"
- ],
"text/plain": [
- " Unnamed: 0 week indicator inc inc_low inc_up inc100 inc100_low \\\n",
- "1611 1611 198919 3 0 NaN NaN 0 NaN \n",
- "\n",
- " inc100_up geo_insee geo_name \n",
- "1611 NaN FR France "
+ "False"
]
},
"execution_count": 5,
@@ -1187,20 +1125,77 @@
}
],
"source": [
- "raw_data[raw_data.isnull().any(axis=1)]"
+ "(raw_data == '-').any(axis=1).any()"
]
},
{
"cell_type": "markdown",
"metadata": {},
"source": [
- "Nous éliminons ce point, ce qui n'a pas d'impact fort sur notre analyse qui est assez simple."
+ "Il n'y a aucun point manquant dans ce jeu de données. Nous poursuivons donc l'analyse avec le jeu de données complet."
]
},
{
"cell_type": "code",
"execution_count": 6,
"metadata": {},
+ "outputs": [],
+ "source": [
+ "data = raw_data"
+ ]
+ },
+ {
+ "cell_type": "markdown",
+ "metadata": {},
+ "source": [
+ "Nos données utilisent une convention inhabituelle: le numéro de\n",
+ "semaine est collé à l'année, donnant l'impression qu'il s'agit\n",
+ "de nombre entier. C'est comme ça que Pandas les interprète.\n",
+ " \n",
+ "Un deuxième problème est que Pandas ne comprend pas les numéros de\n",
+ "semaine. Il faut lui fournir les dates de début et de fin de\n",
+ "semaine. Nous utilisons pour cela la bibliothèque `isoweek`.\n",
+ "\n",
+ "Comme la conversion des semaines est devenu assez complexe, nous\n",
+ "écrivons une petite fonction Python pour cela. Ensuite, nous\n",
+ "l'appliquons à tous les points de nos donnés. Les résultats vont\n",
+ "dans une nouvelle colonne 'period'."
+ ]
+ },
+ {
+ "cell_type": "code",
+ "execution_count": 7,
+ "metadata": {},
+ "outputs": [],
+ "source": [
+ "def convert_week(year_and_week_int):\n",
+ " year_and_week_str = str(year_and_week_int)\n",
+ " year = int(year_and_week_str[:4])\n",
+ " week = int(year_and_week_str[4:])\n",
+ " w = isoweek.Week(year, week)\n",
+ " return pd.Period(w.day(0), 'W')\n",
+ "\n",
+ "data['period'] = [convert_week(yw) for yw in data['week']]"
+ ]
+ },
+ {
+ "cell_type": "markdown",
+ "metadata": {},
+ "source": [
+ "Il restent deux petites modifications à faire.\n",
+ "\n",
+ "Premièrement, nous définissons les périodes d'observation\n",
+ "comme nouvel index de notre jeux de données. Ceci en fait\n",
+ "une suite chronologique, ce qui sera pratique par la suite.\n",
+ "\n",
+ "Deuxièmement, nous trions les points par période, dans\n",
+ "le sens chronologique."
+ ]
+ },
+ {
+ "cell_type": "code",
+ "execution_count": 8,
+ "metadata": {},
"outputs": [
{
"data": {
@@ -1235,425 +1230,439 @@
"
geo_insee
\n",
"
geo_name
\n",
" \n",
+ "
\n",
+ "
period
\n",
+ "
\n",
+ "
\n",
+ "
\n",
+ "
\n",
+ "
\n",
+ "
\n",
+ "
\n",
+ "
\n",
+ "
\n",
+ "
\n",
+ "
\n",
+ "
\n",
" \n",
" \n",
"
\n",
- "
0
\n",
- "
0
\n",
- "
202013
\n",
- "
3
\n",
+ "
1990-12-03/1990-12-09
\n",
+ "
1529
\n",
+ "
199049
\n",
+ "
7
\n",
+ "
1143
\n",
"
0
\n",
- "
0.0
\n",
- "
0.0
\n",
+ "
2610
\n",
+ "
2
\n",
"
0
\n",
- "
0.0
\n",
- "
0.0
\n",
+ "
5
\n",
"
FR
\n",
"
France
\n",
"
\n",
"
\n",
- "
1
\n",
- "
1
\n",
- "
202012
\n",
- "
3
\n",
- "
8321
\n",
- "
5873.0
\n",
- "
10769.0
\n",
- "
13
\n",
- "
9.0
\n",
- "
17.0
\n",
+ "
1990-12-10/1990-12-16
\n",
+ "
1528
\n",
+ "
199050
\n",
+ "
7
\n",
+ "
11079
\n",
+ "
6660
\n",
+ "
15498
\n",
+ "
20
\n",
+ "
12
\n",
+ "
28
\n",
"
FR
\n",
"
France
\n",
"
\n",
"
\n",
- "
2
\n",
- "
2
\n",
- "
202011
\n",
- "
3
\n",
- "
101704
\n",
- "
93652.0
\n",
- "
109756.0
\n",
- "
154
\n",
- "
142.0
\n",
- "
166.0
\n",
+ "
1990-12-17/1990-12-23
\n",
+ "
1527
\n",
+ "
199051
\n",
+ "
7
\n",
+ "
19080
\n",
+ "
13807
\n",
+ "
24353
\n",
+ "
34
\n",
+ "
25
\n",
+ "
43
\n",
"
FR
\n",
"
France
\n",
"
\n",
"
\n",
- "
3
\n",
- "
3
\n",
- "
202010
\n",
- "
3
\n",
- "
