\n",
227 " <td>319.207273</td>\n",
228 " <td>391.264999</td>\n",
229 " <td>135.048719</td>\n",
230 " <td>110.241037</td>\n",
231 " </tr>\n",
232 " <tr>\n",
233 " <td>2020-12-10</td>\n",
234 " <td>16578</td>\n",
235 " <td>533</td>\n",
236 " <td>1766819</td>\n",
237 " <td>62566</td>\n",
238 " <td>4297.0</td>\n",
239 " <td>-66.0</td>\n",
240 " <td>15366.142857</td>\n",
241 " <td>409.571429</td>\n",
242 " <td>343.603005</td>\n",
243 " <td>380.495816</td>\n",
244 " <td>126.560073</td>\n",
245 " <td>114.322369</td>\n",
246 " </tr>\n",
247 " </tbody>\n",
248 "</table>\n",
249 "<p>346 rows × 12 columns</p>\n",
250 "</div>"
251 ],
252 "text/plain": [
253 " cases deaths cases_culm deaths_culm cases_diff deaths_diff \\\n",
254 "dateRep \n",
255 "2019-12-31 0 0 0 0 NaN NaN \n",
256 "2020-01-01 0 0 0 0 0.0 0.0 \n",
257 "2020-01-02 0 0 0 0 0.0 0.0 \n",
258 "2020-01-03 0 0 0 0 0.0 0.0 \n",
259 "2020-01-04 0 0 0 0 0.0 0.0 \n",
260 "... ... ... ... ... ... ... \n",
261 "2020-12-06 15539 397 1705971 61014 -759.0 -107.0 \n",
262 "2020-12-07 17271 231 1723242 61245 1732.0 -166.0 \n",
263 "2020-12-08 14718 189 1737960 61434 -2553.0 -42.0 \n",
264 "2020-12-09 12281 599 1750241 62033 -2437.0 410.0 \n",
265 "2020-12-10 16578 533 1766819 62566 4297.0 -66.0 \n",
266 "\n",
267 " cases_m7 deaths_m7 deaths_g4 deaths_g7 doubling_time \\\n",
268 "dateRep \n",
269 "2019-12-31 0.000000 0.000000 0.000000 0.000000 NaN \n",
270 "2020-01-01 0.000000 0.000000 0.000000 0.000000 NaN \n",
271 "2020-01-02 0.000000 0.000000 0.000000 0.000000 NaN \n",
272 "2020-01-03 0.000000 0.000000 0.000000 0.000000 NaN \n",
273 "2020-01-04 0.000000 0.000000 0.000000 0.000000 NaN \n",
274 "... ... ... ... ... ... \n",
275 "2020-12-06 14399.857143 426.285714 481.336835 391.619248 88.209086 \n",
276 "2020-12-07 15130.714286 428.571429 371.927543 395.655665 114.486195 \n",
277 "2020-12-08 15471.857143 426.571429 305.719899 391.637191 139.633275 \n",
278 "2020-12-09 15307.857143 426.000000 319.207273 391.264999 135.048719 \n",
279 "2020-12-10 15366.142857 409.571429 343.603005 380.495816 126.560073 \n",
280 "\n",
281 " doubling_time_7 \n",
282 "dateRep \n",
283 "2019-12-31 NaN \n",
284 "2020-01-01 NaN \n",
285 "2020-01-02 NaN \n",
286 "2020-01-03 NaN \n",
287 "2020-01-04 NaN \n",
288 "... ... \n",
289 "2020-12-06 108.338041 \n",
290 "2020-12-07 107.641011 \n",
291 "2020-12-08 109.076442 \n",
292 "2020-12-09 110.241037 \n",
293 "2020-12-10 114.322369 \n",
294 "\n",
295 "[346 rows x 12 columns]"
296 ]
297 },
298 "execution_count": 66,
299 "metadata": {},
300 "output_type": "execute_result"
301 }
302 ],
303 "source": [
304 "data_by_day = pd.read_csv('data_by_day_uk.csv', index_col='dateRep', parse_dates=True)\n",
305 "data_by_day"
306 ]
307 },
308 {
309 "cell_type": "code",
310 "execution_count": 67,
311 "metadata": {
312 "Collapsed": "false"
313 },
314 "outputs": [
315 {
316 "data": {
317 "text/html": [
318 "<div>\n",
319 "<style scoped>\n",
320 " .dataframe tbody tr th:only-of-type {\n",
321 " vertical-align: middle;\n",
322 " }\n",
323 "\n",
324 " .dataframe tbody tr th {\n",
325 " vertical-align: top;\n",
326 " }\n",
327 "\n",
328 " .dataframe thead th {\n",
329 " text-align: right;\n",
330 " }\n",
331 "</style>\n",
332 "<table border=\"1\" class=\"dataframe\">\n",
333 " <thead>\n",
334 " <tr style=\"text-align: right;\">\n",
335 " <th></th>\n",
336 " <th>total_2020</th>\n",
337 " <th>total_2019</th>\n",
338 " <th>total_2018</th>\n",
339 " <th>total_2017</th>\n",
340 " <th>total_2016</th>\n",
341 " <th>total_2015</th>\n",
342 " <th>previous_mean</th>\n",
343 " </tr>\n",
344 " <tr>\n",
345 " <th>week_ended</th>\n",
346 " <th></th>\n",
347 " <th></th>\n",
348 " <th></th>\n",
349 " <th></th>\n",
350 " <th></th>\n",
351 " <th></th>\n",
352 " <th></th>\n",
353 " </tr>\n",
354 " </thead>\n",
355 " <tbody>\n",
356 " <tr>\n",
357 " <td>2020-01-03</td>\n",
358 " <td>13768.0</td>\n",
359 " <td>12424.0</td>\n",
360 " <td>14701.0</td>\n",
361 " <td>13612.0</td>\n",
362 " <td>14863.0</td>\n",
363 " <td>13751</td>\n",
364 " <td>13870.2</td>\n",
365 " </tr>\n",
366 " <tr>\n",
367 " <td>2020-01-10</td>\n",
368 " <td>16020.0</td>\n",
369 " <td>14487.0</td>\n",
370 " <td>17430.0</td>\n",
371 " <td>15528.0</td>\n",
372 " <td>13154.0</td>\n",
373 " <td>18318</td>\n",
374 " <td>15783.4</td>\n",
375 " </tr>\n",
376 " <tr>\n",
377 " <td>2020-01-17</td>\n",
378 " <td>14723.0</td>\n",
379 " <td>13545.0</td>\n",
380 " <td>16355.0</td>\n",
381 " <td>15231.0</td>\n",
382 " <td>13060.0</td>\n",
383 " <td>16738</td>\n",
384 " <td>14985.8</td>\n",
385 " </tr>\n",
386 " <tr>\n",
387 " <td>2020-01-24</td>\n",
388 " <td>13429.0</td>\n",
389 " <td>13283.0</td>\n",
390 " <td>15971.0</td>\n",
391 " <td>14461.0</td>\n",
392 " <td>12859.0</td>\n",
393 " <td>15712</td>\n",
394 " <td>14457.2</td>\n",
395 " </tr>\n",
396 " <tr>\n",
397 " <td>2020-01-31</td>\n",
398 " <td>13123.0</td>\n",
399 " <td>12799.0</td>\n",
400 " <td>15087.0</td>\n",
401 " <td>14188.0</td>\n",
402 " <td>12571.0</td>\n",
403 " <td>14560</td>\n",
404 " <td>13841.0</td>\n",
405 " </tr>\n",
406 " <tr>\n",
407 " <td>2020-02-07</td>\n",
408 " <td>12534.0</td>\n",
409 " <td>13222.0</td>\n",
410 " <td>14111.0</td>\n",
411 " <td>13805.0</td>\n",
412 " <td>12697.0</td>\n",
413 " <td>13730</td>\n",
414 " <td>13513.0</td>\n",
415 " </tr>\n",
416 " <tr>\n",
417 " <td>2020-02-14</td>\n",
418 " <td>12412.0</td>\n",
419 " <td>13347.0</td>\n",
420 " <td>13925.0</td>\n",
421 " <td>13212.0</td>\n",
422 " <td>12016.0</td>\n",
423 " <td>13510</td>\n",
424 " <td>13202.0</td>\n",
425 " </tr>\n",
426 " <tr>\n",
427 " <td>2020-02-21</td>\n",
428 " <td>12300.0</td>\n",
429 " <td>12877.0</td>\n",
430 " <td>13753.0</td>\n",
431 " <td>13330.0</td>\n",
432 " <td>12718.0</td>\n",
433 " <td>13071</td>\n",
434 " <td>13149.8</td>\n",
435 " </tr>\n",
436 " <tr>\n",
437 " <td>2020-02-28</td>\n",
438 " <td>12334.0</td>\n",
439 " <td>12479.0</td>\n",
440 " <td>12190.0</td>\n",
441 " <td>12819.0</td>\n",
442 " <td>12733.0</td>\n",
443 " <td>13181</td>\n",
444 " <td>12680.4</td>\n",
445 " </tr>\n",
446 " <tr>\n",
447 " <td>2020-03-06</td>\n",
448 " <td>12415.0</td>\n",
449 " <td>12396.0</td>\n",
450 " <td>14859.0</td>\n",
451 " <td>12580.0</td>\n",
452 " <td>12493.0</td>\n",
453 " <td>13007</td>\n",
454 " <td>13067.0</td>\n",
455 " </tr>\n",
456 " <tr>\n",
457 " <td>2020-03-13</td>\n",
458 " <td>12499.0</td>\n",
459 " <td>12018.0</td>\n",
460 " <td>14367.0</td>\n",
461 " <td>12089.0</td>\n",
462 " <td>12489.0</td>\n",
463 " <td>12475</td>\n",
464 " <td>12687.6</td>\n",
465 " </tr>\n",
466 " <tr>\n",
467 " <td>2020-03-20</td>\n",
468 " <td>12112.0</td>\n",
469 " <td>11797.0</td>\n",
470 " <td>13397.0</td>\n",
471 " <td>11833.0</td>\n",
472 " <td>10983.0</td>\n",
473 " <td>12027</td>\n",
474 " <td>12007.4</td>\n",
475 " </tr>\n",
476 " <tr>\n",
477 " <td>2020-03-27</td>\n",
478 " <td>12507.0</td>\n",
479 " <td>11260.0</td>\n",
480 " <td>11310.0</td>\n",
481 " <td>11453.0</td>\n",
482 " <td>11738.0</td>\n",
483 " <td>11987</td>\n",
484 " <td>11549.6</td>\n",
485 " </tr>\n",
486 " <tr>\n",
487 " <td>2020-04-03</td>\n",
488 " <td>18565.0</td>\n",
489 " <td>11445.0</td>\n",
490 " <td>12272.0</td>\n",
491 " <td>11305.0</td>\n",
492 " <td>13060.0</td>\n",
493 " <td>10325</td>\n",
494 " <td>11681.4</td>\n",
495 " </tr>\n",
496 " <tr>\n",
497 " <td>2020-04-10</td>\n",
498 " <td>20929.0</td>\n",
499 " <td>11661.0</td>\n",
500 " <td>13843.0</td>\n",
501 " <td>9761.0</td>\n",
502 " <td>12757.0</td>\n",
503 " <td>11575</td>\n",
504 " <td>11919.4</td>\n",
505 " </tr>\n",
506 " <tr>\n",
507 " <td>2020-04-17</td>\n",
508 " <td>24691.0</td>\n",
509 " <td>10243.0</td>\n",
510 " <td>12639.0</td>\n",
511 " <td>11000.0</td>\n",
512 " <td>12310.0</td>\n",
513 " <td>13061</td>\n",
514 " <td>11850.6</td>\n",
515 " </tr>\n",
516 " <tr>\n",
517 " <td>2020-04-24</td>\n",
518 " <td>24303.0</td>\n",
519 " <td>11452.0</td>\n",
520 " <td>11596.0</td>\n",
521 " <td>12356.0</td>\n",
522 " <td>11795.0</td>\n",
523 " <td>12023</td>\n",
524 " <td>11844.4</td>\n",
525 " </tr>\n",
526 " <tr>\n",
527 " <td>2020-05-01</td>\n",
528 " <td>20059.0</td>\n",
529 " <td>12695.0</td>\n",
530 " <td>11538.0</td>\n",
531 " <td>10372.0</td>\n",
532 " <td>10401.0</td>\n",
533 " <td>11586</td>\n",
534 " <td>11318.4</td>\n",
535 " </tr>\n",
536 " <tr>\n",
537 " <td>2020-05-08</td>\n",
538 " <td>14428.0</td>\n",
539 " <td>10361.0</td>\n",
540 " <td>9821.0</td>\n",
541 " <td>12114.0</td>\n",
542 " <td>12002.0</td>\n",
543 " <td>10138</td>\n",
544 " <td>10887.2</td>\n",
545 " </tr>\n",
546 " <tr>\n",
547 " <td>2020-05-15</td>\n",
548 " <td>16390.0</td>\n",
549 " <td>11717.0</td>\n",
550 " <td>11386.0</td>\n",
551 " <td>11718.0</td>\n",
552 " <td>11222.0</td>\n",
553 " <td>11692</td>\n",
554 " <td>11547.0</td>\n",
555 " </tr>\n",
556 " <tr>\n",
557 " <td>2020-05-22</td>\n",
558 " <td>13839.0</td>\n",
559 " <td>11653.0</td>\n",
560 " <td>10974.0</td>\n",
561 " <td>11431.0</td>\n",
562 " <td>11013.0</td>\n",
563 " <td>11334</td>\n",
564 " <td>11281.0</td>\n",
565 " </tr>\n",
566 " <tr>\n",
567 " <td>2020-05-29</td>\n",
568 " <td>11265.0</td>\n",
569 " <td>9534.0</td>\n",
570 " <td>9397.0</td>\n",
571 " <td>9603.0</td>\n",
572 " <td>9192.0</td>\n",
573 " <td>9514</td>\n",
574 " <td>9448.0</td>\n",
575 " </tr>\n",
576 " <tr>\n",
577 " <td>2020-06-05</td>\n",
578 " <td>12106.0</td>\n",
579 " <td>11461.0</td>\n",
580 " <td>11259.0</td>\n",
581 " <td>11134.0</td>\n",
582 " <td>11171.0</td>\n",
583 " <td>11603</td>\n",
584 " <td>11325.6</td>\n",
585 " </tr>\n",
586 " <tr>\n",
587 " <td>2020-06-12</td>\n",
588 " <td>11302.0</td>\n",
589 " <td>10754.0</td>\n",
590 " <td>10535.0</td>\n",
591 " <td>10698.0</td>\n",
592 " <td>10673.0</td>\n",
593 " <td>10858</td>\n",
594 " <td>10703.6</td>\n",
595 " </tr>\n",
596 " <tr>\n",
597 " <td>2020-06-19</td>\n",
598 " <td>10694.0</td>\n",
599 " <td>10807.0</td>\n",
600 " <td>10514.0</td>\n",
601 " <td>10930.0</td>\n",
602 " <td>10611.0</td>\n",
603 " <td>10629</td>\n",
604 " <td>10698.2</td>\n",
605 " </tr>\n",
606 " <tr>\n",
607 " <td>2020-06-26</td>\n",
608 " <td>10282.0</td>\n",
609 " <td>10824.0</td>\n",
610 " <td>10529.0</td>\n",
611 " <td>10624.0</td>\n",
612 " <td>10526.0</td>\n",
613 " <td>10525</td>\n",
614 " <td>10605.6</td>\n",
615 " </tr>\n",
616 " <tr>\n",
617 " <td>2020-07-03</td>\n",
618 " <td>10412.0</td>\n",
619 " <td>10328.0</td>\n",
620 " <td>10565.0</td>\n",
621 " <td>10565.0</td>\n",
622 " <td>10412.0</td>\n",
623 " <td>10545</td>\n",
624 " <td>10483.0</td>\n",
625 " </tr>\n",
626 " <tr>\n",
627 " <td>2020-07-10</td>\n",
628 " <td>9941.0</td>\n",
629 " <td>10512.0</td>\n",
630 " <td>10467.0</td>\n",
631 " <td>10643.0</td>\n",
632 " <td>10647.0</td>\n",
633 " <td>10278</td>\n",
634 " <td>10509.4</td>\n",
635 " </tr>\n",
636 " <tr>\n",
637 " <td>2020-07-17</td>\n",
638 " <td>10096.0</td>\n",
639 " <td>10324.0</td>\n",
640 " <td>10353.0</td>\n",
641 " <td>10426.0</td>\n",
642 " <td>10672.0</td>\n",
643 " <td>10028</td>\n",
644 " <td>10360.6</td>\n",
645 " </tr>\n",
646 " <tr>\n",
647 " <td>2020-07-24</td>\n",
648 " <td>10159.0</td>\n",
649 " <td>10422.0</td>\n",
650 " <td>10356.0</td>\n",
651 " <td>10147.0</td>\n",
652 " <td>10612.0</td>\n",
653 " <td>10021</td>\n",
654 " <td>10311.6</td>\n",
655 " </tr>\n",
656 " <tr>\n",
657 " <td>2020-07-31</td>\n",
658 " <td>10262.0</td>\n",
659 " <td>10564.0</td>\n",
660 " <td>10408.0</td>\n",
661 " <td>10239.0</td>\n",
662 " <td>10433.0</td>\n",
663 " <td>9893</td>\n",
664 " <td>10307.4</td>\n",
665 " </tr>\n",
666 " <tr>\n",
667 " <td>2020-08-07</td>\n",
668 " <td>10236.0</td>\n",
669 " <td>10406.0</td>\n",
670 " <td>10542.0</td>\n",
671 " <td>10278.0</td>\n",
672 " <td>10439.0</td>\n",
673 " <td>10153</td>\n",
674 " <td>10363.6</td>\n",
675 " </tr>\n",
676 " <tr>\n",
677 " <td>2020-08-14</td>\n",
678 " <td>10592.0</td>\n",
679 " <td>10405.0</td>\n",
680 " <td>10091.0</td>\n",
681 " <td>10569.0</td>\n",
682 " <td>10312.0</td>\n",
683 " <td>10352</td>\n",
684 " <td>10345.8</td>\n",
685 " </tr>\n",
686 " <tr>\n",
687 " <td>2020-08-21</td>\n",
688 " <td>10990.0</td>\n",
689 " <td>10279.0</td>\n",
690 " <td>10199.0</td>\n",
691 " <td>10698.0</td>\n",
692 " <td>10637.0</td>\n",
693 " <td>10354</td>\n",
694 " <td>10433.4</td>\n",
695 " </tr>\n",
696 " <tr>\n",
697 " <td>2020-08-28</td>\n",
698 " <td>10364.0</td>\n",
699 " <td>9478.0</td>\n",
700 " <td>9046.0</td>\n",
701 " <td>9372.0</td>\n",
702 " <td>9226.0</td>\n",
703 " <td>10239</td>\n",
704 " <td>9472.2</td>\n",
705 " </tr>\n",
706 " <tr>\n",
707 " <td>2020-09-04</td>\n",
708 " <td>9023.0</td>\n",
709 " <td>10918.0</td>\n",
710 " <td>10680.0</td>\n",
711 " <td>10781.0</td>\n",
712 " <td>10681.0</td>\n",
713 " <td>9092</td>\n",
714 " <td>10430.4</td>\n",
715 " </tr>\n",
716 " <tr>\n",
717 " <td>2020-09-11</td>\n",
718 " <td>11176.0</td>\n",
719 " <td>10892.0</td>\n",
720 " <td>10496.0</td>\n",
721 " <td>10692.0</td>\n",
722 " <td>10401.0</td>\n",
723 " <td>10573</td>\n",
724 " <td>10610.8</td>\n",
725 " </tr>\n",
726 " <tr>\n",
727 " <td>2020-09-18</td>\n",
728 " <td>10797.0</td>\n",
729 " <td>10792.0</td>\n",
730 " <td>10498.0</td>\n",
731 " <td>10875.0</td>\n",
732 " <td>10183.0</td>\n",
733 " <td>10381</td>\n",
734 " <td>10545.8</td>\n",
735 " </tr>\n",
736 " <tr>\n",
737 " <td>2020-09-25</td>\n",
738 " <td>10890.0</td>\n",
739 " <td>10954.0</td>\n",
740 " <td>10463.0</td>\n",
741 " <td>11027.0</td>\n",
742 " <td>10278.0</td>\n",
743 " <td>10826</td>\n",
744 " <td>10709.6</td>\n",
745 " </tr>\n",
746 " <tr>\n",
747 " <td>2020-10-02</td>\n",
748 " <td>11468.0</td>\n",
749 " <td>11113.0</td>\n",
750 " <td>10869.0</td>\n",
751 " <td>11101.0</td>\n",
752 " <td>10671.0</td>\n",
753 " <td>10700</td>\n",
754 " <td>10890.8</td>\n",
755 " </tr>\n",
756 " <tr>\n",
757 " <td>2020-10-09</td>\n",
758 " <td>11373.0</td>\n",
759 " <td>11403.0</td>\n",
760 " <td>11048.0</td>\n",
761 " <td>11357.0</td>\n",
762 " <td>11016.0</td>\n",
763 " <td>11108</td>\n",
764 " <td>11186.4</td>\n",
765 " </tr>\n",
766 " <tr>\n",
767 " <td>2020-10-16</td>\n",
768 " <td>11943.0</td>\n",
769 " <td>11625.0</td>\n",
770 " <td>11177.0</td>\n",
771 " <td>11389.0</td>\n",
772 " <td>11134.0</td>\n",
773 " <td>10799</td>\n",
774 " <td>11224.8</td>\n",
775 " </tr>\n",
776 " <tr>\n",
777 " <td>2020-10-23</td>\n",
778 " <td>12317.0</td>\n",
779 " <td>11415.0</td>\n",
780 " <td>10885.0</td>\n",
781 " <td>11152.0</td>\n",
782 " <td>11048.0</td>\n",
783 " <td>10966</td>\n",
784 " <td>11093.2</td>\n",
785 " </tr>\n",
786 " <tr>\n",
787 " <td>2020-10-30</td>\n",
788 " <td>12517.0</td>\n",
789 " <td>11567.0</td>\n",
790 " <td>10866.0</td>\n",
791 " <td>11366.0</td>\n",
792 " <td>11463.0</td>\n",
793 " <td>11026</td>\n",
794 " <td>11257.6</td>\n",
795 " </tr>\n",
796 " <tr>\n",
797 " <td>2020-11-06</td>\n",
798 " <td>13448.0</td>\n",
799 " <td>12177.0</td>\n",
800 " <td>11588.0</td>\n",
801 " <td>11767.0</td>\n",
802 " <td>11803.0</td>\n",
803 " <td>11312</td>\n",
804 " <td>11729.4</td>\n",
805 " </tr>\n",
806 " <tr>\n",
807 " <td>2020-11-13</td>\n",
808 " <td>13798.0</td>\n",
809 " <td>12146.0</td>\n",
810 " <td>11552.0</td>\n",
811 " <td>11773.0</td>\n",
812 " <td>12209.0</td>\n",
813 " <td>11338</td>\n",
814 " <td>11803.6</td>\n",
815 " </tr>\n",
816 " <tr>\n",
817 " <td>2020-11-20</td>\n",
818 " <td>14291.0</td>\n",
819 " <td>12472.0</td>\n",
820 " <td>11289.0</td>\n",
821 " <td>12102.0</td>\n",
822 " <td>12064.0</td>\n",
823 " <td>11178</td>\n",
824 " <td>11821.0</td>\n",
825 " </tr>\n",
826 " <tr>\n",
827 " <td>2020-11-27</td>\n",
828 " <td>14132.0</td>\n",
829 " <td>12455.0</td>\n",
830 " <td>11392.0</td>\n",
831 " <td>12046.0</td>\n",
832 " <td>11901.0</td>\n",
833 " <td>11216</td>\n",
834 " <td>11802.0</td>\n",
835 " </tr>\n",
836 " <tr>\n",
837 " <td>2020-12-04</td>\n",
838 " <td>NaN</td>\n",
839 " <td>12275.0</td>\n",
840 " <td>11687.0</td>\n",
841 " <td>12342.0</td>\n",
842 " <td>12733.0</td>\n",
843 " <td>11748</td>\n",
844 " <td>12157.0</td>\n",
845 " </tr>\n",
846 " <tr>\n",
847 " <td>2020-12-11</td>\n",
848 " <td>NaN</td>\n",
849 " <td>12853.0</td>\n",
850 " <td>12078.0</td>\n",
851 " <td>12924.0</td>\n",
852 " <td>12076.0</td>\n",
853 " <td>11713</td>\n",
854 " <td>12328.8</td>\n",
855 " </tr>\n",
856 " <tr>\n",
857 " <td>2020-12-18</td>\n",
858 " <td>NaN</td>\n",
859 " <td>13566.0</td>\n",
860 " <td>12649.0</td>\n",
861 " <td>14308.0</td>\n",
862 " <td>13137.0</td>\n",
863 " <td>12136</td>\n",
864 " <td>13159.2</td>\n",
865 " </tr>\n",
866 " <tr>\n",
867 " <td>2020-12-25</td>\n",
868 " <td>NaN</td>\n",
869 " <td>8727.0</td>\n",
870 " <td>8384.0</td>\n",
871 " <td>9904.0</td>\n",
872 " <td>9335.0</td>\n",
873 " <td>9806</td>\n",
874 " <td>9231.2</td>\n",
875 " </tr>\n",
876 " </tbody>\n",
877 "</table>\n",
878 "</div>"
879 ],
880 "text/plain": [
881 " total_2020 total_2019 total_2018 total_2017 total_2016 \\\n",
882 "week_ended \n",
883 "2020-01-03 13768.0 12424.0 14701.0 13612.0 14863.0 \n",
884 "2020-01-10 16020.0 14487.0 17430.0 15528.0 13154.0 \n",
885 "2020-01-17 14723.0 13545.0 16355.0 15231.0 13060.0 \n",
886 "2020-01-24 13429.0 13283.0 15971.0 14461.0 12859.0 \n",
887 "2020-01-31 13123.0 12799.0 15087.0 14188.0 12571.0 \n",
888 "2020-02-07 12534.0 13222.0 14111.0 13805.0 12697.0 \n",
889 "2020-02-14 12412.0 13347.0 13925.0 13212.0 12016.0 \n",
890 "2020-02-21 12300.0 12877.0 13753.0 13330.0 12718.0 \n",
891 "2020-02-28 12334.0 12479.0 12190.0 12819.0 12733.0 \n",
892 "2020-03-06 12415.0 12396.0 14859.0 12580.0 12493.0 \n",
893 "2020-03-13 12499.0 12018.0 14367.0 12089.0 12489.0 \n",
894 "2020-03-20 12112.0 11797.0 13397.0 11833.0 10983.0 \n",
895 "2020-03-27 12507.0 11260.0 11310.0 11453.0 11738.0 \n",
896 "2020-04-03 18565.0 11445.0 12272.0 11305.0 13060.0 \n",
897 "2020-04-10 20929.0 11661.0 13843.0 9761.0 12757.0 \n",
898 "2020-04-17 24691.0 10243.0 12639.0 11000.0 12310.0 \n",
899 "2020-04-24 24303.0 11452.0 11596.0 12356.0 11795.0 \n",
900 "2020-05-01 20059.0 12695.0 11538.0 10372.0 10401.0 \n",
901 "2020-05-08 14428.0 10361.0 9821.0 12114.0 12002.0 \n",
902 "2020-05-15 16390.0 11717.0 11386.0 11718.0 11222.0 \n",
903 "2020-05-22 13839.0 11653.0 10974.0 11431.0 11013.0 \n",
904 "2020-05-29 11265.0 9534.0 9397.0 9603.0 9192.0 \n",
905 "2020-06-05 12106.0 11461.0 11259.0 11134.0 11171.0 \n",
906 "2020-06-12 11302.0 10754.0 10535.0 10698.0 10673.0 \n",
907 "2020-06-19 10694.0 10807.0 10514.0 10930.0 10611.0 \n",
908 "2020-06-26 10282.0 10824.0 10529.0 10624.0 10526.0 \n",
909 "2020-07-03 10412.0 10328.0 10565.0 10565.0 10412.0 \n",
910 "2020-07-10 9941.0 10512.0 10467.0 10643.0 10647.0 \n",
911 "2020-07-17 10096.0 10324.0 10353.0 10426.0 10672.0 \n",
912 "2020-07-24 10159.0 10422.0 10356.0 10147.0 10612.0 \n",
913 "2020-07-31 10262.0 10564.0 10408.0 10239.0 10433.0 \n",
914 "2020-08-07 10236.0 10406.0 10542.0 10278.0 10439.0 \n",
915 "2020-08-14 10592.0 10405.0 10091.0 10569.0 10312.0 \n",
916 "2020-08-21 10990.0 10279.0 10199.0 10698.0 10637.0 \n",
917 "2020-08-28 10364.0 9478.0 9046.0 9372.0 9226.0 \n",
918 "2020-09-04 9023.0 10918.0 10680.0 10781.0 10681.0 \n",
919 "2020-09-11 11176.0 10892.0 10496.0 10692.0 10401.0 \n",
920 "2020-09-18 10797.0 10792.0 10498.0 10875.0 10183.0 \n",
921 "2020-09-25 10890.0 10954.0 10463.0 11027.0 10278.0 \n",
922 "2020-10-02 11468.0 11113.0 10869.0 11101.0 10671.0 \n",
923 "2020-10-09 11373.0 11403.0 11048.0 11357.0 11016.0 \n",
924 "2020-10-16 11943.0 11625.0 11177.0 11389.0 11134.0 \n",
925 "2020-10-23 12317.0 11415.0 10885.0 11152.0 11048.0 \n",
926 "2020-10-30 12517.0 11567.0 10866.0 11366.0 11463.0 \n",
927 "2020-11-06 13448.0 12177.0 11588.0 11767.0 11803.0 \n",
928 "2020-11-13 13798.0 12146.0 11552.0 11773.0 12209.0 \n",
929 "2020-11-20 14291.0 12472.0 11289.0 12102.0 12064.0 \n",
930 "2020-11-27 14132.0 12455.0 11392.0 12046.0 11901.0 \n",
931 "2020-12-04 NaN 12275.0 11687.0 12342.0 12733.0 \n",
932 "2020-12-11 NaN 12853.0 12078.0 12924.0 12076.0 \n",
933 "2020-12-18 NaN 13566.0 12649.0 14308.0 13137.0 \n",
934 "2020-12-25 NaN 8727.0 8384.0 9904.0 9335.0 \n",
935 "\n",
936 " total_2015 previous_mean \n",
937 "week_ended \n",
938 "2020-01-03 13751 13870.2 \n",
939 "2020-01-10 18318 15783.4 \n",
940 "2020-01-17 16738 14985.8 \n",
941 "2020-01-24 15712 14457.2 \n",
942 "2020-01-31 14560 13841.0 \n",
943 "2020-02-07 13730 13513.0 \n",
944 "2020-02-14 13510 13202.0 \n",
945 "2020-02-21 13071 13149.8 \n",
946 "2020-02-28 13181 12680.4 \n",
947 "2020-03-06 13007 13067.0 \n",
948 "2020-03-13 12475 12687.6 \n",
949 "2020-03-20 12027 12007.4 \n",
950 "2020-03-27 11987 11549.6 \n",
951 "2020-04-03 10325 11681.4 \n",
952 "2020-04-10 11575 11919.4 \n",
953 "2020-04-17 13061 11850.6 \n",
954 "2020-04-24 12023 11844.4 \n",
955 "2020-05-01 11586 11318.4 \n",
956 "2020-05-08 10138 10887.2 \n",
957 "2020-05-15 11692 11547.0 \n",
958 "2020-05-22 11334 11281.0 \n",
959 "2020-05-29 9514 9448.0 \n",
960 "2020-06-05 11603 11325.6 \n",
961 "2020-06-12 10858 10703.6 \n",
962 "2020-06-19 10629 10698.2 \n",
963 "2020-06-26 10525 10605.6 \n",
964 "2020-07-03 10545 10483.0 \n",
965 "2020-07-10 10278 10509.4 \n",
966 "2020-07-17 10028 10360.6 \n",
967 "2020-07-24 10021 10311.6 \n",
968 "2020-07-31 9893 10307.4 \n",
969 "2020-08-07 10153 10363.6 \n",
970 "2020-08-14 10352 10345.8 \n",
971 "2020-08-21 10354 10433.4 \n",
972 "2020-08-28 10239 9472.2 \n",
973 "2020-09-04 9092 10430.4 \n",
974 "2020-09-11 10573 10610.8 \n",
975 "2020-09-18 10381 10545.8 \n",
976 "2020-09-25 10826 10709.6 \n",
977 "2020-10-02 10700 10890.8 \n",
978 "2020-10-09 11108 11186.4 \n",
979 "2020-10-16 10799 11224.8 \n",
980 "2020-10-23 10966 11093.2 \n",
981 "2020-10-30 11026 11257.6 \n",
982 "2020-11-06 11312 11729.4 \n",
983 "2020-11-13 11338 11803.6 \n",
984 "2020-11-20 11178 11821.0 \n",
985 "2020-11-27 11216 11802.0 \n",
986 "2020-12-04 11748 12157.0 \n",
987 "2020-12-11 11713 12328.8 \n",
988 "2020-12-18 12136 13159.2 \n",
989 "2020-12-25 9806 9231.2 "
990 ]
991 },
992 "execution_count": 67,
993 "metadata": {},
994 "output_type": "execute_result"
995 }
996 ],
997 "source": [
998 "deaths_by_week = pd.read_csv('deaths_by_week.csv', index_col='week_ended', parse_dates=True)\n",
999 "deaths_by_week"
1000 ]
1001 },
1002 {
1003 "cell_type": "code",
1004 "execution_count": 68,
1005 "metadata": {
1006 "Collapsed": "false"
1007 },
1008 "outputs": [
1009 {
1010 "data": {
1011 "text/html": [
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1025 "</style>\n",
1026 "<table border=\"1\" class=\"dataframe\">\n",
1027 " <thead>\n",
1028 " <tr style=\"text-align: right;\">\n",
1029 " <th></th>\n",
1030 " <th>cases</th>\n",
1031 " <th>deaths</th>\n",
1032 " <th>cases_culm</th>\n",
1033 " <th>deaths_culm</th>\n",
1034 " <th>cases_diff</th>\n",
1035 " <th>deaths_diff</th>\n",
1036 " <th>cases_m7</th>\n",
1037 " <th>deaths_m7</th>\n",
1038 " <th>deaths_g4</th>\n",
1039 " <th>deaths_g7</th>\n",
1040 " <th>doubling_time</th>\n",
1041 " <th>doubling_time_7</th>\n",
1042 " </tr>\n",
1043 " <tr>\n",
1044 " <th>dateRep</th>\n",
1045 " <th></th>\n",
1046 " <th></th>\n",
1047 " <th></th>\n",
1048 " <th></th>\n",
1049 " <th></th>\n",
1050 " <th></th>\n",
1051 " <th></th>\n",
1052 " <th></th>\n",
1053 " <th></th>\n",
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1055 " <th></th>\n",
1056 " <th></th>\n",
1057 " </tr>\n",
1058 " </thead>\n",
1059 " <tbody>\n",
1060 " <tr>\n",
1061 " <td>2020-01-03</td>\n",
1062 " <td>0</td>\n",
1063 " <td>0</td>\n",
1064 " <td>0</td>\n",
1065 " <td>0</td>\n",
1066 " <td>0.0</td>\n",
1067 " <td>0.0</td>\n",
1068 " <td>0.000000</td>\n",
1069 " <td>0.000000</td>\n",
1070 " <td>0.000000</td>\n",
1071 " <td>0.000000</td>\n",
1072 " <td>0.000000e+00</td>\n",
1073 " <td>0.000000e+00</td>\n",
1074 " </tr>\n",
1075 " <tr>\n",
1076 " <td>2020-01-10</td>\n",
1077 " <td>0</td>\n",
1078 " <td>0</td>\n",
1079 " <td>0</td>\n",
1080 " <td>0</td>\n",
1081 " <td>0.0</td>\n",
1082 " <td>0.0</td>\n",
1083 " <td>0.000000</td>\n",
1084 " <td>0.000000</td>\n",
1085 " <td>0.000000</td>\n",
1086 " <td>0.000000</td>\n",
1087 " <td>0.000000e+00</td>\n",
1088 " <td>0.000000e+00</td>\n",
1089 " </tr>\n",
1090 " <tr>\n",
1091 " <td>2020-01-17</td>\n",
1092 " <td>0</td>\n",
1093 " <td>0</td>\n",
1094 " <td>0</td>\n",
1095 " <td>0</td>\n",
1096 " <td>0.0</td>\n",
1097 " <td>0.0</td>\n",
1098 " <td>0.000000</td>\n",
1099 " <td>0.000000</td>\n",
1100 " <td>0.000000</td>\n",
1101 " <td>0.000000</td>\n",
1102 " <td>0.000000e+00</td>\n",
1103 " <td>0.000000e+00</td>\n",
1104 " </tr>\n",
1105 " <tr>\n",
1106 " <td>2020-01-24</td>\n",
1107 " <td>0</td>\n",
1108 " <td>0</td>\n",
1109 " <td>0</td>\n",
1110 " <td>0</td>\n",
1111 " <td>0.0</td>\n",
1112 " <td>0.0</td>\n",
1113 " <td>0.000000</td>\n",
1114 " <td>0.000000</td>\n",
1115 " <td>0.000000</td>\n",
1116 " <td>0.000000</td>\n",
1117 " <td>0.000000e+00</td>\n",
1118 " <td>0.000000e+00</td>\n",
1119 " </tr>\n",
1120 " <tr>\n",
1121 " <td>2020-01-31</td>\n",
1122 " <td>0</td>\n",
1123 " <td>0</td>\n",
1124 " <td>0</td>\n",
1125 " <td>0</td>\n",
1126 " <td>0.0</td>\n",
1127 " <td>0.0</td>\n",
1128 " <td>0.000000</td>\n",
1129 " <td>0.000000</td>\n",
1130 " <td>0.000000</td>\n",
1131 " <td>0.000000</td>\n",
1132 " <td>0.000000e+00</td>\n",
1133 " <td>0.000000e+00</td>\n",
1134 " </tr>\n",
1135 " <tr>\n",
1136 " <td>2020-02-07</td>\n",
1137 " <td>4</td>\n",
1138 " <td>0</td>\n",
1139 " <td>18</td>\n",
1140 " <td>0</td>\n",
1141 " <td>1.0</td>\n",
1142 " <td>0.0</td>\n",
1143 " <td>2.571429</td>\n",
1144 " <td>0.000000</td>\n",
1145 " <td>0.000000</td>\n",
1146 " <td>0.000000</td>\n",
1147 " <td>0.000000e+00</td>\n",
1148 " <td>0.000000e+00</td>\n",
1149 " </tr>\n",
1150 " <tr>\n",
1151 " <td>2020-02-14</td>\n",
1152 " <td>6</td>\n",
1153 " <td>0</td>\n",
1154 " <td>54</td>\n",
1155 " <td>0</td>\n",
1156 " <td>-1.0</td>\n",
1157 " <td>0.0</td>\n",
1158 " <td>5.142857</td>\n",
1159 " <td>0.000000</td>\n",
1160 " <td>0.000000</td>\n",
1161 " <td>0.000000</td>\n",
1162 " <td>0.000000e+00</td>\n",
1163 " <td>0.000000e+00</td>\n",
1164 " </tr>\n",
1165 " <tr>\n",
1166 " <td>2020-02-21</td>\n",
1167 " <td>0</td>\n",
1168 " <td>0</td>\n",
1169 " <td>70</td>\n",
1170 " <td>0</td>\n",
1171 " <td>0.0</td>\n",
1172 " <td>0.0</td>\n",
1173 " <td>2.285714</td>\n",
1174 " <td>0.000000</td>\n",
1175 " <td>0.000000</td>\n",
1176 " <td>0.000000</td>\n",
1177 " <td>0.000000e+00</td>\n",
1178 " <td>0.000000e+00</td>\n",
1179 " </tr>\n",
1180 " <tr>\n",
1181 " <td>2020-02-28</td>\n",
1182 " <td>12</td>\n",
1183 " <td>0</td>\n",
1184 " <td>96</td>\n",
1185 " <td>0</td>\n",
1186 " <td>4.0</td>\n",
1187 " <td>0.0</td>\n",
1188 " <td>3.714286</td>\n",
1189 " <td>0.000000</td>\n",
1190 " <td>0.000000</td>\n",
1191 " <td>0.000000</td>\n",
1192 " <td>0.000000e+00</td>\n",
1193 " <td>0.000000e+00</td>\n",
1194 " </tr>\n",
1195 " <tr>\n",
1196 " <td>2020-03-06</td>\n",
1197 " <td>198</td>\n",
1198 " <td>0</td>\n",
1199 " <td>681</td>\n",
1200 " <td>0</td>\n",
1201 " <td>52.0</td>\n",
1202 " <td>0.0</td>\n",
1203 " <td>83.571429</td>\n",
1204 " <td>0.000000</td>\n",
1205 " <td>0.000000</td>\n",
1206 " <td>0.000000</td>\n",
1207 " <td>0.000000e+00</td>\n",
1208 " <td>0.000000e+00</td>\n",
1209 " </tr>\n",
1210 " <tr>\n",
1211 " <td>2020-03-13</td>\n",
1212 " <td>1062</td>\n",
1213 " <td>9</td>\n",
1214 " <td>4279</td>\n",
1215 " <td>31</td>\n",
1216 " <td>350.0</td>\n",
1217 " <td>2.0</td>\n",
1218 " <td>514.000000</td>\n",
1219 " <td>4.428571</td>\n",
1220 " <td>0.000000</td>\n",
1221 " <td>0.000000</td>\n",
1222 " <td>inf</td>\n",
1223 " <td>inf</td>\n",
1224 " </tr>\n",
1225 " <tr>\n",
1226 " <td>2020-03-20</td>\n",
1227 " <td>4144</td>\n",
1228 " <td>153</td>\n",
1229 " <td>23173</td>\n",
1230 " <td>507</td>\n",
1231 " <td>593.0</td>\n",
1232 " <td>44.0</td>\n",
1233 " <td>2699.142857</td>\n",
1234 " <td>68.000000</td>\n",
1235 " <td>79.504887</td>\n",
1236 " <td>24.257733</td>\n",
1237 " <td>inf</td>\n",
1238 " <td>inf</td>\n",
1239 " </tr>\n",
1240 " <tr>\n",
1241 " <td>2020-03-27</td>\n",
1242 " <td>12291</td>\n",
1243 " <td>722</td>\n",
1244 " <td>78855</td>\n",
1245 " <td>3197</td>\n",
1246 " <td>1693.0</td>\n",
1247 " <td>135.0</td>\n",
1248 " <td>7954.571429</td>\n",
1249 " <td>384.285714</td>\n",
1250 " <td>464.807614</td>\n",
1251 " <td>327.583287</td>\n",
1252 " <td>3.577040e+01</td>\n",
1253 " <td>4.797282e+01</td>\n",
1254 " </tr>\n",
1255 " <tr>\n",
1256 " <td>2020-04-03</td>\n",
1257 " <td>25664</td>\n",
1258 " <td>2898</td>\n",
1259 " <td>217112</td>\n",
1260 " <td>15722</td>\n",
1261 " <td>2221.0</td>\n",