104977
\n",
- "
96650.0
\n",
- "
113304.0
\n",
- "
159
\n",
- "
146.0
\n",
- "
172.0
\n",
+ "
1990-12-24/1990-12-30
\n",
+ "
1526
\n",
+ "
199052
\n",
+ "
7
\n",
+ "
19375
\n",
+ "
13295
\n",
+ "
25455
\n",
+ "
34
\n",
+ "
23
\n",
+ "
45
\n",
"
FR
\n",
"
France
\n",
"
\n",
"
\n",
- "
4
\n",
- "
4
\n",
- "
202009
\n",
- "
3
\n",
- "
110696
\n",
- "
102066.0
\n",
- "
119326.0
\n",
- "
168
\n",
- "
155.0
\n",
- "
181.0
\n",
+ "
1990-12-31/1991-01-06
\n",
+ "
1525
\n",
+ "
199101
\n",
+ "
7
\n",
+ "
15565
\n",
+ "
10271
\n",
+ "
20859
\n",
+ "
27
\n",
+ "
18
\n",
+ "
36
\n",
"
FR
\n",
"
France
\n",
"
\n",
"
\n",
- "
5
\n",
- "
5
\n",
- "
202008
\n",
- "
3
\n",
- "
143753
\n",
- "
133984.0
\n",
- "
153522.0
\n",
- "
218
\n",
- "
203.0
\n",
- "
233.0
\n",
+ "
1991-01-07/1991-01-13
\n",
+ "
1524
\n",
+ "
199102
\n",
+ "
7
\n",
+ "
16277
\n",
+ "
11046
\n",
+ "
21508
\n",
+ "
29
\n",
+ "
20
\n",
+ "
38
\n",
"
FR
\n",
"
France
\n",
"
\n",
"
\n",
- "
6
\n",
- "
6
\n",
- "
202007
\n",
- "
3
\n",
- "
183610
\n",
- "
172812.0
\n",
- "
194408.0
\n",
- "
279
\n",
- "
263.0
\n",
- "
295.0
\n",
+ "
1991-01-14/1991-01-20
\n",
+ "
1523
\n",
+ "
199103
\n",
+ "
7
\n",
+ "
15387
\n",
+ "
10484
\n",
+ "
20290
\n",
+ "
27
\n",
+ "
18
\n",
+ "
36
\n",
"
FR
\n",
"
France
\n",
"
\n",
"
\n",
- "
7
\n",
+ "
1991-01-21/1991-01-27
\n",
+ "
1522
\n",
+ "
199104
\n",
"
7
\n",
- "
202006
\n",
- "
3
\n",
- "
206669
\n",
- "
195481.0
\n",
- "
217857.0
\n",
- "
314
\n",
- "
297.0
\n",
- "
331.0
\n",
+ "
7913
\n",
+ "
4563
\n",
+ "
11263
\n",
+ "
14
\n",
+ "
8
\n",
+ "
20
\n",
"
FR
\n",
"
France
\n",
"
\n",
"
\n",
- "
8
\n",
- "
8
\n",
- "
202005
\n",
- "
3
\n",
- "
187957
\n",
- "
177445.0
\n",
- "
198469.0
\n",
- "
285
\n",
- "
269.0
\n",
- "
301.0
\n",
+ "
1991-01-28/1991-02-03
\n",
+ "
1521
\n",
+ "
199105
\n",
+ "
7
\n",
+ "
10442
\n",
+ "
6544
\n",
+ "
14340
\n",
+ "
18
\n",
+ "
11
\n",
+ "
25
\n",
"
FR
\n",
"
France
\n",
"
\n",
"
\n",
- "
9
\n",
- "
9
\n",
- "
202004
\n",
- "
3
\n",
- "
122331
\n",
- "
113492.0
\n",
- "
131170.0
\n",
- "
186
\n",
- "
173.0
\n",
- "
199.0
\n",
+ "
1991-02-04/1991-02-10
\n",
+ "
1520
\n",
+ "
199106
\n",
+ "
7
\n",
+ "
10877
\n",
+ "
7013
\n",
+ "
14741
\n",
+ "
19
\n",
+ "
12
\n",
+ "
26
\n",
"
FR
\n",
"
France
\n",
"
\n",
"
\n",
- "
10
\n",
- "
10
\n",
- "
202003
\n",
- "
3
\n",
- "
78413
\n",
- "
71330.0
\n",
- "
85496.0
\n",
- "
119
\n",
- "
108.0
\n",
- "
130.0
\n",
+ "
1991-02-11/1991-02-17
\n",
+ "
1519
\n",
+ "
199107
\n",
+ "
7
\n",
+ "
12337
\n",
+ "
8077
\n",
+ "
16597
\n",
+ "
22
\n",
+ "
15
\n",
+ "
29
\n",
"
FR
\n",
"
France
\n",
"
\n",
"
\n",
- "
11
\n",
- "
11
\n",
- "
202002
\n",
- "
3
\n",
- "
53614
\n",
- "
47654.0
\n",
- "
59574.0
\n",
- "
81
\n",
- "
72.0
\n",
- "
90.0
\n",
+ "
1991-02-18/1991-02-24
\n",
+ "
1518
\n",
+ "
199108
\n",
+ "
7
\n",
+ "
13289
\n",
+ "
8813
\n",
+ "
17765
\n",
+ "
23
\n",
+ "
15
\n",
+ "
31
\n",
"
FR
\n",
"
France
\n",
"
\n",
"
\n",
- "
12
\n",
- "
12
\n",
- "
202001
\n",
- "
3
\n",
- "
36850
\n",
- "
31608.0
\n",
- "
42092.0
\n",
- "
56
\n",
- "
48.0
\n",
- "
64.0
\n",
+ "
1991-02-25/1991-03-03
\n",
+ "
1517
\n",
+ "
199109
\n",
+ "
7
\n",
+ "
13741
\n",
+ "
8780
\n",
+ "
18702
\n",
+ "
24
\n",
+ "
15
\n",
+ "
33
\n",
"
FR
\n",
"
France
\n",
"
\n",
"
\n",
- "
13
\n",
- "
13
\n",
- "
201952
\n",
- "
3
\n",
- "
28135
\n",
- "
23220.0
\n",
- "
33050.0
\n",
- "
43
\n",
- "
36.0
\n",
- "
50.0
\n",
+ "
1991-03-04/1991-03-10
\n",
+ "
1516
\n",
+ "
199110
\n",
+ "
7
\n",
+ "
16643
\n",
+ "
11372
\n",
+ "
21914
\n",
+ "
29
\n",
+ "
20
\n",
+ "
38
\n",
"
FR
\n",
"
France
\n",
"
\n",
"
\n",
- "
14
\n",
- "
14
\n",
- "
201951
\n",
- "
3
\n",
- "
29786
\n",
- "
25042.0
\n",
- "
34530.0
\n",
- "
45
\n",