1262 " <td>476.0</td>\n",
1263 " <td>19751.000000</td>\n",
1264 " <td>1789.285714</td>\n",
1265 " <td>2153.720503</td>\n",
1266 " <td>1633.574291</td>\n",
1267 " <td>3.702651e+01</td>\n",
1268 " <td>4.931862e+01</td>\n",
1269 " </tr>\n",
1270 " <tr>\n",
1271 " <td>2020-04-10</td>\n",
1272 " <td>33254</td>\n",
1273 " <td>5909</td>\n",
1274 " <td>433554</td>\n",
1275 " <td>47916</td>\n",
1276 " <td>218.0</td>\n",
1277 " <td>459.0</td>\n",
1278 " <td>30920.285714</td>\n",
1279 " <td>4599.142857</td>\n",
1280 " <td>5088.524097</td>\n",
1281 " <td>4416.476344</td>\n",
1282 " <td>4.749914e+01</td>\n",
1283 " <td>5.457682e+01</td>\n",
1284 " </tr>\n",
1285 " <tr>\n",
1286 " <td>2020-04-17</td>\n",
1287 " <td>29808</td>\n",
1288 " <td>6338</td>\n",
1289 " <td>654431</td>\n",
1290 " <td>92954</td>\n",
1291 " <td>-66.0</td>\n",
1292 " <td>-80.0</td>\n",
1293 " <td>31553.857143</td>\n",
1294 " <td>6434.000000</td>\n",
1295 " <td>6392.991495</td>\n",
1296 " <td>6269.311492</td>\n",
1297 " <td>7.441501e+01</td>\n",
1298 " <td>7.427834e+01</td>\n",
1299 " </tr>\n",
1300 " <tr>\n",
1301 " <td>2020-04-24</td>\n",
1302 " <td>33923</td>\n",
1303 " <td>5773</td>\n",
1304 " <td>880467</td>\n",
1305 " <td>135712</td>\n",
1306 " <td>422.0</td>\n",
1307 " <td>-354.0</td>\n",
1308 " <td>32290.857143</td>\n",
1309 " <td>6108.285714</td>\n",
1310 " <td>5745.091557</td>\n",
1311 " <td>5865.493228</td>\n",
1312 " <td>1.196415e+02</td>\n",
1313 " <td>1.151654e+02</td>\n",
1314 " </tr>\n",
1315 " <tr>\n",
1316 " <td>2020-05-01</td>\n",
1317 " <td>32226</td>\n",
1318 " <td>4881</td>\n",
1319 " <td>1110138</td>\n",
1320 " <td>172753</td>\n",
1321 " <td>-45.0</td>\n",
1322 " <td>-48.0</td>\n",
1323 " <td>32810.142857</td>\n",
1324 " <td>5291.571429</td>\n",
1325 " <td>4695.525928</td>\n",
1326 " <td>4919.730986</td>\n",
1327 " <td>1.890979e+02</td>\n",
1328 " <td>1.744465e+02</td>\n",
1329 " </tr>\n",
1330 " <tr>\n",
1331 " <td>2020-05-08</td>\n",
1332 " <td>26812</td>\n",
1333 " <td>3638</td>\n",
1334 " <td>1320759</td>\n",
1335 " <td>201454</td>\n",
1336 " <td>-1615.0</td>\n",
1337 " <td>-176.0</td>\n",
1338 " <td>30088.714286</td>\n",
1339 " <td>4100.142857</td>\n",
1340 " <td>3669.542328</td>\n",
1341 " <td>3786.175573</td>\n",
1342 " <td>2.839767e+02</td>\n",
1343 " <td>2.627153e+02</td>\n",
1344 " </tr>\n",
1345 " <tr>\n",
1346 " <td>2020-05-15</td>\n",
1347 " <td>21611</td>\n",
1348 " <td>2671</td>\n",
1349 " <td>1481545</td>\n",
1350 " <td>222871</td>\n",
1351 " <td>-520.0</td>\n",
1352 " <td>-106.0</td>\n",
1353 " <td>22969.428571</td>\n",
1354 " <td>3059.571429</td>\n",
1355 " <td>2677.524456</td>\n",
1356 " <td>2785.255471</td>\n",
1357 " <td>4.329725e+02</td>\n",
1358 " <td>3.948088e+02</td>\n",
1359 " </tr>\n",
1360 " <tr>\n",
1361 " <td>2020-05-22</td>\n",
1362 " <td>17430</td>\n",
1363 " <td>2075</td>\n",
1364 " <td>1614993</td>\n",
1365 " <td>239208</td>\n",
1366 " <td>-589.0</td>\n",
1367 " <td>-79.0</td>\n",
1368 " <td>19064.000000</td>\n",
1369 " <td>2333.857143</td>\n",
1370 " <td>1947.928544</td>\n",
1371 " <td>2022.217125</td>\n",
1372 " <td>6.541432e+02</td>\n",
1373 " <td>5.836862e+02</td>\n",
1374 " </tr>\n",
1375 " <tr>\n",
1376 " <td>2020-05-29</td>\n",
1377 " <td>12658</td>\n",
1378 " <td>1890</td>\n",
1379 " <td>1722647</td>\n",
1380 " <td>252717</td>\n",
1381 " <td>-883.0</td>\n",
1382 " <td>70.0</td>\n",
1383 " <td>15379.142857</td>\n",
1384 " <td>1929.857143</td>\n",
1385 " <td>1732.798698</td>\n",
1386 " <td>1728.444472</td>\n",
1387 " <td>7.391467e+02</td>\n",
1388 " <td>7.173609e+02</td>\n",
1389 " </tr>\n",
1390 " <tr>\n",
1391 " <td>2020-06-05</td>\n",
1392 " <td>9772</td>\n",
1393 " <td>1207</td>\n",
1394 " <td>1797791</td>\n",
1395 " <td>263570</td>\n",
1396 " <td>-479.0</td>\n",
1397 " <td>-213.0</td>\n",
1398 " <td>10734.857143</td>\n",
1399 " <td>1550.428571</td>\n",
1400 " <td>1257.247277</td>\n",
1401 " <td>1322.817820</td>\n",
1402 " <td>1.135760e+03</td>\n",
1403 " <td>9.930720e+02</td>\n",
1404 " </tr>\n",
1405 " <tr>\n",
1406 " <td>2020-06-12</td>\n",
1407 " <td>7341</td>\n",
1408 " <td>937</td>\n",
1409 " <td>1855247</td>\n",
1410 " <td>271259</td>\n",
1411 " <td>-157.0</td>\n",
1412 " <td>-54.0</td>\n",
1413 " <td>8208.000000</td>\n",
1414 " <td>1098.428571</td>\n",
1415 " <td>916.682753</td>\n",
1416 " <td>940.775215</td>\n",
1417 " <td>1.593893e+03</td>\n",
1418 " <td>1.416581e+03</td>\n",
1419 " </tr>\n",
1420 " <tr>\n",
1421 " <td>2020-06-19</td>\n",
1422 " <td>6939</td>\n",
1423 " <td>591</td>\n",
1424 " <td>1905027</td>\n",
1425 " <td>276164</td>\n",
1426 " <td>-186.0</td>\n",
1427 " <td>-9.0</td>\n",
1428 " <td>7111.428571</td>\n",
1429 " <td>700.714286</td>\n",
1430 " <td>563.512973</td>\n",
1431 " <td>593.415144</td>\n",
1432 " <td>2.647618e+03</td>\n",
1433 " <td>2.299498e+03</td>\n",
1434 " </tr>\n",
1435 " <tr>\n",
1436 " <td>2020-06-26</td>\n",
1437 " <td>5899</td>\n",
1438 " <td>480</td>\n",
1439 " <td>1950419</td>\n",
1440 " <td>279624</td>\n",
1441 " <td>-235.0</td>\n",
1442 " <td>32.0</td>\n",
1443 " <td>6484.571429</td>\n",
1444 " <td>494.285714</td>\n",
1445 " <td>416.381335</td>\n",
1446 " <td>421.990143</td>\n",
1447 " <td>3.585584e+03</td>\n",
1448 " <td>3.235524e+03</td>\n",
1449 " </tr>\n",
1450 " <tr>\n",
1451 " <td>2020-07-03</td>\n",
1452 " <td>4485</td>\n",
1453 " <td>360</td>\n",
1454 " <td>1985555</td>\n",
1455 " <td>282616</td>\n",
1456 " <td>-127.0</td>\n",
1457 " <td>-58.0</td>\n",
1458 " <td>5019.428571</td>\n",
1459 " <td>427.428571</td>\n",
1460 " <td>376.617800</td>\n",
1461 " <td>366.017611</td>\n",
1462 " <td>4.038218e+03</td>\n",
1463 " <td>3.764706e+03</td>\n",
1464 " </tr>\n",
1465 " <tr>\n",
1466 " <td>2020-07-10</td>\n",
1467 " <td>4131</td>\n",
1468 " <td>253</td>\n",
1469 " <td>2014685</td>\n",
1470 " <td>284705</td>\n",
1471 " <td>42.0</td>\n",
1472 " <td>-10.0</td>\n",
1473 " <td>4161.428571</td>\n",
1474 " <td>298.428571</td>\n",
1475 " <td>248.675598</td>\n",
1476 " <td>258.540406</td>\n",
1477 " <td>6.117937e+03</td>\n",
1478 " <td>5.408341e+03</td>\n",
1479 " </tr>\n",
1480 " <tr>\n",
1481 " <td>2020-07-17</td>\n",
1482 " <td>4266</td>\n",
1483 " <td>164</td>\n",
1484 " <td>2044059</td>\n",
1485 " <td>286128</td>\n",
1486 " <td>79.0</td>\n",
1487 " <td>-7.0</td>\n",
1488 " <td>4196.285714</td>\n",
1489 " <td>203.285714</td>\n",
1490 " <td>166.283290</td>\n",
1491 " <td>171.181184</td>\n",
1492 " <td>9.430925e+03</td>\n",
1493 " <td>8.243797e+03</td>\n",
1494 " </tr>\n",
1495 " <tr>\n",
1496 " <td>2020-07-24</td>\n",
1497 " <td>4496</td>\n",
1498 " <td>107</td>\n",
1499 " <td>2074665</td>\n",
1500 " <td>287092</td>\n",
1501 " <td>1.0</td>\n",
1502 " <td>-15.0</td>\n",
1503 " <td>4372.285714</td>\n",
1504 " <td>137.714286</td>\n",
1505 " <td>118.278798</td>\n",
1506 " <td>120.912224</td>\n",
1507 " <td>1.271636e+04</td>\n",
1508 " <td>1.165442e+04</td>\n",
1509 " </tr>\n",
1510 " <tr>\n",
1511 " <td>2020-07-31</td>\n",
1512 " <td>3869</td>\n",
1513 " <td>113</td>\n",
1514 " <td>2104314</td>\n",
1515 " <td>287889</td>\n",
1516 " <td>73.0</td>\n",
1517 " <td>-9.0</td>\n",
1518 " <td>4235.571429</td>\n",
1519 " <td>113.857143</td>\n",
1520 " <td>79.927160</td>\n",
1521 " <td>82.049806</td>\n",
1522 " <td>inf</td>\n",
1523 " <td>inf</td>\n",
1524 " </tr>\n",
1525 " <tr>\n",
1526 " <td>2020-08-07</td>\n",
1527 " <td>5833</td>\n",
1528 " <td>89</td>\n",
1529 " <td>2139062</td>\n",
1530 " <td>288530</td>\n",
1531 " <td>104.0</td>\n",
1532 " <td>18.0</td>\n",
1533 " <td>4964.000000</td>\n",
1534 " <td>91.571429</td>\n",
1535 " <td>26.017737</td>\n",
1536 " <td>9.273227</td>\n",
1537 " <td>inf</td>\n",
1538 " <td>inf</td>\n",
1539 " </tr>\n",
1540 " <tr>\n",
1541 " <td>2020-08-14</td>\n",
1542 " <td>6793</td>\n",
1543 " <td>89</td>\n",
1544 " <td>2182748</td>\n",
1545 " <td>289102</td>\n",
1546 " <td>179.0</td>\n",
1547 " <td>0.0</td>\n",
1548 " <td>6240.857143</td>\n",
1549 " <td>81.714286</td>\n",
1550 " <td>77.224731</td>\n",
1551 " <td>64.479846</td>\n",
1552 " <td>2.011138e+04</td>\n",
1553 " <td>2.245319e+04</td>\n",
1554 " </tr>\n",
1555 " <tr>\n",
1556 " <td>2020-08-21</td>\n",
1557 " <td>7353</td>\n",
1558 " <td>56</td>\n",
1559 " <td>2235156</td>\n",
1560 " <td>289635</td>\n",
1561 " <td>53.0</td>\n",
1562 " <td>-12.0</td>\n",
1563 " <td>7486.857143</td>\n",
1564 " <td>76.142857</td>\n",
1565 " <td>57.415692</td>\n",
1566 " <td>61.994254</td>\n",
1567 " <td>2.822494e+04</td>\n",
1568 " <td>2.333077e+04</td>\n",
1569 " </tr>\n",
1570 " <tr>\n",
1571 " <td>2020-08-28</td>\n",
1572 " <td>8088</td>\n",
1573 " <td>74</td>\n",
1574 " <td>2287182</td>\n",
1575 " <td>290081</td>\n",
1576 " <td>340.0</td>\n",
1577 " <td>6.0</td>\n",
1578 " <td>7432.285714</td>\n",
1579 " <td>63.714286</td>\n",
1580 " <td>54.517208</td>\n",
1581 " <td>49.287140</td>\n",
1582 " <td>2.710076e+04</td>\n",
1583 " <td>2.908195e+04</td>\n",
1584 " </tr>\n",
1585 " <tr>\n",
1586 " <td>2020-09-04</td>\n",
1587 " <td>10043</td>\n",
1588 " <td>50</td>\n",
1589 " <td>2350991</td>\n",
1590 " <td>290529</td>\n",
1591 " <td>213.0</td>\n",
1592 " <td>1.0</td>\n",
1593 " <td>9115.571429</td>\n",
1594 " <td>64.000000</td>\n",
1595 " <td>45.709346</td>\n",
1596 " <td>49.612299</td>\n",
1597 " <td>4.258905e+04</td>\n",
1598 " <td>3.069208e+04</td>\n",
1599 " </tr>\n",
1600 " <tr>\n",
1601 " <td>2020-09-11</td>\n",
1602 " <td>17727</td>\n",
1603 " <td>81</td>\n",
1604 " <td>2449684</td>\n",
1605 " <td>290979</td>\n",
1606 " <td>1184.0</td>\n",
1607 " <td>1.0</td>\n",
1608 " <td>14099.000000</td>\n",
1609 " <td>64.285714</td>\n",
1610 " <td>55.103648</td>\n",
1611 " <td>46.741257</td>\n",
1612 " <td>2.723477e+04</td>\n",
1613 " <td>3.156956e+04</td>\n",
1614 " </tr>\n",
1615 " <tr>\n",
1616 " <td>2020-09-18</td>\n",
1617 " <td>23476</td>\n",
1618 " <td>97</td>\n",
1619 " <td>2600541</td>\n",
1620 " <td>291555</td>\n",
1621 " <td>476.0</td>\n",
1622 " <td>7.0</td>\n",
1623 " <td>21551.000000</td>\n",
1624 " <td>82.285714</td>\n",
1625 " <td>76.375361</td>\n",
1626 " <td>65.232921</td>\n",
1627 " <td>2.020206e+04</td>\n",
1628 " <td>2.224637e+04</td>\n",
1629 " </tr>\n",
1630 " <tr>\n",
1631 " <td>2020-09-25</td>\n",
1632 " <td>34749</td>\n",
1633 " <td>197</td>\n",
1634 " <td>2798819</td>\n",
1635 " <td>292645</td>\n",
1636 " <td>3239.0</td>\n",
1637 " <td>19.0</td>\n",
1638 " <td>28325.428571</td>\n",
1639 " <td>155.714286</td>\n",
1640 " <td>161.214801</td>\n",
1641 " <td>143.205548</td>\n",
1642 " <td>8.901465e+03</td>\n",
1643 " <td>1.026870e+04</td>\n",
1644 " </tr>\n",
1645 " <tr>\n",
1646 " <td>2020-10-02</td>\n",
1647 " <td>43815</td>\n",
1648 " <td>300</td>\n",
1649 " <td>3086093</td>\n",
1650 " <td>294313</td>\n",
1651 " <td>280.0</td>\n",
1652 " <td>19.0</td>\n",
1653 " <td>41039.142857</td>\n",
1654 " <td>238.285714</td>\n",
1655 " <td>230.060916</td>\n",
1656 " <td>211.544534</td>\n",
1657 " <td>6.473932e+03</td>\n",
1658 " <td>6.827996e+03</td>\n",
1659 " </tr>\n",
1660 " <tr>\n",
1661 " <td>2020-10-09</td>\n",
1662 " <td>101637</td>\n",
1663 " <td>390</td>\n",
1664 " <td>3601915</td>\n",
1665 " <td>296856</td>\n",
1666 " <td>10626.0</td>\n",
1667 " <td>18.0</td>\n",
1668 " <td>73688.857143</td>\n",
1669 " <td>363.285714</td>\n",
1670 " <td>349.704548</td>\n",
1671 " <td>322.563025</td>\n",
1672 " <td>4.291457e+03</td>\n",
1673 " <td>4.498907e+03</td>\n",
1674 " </tr>\n",
1675 " <tr>\n",
1676 " <td>2020-10-16</td>\n",
1677 " <td>111807</td>\n",
1678 " <td>701</td>\n",
1679 " <td>4351113</td>\n",
1680 " <td>300605</td>\n",
1681 " <td>1438.0</td>\n",
1682 " <td>61.0</td>\n",
1683 " <td>107028.285714</td>\n",
1684 " <td>535.571429</td>\n",
1685 " <td>577.496284</td>\n",
1686 " <td>499.621044</td>\n",
1687 " <td>2.571463e+03</td>\n",
1688 " <td>3.038155e+03</td>\n",
1689 " </tr>\n",
1690 " <tr>\n",
1691 " <td>2020-10-23</td>\n",
1692 " <td>136845</td>\n",
1693 " <td>1054</td>\n",
1694 " <td>5220544</td>\n",
1695 " <td>306852</td>\n",
1696 " <td>2260.0</td>\n",
1697 " <td>51.0</td>\n",
1698 " <td>124204.428571</td>\n",
1699 " <td>892.428571</td>\n",
1700 " <td>903.798899</td>\n",
1701 " <td>829.790586</td>\n",
1702 " <td>1.681682e+03</td>\n",
1703 " <td>1.816643e+03</td>\n",
1704 " </tr>\n",
1705 " <tr>\n",
1706 " <td>2020-10-30</td>\n",
1707 " <td>154873</td>\n",
1708 " <td>1608</td>\n",
1709 " <td>6278688</td>\n",
1710 " <td>316205</td>\n",
1711 " <td>1827.0</td>\n",
1712 " <td>91.0</td>\n",
1713 " <td>151163.428571</td>\n",
1714 " <td>1336.142857</td>\n",
1715 " <td>1363.375912</td>\n",
1716 " <td>1244.302740</td>\n",
1717 " <td>1.144987e+03</td>\n",
1718 " <td>1.253041e+03</td>\n",
1719 " </tr>\n",
1720 " <tr>\n",
1721 " <td>2020-11-06</td>\n",
1722 " <td>157857</td>\n",
1723 " <td>2165</td>\n",
1724 " <td>7386321</td>\n",
1725 " <td>329466</td>\n",
1726 " <td>1073.0</td>\n",
1727 " <td>98.0</td>\n",
1728 " <td>158233.285714</td>\n",
1729 " <td>1894.428571</td>\n",
1730 " <td>1869.072858</td>\n",
1731 " <td>1756.119532</td>\n",
1732 " <td>8.748452e+02</td>\n",
1733 " <td>9.175873e+02</td>\n",
1734 " </tr>\n",
1735 " <tr>\n",
1736 " <td>2020-11-13</td>\n",
1737 " <td>166998</td>\n",
1738 " <td>2808</td>\n",
1739 " <td>8503996</td>\n",
1740 " <td>346708</td>\n",
1741 " <td>9332.0</td>\n",
1742 " <td>185.0</td>\n",
1743 " <td>159667.857143</td>\n",
1744 " <td>2463.142857</td>\n",
1745 " <td>2401.361299</td>\n",
1746 " <td>2249.701288</td>\n",
1747 " <td>7.273019e+02</td>\n",
1748 " <td>7.528714e+02</td>\n",
1749 " </tr>\n",
1750 " <tr>\n",
1751 " <td>2020-11-20</td>\n",
1752 " <td>163061</td>\n",
1753 " <td>2847</td>\n",
1754 " <td>9716180</td>\n",
1755 " <td>366945</td>\n",
1756 " <td>-10555.0</td>\n",
1757 " <td>-62.0</td>\n",
1758 " <td>173169.142857</td>\n",
1759 " <td>2891.000000</td>\n",
1760 " <td>2708.892132</td>\n",
1761 " <td>2619.031072</td>\n",
1762 " <td>6.907600e+02</td>\n",
1763 " <td>6.823344e+02</td>\n",
1764 " </tr>\n",
1765 " <tr>\n",
1766 " <td>2020-11-27</td>\n",
1767 " <td>121306</td>\n",
1768 " <td>3256</td>\n",
1769 " <td>10676794</td>\n",
1770 " <td>388295</td>\n",
1771 " <td>-5360.0</td>\n",
1772 " <td>-3.0</td>\n",
1773 " <td>137230.571429</td>\n",
1774 " <td>3050.000000</td>\n",
1775 " <td>2934.861534</td>\n",
1776 " <td>2753.026893</td>\n",
1777 " <td>6.765205e+02</td>\n",
1778 " <td>6.882603e+02</td>\n",
1779 " </tr>\n",
1780 " <tr>\n",
1781 " <td>2020-12-04</td>\n",
1782 " <td>99572</td>\n",
1783 " <td>3082</td>\n",
1784 " <td>11417933</td>\n",
1785 " <td>411137</td>\n",
1786 " <td>-2677.0</td>\n",
1787 " <td>-84.0</td>\n",
1788 " <td>105877.000000</td>\n",
1789 " <td>3263.142857</td>\n",
1790 " <td>2966.168647</td>\n",
1791 " <td>2988.661808</td>\n",
1792 " <td>7.059253e+02</td>\n",
1793 " <td>6.717400e+02</td>\n",
1794 " </tr>\n",
1795 " <tr>\n",
1796 " <td>2020-12-11</td>\n",
1797 " <td>92685</td>\n",
1798 " <td>2453</td>\n",
1799 " <td>10374665</td>\n",
1800 " <td>368909</td>\n",
1801 " <td>1700.0</td>\n",
1802 " <td>119.0</td>\n",
1803 " <td>90123.714286</td>\n",
1804 " <td>2555.000000</td>\n",
1805 " <td>2356.150688</td>\n",
1806 " <td>2352.938908</td>\n",
1807 " <td>6.829136e+02</td>\n",
1808 " <td>6.544146e+02</td>\n",
1809 " </tr>\n",
1810 " </tbody>\n",
1811 "</table>\n",
1812 "</div>"
1813 ],
1814 "text/plain": [
1815 " cases deaths cases_culm deaths_culm cases_diff deaths_diff \\\n",
1816 "dateRep \n",
1817 "2020-01-03 0 0 0 0 0.0 0.0 \n",
1818 "2020-01-10 0 0 0 0 0.0 0.0 \n",
1819 "2020-01-17 0 0 0 0 0.0 0.0 \n",
1820 "2020-01-24 0 0 0 0 0.0 0.0 \n",
1821 "2020-01-31 0 0 0 0 0.0 0.0 \n",
1822 "2020-02-07 4 0 18 0 1.0 0.0 \n",
1823 "2020-02-14 6 0 54 0 -1.0 0.0 \n",
1824 "2020-02-21 0 0 70 0 0.0 0.0 \n",
1825 "2020-02-28 12 0 96 0 4.0 0.0 \n",
1826 "2020-03-06 198 0 681 0 52.0 0.0 \n",
1827 "2020-03-13 1062 9 4279 31 350.0 2.0 \n",
1828 "2020-03-20 4144 153 23173 507 593.0 44.0 \n",
1829 "2020-03-27 12291 722 78855 3197 1693.0 135.0 \n",
1830 "2020-04-03 25664 2898 217112 15722 2221.0 476.0 \n",
1831 "2020-04-10 33254 5909 433554 47916 218.0 459.0 \n",
1832 "2020-04-17 29808 6338 654431 92954 -66.0 -80.0 \n",
1833 "2020-04-24 33923 5773 880467 135712 422.0 -354.0 \n",
1834 "2020-05-01 32226 4881 1110138 172753 -45.0 -48.0 \n",
1835 "2020-05-08 26812 3638 1320759 201454 -1615.0 -176.0 \n",
1836 "2020-05-15 21611 2671 1481545 222871 -520.0 -106.0 \n",
1837 "2020-05-22 17430 2075 1614993 239208 -589.0 -79.0 \n",
1838 "2020-05-29 12658 1890 1722647 252717 -883.0 70.0 \n",
1839 "2020-06-05 9772 1207 1797791 263570 -479.0 -213.0 \n",
1840 "2020-06-12 7341 937 1855247 271259 -157.0 -54.0 \n",
1841 "2020-06-19 6939 591 1905027 276164 -186.0 -9.0 \n",
1842 "2020-06-26 5899 480 1950419 279624 -235.0 32.0 \n",
1843 "2020-07-03 4485 360 1985555 282616 -127.0 -58.0 \n",
1844 "2020-07-10 4131 253 2014685 284705 42.0 -10.0 \n",
1845 "2020-07-17 4266 164 2044059 286128 79.0 -7.0 \n",
1846 "2020-07-24 4496 107 2074665 287092 1.0 -15.0 \n",
1847 "2020-07-31 3869 113 2104314 287889 73.0 -9.0 \n",
1848 "2020-08-07 5833 89 2139062 288530 104.0 18.0 \n",
1849 "2020-08-14 6793 89 2182748 289102 179.0 0.0 \n",
1850 "2020-08-21 7353 56 2235156 289635 53.0 -12.0 \n",
1851 "2020-08-28 8088 74 2287182 290081 340.0 6.0 \n",
1852 "2020-09-04 10043 50 2350991 290529 213.0 1.0 \n",
1853 "2020-09-11 17727 81 2449684 290979 1184.0 1.0 \n",
1854 "2020-09-18 23476 97 2600541 291555 476.0 7.0 \n",
1855 "2020-09-25 34749 197 2798819 292645 3239.0 19.0 \n",
1856 "2020-10-02 43815 300 3086093 294313 280.0 19.0 \n",
1857 "2020-10-09 101637 390 3601915 296856 10626.0 18.0 \n",
1858 "2020-10-16 111807 701 4351113 300605 1438.0 61.0 \n",
1859 "2020-10-23 136845 1054 5220544 306852 2260.0 51.0 \n",
1860 "2020-10-30 154873 1608 6278688 316205 1827.0 91.0 \n",
1861 "2020-11-06 157857 2165 7386321 329466 1073.0 98.0 \n",
1862 "2020-11-13 166998 2808 8503996 346708 9332.0 185.0 \n",
1863 "2020-11-20 163061 2847 9716180 366945 -10555.0 -62.0 \n",
1864 "2020-11-27 121306 3256 10676794 388295 -5360.0 -3.0 \n",
1865 "2020-12-04 99572 3082 11417933 411137 -2677.0 -84.0 \n",
1866 "2020-12-11 92685 2453 10374665 368909 1700.0 119.0 \n",
1867 "\n",
1868 " cases_m7 deaths_m7 deaths_g4 deaths_g7 \\\n",
1869 "dateRep \n",
1870 "2020-01-03 0.000000 0.000000 0.000000 0.000000 \n",
1871 "2020-01-10 0.000000 0.000000 0.000000 0.000000 \n",
1872 "2020-01-17 0.000000 0.000000 0.000000 0.000000 \n",
1873 "2020-01-24 0.000000 0.000000 0.000000 0.000000 \n",
1874 "2020-01-31 0.000000 0.000000 0.000000 0.000000 \n",
1875 "2020-02-07 2.571429 0.000000 0.000000 0.000000 \n",
1876 "2020-02-14 5.142857 0.000000 0.000000 0.000000 \n",
1877 "2020-02-21 2.285714 0.000000 0.000000 0.000000 \n",
1878 "2020-02-28 3.714286 0.000000 0.000000 0.000000 \n",
1879 "2020-03-06 83.571429 0.000000 0.000000 0.000000 \n",
1880 "2020-03-13 514.000000 4.428571 0.000000 0.000000 \n",
1881 "2020-03-20 2699.142857 68.000000 79.504887 24.257733 \n",
1882 "2020-03-27 7954.571429 384.285714 464.807614 327.583287 \n",
1883 "2020-04-03 19751.000000 1789.285714 2153.720503 1633.574291 \n",
1884 "2020-04-10 30920.285714 4599.142857 5088.524097 4416.476344 \n",
1885 "2020-04-17 31553.857143 6434.000000 6392.991495 6269.311492 \n",
1886 "2020-04-24 32290.857143 6108.285714 5745.091557 5865.493228 \n",
1887 "2020-05-01 32810.142857 5291.571429 4695.525928 4919.730986 \n",
1888 "2020-05-08 30088.714286 4100.142857 3669.542328 3786.175573 \n",
1889 "2020-05-15 22969.428571 3059.571429 2677.524456 2785.255471 \n",
1890 "2020-05-22 19064.000000 2333.857143 1947.928544 2022.217125 \n",
1891 "2020-05-29 15379.142857 1929.857143 1732.798698 1728.444472 \n",
1892 "2020-06-05 10734.857143 1550.428571 1257.247277 1322.817820 \n",
1893 "2020-06-12 8208.000000 1098.428571 916.682753 940.775215 \n",
1894 "2020-06-19 7111.428571 700.714286 563.512973 593.415144 \n",
1895 "2020-06-26 6484.571429 494.285714 416.381335 421.990143 \n",
1896 "2020-07-03 5019.428571 427.428571 376.617800 366.017611 \n",
1897 "2020-07-10 4161.428571 298.428571 248.675598 258.540406 \n",
1898 "2020-07-17 4196.285714 203.285714 166.283290 171.181184 \n",
1899 "2020-07-24 4372.285714 137.714286 118.278798 120.912224 \n",
1900 "2020-07-31 4235.571429 113.857143 79.927160 82.049806 \n",
1901 "2020-08-07 4964.000000 91.571429 26.017737 9.273227 \n",
1902 "2020-08-14 6240.857143 81.714286 77.224731 64.479846 \n",
1903 "2020-08-21 7486.857143 76.142857 57.415692 61.994254 \n",
1904 "2020-08-28 7432.285714 63.714286 54.517208 49.287140 \n",
1905 "2020-09-04 9115.571429 64.000000 45.709346 49.612299 \n",
1906 "2020-09-11 14099.000000 64.285714 55.103648 46.741257 \n",
1907 "2020-09-18 21551.000000 82.285714 76.375361 65.232921 \n",
1908 "2020-09-25 28325.428571 155.714286 161.214801 143.205548 \n",
1909 "2020-10-02 41039.142857 238.285714 230.060916 211.544534 \n",
1910 "2020-10-09 73688.857143 363.285714 349.704548 322.563025 \n",
1911 "2020-10-16 107028.285714 535.571429 577.496284 499.621044 \n",
1912 "2020-10-23 124204.428571 892.428571 903.798899 829.790586 \n",
1913 "2020-10-30 151163.428571 1336.142857 1363.375912 1244.302740 \n",
1914 "2020-11-06 158233.285714 1894.428571 1869.072858 1756.119532 \n",
1915 "2020-11-13 159667.857143 2463.142857 2401.361299 2249.701288 \n",
1916 "2020-11-20 173169.142857 2891.000000 2708.892132 2619.031072 \n",
1917 "2020-11-27 137230.571429 3050.000000 2934.861534 2753.026893 \n",
1918 "2020-12-04 105877.000000 3263.142857 2966.168647 2988.661808 \n",
1919 "2020-12-11 90123.714286 2555.000000 2356.150688 2352.938908 \n",
1920 "\n",
1921 " doubling_time doubling_time_7 \n",
1922 "dateRep \n",
1923 "2020-01-03 0.000000e+00 0.000000e+00 \n",
1924 "2020-01-10 0.000000e+00 0.000000e+00 \n",
1925 "2020-01-17 0.000000e+00 0.000000e+00 \n",
1926 "2020-01-24 0.000000e+00 0.000000e+00 \n",
1927 "2020-01-31 0.000000e+00 0.000000e+00 \n",
1928 "2020-02-07 0.000000e+00 0.000000e+00 \n",
1929 "2020-02-14 0.000000e+00 0.000000e+00 \n",
1930 "2020-02-21 0.000000e+00 0.000000e+00 \n",
1931 "2020-02-28 0.000000e+00 0.000000e+00 \n",
1932 "2020-03-06 0.000000e+00 0.000000e+00 \n",
1933 "2020-03-13 inf inf \n",
1934 "2020-03-20 inf inf \n",
1935 "2020-03-27 3.577040e+01 4.797282e+01 \n",
1936 "2020-04-03 3.702651e+01 4.931862e+01 \n",
1937 "2020-04-10 4.749914e+01 5.457682e+01 \n",
1938 "2020-04-17 7.441501e+01 7.427834e+01 \n",
1939 "2020-04-24 1.196415e+02 1.151654e+02 \n",
1940 "2020-05-01 1.890979e+02 1.744465e+02 \n",
1941 "2020-05-08 2.839767e+02 2.627153e+02 \n",
1942 "2020-05-15 4.329725e+02 3.948088e+02 \n",
1943 "2020-05-22 6.541432e+02 5.836862e+02 \n",
1944 "2020-05-29 7.391467e+02 7.173609e+02 \n",
1945 "2020-06-05 1.135760e+03 9.930720e+02 \n",
1946 "2020-06-12 1.593893e+03 1.416581e+03 \n",
1947 "2020-06-19 2.647618e+03 2.299498e+03 \n",
1948 "2020-06-26 3.585584e+03 3.235524e+03 \n",
1949 "2020-07-03 4.038218e+03 3.764706e+03 \n",
1950 "2020-07-10 6.117937e+03 5.408341e+03 \n",
1951 "2020-07-17 9.430925e+03 8.243797e+03 \n",
1952 "2020-07-24 1.271636e+04 1.165442e+04 \n",
1953 "2020-07-31 inf inf \n",
1954 "2020-08-07 inf inf \n",
1955 "2020-08-14 2.011138e+04 2.245319e+04 \n",
1956 "2020-08-21 2.822494e+04 2.333077e+04 \n",
1957 "2020-08-28 2.710076e+04 2.908195e+04 \n",
1958 "2020-09-04 4.258905e+04 3.069208e+04 \n",
1959 "2020-09-11 2.723477e+04 3.156956e+04 \n",
1960 "2020-09-18 2.020206e+04 2.224637e+04 \n",
1961 "2020-09-25 8.901465e+03 1.026870e+04 \n",
1962 "2020-10-02 6.473932e+03 6.827996e+03 \n",
1963 "2020-10-09 4.291457e+03 4.498907e+03 \n",
1964 "2020-10-16 2.571463e+03 3.038155e+03 \n",
1965 "2020-10-23 1.681682e+03 1.816643e+03 \n",
1966 "2020-10-30 1.144987e+03 1.253041e+03 \n",
1967 "2020-11-06 8.748452e+02 9.175873e+02 \n",
1968 "2020-11-13 7.273019e+02 7.528714e+02 \n",
1969 "2020-11-20 6.907600e+02 6.823344e+02 \n",
1970 "2020-11-27 6.765205e+02 6.882603e+02 \n",
1971 "2020-12-04 7.059253e+02 6.717400e+02 \n",
1972 "2020-12-11 6.829136e+02 6.544146e+02 "
1973 ]
1974 },
1975 "execution_count": 68,
1976 "metadata": {},
1977 "output_type": "execute_result"
1978 }
1979 ],
1980 "source": [
1981 "data_by_week = data_by_day.resample(pd.offsets.Week(weekday=4)).sum()\n",
1982 "data_by_week"
1983 ]
1984 },
1985 {
1986 "cell_type": "code",
1987 "execution_count": 69,
1988 "metadata": {
1989 "Collapsed": "false"
1990 },
1991 "outputs": [
1992 {
1993 "data": {
1994 "text/html": [
1995 "<div>\n",
1996 "<style scoped>\n",
1997 " .dataframe tbody tr th:only-of-type {\n",
1998 " vertical-align: middle;\n",
1999 " }\n",
2000 "\n",
2001 " .dataframe tbody tr th {\n",
2002 " vertical-align: top;\n",
2003 " }\n",
2004 "\n",
2005 " .dataframe thead th {\n",
2006 " text-align: right;\n",
2007 " }\n",
2008 "</style>\n",
2009 "<table border=\"1\" class=\"dataframe\">\n",
2010 " <thead>\n",
2011 " <tr style=\"text-align: right;\">\n",
2012 " <th></th>\n",
2013 " <th>total_2020</th>\n",
2014 " <th>previous_mean</th>\n",
2015 " <th>covid_deaths</th>\n",
2016 " </tr>\n",
2017 " </thead>\n",
2018 " <tbody>\n",
2019 " <tr>\n",
2020 " <td>2020-03-20</td>\n",
2021 " <td>12112.0</td>\n",
2022 " <td>12007.4</td>\n",
2023 " <td>153</td>\n",
2024 " </tr>\n",
2025 " <tr>\n",
2026 " <td>2020-03-27</td>\n",
2027 " <td>12507.0</td>\n",
2028 " <td>11549.6</td>\n",
2029 " <td>722</td>\n",
2030 " </tr>\n",
2031 " <tr>\n",
2032 " <td>2020-04-03</td>\n",
2033 " <td>18565.0</td>\n",
2034 " <td>11681.4</td>\n",
2035 " <td>2898</td>\n",
2036 " </tr>\n",
2037 " <tr>\n",
2038 " <td>2020-04-10</td>\n",
2039 " <td>20929.0</td>\n",
2040 " <td>11919.4</td>\n",
2041 " <td>5909</td>\n",
2042 " </tr>\n",
2043 " <tr>\n",
2044 " <td>2020-04-17</td>\n",
2045 " <td>24691.0</td>\n",
2046 " <td>11850.6</td>\n",
2047 " <td>6338</td>\n",
2048 " </tr>\n",
2049 " <tr>\n",
2050 " <td>2020-04-24</td>\n",
2051 " <td>24303.0</td>\n",
2052 " <td>11844.4</td>\n",
2053 " <td>5773</td>\n",
2054 " </tr>\n",
2055 " <tr>\n",
2056 " <td>2020-05-01</td>\n",
2057 " <td>20059.0</td>\n",
2058 " <td>11318.4</td>\n",
2059 " <td>4881</td>\n",
2060 " </tr>\n",
2061 " <tr>\n",
2062 " <td>2020-05-08</td>\n",
2063 " <td>14428.0</td>\n",
2064 " <td>10887.2</td>\n",
2065 " <td>3638</td>\n",
2066 " </tr>\n",
2067 " <tr>\n",
2068 " <td>2020-05-15</td>\n",
2069 " <td>16390.0</td>\n",
2070 " <td>11547.0</td>\n",
2071 " <td>2671</td>\n",
2072 " </tr>\n",
2073 " <tr>\n",
2074 " <td>2020-05-22</td>\n",
2075 " <td>13839.0</td>\n",
2076 " <td>11281.0</td>\n",
2077 " <td>2075</td>\n",
2078 " </tr>\n",
2079 " <tr>\n",
2080 " <td>2020-05-29</td>\n",
2081 " <td>11265.0</td>\n",
2082 " <td>9448.0</td>\n",
2083 " <td>1890</td>\n",
2084 " </tr>\n",
2085 " <tr>\n",
2086 " <td>2020-06-05</td>\n",
2087 " <td>12106.0</td>\n",
2088 " <td>11325.6</td>\n",
2089 " <td>1207</td>\n",
2090 " </tr>\n",
2091 " <tr>\n",
2092 " <td>2020-06-12</td>\n",
2093 " <td>11302.0</td>\n",
2094 " <td>10703.6</td>\n",
2095 " <td>937</td>\n",
2096 " </tr>\n",
2097 " <tr>\n",
2098 " <td>2020-06-19</td>\n",
2099 " <td>10694.0</td>\n",
2100 " <td>10698.2</td>\n",
2101 " <td>591</td>\n",
2102 " </tr>\n",
2103 " <tr>\n",
2104 " <td>2020-06-26</td>\n",
2105 " <td>10282.0</td>\n",
2106 " <td>10605.6</td>\n",
2107 " <td>480</td>\n",
2108 " </tr>\n",
2109 " <tr>\n",
2110 " <td>2020-07-03</td>\n",
2111 " <td>10412.0</td>\n",
2112 " <td>10483.0</td>\n",
2113 " <td>360</td>\n",
2114 " </tr>\n",
2115 " <tr>\n",
2116 " <td>2020-07-10</td>\n",
2117 " <td>9941.0</td>\n",
2118 " <td>10509.4</td>\n",
2119 " <td>253</td>\n",
2120 " </tr>\n",
2121 " <tr>\n",
2122 " <td>2020-07-17</td>\n",
2123 " <td>10096.0</td>\n",
2124 " <td>10360.6</td>\n",
2125 " <td>164</td>\n",
2126 " </tr>\n",
2127 " <tr>\n",
2128 " <td>2020-07-24</td>\n",
2129 " <td>10159.0</td>\n",
2130 " <td>10311.6</td>\n",
2131 " <td>107</td>\n",
2132 " </tr>\n",
2133 " <tr>\n",
2134 " <td>2020-07-31</td>\n",
2135 " <td>10262.0</td>\n",
2136 " <td>10307.4</td>\n",
2137 " <td>113</td>\n",
2138 " </tr>\n",
2139 " <tr>\n",
2140 " <td>2020-08-07</td>\n",
2141 " <td>10236.0</td>\n",
2142 " <td>10363.6</td>\n",
2143 " <td>89</td>\n",
2144 " </tr>\n",
2145 " <tr>\n",
2146 " <td>2020-08-14</td>\n",
2147 " <td>10592.0</td>\n",
2148 " <td>10345.8</td>\n",
2149 " <td>89</td>\n",
2150 " </tr>\n",
2151 " <tr>\n",
2152 " <td>2020-08-21</td>\n",
2153 " <td>10990.0</td>\n",
2154 " <td>10433.4</td>\n",
2155 " <td>56</td>\n",
2156 " </tr>\n",
2157 " <tr>\n",
2158 " <td>2020-08-28</td>\n",
2159 " <td>10364.0</td>\n",
2160 " <td>9472.2</td>\n",
2161 " <td>74</td>\n",
2162 " </tr>\n",
2163 " <tr>\n",
2164 " <td>2020-09-04</td>\n",
2165 " <td>9023.0</td>\n",
2166 " <td>10430.4</td>\n",
2167 " <td>50</td>\n",
2168 " </tr>\n",
2169 " <tr>\n",