- "
38.0
\n",
- "
52.0
\n",
+ "
1991-03-11/1991-03-17
\n",
+ "
1515
\n",
+ "
199111
\n",
+ "
7
\n",
+ "
15574
\n",
+ "
11184
\n",
+ "
19964
\n",
+ "
27
\n",
+ "
19
\n",
+ "
35
\n",
"
FR
\n",
"
France
\n",
"
\n",
"
\n",
- "
15
\n",
- "
15
\n",
- "
201950
\n",
- "
3
\n",
- "
34223
\n",
- "
29156.0
\n",
- "
39290.0
\n",
- "
52
\n",
- "
44.0
\n",
- "
60.0
\n",
+ "
1991-03-18/1991-03-24
\n",
+ "
1514
\n",
+ "
199112
\n",
+ "
7
\n",
+ "
10864
\n",
+ "
7331
\n",
+ "
14397
\n",
+ "
19
\n",
+ "
13
\n",
+ "
25
\n",
"
FR
\n",
"
France
\n",
"
\n",
"
\n",
- "
16
\n",
- "
16
\n",
- "
201949
\n",
- "
3
\n",
- "
25662
\n",
- "
21414.0
\n",
- "
29910.0
\n",
- "
39
\n",
- "
33.0
\n",
- "
45.0
\n",
+ "
1991-03-25/1991-03-31
\n",
+ "
1513
\n",
+ "
199113
\n",
+ "
7
\n",
+ "
9567
\n",
+ "
6041
\n",
+ "
13093
\n",
+ "
17
\n",
+ "
11
\n",
+ "
23
\n",
"
FR
\n",
"
France
\n",
"
\n",
"
\n",
- "
17
\n",
- "
17
\n",
- "
201948
\n",
- "
3
\n",
- "
22367
\n",
- "
18055.0
\n",
- "
26679.0
\n",
- "
34
\n",
- "
27.0
\n",
- "
41.0
\n",
+ "
1991-04-01/1991-04-07
\n",
+ "
1512
\n",
+ "
199114
\n",
+ "
7
\n",
+ "
12265
\n",
+ "
7684
\n",
+ "
16846
\n",
+ "
22
\n",
+ "
14
\n",
+ "
30
\n",
"
FR
\n",
"
France
\n",
"
\n",
"
\n",
- "
18
\n",
+ "
1991-04-08/1991-04-14
\n",
+ "
1511
\n",
+ "
199115
\n",
+ "
7
\n",
+ "
13975
\n",
+ "
9781
\n",
+ "
18169
\n",
+ "
25
\n",
"
18
\n",
- "
201947
\n",
- "
3
\n",
- "
18669
\n",
- "
14759.0
\n",
- "
22579.0
\n",
- "
28
\n",
- "
22.0
\n",
- "
34.0
\n",
+ "
32
\n",
"
FR
\n",
"
France
\n",
"
\n",
"
\n",
- "
19
\n",
- "
19
\n",
- "
201946
\n",
- "
3
\n",
- "
16030
\n",
- "
12567.0
\n",
- "
19493.0
\n",
- "
24
\n",
- "
19.0
\n",
- "
29.0
\n",
+ "
1991-04-15/1991-04-21
\n",
+ "
1510
\n",
+ "
199116
\n",
+ "
7
\n",
+ "
14857
\n",
+ "
10068
\n",
+ "
19646
\n",
+ "
26
\n",
+ "
18
\n",
+ "
34
\n",
"
FR
\n",
"
France
\n",
"
\n",
"
\n",
- "
20
\n",
- "
20
\n",
- "
201945
\n",
- "
3
\n",
- "
10138
\n",
- "
7160.0
\n",
- "
13116.0
\n",
- "
15
\n",
- "
10.0
\n",
- "
20.0
\n",
+ "
1991-04-22/1991-04-28
\n",
+ "
1509
\n",
+ "
199117
\n",
+ "
7
\n",
+ "
13462
\n",
+ "
8877
\n",
+ "
18047
\n",
+ "
24
\n",
+ "
16
\n",
+ "
32
\n",
"
FR
\n",
"
France
\n",
"
\n",
"
\n",
- "
21
\n",
- "
21
\n",
- "
201944
\n",
- "
3
\n",
- "
7822
\n",
- "
5010.0
\n",
- "
10634.0
\n",
- "
12
\n",
- "
8.0
\n",
- "
16.0
\n",
+ "
1991-04-29/1991-05-05
\n",
+ "
1508
\n",
+ "
199118
\n",
+ "
7
\n",
+ "
21385
\n",
+ "
13882
\n",
+ "
28888
\n",
+ "
38
\n",
+ "
25
\n",
+ "
51
\n",
"
FR
\n",
"
France
\n",
"
\n",
"
\n",
- "
22
\n",
- "
22
\n",
- "
201943
\n",
- "
3
\n",
- "
9487
\n",
- "
6448.0
\n",
- "
12526.0
\n",
- "
14
\n",
- "
9.0
\n",
- "
19.0
\n",
+ "
1991-05-06/1991-05-12
\n",
+ "
1507
\n",
+ "
199119
\n",
+ "
7
\n",
+ "
16739
\n",
+ "
11246
\n",
+ "
22232
\n",
+ "
29
\n",
+ "
19
\n",
+ "
39
\n",
"
FR
\n",
"
France
\n",
"
\n",
"
\n",
- "
23
\n",
+ "
1991-05-13/1991-05-19
\n",
+ "
1506
\n",
+ "
199120
\n",
+ "
7
\n",
+ "
19053
\n",
+ "
12742
\n",
+ "
25364
\n",
+ "
34
\n",
"
23
\n",
- "
201942
\n",
- "
3
\n",
- "
7747
\n",
- "
5243.0
\n",
- "
10251.0
\n",
- "
12
\n",
- "
8.0
\n",
- "
16.0
\n",
+ "
45
\n",
"
FR
\n",
"
France
\n",
"
\n",
"
\n",
- "
24
\n",
- "
24
\n",
- "
201941
\n",
- "
3
\n",
- "
7122
\n",
- "
4720.0
\n",
- "
9524.0
\n",
- "
11
\n",
- "
7.0
\n",
- "
15.0
\n",
+ "
1991-05-20/1991-05-26
\n",
+ "
1505
\n",
+ "
199121
\n",
+ "
7
\n",
+ "
14903
\n",
+ "
8975
\n",
+ "
20831
\n",
+ "
26
\n",
+ "
16
\n",
+ "
36
\n",
"
FR
\n",
"
France
\n",
"
\n",
"
\n",
- "
25
\n",
- "
25
\n",
- "
201940
\n",
- "
3
\n",
- "
8505
\n",
- "
5784.0
\n",
- "
11226.0
\n",
- "
13
\n",
- "
9.0
\n",
- "
17.0
\n",
+ "
1991-05-27/1991-06-02
\n",
+ "
1504
\n",
+ "
199122
\n",
+ "
7
\n",
+ "
15452
\n",
+ "
9953
\n",
+ "
20951
\n",
+ "
27
\n",
+ "
17
\n",
+ "
37
\n",
"
FR
\n",
"
France
\n",
"
\n",
"
\n",
- "
26
\n",
- "
26
\n",
- "
201939
\n",
- "
3
\n",
- "
7091
\n",
- "
4462.0
\n",
- "
9720.0
\n",
- "
11
\n",
- "
7.0
\n",
- "
15.0
\n",
+ "
1991-06-03/1991-06-09
\n",
+ "
1503
\n",
+ "
199123
\n",
+ "
7
\n",
+ "
11947
\n",
+ "
7671
\n",
+ "
16223
\n",
+ "
21
\n",
+ "
13
\n",
+ "
29
\n",
"
FR
\n",
"
France
\n",
"
\n",
"
\n",
- "
27
\n",
- "
27
\n",
- "
201938
\n",
- "
3
\n",
- "
4897
\n",
- "
2891.0
\n",
- "
6903.0
\n",
+ "
1991-06-10/1991-06-16
\n",
+ "
1502
\n",
+ "
199124
\n",
"
7
\n",
- "
4.0
\n",
- "
10.0
\n",
+ "
16171
\n",
+ "
10071
\n",
+ "
22271
\n",
+ "
28
\n",
+ "
17
\n",
+ "
39
\n",
"
FR
\n",
"
France
\n",
"
\n",
"
\n",
- "
28
\n",
+ "
1991-06-17/1991-06-23
\n",
+ "
1501
\n",
+ "
199125
\n",
+ "
7
\n",
+ "
16169
\n",
+ "
10700
\n",
+ "
21638
\n",
"
28
\n",
- "
201937
\n",
- "
3
\n",
- "
3172
\n",
- "
1367.0
\n",
- "
4977.0
\n",
- "
5
\n",
- "
2.0
\n",
- "
8.0
\n",
+ "
18
\n",
+ "
38
\n",
"
FR
\n",
"
France
\n",
"
\n",
"
\n",
- "
29
\n",
- "
29
\n",
- "
201936
\n",
- "
3
\n",
- "
2295
\n",
- "
728.0
\n",
- "
3862.0
\n",
- "
3
\n",
- "
1.0
\n",
- "
5.0
\n",
+ "
1991-06-24/1991-06-30
\n",
+ "
1500
\n",
+ "
199126
\n",
+ "
7
\n",
+ "
17608
\n",
+ "
11304
\n",
+ "
23912
\n",
+ "
31
\n",
+ "
20
\n",
+ "
42
\n",
"
FR
\n",
"
France
\n",
"
\n",
@@ -1672,625 +1681,570 @@
"
...
\n",
" \n",
"
\n",
- "
1818
\n",
- "
1818
\n",
- "
198521
\n",
- "
3
\n",
- "
26096
\n",
- "
19621.0
\n",
- "
32571.0
\n",
- "
47
\n",
- "
35.0
\n",
- "
59.0
\n",
+ "
2019-09-02/2019-09-08
\n",
+ "
29
\n",
+ "
201936
\n",
+ "
7
\n",
+ "
1277
\n",
+ "
263
\n",
+ "
2291
\n",
+ "
2
\n",
+ "
0
\n",
+ "
4
\n",
"
FR
\n",
"
France
\n",
"
\n",
"
\n",
- "
1819
\n",
- "
1819
\n",
- "
198520
\n",
- "
3
\n",
- "
27896
\n",
- "
20885.0
\n",
- "
34907.0
\n",
- "
51
\n",
- "
38.0
\n",
- "
64.0
\n",
+ "
2019-09-09/2019-09-15
\n",
+ "
28
\n",
+ "
201937
\n",
+ "
7
\n",
+ "
970
\n",
+ "
162
\n",
+ "
1778
\n",
+ "
1
\n",
+ "
0
\n",
+ "
2
\n",
"
FR
\n",
"
France
\n",
"
\n",
"
\n",
- "
1820
\n",
- "
1820
\n",
- "
198519
\n",
- "
3
\n",
- "
43154
\n",
- "
32821.0
\n",
- "
53487.0
\n",
- "
78
\n",
- "
59.0
\n",
- "
97.0
\n",
+ "
2019-09-16/2019-09-22
\n",
+ "
27
\n",
+ "
201938
\n",
+ "
7
\n",
+ "
3078
\n",
+ "
1416
\n",
+ "
4740
\n",
+ "
5
\n",
+ "
2
\n",
+ "
8
\n",
"
FR
\n",
"
France
\n",
"
\n",
"
\n",
- "
1821
\n",
- "
1821
\n",
- "
198518
\n",
- "
3
\n",
- "
40555
\n",
- "
29935.0
\n",
- "
51175.0
\n",
- "
74
\n",
- "
55.0
\n",
- "
93.0
\n",
+ "
2019-09-23/2019-09-29
\n",
+ "
26
\n",
+ "
201939
\n",
+ "
7
\n",
+ "
3137
\n",
+ "
1310
\n",
+ "
4964
\n",
+ "
5
\n",
+ "
2
\n",
+ "
8
\n",
"
FR
\n",
"
France
\n",
"
\n",
"
\n",
- "
1822
\n",
- "
1822
\n",
- "
198517
\n",
+ "
2019-09-30/2019-10-06
\n",
+ "
25
\n",
+ "
201940
\n",
+ "
7
\n",
+ "
4211
\n",
+ "
2218
\n",
+ "
6204
\n",
+ "
6
\n",
"
3
\n",
- "
34053
\n",
- "
24366.0
\n",
- "
43740.0
\n",
- "
62
\n",
- "
44.0
\n",
- "
80.0
\n",
+ "
9
\n",
"
FR
\n",
"
France
\n",
"
\n",
"
\n",
- "
1823
\n",
- "
1823
\n",
- "
198516
\n",
+ "
2019-10-07/2019-10-13
\n",
+ "
24
\n",
+ "
201941
\n",
+ "
7
\n",
+ "
4130
\n",
+ "
2030
\n",
+ "
6230
\n",
+ "
6
\n",
"
3
\n",
- "
50362
\n",
- "
36451.0
\n",
- "
64273.0
\n",
- "
91
\n",
- "
66.0
\n",
- "
116.0
\n",
+ "
9
\n",
"
FR
\n",
"
France
\n",
"
\n",
"
\n",
- "
1824
\n",
- "
1824
\n",
- "
198515
\n",
- "
3
\n",
- "
63881
\n",
- "
45538.0
\n",
- "
82224.0
\n",
- "
116
\n",
- "
83.0
\n",
- "
149.0
\n",
+ "
2019-10-14/2019-10-20
\n",
+ "
23
\n",
+ "
201942
\n",
+ "
7
\n",
+ "
6279
\n",
+ "
3989
\n",
+ "
8569
\n",
+ "
10
\n",
+ "
7
\n",
+ "
13
\n",
"
FR
\n",
"
France
\n",
"
\n",
"
\n",
- "
1825
\n",
- "
1825
\n",