2170 " <td>2020-09-11</td>\n",
2171 " <td>11176.0</td>\n",
2172 " <td>10610.8</td>\n",
2173 " <td>81</td>\n",
2174 " </tr>\n",
2175 " <tr>\n",
2176 " <td>2020-09-18</td>\n",
2177 " <td>10797.0</td>\n",
2178 " <td>10545.8</td>\n",
2179 " <td>97</td>\n",
2180 " </tr>\n",
2181 " <tr>\n",
2182 " <td>2020-09-25</td>\n",
2183 " <td>10890.0</td>\n",
2184 " <td>10709.6</td>\n",
2185 " <td>197</td>\n",
2186 " </tr>\n",
2187 " <tr>\n",
2188 " <td>2020-10-02</td>\n",
2189 " <td>11468.0</td>\n",
2190 " <td>10890.8</td>\n",
2191 " <td>300</td>\n",
2192 " </tr>\n",
2193 " <tr>\n",
2194 " <td>2020-10-09</td>\n",
2195 " <td>11373.0</td>\n",
2196 " <td>11186.4</td>\n",
2197 " <td>390</td>\n",
2198 " </tr>\n",
2199 " <tr>\n",
2200 " <td>2020-10-16</td>\n",
2201 " <td>11943.0</td>\n",
2202 " <td>11224.8</td>\n",
2203 " <td>701</td>\n",
2204 " </tr>\n",
2205 " <tr>\n",
2206 " <td>2020-10-23</td>\n",
2207 " <td>12317.0</td>\n",
2208 " <td>11093.2</td>\n",
2209 " <td>1054</td>\n",
2210 " </tr>\n",
2211 " <tr>\n",
2212 " <td>2020-10-30</td>\n",
2213 " <td>12517.0</td>\n",
2214 " <td>11257.6</td>\n",
2215 " <td>1608</td>\n",
2216 " </tr>\n",
2217 " <tr>\n",
2218 " <td>2020-11-06</td>\n",
2219 " <td>13448.0</td>\n",
2220 " <td>11729.4</td>\n",
2221 " <td>2165</td>\n",
2222 " </tr>\n",
2223 " <tr>\n",
2224 " <td>2020-11-13</td>\n",
2225 " <td>13798.0</td>\n",
2226 " <td>11803.6</td>\n",
2227 " <td>2808</td>\n",
2228 " </tr>\n",
2229 " <tr>\n",
2230 " <td>2020-11-20</td>\n",
2231 " <td>14291.0</td>\n",
2232 " <td>11821.0</td>\n",
2233 " <td>2847</td>\n",
2234 " </tr>\n",
2235 " <tr>\n",
2236 " <td>2020-11-27</td>\n",
2237 " <td>14132.0</td>\n",
2238 " <td>11802.0</td>\n",
2239 " <td>3256</td>\n",
2240 " </tr>\n",
2241 " </tbody>\n",
2242 "</table>\n",
2243 "</div>"
2244 ],
2245 "text/plain": [
2246 " total_2020 previous_mean covid_deaths\n",
2247 "2020-03-20 12112.0 12007.4 153\n",
2248 "2020-03-27 12507.0 11549.6 722\n",
2249 "2020-04-03 18565.0 11681.4 2898\n",
2250 "2020-04-10 20929.0 11919.4 5909\n",
2251 "2020-04-17 24691.0 11850.6 6338\n",
2252 "2020-04-24 24303.0 11844.4 5773\n",
2253 "2020-05-01 20059.0 11318.4 4881\n",
2254 "2020-05-08 14428.0 10887.2 3638\n",
2255 "2020-05-15 16390.0 11547.0 2671\n",
2256 "2020-05-22 13839.0 11281.0 2075\n",
2257 "2020-05-29 11265.0 9448.0 1890\n",
2258 "2020-06-05 12106.0 11325.6 1207\n",
2259 "2020-06-12 11302.0 10703.6 937\n",
2260 "2020-06-19 10694.0 10698.2 591\n",
2261 "2020-06-26 10282.0 10605.6 480\n",
2262 "2020-07-03 10412.0 10483.0 360\n",
2263 "2020-07-10 9941.0 10509.4 253\n",
2264 "2020-07-17 10096.0 10360.6 164\n",
2265 "2020-07-24 10159.0 10311.6 107\n",
2266 "2020-07-31 10262.0 10307.4 113\n",
2267 "2020-08-07 10236.0 10363.6 89\n",
2268 "2020-08-14 10592.0 10345.8 89\n",
2269 "2020-08-21 10990.0 10433.4 56\n",
2270 "2020-08-28 10364.0 9472.2 74\n",
2271 "2020-09-04 9023.0 10430.4 50\n",
2272 "2020-09-11 11176.0 10610.8 81\n",
2273 "2020-09-18 10797.0 10545.8 97\n",
2274 "2020-09-25 10890.0 10709.6 197\n",
2275 "2020-10-02 11468.0 10890.8 300\n",
2276 "2020-10-09 11373.0 11186.4 390\n",
2277 "2020-10-16 11943.0 11224.8 701\n",
2278 "2020-10-23 12317.0 11093.2 1054\n",
2279 "2020-10-30 12517.0 11257.6 1608\n",
2280 "2020-11-06 13448.0 11729.4 2165\n",
2281 "2020-11-13 13798.0 11803.6 2808\n",
2282 "2020-11-20 14291.0 11821.0 2847\n",
2283 "2020-11-27 14132.0 11802.0 3256"
2284 ]
2285 },
2286 "execution_count": 69,
2287 "metadata": {},
2288 "output_type": "execute_result"
2289 }
2290 ],
2291 "source": [
2292 "excess_deaths = deaths_by_week.loc['2020-03-20':, ['total_2020', 'previous_mean']].merge(\n",
2293 " data_by_week['deaths'], left_index=True, right_index=True)\n",
2294 "excess_deaths.rename(columns={'deaths': 'covid_deaths'}, inplace=True)\n",
2295 "excess_deaths.dropna(inplace=True)\n",
2296 "excess_deaths"
2297 ]
2298 },
2299 {
2300 "cell_type": "markdown",
2301 "metadata": {
2302 "Collapsed": "false"
2303 },
2304 "source": [
2305 "## Correction for the dip in deaths being in week 36, not the usual week 35"
2306 ]
2307 },
2308 {
2309 "cell_type": "code",
2310 "execution_count": 70,
2311 "metadata": {
2312 "Collapsed": "false"
2313 },
2314 "outputs": [
2315 {
2316 "data": {
2317 "text/html": [
2318 "<div>\n",
2319 "<style scoped>\n",
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2323 "\n",
2324 " .dataframe tbody tr th {\n",
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2326 " }\n",
2327 "\n",
2328 " .dataframe thead th {\n",
2329 " text-align: right;\n",
2330 " }\n",
2331 "</style>\n",
2332 "<table border=\"1\" class=\"dataframe\">\n",
2333 " <thead>\n",
2334 " <tr style=\"text-align: right;\">\n",
2335 " <th></th>\n",
2336 " <th>total_2020</th>\n",
2337 " <th>previous_mean</th>\n",
2338 " <th>covid_deaths</th>\n",
2339 " </tr>\n",
2340 " </thead>\n",
2341 " <tbody>\n",
2342 " <tr>\n",
2343 " <td>2020-08-14</td>\n",
2344 " <td>10592.0</td>\n",
2345 " <td>10345.8</td>\n",
2346 " <td>89</td>\n",
2347 " </tr>\n",
2348 " <tr>\n",
2349 " <td>2020-08-21</td>\n",
2350 " <td>10990.0</td>\n",
2351 " <td>10433.4</td>\n",
2352 " <td>56</td>\n",
2353 " </tr>\n",
2354 " <tr>\n",
2355 " <td>2020-08-28</td>\n",
2356 " <td>9023.0</td>\n",
2357 " <td>9472.2</td>\n",
2358 " <td>74</td>\n",
2359 " </tr>\n",
2360 " <tr>\n",
2361 " <td>2020-09-04</td>\n",
2362 " <td>10364.0</td>\n",
2363 " <td>10430.4</td>\n",
2364 " <td>50</td>\n",
2365 " </tr>\n",
2366 " <tr>\n",
2367 " <td>2020-09-11</td>\n",
2368 " <td>11176.0</td>\n",
2369 " <td>10610.8</td>\n",
2370 " <td>81</td>\n",
2371 " </tr>\n",
2372 " <tr>\n",
2373 " <td>2020-09-18</td>\n",
2374 " <td>10797.0</td>\n",
2375 " <td>10545.8</td>\n",
2376 " <td>97</td>\n",
2377 " </tr>\n",
2378 " <tr>\n",
2379 " <td>2020-09-25</td>\n",
2380 " <td>10890.0</td>\n",
2381 " <td>10709.6</td>\n",
2382 " <td>197</td>\n",
2383 " </tr>\n",
2384 " <tr>\n",
2385 " <td>2020-10-02</td>\n",
2386 " <td>11468.0</td>\n",
2387 " <td>10890.8</td>\n",
2388 " <td>300</td>\n",
2389 " </tr>\n",
2390 " <tr>\n",
2391 " <td>2020-10-09</td>\n",
2392 " <td>11373.0</td>\n",
2393 " <td>11186.4</td>\n",
2394 " <td>390</td>\n",
2395 " </tr>\n",
2396 " <tr>\n",
2397 " <td>2020-10-16</td>\n",
2398 " <td>11943.0</td>\n",
2399 " <td>11224.8</td>\n",
2400 " <td>701</td>\n",
2401 " </tr>\n",
2402 " <tr>\n",
2403 " <td>2020-10-23</td>\n",
2404 " <td>12317.0</td>\n",
2405 " <td>11093.2</td>\n",
2406 " <td>1054</td>\n",
2407 " </tr>\n",
2408 " <tr>\n",
2409 " <td>2020-10-30</td>\n",
2410 " <td>12517.0</td>\n",
2411 " <td>11257.6</td>\n",
2412 " <td>1608</td>\n",
2413 " </tr>\n",
2414 " <tr>\n",
2415 " <td>2020-11-06</td>\n",
2416 " <td>13448.0</td>\n",
2417 " <td>11729.4</td>\n",
2418 " <td>2165</td>\n",
2419 " </tr>\n",
2420 " <tr>\n",
2421 " <td>2020-11-13</td>\n",
2422 " <td>13798.0</td>\n",
2423 " <td>11803.6</td>\n",
2424 " <td>2808</td>\n",
2425 " </tr>\n",
2426 " <tr>\n",
2427 " <td>2020-11-20</td>\n",
2428 " <td>14291.0</td>\n",
2429 " <td>11821.0</td>\n",
2430 " <td>2847</td>\n",
2431 " </tr>\n",
2432 " <tr>\n",
2433 " <td>2020-11-27</td>\n",
2434 " <td>14132.0</td>\n",
2435 " <td>11802.0</td>\n",
2436 " <td>3256</td>\n",
2437 " </tr>\n",
2438 " </tbody>\n",
2439 "</table>\n",
2440 "</div>"
2441 ],
2442 "text/plain": [
2443 " total_2020 previous_mean covid_deaths\n",
2444 "2020-08-14 10592.0 10345.8 89\n",
2445 "2020-08-21 10990.0 10433.4 56\n",
2446 "2020-08-28 9023.0 9472.2 74\n",
2447 "2020-09-04 10364.0 10430.4 50\n",
2448 "2020-09-11 11176.0 10610.8 81\n",
2449 "2020-09-18 10797.0 10545.8 97\n",
2450 "2020-09-25 10890.0 10709.6 197\n",
2451 "2020-10-02 11468.0 10890.8 300\n",
2452 "2020-10-09 11373.0 11186.4 390\n",
2453 "2020-10-16 11943.0 11224.8 701\n",
2454 "2020-10-23 12317.0 11093.2 1054\n",
2455 "2020-10-30 12517.0 11257.6 1608\n",
2456 "2020-11-06 13448.0 11729.4 2165\n",
2457 "2020-11-13 13798.0 11803.6 2808\n",
2458 "2020-11-20 14291.0 11821.0 2847\n",
2459 "2020-11-27 14132.0 11802.0 3256"
2460 ]
2461 },
2462 "execution_count": 70,
2463 "metadata": {},
2464 "output_type": "execute_result"
2465 }
2466 ],
2467 "source": [
2468 "temp1 = excess_deaths.loc['2020-08-28'].total_2020\n",
2469 "temp2 = excess_deaths.loc['2020-09-04'].total_2020\n",
2470 "excess_deaths.loc['2020-08-28', 'total_2020'] = temp2\n",
2471 "excess_deaths.loc['2020-09-04', 'total_2020'] = temp1\n",
2472 "excess_deaths.loc['2020-08-14':]"
2473 ]
2474 },
2475 {
2476 "cell_type": "code",
2477 "execution_count": 71,
2478 "metadata": {
2479 "Collapsed": "false"
2480 },
2481 "outputs": [
2482 {
2483 "data": {
2484 "text/plain": [
2485 "(10364.0, 9023.0)"
2486 ]
2487 },
2488 "execution_count": 71,
2489 "metadata": {},
2490 "output_type": "execute_result"
2491 }
2492 ],
2493 "source": [
2494 "temp1, temp2"
2495 ]
2496 },
2497 {
2498 "cell_type": "code",
2499 "execution_count": 72,
2500 "metadata": {
2501 "Collapsed": "false"
2502 },
2503 "outputs": [
2504 {
2505 "data": {
2506 "text/html": [
2507 "<div>\n",
2508 "<style scoped>\n",
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2512 "\n",
2513 " .dataframe tbody tr th {\n",
2514 " vertical-align: top;\n",
2515 " }\n",
2516 "\n",
2517 " .dataframe thead th {\n",
2518 " text-align: right;\n",
2519 " }\n",
2520 "</style>\n",
2521 "<table border=\"1\" class=\"dataframe\">\n",
2522 " <thead>\n",
2523 " <tr style=\"text-align: right;\">\n",
2524 " <th></th>\n",
2525 " <th>total_2020</th>\n",
2526 " <th>previous_mean</th>\n",
2527 " <th>covid_deaths</th>\n",
2528 " <th>excess</th>\n",
2529 " <th>attributable</th>\n",
2530 " </tr>\n",
2531 " </thead>\n",
2532 " <tbody>\n",
2533 " <tr>\n",
2534 " <td>2020-03-20</td>\n",
2535 " <td>12112.0</td>\n",
2536 " <td>12007.4</td>\n",
2537 " <td>153</td>\n",
2538 " <td>104.6</td>\n",
2539 " <td>153.0</td>\n",
2540 " </tr>\n",
2541 " <tr>\n",
2542 " <td>2020-03-27</td>\n",
2543 " <td>12507.0</td>\n",
2544 " <td>11549.6</td>\n",
2545 " <td>722</td>\n",
2546 " <td>957.4</td>\n",
2547 " <td>957.4</td>\n",
2548 " </tr>\n",
2549 " <tr>\n",
2550 " <td>2020-04-03</td>\n",
2551 " <td>18565.0</td>\n",
2552 " <td>11681.4</td>\n",
2553 " <td>2898</td>\n",
2554 " <td>6883.6</td>\n",
2555 " <td>6883.6</td>\n",
2556 " </tr>\n",
2557 " <tr>\n",
2558 " <td>2020-04-10</td>\n",
2559 " <td>20929.0</td>\n",
2560 " <td>11919.4</td>\n",
2561 " <td>5909</td>\n",
2562 " <td>9009.6</td>\n",
2563 " <td>9009.6</td>\n",
2564 " </tr>\n",
2565 " <tr>\n",
2566 " <td>2020-04-17</td>\n",
2567 " <td>24691.0</td>\n",
2568 " <td>11850.6</td>\n",
2569 " <td>6338</td>\n",
2570 " <td>12840.4</td>\n",
2571 " <td>12840.4</td>\n",
2572 " </tr>\n",
2573 " <tr>\n",
2574 " <td>2020-04-24</td>\n",
2575 " <td>24303.0</td>\n",
2576 " <td>11844.4</td>\n",
2577 " <td>5773</td>\n",
2578 " <td>12458.6</td>\n",
2579 " <td>12458.6</td>\n",
2580 " </tr>\n",
2581 " <tr>\n",
2582 " <td>2020-05-01</td>\n",
2583 " <td>20059.0</td>\n",
2584 " <td>11318.4</td>\n",
2585 " <td>4881</td>\n",
2586 " <td>8740.6</td>\n",
2587 " <td>8740.6</td>\n",
2588 " </tr>\n",
2589 " <tr>\n",
2590 " <td>2020-05-08</td>\n",
2591 " <td>14428.0</td>\n",
2592 " <td>10887.2</td>\n",
2593 " <td>3638</td>\n",
2594 " <td>3540.8</td>\n",
2595 " <td>3638.0</td>\n",
2596 " </tr>\n",
2597 " <tr>\n",
2598 " <td>2020-05-15</td>\n",
2599 " <td>16390.0</td>\n",
2600 " <td>11547.0</td>\n",
2601 " <td>2671</td>\n",
2602 " <td>4843.0</td>\n",
2603 " <td>4843.0</td>\n",
2604 " </tr>\n",
2605 " <tr>\n",
2606 " <td>2020-05-22</td>\n",
2607 " <td>13839.0</td>\n",
2608 " <td>11281.0</td>\n",
2609 " <td>2075</td>\n",
2610 " <td>2558.0</td>\n",
2611 " <td>2558.0</td>\n",
2612 " </tr>\n",
2613 " <tr>\n",
2614 " <td>2020-05-29</td>\n",
2615 " <td>11265.0</td>\n",
2616 " <td>9448.0</td>\n",
2617 " <td>1890</td>\n",
2618 " <td>1817.0</td>\n",
2619 " <td>1890.0</td>\n",
2620 " </tr>\n",
2621 " <tr>\n",
2622 " <td>2020-06-05</td>\n",
2623 " <td>12106.0</td>\n",
2624 " <td>11325.6</td>\n",
2625 " <td>1207</td>\n",
2626 " <td>780.4</td>\n",
2627 " <td>1207.0</td>\n",
2628 " </tr>\n",
2629 " <tr>\n",
2630 " <td>2020-06-12</td>\n",
2631 " <td>11302.0</td>\n",
2632 " <td>10703.6</td>\n",
2633 " <td>937</td>\n",
2634 " <td>598.4</td>\n",
2635 " <td>937.0</td>\n",
2636 " </tr>\n",
2637 " <tr>\n",
2638 " <td>2020-06-19</td>\n",
2639 " <td>10694.0</td>\n",
2640 " <td>10698.2</td>\n",
2641 " <td>591</td>\n",
2642 " <td>-4.2</td>\n",
2643 " <td>591.0</td>\n",
2644 " </tr>\n",
2645 " <tr>\n",
2646 " <td>2020-06-26</td>\n",
2647 " <td>10282.0</td>\n",
2648 " <td>10605.6</td>\n",
2649 " <td>480</td>\n",
2650 " <td>-323.6</td>\n",
2651 " <td>480.0</td>\n",
2652 " </tr>\n",
2653 " <tr>\n",
2654 " <td>2020-07-03</td>\n",
2655 " <td>10412.0</td>\n",
2656 " <td>10483.0</td>\n",
2657 " <td>360</td>\n",
2658 " <td>-71.0</td>\n",
2659 " <td>360.0</td>\n",
2660 " </tr>\n",
2661 " <tr>\n",
2662 " <td>2020-07-10</td>\n",
2663 " <td>9941.0</td>\n",
2664 " <td>10509.4</td>\n",
2665 " <td>253</td>\n",
2666 " <td>-568.4</td>\n",
2667 " <td>253.0</td>\n",
2668 " </tr>\n",
2669 " <tr>\n",
2670 " <td>2020-07-17</td>\n",
2671 " <td>10096.0</td>\n",
2672 " <td>10360.6</td>\n",
2673 " <td>164</td>\n",
2674 " <td>-264.6</td>\n",
2675 " <td>164.0</td>\n",
2676 " </tr>\n",
2677 " <tr>\n",
2678 " <td>2020-07-24</td>\n",
2679 " <td>10159.0</td>\n",
2680 " <td>10311.6</td>\n",
2681 " <td>107</td>\n",
2682 " <td>-152.6</td>\n",
2683 " <td>107.0</td>\n",
2684 " </tr>\n",
2685 " <tr>\n",
2686 " <td>2020-07-31</td>\n",
2687 " <td>10262.0</td>\n",
2688 " <td>10307.4</td>\n",
2689 " <td>113</td>\n",
2690 " <td>-45.4</td>\n",
2691 " <td>113.0</td>\n",
2692 " </tr>\n",
2693 " <tr>\n",
2694 " <td>2020-08-07</td>\n",
2695 " <td>10236.0</td>\n",
2696 " <td>10363.6</td>\n",
2697 " <td>89</td>\n",
2698 " <td>-127.6</td>\n",
2699 " <td>89.0</td>\n",
2700 " </tr>\n",
2701 " <tr>\n",
2702 " <td>2020-08-14</td>\n",
2703 " <td>10592.0</td>\n",
2704 " <td>10345.8</td>\n",
2705 " <td>89</td>\n",
2706 " <td>246.2</td>\n",
2707 " <td>246.2</td>\n",
2708 " </tr>\n",
2709 " <tr>\n",
2710 " <td>2020-08-21</td>\n",
2711 " <td>10990.0</td>\n",
2712 " <td>10433.4</td>\n",
2713 " <td>56</td>\n",
2714 " <td>556.6</td>\n",
2715 " <td>556.6</td>\n",
2716 " </tr>\n",
2717 " <tr>\n",
2718 " <td>2020-08-28</td>\n",
2719 " <td>9023.0</td>\n",
2720 " <td>9472.2</td>\n",
2721 " <td>74</td>\n",
2722 " <td>-449.2</td>\n",