- "
198514
\n",
- "
3
\n",
- "
134545
\n",
- "
114400.0
\n",
- "
154690.0
\n",
- "
244
\n",
- "
207.0
\n",
- "
281.0
\n",
+ "
2019-10-21/2019-10-27
\n",
+ "
22
\n",
+ "
201943
\n",
+ "
7
\n",
+ "
4834
\n",
+ "
2751
\n",
+ "
6917
\n",
+ "
7
\n",
+ "
4
\n",
+ "
10
\n",
"
FR
\n",
"
France
\n",
"
\n",
"
\n",
- "
1826
\n",
- "
1826
\n",
- "
198513
\n",
- "
3
\n",
- "
197206
\n",
- "
176080.0
\n",
- "
218332.0
\n",
- "
357
\n",
- "
319.0
\n",
- "
395.0
\n",
+ "
2019-10-28/2019-11-03
\n",
+ "
21
\n",
+ "
201944
\n",
+ "
7
\n",
+ "
5728
\n",
+ "
3627
\n",
+ "
7829
\n",
+ "
9
\n",
+ "
6
\n",
+ "
12
\n",
"
FR
\n",
"
France
\n",
"
\n",
"
\n",
- "
1827
\n",
- "
1827
\n",
- "
198512
\n",
- "
3
\n",
- "
245240
\n",
- "
223304.0
\n",
- "
267176.0
\n",
- "
445
\n",
- "
405.0
\n",
- "
485.0
\n",
+ "
2019-11-04/2019-11-10
\n",
+ "
20
\n",
+ "
201945
\n",
+ "
7
\n",
+ "
4492
\n",
+ "
2615
\n",
+ "
6369
\n",
+ "
7
\n",
+ "
4
\n",
+ "
10
\n",
"
FR
\n",
"
France
\n",
"
\n",
"
\n",
- "
1828
\n",
- "
1828
\n",
- "
198511
\n",
- "
3
\n",
- "
276205
\n",
- "
252399.0
\n",
- "
300011.0
\n",
- "
501
\n",
- "
458.0
\n",
- "
544.0
\n",
+ "
2019-11-11/2019-11-17
\n",
+ "
19
\n",
+ "
201946
\n",
+ "
7
\n",
+ "
2638
\n",
+ "
1316
\n",
+ "
3960
\n",
+ "
4
\n",
+ "
2
\n",
+ "
6
\n",
"
FR
\n",
"
France
\n",
"
\n",
"
\n",
- "
1829
\n",
- "
1829
\n",
- "
198510
\n",
- "
3
\n",
- "
353231
\n",
- "
326279.0
\n",
- "
380183.0
\n",
- "
640
\n",
- "
591.0
\n",
- "
689.0
\n",
+ "
2019-11-18/2019-11-24
\n",
+ "
18
\n",
+ "
201947
\n",
+ "
7
\n",
+ "
7536
\n",
+ "
5058
\n",
+ "
10014
\n",
+ "
11
\n",
+ "
7
\n",
+ "
15
\n",
"
FR
\n",
"
France
\n",
"
\n",
"
\n",
- "
1830
\n",
- "
1830
\n",
- "
198509
\n",
- "
3
\n",
- "
369895
\n",
- "
341109.0
\n",
- "
398681.0
\n",
- "
670
\n",
- "
618.0
\n",
- "
722.0
\n",
+ "
2019-11-25/2019-12-01
\n",
+ "
17
\n",
+ "
201948
\n",
+ "
7
\n",
+ "
5542
\n",
+ "
3383
\n",
+ "
7701
\n",
+ "
8
\n",
+ "
5
\n",
+ "
11
\n",
"
FR
\n",
"
France
\n",
"
\n",
"
\n",
- "
1831
\n",
- "
1831
\n",
- "
198508
\n",
- "
3
\n",
- "
389886
\n",
- "
359529.0
\n",
- "
420243.0
\n",
- "
707
\n",
- "
652.0
\n",
- "
762.0
\n",
+ "
2019-12-02/2019-12-08
\n",
+ "
16
\n",
+ "
201949
\n",
+ "
7
\n",
+ "
6621
\n",
+ "
4540
\n",
+ "
8702
\n",
+ "
10
\n",
+ "
7
\n",
+ "
13
\n",
"
FR
\n",
"
France
\n",
"
\n",
"
\n",
- "
1832
\n",
- "
1832
\n",
- "
198507
\n",
- "
3
\n",
- "
471852
\n",
- "
432599.0
\n",
- "
511105.0
\n",
- "
855
\n",
- "
784.0
\n",
- "
926.0
\n",
+ "
2019-12-09/2019-12-15
\n",
+ "
15
\n",
+ "
201950
\n",
+ "
7
\n",
+ "
6424
\n",
+ "
4276
\n",
+ "
8572
\n",
+ "
10
\n",
+ "
7
\n",
+ "
13
\n",
"
FR
\n",
"
France
\n",
"
\n",
"
\n",
- "
1833
\n",
- "
1833
\n",
- "
198506
\n",
- "
3
\n",
- "
565825
\n",
- "
518011.0
\n",
- "
613639.0
\n",
- "
1026
\n",
- "
939.0
\n",
- "
1113.0
\n",
+ "
2019-12-16/2019-12-22
\n",
+ "
14
\n",
+ "
201951
\n",
+ "
7
\n",
+ "
5823
\n",
+ "
3675
\n",
+ "
7971
\n",
+ "
9
\n",
+ "
6
\n",
+ "
12
\n",
"
FR
\n",
"
France
\n",
"
\n",
"
\n",
- "
1834
\n",
- "
1834
\n",
- "
198505
\n",
- "
3
\n",
- "
637302
\n",
- "
592795.0
\n",
- "
681809.0
\n",
- "
1155
\n",
- "
1074.0
\n",
- "
1236.0
\n",
+ "
2019-12-23/2019-12-29
\n",
+ "
13
\n",
+ "
201952
\n",
+ "
7
\n",
+ "
7941
\n",
+ "
5246
\n",
+ "
10636
\n",
+ "
12
\n",
+ "
8
\n",
+ "
16
\n",
"
FR
\n",
"
France
\n",
"
\n",
"
\n",
- "
1835
\n",
- "
1835
\n",
- "
198504
\n",
- "
3
\n",
- "
424937
\n",
- "
390794.0
\n",
- "
459080.0
\n",
- "
770
\n",
- "
708.0
\n",
- "
832.0
\n",
+ "
2019-12-30/2020-01-05
\n",
+ "
12
\n",
+ "
202001
\n",
+ "
7
\n",
+ "
9835
\n",
+ "
7019
\n",
+ "
12651
\n",
+ "
15
\n",
+ "
11
\n",
+ "
19
\n",
"
FR
\n",
"
France
\n",
"
\n",
"
\n",
- "
1836
\n",
- "
1836
\n",
- "
198503
\n",
- "
3
\n",
- "
213901
\n",
- "
174689.0
\n",
- "
253113.0
\n",
- "
388
\n",
- "
317.0
\n",
- "
459.0
\n",
+ "
2020-01-06/2020-01-12
\n",
+ "
11
\n",
+ "
202002
\n",
+ "
7
\n",
+ "
6534
\n",
+ "
4530
\n",
+ "
8538
\n",
+ "
10
\n",
+ "
7
\n",
+ "
13
\n",
"
FR
\n",
"
France
\n",
"
\n",
"
\n",
- "
1837
\n",
- "
1837
\n",
- "
198502
\n",
- "
3
\n",
- "
97586
\n",
- "
80949.0
\n",
- "
114223.0
\n",
- "
177
\n",
- "
147.0
\n",
- "
207.0
\n",
+ "
2020-01-13/2020-01-19
\n",
+ "
10
\n",
+ "
202003
\n",
+ "
7
\n",
+ "
5968
\n",
+ "
4100
\n",
+ "
7836
\n",
+ "
9
\n",
+ "
6
\n",
+ "
12
\n",
"
FR
\n",
"
France
\n",
"
\n",
"
\n",
- "
1838
\n",
- "
1838
\n",
- "
198501
\n",
- "
3
\n",
- "
85489
\n",
- "
65918.0
\n",
- "
105060.0
\n",
- "
155
\n",
- "
120.0
\n",
- "
190.0
\n",
+ "
2020-01-20/2020-01-26
\n",
+ "
9
\n",
+ "
202004
\n",
+ "
7
\n",
+ "
7991
\n",
+ "
5831
\n",
+ "
10151
\n",
+ "
12
\n",
+ "
9
\n",
+ "
15
\n",
"
FR
\n",
"
France
\n",
"
\n",
"
\n",
- "
1839
\n",
- "
1839
\n",
- "
198452
\n",
- "
3
\n",
- "
84830
\n",
- "
60602.0
\n",
- "
109058.0
\n",
- "
154
\n",
- "
110.0
\n",
- "
198.0
\n",
+ "
2020-01-27/2020-02-02
\n",
+ "
8
\n",
+ "
202005
\n",
+ "
7
\n",
+ "
8505
\n",
+ "
6314
\n",
+ "
10696
\n",
+ "
13
\n",
+ "
10
\n",
+ "
16
\n",
"
FR
\n",
"
France
\n",
"
\n",
"
\n",
- "
1840
\n",
- "
1840
\n",
- "
198451
\n",
- "
3
\n",
- "
101726
\n",
- "
80242.0
\n",
- "
123210.0
\n",
- "
185
\n",
- "
146.0
\n",
- "
224.0
\n",
+ "
2020-02-03/2020-02-09
\n",
+ "
7
\n",
+ "
202006
\n",
+ "
7
\n",
+ "
9264
\n",
+ "
6925
\n",
+ "
11603
\n",
+ "
14
\n",
+ "
10
\n",
+ "
18
\n",
"
FR
\n",
"
France
\n",
"
\n",
"
\n",
- "
1841
\n",
- "
1841
\n",
- "
198450
\n",
- "
3
\n",
- "
123680
\n",
- "
101401.0
\n",
- "
145959.0
\n",
- "
225
\n",
- "
184.0
\n",
- "
266.0
\n",
+ "
2020-02-10/2020-02-16
\n",
+ "
6
\n",
+ "
202007
\n",
+ "
7
\n",
+ "
8959
\n",
+ "
6574
\n",
+ "
11344
\n",
+ "
14
\n",
+ "
10
\n",
+ "
18
\n",
"
FR
\n",
"
France
\n",
"
\n",
"
\n",
- "
1842
\n",
- "
1842
\n",
- "
198449
\n",
- "
3
\n",
- "
101073
\n",
- "
81684.0
\n",
- "
120462.0
\n",
- "
184
\n",
- "
149.0
\n",
- "
219.0
\n",
+ "
2020-02-17/2020-02-23
\n",
+ "
5
\n",
+ "
202008
\n",
+ "
7
\n",
+ "
10424
\n",
+ "
7708
\n",
+ "
13140
\n",
+ "
16
\n",
+ "
12
\n",
+ "
20
\n",
"
FR
\n",
"
France
\n",
"
\n",
"
\n",
- "
1843
\n",
- "
1843
\n",
- "
198448
\n",
- "
3
\n",
- "
78620
\n",
- "
60634.0
\n",
- "
96606.0
\n",
- "
143
\n",
- "
110.0
\n",
- "
176.0
\n",
+ "
2020-02-24/2020-03-01
\n",
+ "
4
\n",
+ "
202009
\n",
+ "
7
\n",
+ "
13631
\n",
+ "
10544
\n",
+ "
16718
\n",
+ "
21
\n",
+ "
16
\n",
+ "
26
\n",
"
FR
\n",
"
France
\n",
"
\n",
"
\n",
- "
1844
\n",
- "
1844
\n",
- "
198447
\n",
+ "
2020-03-02/2020-03-08
\n",
"
3
\n",
- "
72029
\n",
- "
54274.0
\n",
- "
89784.0
\n",
- "
131
\n",
- "
99.0
\n",
- "
163.0
\n",
+ "
202010
\n",
+ "
7
\n",
+ "
9011
\n",
+ "
6691
\n",
+ "
11331
\n",
+ "
14
\n",
+ "
10
\n",
+ "
18
\n",
"
FR
\n",
"
France
\n",
"
\n",
"
\n",
- "
1845
\n",
- "
1845
\n",
- "
198446
\n",
- "
3
\n",
- "
87330
\n",
- "
67686.0
\n",
- "
106974.0
\n",
- "
159
\n",
- "
123.0
\n",
- "
195.0
\n",
+ "
2020-03-09/2020-03-15
\n",
+ "
2
\n",
+ "
202011
\n",
+ "
7
\n",
+ "
10198
\n",
+ "
7568
\n",
+ "
12828
\n",
+ "
15
\n",
+ "
11
\n",
+ "
19
\n",
"
FR
\n",
"
France
\n",
"
\n",
"
\n",
- "
1846
\n",
- "
1846
\n",
- "
198445
\n",
- "
3
\n",
- "
135223
\n",
- "
101414.0
\n",
- "
169032.0
\n",
- "
246
\n",
- "
184.0
\n",
- "
308.0
\n",
+ "
2020-03-16/2020-03-22
\n",
+ "
1
\n",
+ "
202012
\n",
+ "
7
\n",
+ "
8123
\n",
+ "
5790
\n",
+ "
10456
\n",
+ "
12
\n",
+ "
8
\n",
+ "
16
\n",
"
FR
\n",
"
France
\n",
"
\n",
"
\n",
- "
1847
\n",
- "
1847
\n",
- "
198444
\n",
- "
3
\n",
- "
68422
\n",
- "
20056.0
\n",
- "