2723 " <td>74.0</td>\n",
2724 " </tr>\n",
2725 " <tr>\n",
2726 " <td>2020-09-04</td>\n",
2727 " <td>10364.0</td>\n",
2728 " <td>10430.4</td>\n",
2729 " <td>50</td>\n",
2730 " <td>-66.4</td>\n",
2731 " <td>50.0</td>\n",
2732 " </tr>\n",
2733 " <tr>\n",
2734 " <td>2020-09-11</td>\n",
2735 " <td>11176.0</td>\n",
2736 " <td>10610.8</td>\n",
2737 " <td>81</td>\n",
2738 " <td>565.2</td>\n",
2739 " <td>565.2</td>\n",
2740 " </tr>\n",
2741 " <tr>\n",
2742 " <td>2020-09-18</td>\n",
2743 " <td>10797.0</td>\n",
2744 " <td>10545.8</td>\n",
2745 " <td>97</td>\n",
2746 " <td>251.2</td>\n",
2747 " <td>251.2</td>\n",
2748 " </tr>\n",
2749 " <tr>\n",
2750 " <td>2020-09-25</td>\n",
2751 " <td>10890.0</td>\n",
2752 " <td>10709.6</td>\n",
2753 " <td>197</td>\n",
2754 " <td>180.4</td>\n",
2755 " <td>197.0</td>\n",
2756 " </tr>\n",
2757 " <tr>\n",
2758 " <td>2020-10-02</td>\n",
2759 " <td>11468.0</td>\n",
2760 " <td>10890.8</td>\n",
2761 " <td>300</td>\n",
2762 " <td>577.2</td>\n",
2763 " <td>577.2</td>\n",
2764 " </tr>\n",
2765 " <tr>\n",
2766 " <td>2020-10-09</td>\n",
2767 " <td>11373.0</td>\n",
2768 " <td>11186.4</td>\n",
2769 " <td>390</td>\n",
2770 " <td>186.6</td>\n",
2771 " <td>390.0</td>\n",
2772 " </tr>\n",
2773 " <tr>\n",
2774 " <td>2020-10-16</td>\n",
2775 " <td>11943.0</td>\n",
2776 " <td>11224.8</td>\n",
2777 " <td>701</td>\n",
2778 " <td>718.2</td>\n",
2779 " <td>718.2</td>\n",
2780 " </tr>\n",
2781 " <tr>\n",
2782 " <td>2020-10-23</td>\n",
2783 " <td>12317.0</td>\n",
2784 " <td>11093.2</td>\n",
2785 " <td>1054</td>\n",
2786 " <td>1223.8</td>\n",
2787 " <td>1223.8</td>\n",
2788 " </tr>\n",
2789 " <tr>\n",
2790 " <td>2020-10-30</td>\n",
2791 " <td>12517.0</td>\n",
2792 " <td>11257.6</td>\n",
2793 " <td>1608</td>\n",
2794 " <td>1259.4</td>\n",
2795 " <td>1608.0</td>\n",
2796 " </tr>\n",
2797 " <tr>\n",
2798 " <td>2020-11-06</td>\n",
2799 " <td>13448.0</td>\n",
2800 " <td>11729.4</td>\n",
2801 " <td>2165</td>\n",
2802 " <td>1718.6</td>\n",
2803 " <td>2165.0</td>\n",
2804 " </tr>\n",
2805 " <tr>\n",
2806 " <td>2020-11-13</td>\n",
2807 " <td>13798.0</td>\n",
2808 " <td>11803.6</td>\n",
2809 " <td>2808</td>\n",
2810 " <td>1994.4</td>\n",
2811 " <td>2808.0</td>\n",
2812 " </tr>\n",
2813 " <tr>\n",
2814 " <td>2020-11-20</td>\n",
2815 " <td>14291.0</td>\n",
2816 " <td>11821.0</td>\n",
2817 " <td>2847</td>\n",
2818 " <td>2470.0</td>\n",
2819 " <td>2847.0</td>\n",
2820 " </tr>\n",
2821 " <tr>\n",
2822 " <td>2020-11-27</td>\n",
2823 " <td>14132.0</td>\n",
2824 " <td>11802.0</td>\n",
2825 " <td>3256</td>\n",
2826 " <td>2330.0</td>\n",
2827 " <td>3256.0</td>\n",
2828 " </tr>\n",
2829 " </tbody>\n",
2830 "</table>\n",
2831 "</div>"
2832 ],
2833 "text/plain": [
2834 " total_2020 previous_mean covid_deaths excess attributable\n",
2835 "2020-03-20 12112.0 12007.4 153 104.6 153.0\n",
2836 "2020-03-27 12507.0 11549.6 722 957.4 957.4\n",
2837 "2020-04-03 18565.0 11681.4 2898 6883.6 6883.6\n",
2838 "2020-04-10 20929.0 11919.4 5909 9009.6 9009.6\n",
2839 "2020-04-17 24691.0 11850.6 6338 12840.4 12840.4\n",
2840 "2020-04-24 24303.0 11844.4 5773 12458.6 12458.6\n",
2841 "2020-05-01 20059.0 11318.4 4881 8740.6 8740.6\n",
2842 "2020-05-08 14428.0 10887.2 3638 3540.8 3638.0\n",
2843 "2020-05-15 16390.0 11547.0 2671 4843.0 4843.0\n",
2844 "2020-05-22 13839.0 11281.0 2075 2558.0 2558.0\n",
2845 "2020-05-29 11265.0 9448.0 1890 1817.0 1890.0\n",
2846 "2020-06-05 12106.0 11325.6 1207 780.4 1207.0\n",
2847 "2020-06-12 11302.0 10703.6 937 598.4 937.0\n",
2848 "2020-06-19 10694.0 10698.2 591 -4.2 591.0\n",
2849 "2020-06-26 10282.0 10605.6 480 -323.6 480.0\n",
2850 "2020-07-03 10412.0 10483.0 360 -71.0 360.0\n",
2851 "2020-07-10 9941.0 10509.4 253 -568.4 253.0\n",
2852 "2020-07-17 10096.0 10360.6 164 -264.6 164.0\n",
2853 "2020-07-24 10159.0 10311.6 107 -152.6 107.0\n",
2854 "2020-07-31 10262.0 10307.4 113 -45.4 113.0\n",
2855 "2020-08-07 10236.0 10363.6 89 -127.6 89.0\n",
2856 "2020-08-14 10592.0 10345.8 89 246.2 246.2\n",
2857 "2020-08-21 10990.0 10433.4 56 556.6 556.6\n",
2858 "2020-08-28 9023.0 9472.2 74 -449.2 74.0\n",
2859 "2020-09-04 10364.0 10430.4 50 -66.4 50.0\n",
2860 "2020-09-11 11176.0 10610.8 81 565.2 565.2\n",
2861 "2020-09-18 10797.0 10545.8 97 251.2 251.2\n",
2862 "2020-09-25 10890.0 10709.6 197 180.4 197.0\n",
2863 "2020-10-02 11468.0 10890.8 300 577.2 577.2\n",
2864 "2020-10-09 11373.0 11186.4 390 186.6 390.0\n",
2865 "2020-10-16 11943.0 11224.8 701 718.2 718.2\n",
2866 "2020-10-23 12317.0 11093.2 1054 1223.8 1223.8\n",
2867 "2020-10-30 12517.0 11257.6 1608 1259.4 1608.0\n",
2868 "2020-11-06 13448.0 11729.4 2165 1718.6 2165.0\n",
2869 "2020-11-13 13798.0 11803.6 2808 1994.4 2808.0\n",
2870 "2020-11-20 14291.0 11821.0 2847 2470.0 2847.0\n",
2871 "2020-11-27 14132.0 11802.0 3256 2330.0 3256.0"
2872 ]
2873 },
2874 "execution_count": 72,
2875 "metadata": {},
2876 "output_type": "execute_result"
2877 }
2878 ],
2879 "source": [
2880 "excess_deaths['excess'] = excess_deaths.total_2020 - excess_deaths.previous_mean\n",
2881 "excess_deaths['attributable'] = excess_deaths[['covid_deaths', 'excess']].max(axis=1)\n",
2882 "excess_deaths"
2883 ]
2884 },
2885 {
2886 "cell_type": "code",
2887 "execution_count": 73,
2888 "metadata": {
2889 "Collapsed": "false"
2890 },
2891 "outputs": [
2892 {
2893 "data": {
2894 "text/plain": [
2895 "<matplotlib.axes._subplots.AxesSubplot at 0x7f41c44a9610>"
2896 ]
2897 },
2898 "execution_count": 73,
2899 "metadata": {},
2900 "output_type": "execute_result"
2901 },
2902 {
2903 "data": {
2904 "image/png": 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\n",
2905 "text/plain": [
2906 "<Figure size 432x288 with 1 Axes>"
2907 ]
2908 },
2909 "metadata": {
2910 "needs_background": "light"
2911 },
2912 "output_type": "display_data"
2913 }
2914 ],
2915 "source": [
2916 "excess_deaths[['covid_deaths', 'excess']].plot()"
2917 ]
2918 },
2919 {
2920 "cell_type": "code",
2921 "execution_count": 74,
2922 "metadata": {
2923 "Collapsed": "false"
2924 },
2925 "outputs": [
2926 {
2927 "data": {
2928 "text/plain": [
2929 "1.3562695100136786"
2930 ]
2931 },
2932 "execution_count": 74,
2933 "metadata": {},
2934 "output_type": "execute_result"
2935 }
2936 ],
2937 "source": [
2938 "excess_deaths.excess.sum() / excess_deaths.covid_deaths.sum()"
2939 ]
2940 },
2941 {
2942 "cell_type": "code",
2943 "execution_count": 75,
2944 "metadata": {
2945 "Collapsed": "false"
2946 },
2947 "outputs": [
2948 {
2949 "data": {
2950 "text/html": [
2951 "<div>\n",
2952 "<style scoped>\n",
2953 " .dataframe tbody tr th:only-of-type {\n",
2954 " vertical-align: middle;\n",
2955 " }\n",
2956 "\n",
2957 " .dataframe tbody tr th {\n",
2958 " vertical-align: top;\n",
2959 " }\n",
2960 "\n",
2961 " .dataframe thead th {\n",
2962 " text-align: right;\n",
2963 " }\n",
2964 "</style>\n",
2965 "<table border=\"1\" class=\"dataframe\">\n",
2966 " <thead>\n",
2967 " <tr style=\"text-align: right;\">\n",
2968 " <th></th>\n",
2969 " <th>total_2020</th>\n",
2970 " <th>previous_mean</th>\n",
2971 " <th>covid_deaths</th>\n",
2972 " <th>excess</th>\n",
2973 " <th>attributable</th>\n",
2974 " <th>accounted_fraction</th>\n",
2975 " </tr>\n",
2976 " </thead>\n",
2977 " <tbody>\n",
2978 " <tr>\n",
2979 " <td>2020-03-20</td>\n",
2980 " <td>12112.0</td>\n",
2981 " <td>12007.4</td>\n",
2982 " <td>153</td>\n",
2983 " <td>104.6</td>\n",
2984 " <td>153.0</td>\n",
2985 " <td>1.462715</td>\n",
2986 " </tr>\n",
2987 " <tr>\n",
2988 " <td>2020-03-27</td>\n",
2989 " <td>12507.0</td>\n",
2990 " <td>11549.6</td>\n",
2991 " <td>722</td>\n",
2992 " <td>957.4</td>\n",
2993 " <td>957.4</td>\n",
2994 " <td>0.754126</td>\n",
2995 " </tr>\n",
2996 " <tr>\n",
2997 " <td>2020-04-03</td>\n",
2998 " <td>18565.0</td>\n",
2999 " <td>11681.4</td>\n",
3000 " <td>2898</td>\n",
3001 " <td>6883.6</td>\n",
3002 " <td>6883.6</td>\n",
3003 " <td>0.421001</td>\n",
3004 " </tr>\n",
3005 " <tr>\n",
3006 " <td>2020-04-10</td>\n",
3007 " <td>20929.0</td>\n",
3008 " <td>11919.4</td>\n",
3009 " <td>5909</td>\n",
3010 " <td>9009.6</td>\n",
3011 " <td>9009.6</td>\n",
3012 " <td>0.655856</td>\n",
3013 " </tr>\n",
3014 " <tr>\n",
3015 " <td>2020-04-17</td>\n",
3016 " <td>24691.0</td>\n",
3017 " <td>11850.6</td>\n",
3018 " <td>6338</td>\n",
3019 " <td>12840.4</td>\n",
3020 " <td>12840.4</td>\n",
3021 " <td>0.493598</td>\n",
3022 " </tr>\n",
3023 " <tr>\n",
3024 " <td>2020-04-24</td>\n",
3025 " <td>24303.0</td>\n",
3026 " <td>11844.4</td>\n",
3027 " <td>5773</td>\n",
3028 " <td>12458.6</td>\n",
3029 " <td>12458.6</td>\n",
3030 " <td>0.463375</td>\n",
3031 " </tr>\n",
3032 " <tr>\n",
3033 " <td>2020-05-01</td>\n",
3034 " <td>20059.0</td>\n",
3035 " <td>11318.4</td>\n",
3036 " <td>4881</td>\n",
3037 " <td>8740.6</td>\n",
3038 " <td>8740.6</td>\n",
3039 " <td>0.558428</td>\n",
3040 " </tr>\n",
3041 " <tr>\n",
3042 " <td>2020-05-08</td>\n",
3043 " <td>14428.0</td>\n",
3044 " <td>10887.2</td>\n",
3045 " <td>3638</td>\n",
3046 " <td>3540.8</td>\n",
3047 " <td>3638.0</td>\n",
3048 " <td>1.027451</td>\n",
3049 " </tr>\n",
3050 " <tr>\n",
3051 " <td>2020-05-15</td>\n",
3052 " <td>16390.0</td>\n",
3053 " <td>11547.0</td>\n",
3054 " <td>2671</td>\n",
3055 " <td>4843.0</td>\n",
3056 " <td>4843.0</td>\n",
3057 " <td>0.551518</td>\n",
3058 " </tr>\n",
3059 " <tr>\n",
3060 " <td>2020-05-22</td>\n",
3061 " <td>13839.0</td>\n",
3062 " <td>11281.0</td>\n",
3063 " <td>2075</td>\n",
3064 " <td>2558.0</td>\n",
3065 " <td>2558.0</td>\n",
3066 " <td>0.811181</td>\n",
3067 " </tr>\n",
3068 " <tr>\n",
3069 " <td>2020-05-29</td>\n",
3070 " <td>11265.0</td>\n",
3071 " <td>9448.0</td>\n",
3072 " <td>1890</td>\n",
3073 " <td>1817.0</td>\n",
3074 " <td>1890.0</td>\n",
3075 " <td>1.040176</td>\n",
3076 " </tr>\n",
3077 " <tr>\n",
3078 " <td>2020-06-05</td>\n",
3079 " <td>12106.0</td>\n",
3080 " <td>11325.6</td>\n",
3081 " <td>1207</td>\n",
3082 " <td>780.4</td>\n",
3083 " <td>1207.0</td>\n",
3084 " <td>1.546643</td>\n",
3085 " </tr>\n",
3086 " <tr>\n",
3087 " <td>2020-06-12</td>\n",
3088 " <td>11302.0</td>\n",
3089 " <td>10703.6</td>\n",
3090 " <td>937</td>\n",
3091 " <td>598.4</td>\n",
3092 " <td>937.0</td>\n",
3093 " <td>1.565842</td>\n",
3094 " </tr>\n",
3095 " <tr>\n",
3096 " <td>2020-06-19</td>\n",
3097 " <td>10694.0</td>\n",
3098 " <td>10698.2</td>\n",
3099 " <td>591</td>\n",
3100 " <td>-4.2</td>\n",
3101 " <td>591.0</td>\n",
3102 " <td>-140.714286</td>\n",
3103 " </tr>\n",
3104 " <tr>\n",
3105 " <td>2020-06-26</td>\n",
3106 " <td>10282.0</td>\n",
3107 " <td>10605.6</td>\n",
3108 " <td>480</td>\n",
3109 " <td>-323.6</td>\n",
3110 " <td>480.0</td>\n",
3111 " <td>-1.483313</td>\n",
3112 " </tr>\n",
3113 " <tr>\n",
3114 " <td>2020-07-03</td>\n",
3115 " <td>10412.0</td>\n",
3116 " <td>10483.0</td>\n",
3117 " <td>360</td>\n",
3118 " <td>-71.0</td>\n",
3119 " <td>360.0</td>\n",
3120 " <td>-5.070423</td>\n",
3121 " </tr>\n",
3122 " <tr>\n",
3123 " <td>2020-07-10</td>\n",
3124 " <td>9941.0</td>\n",
3125 " <td>10509.4</td>\n",
3126 " <td>253</td>\n",
3127 " <td>-568.4</td>\n",
3128 " <td>253.0</td>\n",
3129 " <td>-0.445109</td>\n",
3130 " </tr>\n",
3131 " <tr>\n",
3132 " <td>2020-07-17</td>\n",
3133 " <td>10096.0</td>\n",
3134 " <td>10360.6</td>\n",
3135 " <td>164</td>\n",
3136 " <td>-264.6</td>\n",
3137 " <td>164.0</td>\n",
3138 " <td>-0.619803</td>\n",
3139 " </tr>\n",
3140 " <tr>\n",
3141 " <td>2020-07-24</td>\n",
3142 " <td>10159.0</td>\n",
3143 " <td>10311.6</td>\n",
3144 " <td>107</td>\n",
3145 " <td>-152.6</td>\n",
3146 " <td>107.0</td>\n",
3147 " <td>-0.701180</td>\n",
3148 " </tr>\n",
3149 " <tr>\n",
3150 " <td>2020-07-31</td>\n",
3151 " <td>10262.0</td>\n",
3152 " <td>10307.4</td>\n",
3153 " <td>113</td>\n",
3154 " <td>-45.4</td>\n",
3155 " <td>113.0</td>\n",
3156 " <td>-2.488987</td>\n",
3157 " </tr>\n",
3158 " <tr>\n",
3159 " <td>2020-08-07</td>\n",
3160 " <td>10236.0</td>\n",
3161 " <td>10363.6</td>\n",
3162 " <td>89</td>\n",
3163 " <td>-127.6</td>\n",
3164 " <td>89.0</td>\n",
3165 " <td>-0.697492</td>\n",
3166 " </tr>\n",
3167 " <tr>\n",
3168 " <td>2020-08-14</td>\n",
3169 " <td>10592.0</td>\n",
3170 " <td>10345.8</td>\n",
3171 " <td>89</td>\n",
3172 " <td>246.2</td>\n",
3173 " <td>246.2</td>\n",
3174 " <td>0.361495</td>\n",
3175 " </tr>\n",
3176 " <tr>\n",
3177 " <td>2020-08-21</td>\n",
3178 " <td>10990.0</td>\n",
3179 " <td>10433.4</td>\n",
3180 " <td>56</td>\n",
3181 " <td>556.6</td>\n",
3182 " <td>556.6</td>\n",
3183 " <td>0.100611</td>\n",
3184 " </tr>\n",
3185 " <tr>\n",
3186 " <td>2020-08-28</td>\n",
3187 " <td>9023.0</td>\n",
3188 " <td>9472.2</td>\n",
3189 " <td>74</td>\n",
3190 " <td>-449.2</td>\n",
3191 " <td>74.0</td>\n",
3192 " <td>-0.164737</td>\n",
3193 " </tr>\n",
3194 " <tr>\n",
3195 " <td>2020-09-04</td>\n",
3196 " <td>10364.0</td>\n",
3197 " <td>10430.4</td>\n",
3198 " <td>50</td>\n",
3199 " <td>-66.4</td>\n",
3200 " <td>50.0</td>\n",
3201 " <td>-0.753012</td>\n",
3202 " </tr>\n",
3203 " <tr>\n",
3204 " <td>2020-09-11</td>\n",
3205 " <td>11176.0</td>\n",
3206 " <td>10610.8</td>\n",
3207 " <td>81</td>\n",
3208 " <td>565.2</td>\n",
3209 " <td>565.2</td>\n",
3210 " <td>0.143312</td>\n",
3211 " </tr>\n",
3212 " <tr>\n",
3213 " <td>2020-09-18</td>\n",
3214 " <td>10797.0</td>\n",
3215 " <td>10545.8</td>\n",
3216 " <td>97</td>\n",
3217 " <td>251.2</td>\n",
3218 " <td>251.2</td>\n",
3219 " <td>0.386146</td>\n",
3220 " </tr>\n",
3221 " <tr>\n",
3222 " <td>2020-09-25</td>\n",
3223 " <td>10890.0</td>\n",
3224 " <td>10709.6</td>\n",
3225 " <td>197</td>\n",
3226 " <td>180.4</td>\n",
3227 " <td>197.0</td>\n",
3228 " <td>1.092018</td>\n",
3229 " </tr>\n",
3230 " <tr>\n",
3231 " <td>2020-10-02</td>\n",
3232 " <td>11468.0</td>\n",
3233 " <td>10890.8</td>\n",
3234 " <td>300</td>\n",
3235 " <td>577.2</td>\n",
3236 " <td>577.2</td>\n",
3237 " <td>0.519751</td>\n",
3238 " </tr>\n",
3239 " <tr>\n",
3240 " <td>2020-10-09</td>\n",
3241 " <td>11373.0</td>\n",
3242 " <td>11186.4</td>\n",
3243 " <td>390</td>\n",
3244 " <td>186.6</td>\n",
3245 " <td>390.0</td>\n",
3246 " <td>2.090032</td>\n",
3247 " </tr>\n",
3248 " <tr>\n",
3249 " <td>2020-10-16</td>\n",
3250 " <td>11943.0</td>\n",
3251 " <td>11224.8</td>\n",
3252 " <td>701</td>\n",
3253 " <td>718.2</td>\n",
3254 " <td>718.2</td>\n",
3255 " <td>0.976051</td>\n",
3256 " </tr>\n",
3257 " <tr>\n",
3258 " <td>2020-10-23</td>\n",
3259 " <td>12317.0</td>\n",