116788.0
\n",
- "
125
\n",
- "
37.0
\n",
- "
213.0
\n",
+ "
2020-03-23/2020-03-29
\n",
+ "
0
\n",
+ "
202013
\n",
+ "
7
\n",
+ "
7371
\n",
+ "
5268
\n",
+ "
9474
\n",
+ "
11
\n",
+ "
8
\n",
+ "
14
\n",
"
FR
\n",
"
France
\n",
"
\n",
" \n",
"\n",
- "
1847 rows × 11 columns
\n",
+ "
1530 rows × 11 columns
\n",
""
],
"text/plain": [
- " Unnamed: 0 week indicator inc inc_low inc_up inc100 \\\n",
- "0 0 202013 3 0 0.0 0.0 0 \n",
- "1 1 202012 3 8321 5873.0 10769.0 13 \n",
- "2 2 202011 3 101704 93652.0 109756.0 154 \n",
- "3 3 202010 3 104977 96650.0 113304.0 159 \n",
- "4 4 202009 3 110696 102066.0 119326.0 168 \n",
- "5 5 202008 3 143753 133984.0 153522.0 218 \n",
- "6 6 202007 3 183610 172812.0 194408.0 279 \n",
- "7 7 202006 3 206669 195481.0 217857.0 314 \n",
- "8 8 202005 3 187957 177445.0 198469.0 285 \n",
- "9 9 202004 3 122331 113492.0 131170.0 186 \n",
- "10 10 202003 3 78413 71330.0 85496.0 119 \n",
- "11 11 202002 3 53614 47654.0 59574.0 81 \n",
- "12 12 202001 3 36850 31608.0 42092.0 56 \n",
- "13 13 201952 3 28135 23220.0 33050.0 43 \n",
- "14 14 201951 3 29786 25042.0 34530.0 45 \n",
- "15 15 201950 3 34223 29156.0 39290.0 52 \n",
- "16 16 201949 3 25662 21414.0 29910.0 39 \n",
- "17 17 201948 3 22367 18055.0 26679.0 34 \n",
- "18 18 201947 3 18669 14759.0 22579.0 28 \n",
- "19 19 201946 3 16030 12567.0 19493.0 24 \n",
- "20 20 201945 3 10138 7160.0 13116.0 15 \n",
- "21 21 201944 3 7822 5010.0 10634.0 12 \n",
- "22 22 201943 3 9487 6448.0 12526.0 14 \n",
- "23 23 201942 3 7747 5243.0 10251.0 12 \n",
- "24 24 201941 3 7122 4720.0 9524.0 11 \n",
- "25 25 201940 3 8505 5784.0 11226.0 13 \n",
- "26 26 201939 3 7091 4462.0 9720.0 11 \n",
- "27 27 201938 3 4897 2891.0 6903.0 7 \n",
- "28 28 201937 3 3172 1367.0 4977.0 5 \n",
- "29 29 201936 3 2295 728.0 3862.0 3 \n",
- "... ... ... ... ... ... ... ... \n",
- "1818 1818 198521 3 26096 19621.0 32571.0 47 \n",
- "1819 1819 198520 3 27896 20885.0 34907.0 51 \n",
- "1820 1820 198519 3 43154 32821.0 53487.0 78 \n",
- "1821 1821 198518 3 40555 29935.0 51175.0 74 \n",
- "1822 1822 198517 3 34053 24366.0 43740.0 62 \n",
- "1823 1823 198516 3 50362 36451.0 64273.0 91 \n",
- "1824 1824 198515 3 63881 45538.0 82224.0 116 \n",
- "1825 1825 198514 3 134545 114400.0 154690.0 244 \n",
- "1826 1826 198513 3 197206 176080.0 218332.0 357 \n",
- "1827 1827 198512 3 245240 223304.0 267176.0 445 \n",
- "1828 1828 198511 3 276205 252399.0 300011.0 501 \n",
- "1829 1829 198510 3 353231 326279.0 380183.0 640 \n",
- "1830 1830 198509 3 369895 341109.0 398681.0 670 \n",
- "1831 1831 198508 3 389886 359529.0 420243.0 707 \n",
- "1832 1832 198507 3 471852 432599.0 511105.0 855 \n",
- "1833 1833 198506 3 565825 518011.0 613639.0 1026 \n",
- "1834 1834 198505 3 637302 592795.0 681809.0 1155 \n",
- "1835 1835 198504 3 424937 390794.0 459080.0 770 \n",
- "1836 1836 198503 3 213901 174689.0 253113.0 388 \n",
- "1837 1837 198502 3 97586 80949.0 114223.0 177 \n",
- "1838 1838 198501 3 85489 65918.0 105060.0 155 \n",
- "1839 1839 198452 3 84830 60602.0 109058.0 154 \n",
- "1840 1840 198451 3 101726 80242.0 123210.0 185 \n",
- "1841 1841 198450 3 123680 101401.0 145959.0 225 \n",
- "1842 1842 198449 3 101073 81684.0 120462.0 184 \n",
- "1843 1843 198448 3 78620 60634.0 96606.0 143 \n",
- "1844 1844 198447 3 72029 54274.0 89784.0 131 \n",
- "1845 1845 198446 3 87330 67686.0 106974.0 159 \n",
- "1846 1846 198445 3 135223 101414.0 169032.0 246 \n",
- "1847 1847 198444 3 68422 20056.0 116788.0 125 \n",
+ " Unnamed: 0 week indicator inc inc_low inc_up \\\n",
+ "period \n",
+ "1990-12-03/1990-12-09 1529 199049 7 1143 0 2610 \n",
+ "1990-12-10/1990-12-16 1528 199050 7 11079 6660 15498 \n",
+ "1990-12-17/1990-12-23 1527 199051 7 19080 13807 24353 \n",