3260 " <td>11093.2</td>\n",
3261 " <td>1054</td>\n",
3262 " <td>1223.8</td>\n",
3263 " <td>1223.8</td>\n",
3264 " <td>0.861252</td>\n",
3265 " </tr>\n",
3266 " <tr>\n",
3267 " <td>2020-10-30</td>\n",
3268 " <td>12517.0</td>\n",
3269 " <td>11257.6</td>\n",
3270 " <td>1608</td>\n",
3271 " <td>1259.4</td>\n",
3272 " <td>1608.0</td>\n",
3273 " <td>1.276798</td>\n",
3274 " </tr>\n",
3275 " <tr>\n",
3276 " <td>2020-11-06</td>\n",
3277 " <td>13448.0</td>\n",
3278 " <td>11729.4</td>\n",
3279 " <td>2165</td>\n",
3280 " <td>1718.6</td>\n",
3281 " <td>2165.0</td>\n",
3282 " <td>1.259746</td>\n",
3283 " </tr>\n",
3284 " <tr>\n",
3285 " <td>2020-11-13</td>\n",
3286 " <td>13798.0</td>\n",
3287 " <td>11803.6</td>\n",
3288 " <td>2808</td>\n",
3289 " <td>1994.4</td>\n",
3290 " <td>2808.0</td>\n",
3291 " <td>1.407942</td>\n",
3292 " </tr>\n",
3293 " <tr>\n",
3294 " <td>2020-11-20</td>\n",
3295 " <td>14291.0</td>\n",
3296 " <td>11821.0</td>\n",
3297 " <td>2847</td>\n",
3298 " <td>2470.0</td>\n",
3299 " <td>2847.0</td>\n",
3300 " <td>1.152632</td>\n",
3301 " </tr>\n",
3302 " <tr>\n",
3303 " <td>2020-11-27</td>\n",
3304 " <td>14132.0</td>\n",
3305 " <td>11802.0</td>\n",
3306 " <td>3256</td>\n",
3307 " <td>2330.0</td>\n",
3308 " <td>3256.0</td>\n",
3309 " <td>1.397425</td>\n",
3310 " </tr>\n",
3311 " </tbody>\n",
3312 "</table>\n",
3313 "</div>"
3314 ],
3315 "text/plain": [
3316 " total_2020 previous_mean covid_deaths excess attributable \\\n",
3317 "2020-03-20 12112.0 12007.4 153 104.6 153.0 \n",
3318 "2020-03-27 12507.0 11549.6 722 957.4 957.4 \n",
3319 "2020-04-03 18565.0 11681.4 2898 6883.6 6883.6 \n",
3320 "2020-04-10 20929.0 11919.4 5909 9009.6 9009.6 \n",
3321 "2020-04-17 24691.0 11850.6 6338 12840.4 12840.4 \n",
3322 "2020-04-24 24303.0 11844.4 5773 12458.6 12458.6 \n",
3323 "2020-05-01 20059.0 11318.4 4881 8740.6 8740.6 \n",
3324 "2020-05-08 14428.0 10887.2 3638 3540.8 3638.0 \n",
3325 "2020-05-15 16390.0 11547.0 2671 4843.0 4843.0 \n",
3326 "2020-05-22 13839.0 11281.0 2075 2558.0 2558.0 \n",
3327 "2020-05-29 11265.0 9448.0 1890 1817.0 1890.0 \n",
3328 "2020-06-05 12106.0 11325.6 1207 780.4 1207.0 \n",
3329 "2020-06-12 11302.0 10703.6 937 598.4 937.0 \n",
3330 "2020-06-19 10694.0 10698.2 591 -4.2 591.0 \n",
3331 "2020-06-26 10282.0 10605.6 480 -323.6 480.0 \n",
3332 "2020-07-03 10412.0 10483.0 360 -71.0 360.0 \n",
3333 "2020-07-10 9941.0 10509.4 253 -568.4 253.0 \n",
3334 "2020-07-17 10096.0 10360.6 164 -264.6 164.0 \n",
3335 "2020-07-24 10159.0 10311.6 107 -152.6 107.0 \n",
3336 "2020-07-31 10262.0 10307.4 113 -45.4 113.0 \n",
3337 "2020-08-07 10236.0 10363.6 89 -127.6 89.0 \n",
3338 "2020-08-14 10592.0 10345.8 89 246.2 246.2 \n",
3339 "2020-08-21 10990.0 10433.4 56 556.6 556.6 \n",
3340 "2020-08-28 9023.0 9472.2 74 -449.2 74.0 \n",
3341 "2020-09-04 10364.0 10430.4 50 -66.4 50.0 \n",
3342 "2020-09-11 11176.0 10610.8 81 565.2 565.2 \n",
3343 "2020-09-18 10797.0 10545.8 97 251.2 251.2 \n",
3344 "2020-09-25 10890.0 10709.6 197 180.4 197.0 \n",
3345 "2020-10-02 11468.0 10890.8 300 577.2 577.2 \n",
3346 "2020-10-09 11373.0 11186.4 390 186.6 390.0 \n",
3347 "2020-10-16 11943.0 11224.8 701 718.2 718.2 \n",
3348 "2020-10-23 12317.0 11093.2 1054 1223.8 1223.8 \n",
3349 "2020-10-30 12517.0 11257.6 1608 1259.4 1608.0 \n",
3350 "2020-11-06 13448.0 11729.4 2165 1718.6 2165.0 \n",
3351 "2020-11-13 13798.0 11803.6 2808 1994.4 2808.0 \n",
3352 "2020-11-20 14291.0 11821.0 2847 2470.0 2847.0 \n",
3353 "2020-11-27 14132.0 11802.0 3256 2330.0 3256.0 \n",
3354 "\n",
3355 " accounted_fraction \n",
3356 "2020-03-20 1.462715 \n",
3357 "2020-03-27 0.754126 \n",
3358 "2020-04-03 0.421001 \n",
3359 "2020-04-10 0.655856 \n",
3360 "2020-04-17 0.493598 \n",
3361 "2020-04-24 0.463375 \n",
3362 "2020-05-01 0.558428 \n",
3363 "2020-05-08 1.027451 \n",
3364 "2020-05-15 0.551518 \n",
3365 "2020-05-22 0.811181 \n",
3366 "2020-05-29 1.040176 \n",
3367 "2020-06-05 1.546643 \n",
3368 "2020-06-12 1.565842 \n",
3369 "2020-06-19 -140.714286 \n",
3370 "2020-06-26 -1.483313 \n",
3371 "2020-07-03 -5.070423 \n",
3372 "2020-07-10 -0.445109 \n",
3373 "2020-07-17 -0.619803 \n",
3374 "2020-07-24 -0.701180 \n",
3375 "2020-07-31 -2.488987 \n",
3376 "2020-08-07 -0.697492 \n",
3377 "2020-08-14 0.361495 \n",
3378 "2020-08-21 0.100611 \n",
3379 "2020-08-28 -0.164737 \n",
3380 "2020-09-04 -0.753012 \n",
3381 "2020-09-11 0.143312 \n",
3382 "2020-09-18 0.386146 \n",
3383 "2020-09-25 1.092018 \n",
3384 "2020-10-02 0.519751 \n",
3385 "2020-10-09 2.090032 \n",
3386 "2020-10-16 0.976051 \n",
3387 "2020-10-23 0.861252 \n",
3388 "2020-10-30 1.276798 \n",
3389 "2020-11-06 1.259746 \n",
3390 "2020-11-13 1.407942 \n",
3391 "2020-11-20 1.152632 \n",
3392 "2020-11-27 1.397425 "
3393 ]
3394 },
3395 "execution_count": 75,
3396 "metadata": {},
3397 "output_type": "execute_result"
3398 }
3399 ],
3400 "source": [
3401 "excess_deaths['accounted_fraction'] = excess_deaths.covid_deaths / excess_deaths.excess\n",
3402 "excess_deaths"
3403 ]
3404 },
3405 {
3406 "cell_type": "code",
3407 "execution_count": 76,
3408 "metadata": {
3409 "Collapsed": "false"
3410 },
3411 "outputs": [
3412 {
3413 "data": {
3414 "text/html": [
3415 "<div>\n",
3416 "<style scoped>\n",
3417 " .dataframe tbody tr th:only-of-type {\n",
3418 " vertical-align: middle;\n",
3419 " }\n",
3420 "\n",
3421 " .dataframe tbody tr th {\n",
3422 " vertical-align: top;\n",
3423 " }\n",
3424 "\n",
3425 " .dataframe thead th {\n",
3426 " text-align: right;\n",
3427 " }\n",
3428 "</style>\n",
3429 "<table border=\"1\" class=\"dataframe\">\n",
3430 " <thead>\n",
3431 " <tr style=\"text-align: right;\">\n",
3432 " <th></th>\n",
3433 " <th>total_2020</th>\n",
3434 " <th>previous_mean</th>\n",
3435 " <th>covid_deaths</th>\n",
3436 " <th>excess</th>\n",
3437 " <th>attributable</th>\n",
3438 " <th>accounted_fraction</th>\n",
3439 " <th>covid_deaths_m2</th>\n",
3440 " <th>excess_m2</th>\n",
3441 " <th>accounted_fraction_m2</th>\n",
3442 " </tr>\n",
3443 " </thead>\n",
3444 " <tbody>\n",
3445 " <tr>\n",
3446 " <td>2020-03-20</td>\n",
3447 " <td>12112.0</td>\n",
3448 " <td>12007.4</td>\n",
3449 " <td>153</td>\n",
3450 " <td>104.6</td>\n",
3451 " <td>153.0</td>\n",
3452 " <td>1.462715</td>\n",
3453 " <td>153.0</td>\n",
3454 " <td>104.6</td>\n",
3455 " <td>1.462715</td>\n",
3456 " </tr>\n",
3457 " <tr>\n",
3458 " <td>2020-03-27</td>\n",
3459 " <td>12507.0</td>\n",
3460 " <td>11549.6</td>\n",
3461 " <td>722</td>\n",
3462 " <td>957.4</td>\n",
3463 " <td>957.4</td>\n",
3464 " <td>0.754126</td>\n",
3465 " <td>437.5</td>\n",
3466 " <td>531.0</td>\n",
3467 " <td>0.823917</td>\n",
3468 " </tr>\n",
3469 " <tr>\n",
3470 " <td>2020-04-03</td>\n",
3471 " <td>18565.0</td>\n",
3472 " <td>11681.4</td>\n",
3473 " <td>2898</td>\n",
3474 " <td>6883.6</td>\n",
3475 " <td>6883.6</td>\n",
3476 " <td>0.421001</td>\n",
3477 " <td>1810.0</td>\n",
3478 " <td>3920.5</td>\n",
3479 " <td>0.461676</td>\n",
3480 " </tr>\n",
3481 " <tr>\n",
3482 " <td>2020-04-10</td>\n",
3483 " <td>20929.0</td>\n",
3484 " <td>11919.4</td>\n",
3485 " <td>5909</td>\n",
3486 " <td>9009.6</td>\n",
3487 " <td>9009.6</td>\n",
3488 " <td>0.655856</td>\n",
3489 " <td>4403.5</td>\n",
3490 " <td>7946.6</td>\n",
3491 " <td>0.554136</td>\n",
3492 " </tr>\n",
3493 " <tr>\n",
3494 " <td>2020-04-17</td>\n",
3495 " <td>24691.0</td>\n",
3496 " <td>11850.6</td>\n",
3497 " <td>6338</td>\n",
3498 " <td>12840.4</td>\n",
3499 " <td>12840.4</td>\n",
3500 " <td>0.493598</td>\n",
3501 " <td>6123.5</td>\n",
3502 " <td>10925.0</td>\n",
3503 " <td>0.560503</td>\n",
3504 " </tr>\n",
3505 " <tr>\n",
3506 " <td>2020-04-24</td>\n",
3507 " <td>24303.0</td>\n",
3508 " <td>11844.4</td>\n",
3509 " <td>5773</td>\n",
3510 " <td>12458.6</td>\n",
3511 " <td>12458.6</td>\n",
3512 " <td>0.463375</td>\n",
3513 " <td>6055.5</td>\n",
3514 " <td>12649.5</td>\n",
3515 " <td>0.478715</td>\n",
3516 " </tr>\n",
3517 " <tr>\n",
3518 " <td>2020-05-01</td>\n",
3519 " <td>20059.0</td>\n",
3520 " <td>11318.4</td>\n",
3521 " <td>4881</td>\n",
3522 " <td>8740.6</td>\n",
3523 " <td>8740.6</td>\n",
3524 " <td>0.558428</td>\n",
3525 " <td>5327.0</td>\n",
3526 " <td>10599.6</td>\n",
3527 " <td>0.502566</td>\n",
3528 " </tr>\n",
3529 " <tr>\n",
3530 " <td>2020-05-08</td>\n",
3531 " <td>14428.0</td>\n",
3532 " <td>10887.2</td>\n",
3533 " <td>3638</td>\n",
3534 " <td>3540.8</td>\n",
3535 " <td>3638.0</td>\n",
3536 " <td>1.027451</td>\n",
3537 " <td>4259.5</td>\n",
3538 " <td>6140.7</td>\n",
3539 " <td>0.693651</td>\n",
3540 " </tr>\n",
3541 " <tr>\n",
3542 " <td>2020-05-15</td>\n",
3543 " <td>16390.0</td>\n",
3544 " <td>11547.0</td>\n",
3545 " <td>2671</td>\n",
3546 " <td>4843.0</td>\n",
3547 " <td>4843.0</td>\n",
3548 " <td>0.551518</td>\n",
3549 " <td>3154.5</td>\n",
3550 " <td>4191.9</td>\n",
3551 " <td>0.752523</td>\n",
3552 " </tr>\n",
3553 " <tr>\n",
3554 " <td>2020-05-22</td>\n",
3555 " <td>13839.0</td>\n",
3556 " <td>11281.0</td>\n",
3557 " <td>2075</td>\n",
3558 " <td>2558.0</td>\n",
3559 " <td>2558.0</td>\n",
3560 " <td>0.811181</td>\n",
3561 " <td>2373.0</td>\n",
3562 " <td>3700.5</td>\n",
3563 " <td>0.641265</td>\n",
3564 " </tr>\n",
3565 " <tr>\n",
3566 " <td>2020-05-29</td>\n",
3567 " <td>11265.0</td>\n",
3568 " <td>9448.0</td>\n",
3569 " <td>1890</td>\n",
3570 " <td>1817.0</td>\n",
3571 " <td>1890.0</td>\n",
3572 " <td>1.040176</td>\n",
3573 " <td>1982.5</td>\n",
3574 " <td>2187.5</td>\n",
3575 " <td>0.906286</td>\n",
3576 " </tr>\n",
3577 " <tr>\n",
3578 " <td>2020-06-05</td>\n",
3579 " <td>12106.0</td>\n",
3580 " <td>11325.6</td>\n",
3581 " <td>1207</td>\n",
3582 " <td>780.4</td>\n",
3583 " <td>1207.0</td>\n",
3584 " <td>1.546643</td>\n",
3585 " <td>1548.5</td>\n",
3586 " <td>1298.7</td>\n",
3587 " <td>1.192346</td>\n",
3588 " </tr>\n",
3589 " <tr>\n",
3590 " <td>2020-06-12</td>\n",
3591 " <td>11302.0</td>\n",
3592 " <td>10703.6</td>\n",
3593 " <td>937</td>\n",
3594 " <td>598.4</td>\n",
3595 " <td>937.0</td>\n",
3596 " <td>1.565842</td>\n",
3597 " <td>1072.0</td>\n",
3598 " <td>689.4</td>\n",
3599 " <td>1.554975</td>\n",
3600 " </tr>\n",
3601 " <tr>\n",
3602 " <td>2020-06-19</td>\n",
3603 " <td>10694.0</td>\n",
3604 " <td>10698.2</td>\n",
3605 " <td>591</td>\n",
3606 " <td>-4.2</td>\n",
3607 " <td>591.0</td>\n",
3608 " <td>-140.714286</td>\n",
3609 " <td>764.0</td>\n",
3610 " <td>297.1</td>\n",
3611 " <td>2.571525</td>\n",
3612 " </tr>\n",
3613 " <tr>\n",
3614 " <td>2020-06-26</td>\n",
3615 " <td>10282.0</td>\n",
3616 " <td>10605.6</td>\n",
3617 " <td>480</td>\n",
3618 " <td>-323.6</td>\n",
3619 " <td>480.0</td>\n",
3620 " <td>-1.483313</td>\n",
3621 " <td>535.5</td>\n",
3622 " <td>-163.9</td>\n",
3623 " <td>-3.267236</td>\n",
3624 " </tr>\n",
3625 " <tr>\n",
3626 " <td>2020-07-03</td>\n",
3627 " <td>10412.0</td>\n",
3628 " <td>10483.0</td>\n",
3629 " <td>360</td>\n",
3630 " <td>-71.0</td>\n",
3631 " <td>360.0</td>\n",
3632 " <td>-5.070423</td>\n",
3633 " <td>420.0</td>\n",
3634 " <td>-197.3</td>\n",
3635 " <td>-2.128738</td>\n",
3636 " </tr>\n",
3637 " <tr>\n",
3638 " <td>2020-07-10</td>\n",
3639 " <td>9941.0</td>\n",
3640 " <td>10509.4</td>\n",
3641 " <td>253</td>\n",
3642 " <td>-568.4</td>\n",
3643 " <td>253.0</td>\n",
3644 " <td>-0.445109</td>\n",
3645 " <td>306.5</td>\n",
3646 " <td>-319.7</td>\n",
3647 " <td>-0.958711</td>\n",
3648 " </tr>\n",
3649 " <tr>\n",
3650 " <td>2020-07-17</td>\n",
3651 " <td>10096.0</td>\n",
3652 " <td>10360.6</td>\n",
3653 " <td>164</td>\n",
3654 " <td>-264.6</td>\n",
3655 " <td>164.0</td>\n",
3656 " <td>-0.619803</td>\n",
3657 " <td>208.5</td>\n",
3658 " <td>-416.5</td>\n",
3659 " <td>-0.500600</td>\n",
3660 " </tr>\n",
3661 " <tr>\n",
3662 " <td>2020-07-24</td>\n",
3663 " <td>10159.0</td>\n",
3664 " <td>10311.6</td>\n",
3665 " <td>107</td>\n",
3666 " <td>-152.6</td>\n",
3667 " <td>107.0</td>\n",
3668 " <td>-0.701180</td>\n",
3669 " <td>135.5</td>\n",
3670 " <td>-208.6</td>\n",
3671 " <td>-0.649569</td>\n",
3672 " </tr>\n",
3673 " <tr>\n",
3674 " <td>2020-07-31</td>\n",
3675 " <td>10262.0</td>\n",
3676 " <td>10307.4</td>\n",
3677 " <td>113</td>\n",
3678 " <td>-45.4</td>\n",
3679 " <td>113.0</td>\n",
3680 " <td>-2.488987</td>\n",
3681 " <td>110.0</td>\n",
3682 " <td>-99.0</td>\n",
3683 " <td>-1.111111</td>\n",
3684 " </tr>\n",
3685 " <tr>\n",
3686 " <td>2020-08-07</td>\n",
3687 " <td>10236.0</td>\n",
3688 " <td>10363.6</td>\n",
3689 " <td>89</td>\n",
3690 " <td>-127.6</td>\n",
3691 " <td>89.0</td>\n",
3692 " <td>-0.697492</td>\n",
3693 " <td>101.0</td>\n",
3694 " <td>-86.5</td>\n",
3695 " <td>-1.167630</td>\n",
3696 " </tr>\n",
3697 " <tr>\n",
3698 " <td>2020-08-14</td>\n",
3699 " <td>10592.0</td>\n",
3700 " <td>10345.8</td>\n",
3701 " <td>89</td>\n",
3702 " <td>246.2</td>\n",
3703 " <td>246.2</td>\n",
3704 " <td>0.361495</td>\n",
3705 " <td>89.0</td>\n",
3706 " <td>59.3</td>\n",
3707 " <td>1.500843</td>\n",
3708 " </tr>\n",
3709 " <tr>\n",
3710 " <td>2020-08-21</td>\n",
3711 " <td>10990.0</td>\n",
3712 " <td>10433.4</td>\n",
3713 " <td>56</td>\n",
3714 " <td>556.6</td>\n",
3715 " <td>556.6</td>\n",
3716 " <td>0.100611</td>\n",
3717 " <td>72.5</td>\n",
3718 " <td>401.4</td>\n",
3719 " <td>0.180618</td>\n",
3720 " </tr>\n",
3721 " <tr>\n",
3722 " <td>2020-08-28</td>\n",
3723 " <td>9023.0</td>\n",
3724 " <td>9472.2</td>\n",
3725 " <td>74</td>\n",
3726 " <td>-449.2</td>\n",
3727 " <td>74.0</td>\n",
3728 " <td>-0.164737</td>\n",
3729 " <td>65.0</td>\n",
3730 " <td>53.7</td>\n",
3731 " <td>1.210428</td>\n",
3732 " </tr>\n",
3733 " <tr>\n",
3734 " <td>2020-09-04</td>\n",
3735 " <td>10364.0</td>\n",
3736 " <td>10430.4</td>\n",
3737 " <td>50</td>\n",
3738 " <td>-66.4</td>\n",
3739 " <td>50.0</td>\n",
3740 " <td>-0.753012</td>\n",
3741 " <td>62.0</td>\n",
3742 " <td>-257.8</td>\n",
3743 " <td>-0.240497</td>\n",
3744 " </tr>\n",
3745 " <tr>\n",
3746 " <td>2020-09-11</td>\n",
3747 " <td>11176.0</td>\n",
3748 " <td>10610.8</td>\n",
3749 " <td>81</td>\n",
3750 " <td>565.2</td>\n",
3751 " <td>565.2</td>\n",
3752 " <td>0.143312</td>\n",
3753 " <td>65.5</td>\n",
3754 " <td>249.4</td>\n",
3755 " <td>0.262630</td>\n",
3756 " </tr>\n",
3757 " <tr>\n",
3758 " <td>2020-09-18</td>\n",
3759 " <td>10797.0</td>\n",
3760 " <td>10545.8</td>\n",
3761 " <td>97</td>\n",
3762 " <td>251.2</td>\n",
3763 " <td>251.2</td>\n",
3764 " <td>0.386146</td>\n",
3765 " <td>89.0</td>\n",
3766 " <td>408.2</td>\n",
3767 " <td>0.218030</td>\n",
3768 " </tr>\n",
3769 " <tr>\n",
3770 " <td>2020-09-25</td>\n",
3771 " <td>10890.0</td>\n",
3772 " <td>10709.6</td>\n",
3773 " <td>197</td>\n",
3774 " <td>180.4</td>\n",
3775 " <td>197.0</td>\n",
3776 " <td>1.092018</td>\n",
3777 " <td>147.0</td>\n",
3778 " <td>215.8</td>\n",
3779 " <td>0.681186</td>\n",
3780 " </tr>\n",
3781 " <tr>\n",
3782 " <td>2020-10-02</td>\n",
3783 " <td>11468.0</td>\n",
3784 " <td>10890.8</td>\n",
3785 " <td>300</td>\n",
3786 " <td>577.2</td>\n",
3787 " <td>577.2</td>\n",
3788 " <td>0.519751</td>\n",
3789 " <td>248.5</td>\n",
3790 " <td>378.8</td>\n",
3791 " <td>0.656019</td>\n",
3792 " </tr>\n",
3793 " <tr>\n",
3794 " <td>2020-10-09</td>\n",
3795 " <td>11373.0</td>\n",
3796 " <td>11186.4</td>\n",
3797 " <td>390</td>\n",
3798 " <td>186.6</td>\n",
3799 " <td>390.0</td>\n",
3800 " <td>2.090032</td>\n",
3801 " <td>345.0</td>\n",
3802 " <td>381.9</td>\n",
3803 " <td>0.903378</td>\n",
3804 " </tr>\n",
3805 " <tr>\n",
3806 " <td>2020-10-16</td>\n",
3807 " <td>11943.0</td>\n",
3808 " <td>11224.8</td>\n",
3809 " <td>701</td>\n",
3810 " <td>718.2</td>\n",
3811 " <td>718.2</td>\n",
3812 " <td>0.976051</td>\n",
3813 " <td>545.5</td>\n",
3814 " <td>452.4</td>\n",
3815 " <td>1.205791</td>\n",
3816 " </tr>\n",
3817 " <tr>\n",
3818 " <td>2020-10-23</td>\n",
3819 " <td>12317.0</td>\n",
3820 " <td>11093.2</td>\n",
3821 " <td>1054</td>\n",
3822 " <td>1223.8</td>\n",
3823 " <td>1223.8</td>\n",
3824 " <td>0.861252</td>\n",
3825 " <td>877.5</td>\n",
3826 " <td>971.0</td>\n",
3827 " <td>0.903708</td>\n",
3828 " </tr>\n",
3829 " <tr>\n",
3830 " <td>2020-10-30</td>\n",
3831 " <td>12517.0</td>\n",
3832 " <td>11257.6</td>\n",
3833 " <td>1608</td>\n",
3834 " <td>1259.4</td>\n",
3835 " <td>1608.0</td>\n",
3836 " <td>1.276798</td>\n",
3837 " <td>1331.0</td>\n",
3838 " <td>1241.6</td>\n",
3839 " <td>1.072004</td>\n",
3840 " </tr>\n",
3841 " <tr>\n",
3842 " <td>2020-11-06</td>\n",
3843 " <td>13448.0</td>\n",
3844 " <td>11729.4</td>\n",
3845 " <td>2165</td>\n",
3846 " <td>1718.6</td>\n",
3847 " <td>2165.0</td>\n",
3848 " <td>1.259746</td>\n",
3849 " <td>1886.5</td>\n",
3850 " <td>1489.0</td>\n",
3851 " <td>1.266958</td>\n",
3852 " </tr>\n",
3853 " <tr>\n",
3854 " <td>2020-11-13</td>\n",
3855 " <td>13798.0</td>\n",
3856 " <td>11803.6</td>\n",
3857 " <td>2808</td>\n",
3858 " <td>1994.4</td>\n",
3859 " <td>2808.0</td>\n",
3860 " <td>1.407942</td>\n",
3861 " <td>2486.5</td>\n",
3862 " <td>1856.5</td>\n",
3863 " <td>1.339348</td>\n",
3864 " </tr>\n",
3865 " <tr>\n",
3866 " <td>2020-11-20</td>\n",
3867 " <td>14291.0</td>\n",
3868 " <td>11821.0</td>\n",
3869 " <td>2847</td>\n",
3870 " <td>2470.0</td>\n",
3871 " <td>2847.0</td>\n",
3872 " <td>1.152632</td>\n",
3873 " <td>2827.5</td>\n",
3874 " <td>2232.2</td>\n",
3875 " <td>1.266688</td>\n",
3876 " </tr>\n",
3877 " <tr>\n",
3878 " <td>2020-11-27</td>\n",
3879 " <td>14132.0</td>\n",
3880 " <td>11802.0</td>\n",
3881 " <td>3256</td>\n",
3882 " <td>2330.0</td>\n",
3883 " <td>3256.0</td>\n",
3884 " <td>1.397425</td>\n",
3885 " <td>3051.5</td>\n",
3886 " <td>2400.0</td>\n",
3887 " <td>1.271458</td>\n",
3888 " </tr>\n",
3889 " </tbody>\n",
3890 "</table>\n",
3891 "</div>"
3892 ],
3893 "text/plain": [
3894 " total_2020 previous_mean covid_deaths excess attributable \\\n",
3895 "2020-03-20 12112.0 12007.4 153 104.6 153.0 \n",
3896 "2020-03-27 12507.0 11549.6 722 957.4 957.4 \n",
3897 "2020-04-03 18565.0 11681.4 2898 6883.6 6883.6 \n",
3898 "2020-04-10 20929.0 11919.4 5909 9009.6 9009.6 \n",
3899 "2020-04-17 24691.0 11850.6 6338 12840.4 12840.4 \n",
3900 "2020-04-24 24303.0 11844.4 5773 12458.6 12458.6 \n",
3901 "2020-05-01 20059.0 11318.4 4881 8740.6 8740.6 \n",
3902 "2020-05-08 14428.0 10887.2 3638 3540.8 3638.0 \n",
3903 "2020-05-15 16390.0 11547.0 2671 4843.0 4843.0 \n",
3904 "2020-05-22 13839.0 11281.0 2075 2558.0 2558.0 \n",
3905 "2020-05-29 11265.0 9448.0 1890 1817.0 1890.0 \n",
3906 "2020-06-05 12106.0 11325.6 1207 780.4 1207.0 \n",
3907 "2020-06-12 11302.0 10703.6 937 598.4 937.0 \n",
3908 "2020-06-19 10694.0 10698.2 591 -4.2 591.0 \n",
3909 "2020-06-26 10282.0 10605.6 480 -323.6 480.0 \n",
3910 "2020-07-03 10412.0 10483.0 360 -71.0 360.0 \n",
3911 "2020-07-10 9941.0 10509.4 253 -568.4 253.0 \n",
3912 "2020-07-17 10096.0 10360.6 164 -264.6 164.0 \n",
3913 "2020-07-24 10159.0 10311.6 107 -152.6 107.0 \n",
3914 "2020-07-31 10262.0 10307.4 113 -45.4 113.0 \n",
3915 "2020-08-07 10236.0 10363.6 89 -127.6 89.0 \n",
3916 "2020-08-14 10592.0 10345.8 89 246.2 246.2 \n",
3917 "2020-08-21 10990.0 10433.4 56 556.6 556.6 \n",
3918 "2020-08-28 9023.0 9472.2 74 -449.2 74.0 \n",
3919 "2020-09-04 10364.0 10430.4 50 -66.4 50.0 \n",
3920 "2020-09-11 11176.0 10610.8 81 565.2 565.2 \n",
3921 "2020-09-18 10797.0 10545.8 97 251.2 251.2 \n",
3922 "2020-09-25 10890.0 10709.6 197 180.4 197.0 \n",
3923 "2020-10-02 11468.0 10890.8 300 577.2 577.2 \n",
3924 "2020-10-09 11373.0 11186.4 390 186.6 390.0 \n",
3925 "2020-10-16 11943.0 11224.8 701 718.2 718.2 \n",
3926 "2020-10-23 12317.0 11093.2 1054 1223.8 1223.8 \n",
3927 "2020-10-30 12517.0 11257.6 1608 1259.4 1608.0 \n",
3928 "2020-11-06 13448.0 11729.4 2165 1718.6 2165.0 \n",
3929 "2020-11-13 13798.0 11803.6 2808 1994.4 2808.0 \n",
3930 "2020-11-20 14291.0 11821.0 2847 2470.0 2847.0 \n",
3931 "2020-11-27 14132.0 11802.0 3256 2330.0 3256.0 \n",
3932 "\n",
3933 " accounted_fraction covid_deaths_m2 excess_m2 \\\n",
3934 "2020-03-20 1.462715 153.0 104.6 \n",
3935 "2020-03-27 0.754126 437.5 531.0 \n",
3936 "2020-04-03 0.421001 1810.0 3920.5 \n",
3937 "2020-04-10 0.655856 4403.5 7946.6 \n",
3938 "2020-04-17 0.493598 6123.5 10925.0 \n",
3939 "2020-04-24 0.463375 6055.5 12649.5 \n",
3940 "2020-05-01 0.558428 5327.0 10599.6 \n",
3941 "2020-05-08 1.027451 4259.5 6140.7 \n",
3942 "2020-05-15 0.551518 3154.5 4191.9 \n",
3943 "2020-05-22 0.811181 2373.0 3700.5 \n",
3944 "2020-05-29 1.040176 1982.5 2187.5 \n",
3945 "2020-06-05 1.546643 1548.5 1298.7 \n",
3946 "2020-06-12 1.565842 1072.0 689.4 \n",
3947 "2020-06-19 -140.714286 764.0 297.1 \n",
3948 "2020-06-26 -1.483313 535.5 -163.9 \n",
3949 "2020-07-03 -5.070423 420.0 -197.3 \n",
3950 "2020-07-10 -0.445109 306.5 -319.7 \n",
3951 "2020-07-17 -0.619803 208.5 -416.5 \n",
3952 "2020-07-24 -0.701180 135.5 -208.6 \n",
3953 "2020-07-31 -2.488987 110.0 -99.0 \n",
3954 "2020-08-07 -0.697492 101.0 -86.5 \n",
3955 "2020-08-14 0.361495 89.0 59.3 \n",
3956 "2020-08-21 0.100611 72.5 401.4 \n",
3957 "2020-08-28 -0.164737 65.0 53.7 \n",
3958 "2020-09-04 -0.753012 62.0 -257.8 \n",
3959 "2020-09-11 0.143312 65.5 249.4 \n",
3960 "2020-09-18 0.386146 89.0 408.2 \n",
3961 "2020-09-25 1.092018 147.0 215.8 \n",
3962 "2020-10-02 0.519751 248.5 378.8 \n",
3963 "2020-10-09 2.090032 345.0 381.9 \n",
3964 "2020-10-16 0.976051 545.5 452.4 \n",
3965 "2020-10-23 0.861252 877.5 971.0 \n",
3966 "2020-10-30 1.276798 1331.0 1241.6 \n",
3967 "2020-11-06 1.259746 1886.5 1489.0 \n",
3968 "2020-11-13 1.407942 2486.5 1856.5 \n",
3969 "2020-11-20 1.152632 2827.5 2232.2 \n",
3970 "2020-11-27 1.397425 3051.5 2400.0 \n",
3971 "\n",
3972 " accounted_fraction_m2 \n",
3973 "2020-03-20 1.462715 \n",
3974 "2020-03-27 0.823917 \n",
3975 "2020-04-03 0.461676 \n",
3976 "2020-04-10 0.554136 \n",
3977 "2020-04-17 0.560503 \n",
3978 "2020-04-24 0.478715 \n",
3979 "2020-05-01 0.502566 \n",
3980 "2020-05-08 0.693651 \n",
3981 "2020-05-15 0.752523 \n",
3982 "2020-05-22 0.641265 \n",
3983 "2020-05-29 0.906286 \n",
3984 "2020-06-05 1.192346 \n",
3985 "2020-06-12 1.554975 \n",
3986 "2020-06-19 2.571525 \n",
3987 "2020-06-26 -3.267236 \n",
3988 "2020-07-03 -2.128738 \n",
3989 "2020-07-10 -0.958711 \n",
3990 "2020-07-17 -0.500600 \n",
3991 "2020-07-24 -0.649569 \n",
3992 "2020-07-31 -1.111111 \n",
3993 "2020-08-07 -1.167630 \n",
3994 "2020-08-14 1.500843 \n",
3995 "2020-08-21 0.180618 \n",
3996 "2020-08-28 1.210428 \n",
3997 "2020-09-04 -0.240497 \n",
3998 "2020-09-11 0.262630 \n",
3999 "2020-09-18 0.218030 \n",
4000 "2020-09-25 0.681186 \n",
4001 "2020-10-02 0.656019 \n",
4002 "2020-10-09 0.903378 \n",
4003 "2020-10-16 1.205791 \n",
4004 "2020-10-23 0.903708 \n",
4005 "2020-10-30 1.072004 \n",
4006 "2020-11-06 1.266958 \n",
4007 "2020-11-13 1.339348 \n",
4008 "2020-11-20 1.266688 \n",
4009 "2020-11-27 1.271458 "
4010 ]
4011 },
4012 "execution_count": 76,
4013 "metadata": {},
4014 "output_type": "execute_result"
4015 }
4016 ],
4017 "source": [
4018 "excess_deaths['covid_deaths_m2'] = excess_deaths.covid_deaths.transform(lambda x: x.rolling(2, 1).mean())\n",
4019 "excess_deaths['excess_m2'] = excess_deaths.excess.transform(lambda x: x.rolling(2, 1).mean())\n",
4020 "excess_deaths['accounted_fraction_m2'] = excess_deaths.covid_deaths_m2 / excess_deaths.excess_m2\n",
4021 "excess_deaths"
4022 ]
4023 },
4024 {
4025 "cell_type": "code",
4026 "execution_count": 77,
4027 "metadata": {
4028 "Collapsed": "false"
4029 },
4030 "outputs": [
4031 {
4032 "data": {
4033 "text/plain": [
4034 "<matplotlib.axes._subplots.AxesSubplot at 0x7f41bf8727d0>"
4035 ]
4036 },
4037 "execution_count": 77,
4038 "metadata": {},
4039 "output_type": "execute_result"
4040 },
4041 {
4042 "data": {
4043 "image/png": 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\n",
4044 "text/plain": [
4045 "<Figure size 432x288 with 1 Axes>"
4046 ]
4047 },
4048 "metadata": {
4049 "needs_background": "light"
4050 },
4051 "output_type": "display_data"
4052 }
4053 ],
4054 "source": [
4055 "excess_deaths[['covid_deaths', 'excess', 'covid_deaths_m2', 'excess_m2']].plot()"
4056 ]
4057 },
4058 {
4059 "cell_type": "code",
4060 "execution_count": 78,
4061 "metadata": {
4062 "Collapsed": "false"
4063 },
4064 "outputs": [
4065 {
4066 "data": {
4067 "text/plain": [
4068 "<matplotlib.axes._subplots.AxesSubplot at 0x7f41bf7b8e10>"
4069 ]
4070 },
4071 "execution_count": 78,
4072 "metadata": {},
4073 "output_type": "execute_result"
4074 },
4075 {
4076 "data": {
4077 "image/png": 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\n",
4078 "text/plain": [
4079 "<Figure size 432x288 with 1 Axes>"
4080 ]
4081 },
4082 "metadata": {
4083 "needs_background": "light"
4084 },
4085 "output_type": "display_data"
4086 }
4087 ],
4088 "source": [
4089 "excess_deaths[['accounted_fraction', 'accounted_fraction_m2']].plot()"
4090 ]
4091 },
4092 {
4093 "cell_type": "code",
4094 "execution_count": 79,
4095 "metadata": {
4096 "Collapsed": "false"
4097 },
4098 "outputs": [
4099 {
4100 "data": {
4101 "text/plain": [
4102 "9772.4"
4103 ]
4104 },
4105 "execution_count": 79,
4106 "metadata": {},
4107 "output_type": "execute_result"
4108 }
4109 ],
4110 "source": [
4111 "excess_deaths.tail(5).excess.sum()"
4112 ]
4113 },
4114 {
4115 "cell_type": "code",
4116 "execution_count": 80,
4117 "metadata": {
4118 "Collapsed": "false"
4119 },
4120 "outputs": [
4121 {
4122 "data": {
4123 "text/plain": [
4124 "12684"
4125 ]
4126 },
4127 "execution_count": 80,
4128 "metadata": {},
4129 "output_type": "execute_result"
4130 }
4131 ],
4132 "source": [
4133 "excess_deaths.tail(5).covid_deaths.sum()"
4134 ]
4135 },
4136 {
4137 "cell_type": "code",
4138 "execution_count": 81,
4139 "metadata": {
4140 "Collapsed": "false"
4141 },
4142 "outputs": [
4143 {
4144 "data": {
4145 "text/plain": [
4146 "0.7704509618416903"
4147 ]
4148 },
4149 "execution_count": 81,
4150 "metadata": {},
4151 "output_type": "execute_result"
4152 }
4153 ],
4154 "source": [
4155 "excess_deaths.tail(5).excess.sum() / excess_deaths.tail(5).covid_deaths.sum()"
4156 ]
4157 },
4158 {
4159 "cell_type": "code",
4160 "execution_count": 82,
4161 "metadata": {
4162 "Collapsed": "false"
4163 },
4164 "outputs": [
4165 {
4166 "data": {
4167 "text/plain": [
4168 "0.7624733475479744"
4169 ]
4170 },
4171 "execution_count": 82,
4172 "metadata": {},
4173 "output_type": "execute_result"
4174 }
4175 ],
4176 "source": [
4177 "excess_deaths.tail(3).excess.sum() / excess_deaths.tail(3).covid_deaths.sum()"
4178 ]
4179 },
4180 {
4181 "cell_type": "code",
4182 "execution_count": 83,
4183 "metadata": {
4184 "Collapsed": "false"
4185 },
4186 "outputs": [
4187 {
4188 "data": {
4189 "text/plain": [
4190 "1"
4191 ]
4192 },
4193 "execution_count": 83,
4194 "metadata": {},
4195 "output_type": "execute_result"
4196 }
4197 ],
4198 "source": [
4199 "max(1, excess_deaths.tail(3).excess.sum() / excess_deaths.tail(3).covid_deaths.sum())"
4200 ]
4201 },
4202 {
4203 "cell_type": "code",
4204 "execution_count": 84,
4205 "metadata": {
4206 "Collapsed": "false"
4207 },
4208 "outputs": [],
4209 "source": [
4210 "# with open('excess_death_accuracy.json', 'w') as f:\n",
4211 "# # json.dump(max(1, excess_deaths.tail(3).excess.sum() / excess_deaths.tail(3).covid_deaths.sum()), f)\n",
4212 "# json.dump(1, f)"
4213 ]
4214 },
4215 {
4216 "cell_type": "code",
4217 "execution_count": 85,
4218 "metadata": {
4219 "Collapsed": "false"
4220 },
4221 "outputs": [
4222 {
4223 "data": {
4224 "text/plain": [
4225 "'85807'"
4226 ]
4227 },
4228 "execution_count": 85,
4229 "metadata": {},
4230 "output_type": "execute_result"
4231 }
4232 ],
4233 "source": [
4234 "f'{excess_deaths.attributable.sum():.0f}'"
4235 ]
4236 },
4237 {
4238 "cell_type": "code",
4239 "execution_count": 86,
4240 "metadata": {
4241 "Collapsed": "false"
4242 },
4243 "outputs": [],
4244 "source": [
4245 "excess_death_data = {\n",
4246 " 'start_date': str(excess_deaths.index[0]),\n",
4247 " 'end_date': str(excess_deaths.index[-1]),\n",
4248 " 'excess_deaths': f'{excess_deaths.attributable.sum():.0f}'\n",
4249 "}\n",
4250 "\n",
4251 "with open('excess_deaths.json', 'w') as f:\n",
4252 " json.dump(excess_death_data, f)"
4253 ]
4254 },
4255 {
4256 "cell_type": "code",
4257 "execution_count": null,
4258 "metadata": {
4259 "Collapsed": "false"
4260 },
4261 "outputs": [],
4262 "source": []
4263 }
4264 ],
4265 "metadata": {
4266 "kernelspec": {
4267 "display_name": "Python 3",
4268 "language": "python",
4269 "name": "python3"
4270 },
4271 "language_info": {
4272 "codemirror_mode": {
4273 "name": "ipython",
4274 "version": 3
4275 },
4276 "file_extension": ".py",
4277 "mimetype": "text/x-python",
4278 "name": "python",
4279 "nbconvert_exporter": "python",
4280 "pygments_lexer": "ipython3",
4281 "version": "3.8.5"
4282 }
4283 },
4284 "nbformat": 4,
4285 "nbformat_minor": 4
4286 }
Code for analysing Covid-19 data