+ "1990-12-24/1990-12-30 1526 199052 7 19375 13295 25455 \n",
+ "1990-12-31/1991-01-06 1525 199101 7 15565 10271 20859 \n",
+ "1991-01-07/1991-01-13 1524 199102 7 16277 11046 21508 \n",
+ "1991-01-14/1991-01-20 1523 199103 7 15387 10484 20290 \n",
+ "1991-01-21/1991-01-27 1522 199104 7 7913 4563 11263 \n",
+ "1991-01-28/1991-02-03 1521 199105 7 10442 6544 14340 \n",
+ "1991-02-04/1991-02-10 1520 199106 7 10877 7013 14741 \n",
+ "1991-02-11/1991-02-17 1519 199107 7 12337 8077 16597 \n",
+ "1991-02-18/1991-02-24 1518 199108 7 13289 8813 17765 \n",
+ "1991-02-25/1991-03-03 1517 199109 7 13741 8780 18702 \n",
+ "1991-03-04/1991-03-10 1516 199110 7 16643 11372 21914 \n",
+ "1991-03-11/1991-03-17 1515 199111 7 15574 11184 19964 \n",
+ "1991-03-18/1991-03-24 1514 199112 7 10864 7331 14397 \n",
+ "1991-03-25/1991-03-31 1513 199113 7 9567 6041 13093 \n",
+ "1991-04-01/1991-04-07 1512 199114 7 12265 7684 16846 \n",
+ "1991-04-08/1991-04-14 1511 199115 7 13975 9781 18169 \n",
+ "1991-04-15/1991-04-21 1510 199116 7 14857 10068 19646 \n",
+ "1991-04-22/1991-04-28 1509 199117 7 13462 8877 18047 \n",
+ "1991-04-29/1991-05-05 1508 199118 7 21385 13882 28888 \n",
+ "1991-05-06/1991-05-12 1507 199119 7 16739 11246 22232 \n",
+ "1991-05-13/1991-05-19 1506 199120 7 19053 12742 25364 \n",
+ "1991-05-20/1991-05-26 1505 199121 7 14903 8975 20831 \n",
+ "1991-05-27/1991-06-02 1504 199122 7 15452 9953 20951 \n",
+ "1991-06-03/1991-06-09 1503 199123 7 11947 7671 16223 \n",
+ "1991-06-10/1991-06-16 1502 199124 7 16171 10071 22271 \n",
+ "1991-06-17/1991-06-23 1501 199125 7 16169 10700 21638 \n",
+ "1991-06-24/1991-06-30 1500 199126 7 17608 11304 23912 \n",
+ "... ... ... ... ... ... ... \n",
+ "2019-09-02/2019-09-08 29 201936 7 1277 263 2291 \n",
+ "2019-09-09/2019-09-15 28 201937 7 970 162 1778 \n",
+ "2019-09-16/2019-09-22 27 201938 7 3078 1416 4740 \n",
+ "2019-09-23/2019-09-29 26 201939 7 3137 1310 4964 \n",
+ "2019-09-30/2019-10-06 25 201940 7 4211 2218 6204 \n",
+ "2019-10-07/2019-10-13 24 201941 7 4130 2030 6230 \n",
+ "2019-10-14/2019-10-20 23 201942 7 6279 3989 8569 \n",
+ "2019-10-21/2019-10-27 22 201943 7 4834 2751 6917 \n",
+ "2019-10-28/2019-11-03 21 201944 7 5728 3627 7829 \n",
+ "2019-11-04/2019-11-10 20 201945 7 4492 2615 6369 \n",
+ "2019-11-11/2019-11-17 19 201946 7 2638 1316 3960 \n",
+ "2019-11-18/2019-11-24 18 201947 7 7536 5058 10014 \n",
+ "2019-11-25/2019-12-01 17 201948 7 5542 3383 7701 \n",
+ "2019-12-02/2019-12-08 16 201949 7 6621 4540 8702 \n",
+ "2019-12-09/2019-12-15 15 201950 7 6424 4276 8572 \n",
+ "2019-12-16/2019-12-22 14 201951 7 5823 3675 7971 \n",
+ "2019-12-23/2019-12-29 13 201952 7 7941 5246 10636 \n",
+ "2019-12-30/2020-01-05 12 202001 7 9835 7019 12651 \n",
+ "2020-01-06/2020-01-12 11 202002 7 6534 4530 8538 \n",
+ "2020-01-13/2020-01-19 10 202003 7 5968 4100 7836 \n",
+ "2020-01-20/2020-01-26 9 202004 7 7991 5831 10151 \n",
+ "2020-01-27/2020-02-02 8 202005 7 8505 6314 10696 \n",
+ "2020-02-03/2020-02-09 7 202006 7 9264 6925 11603 \n",
+ "2020-02-10/2020-02-16 6 202007 7 8959 6574 11344 \n",
+ "2020-02-17/2020-02-23 5 202008 7 10424 7708 13140 \n",
+ "2020-02-24/2020-03-01 4 202009 7 13631 10544 16718 \n",
+ "2020-03-02/2020-03-08 3 202010 7 9011 6691 11331 \n",
+ "2020-03-09/2020-03-15 2 202011 7 10198 7568 12828 \n",
+ "2020-03-16/2020-03-22 1 202012 7 8123 5790 10456 \n",
+ "2020-03-23/2020-03-29 0 202013 7 7371 5268 9474 \n",
"\n",
- " inc100_low inc100_up geo_insee geo_name \n",
- "0 0.0 0.0 FR France \n",
- "1 9.0 17.0 FR France \n",
- "2 142.0 166.0 FR France \n",
- "3 146.0 172.0 FR France \n",
- "4 155.0 181.0 FR France \n",
- "5 203.0 233.0 FR France \n",
- "6 263.0 295.0 FR France \n",
- "7 297.0 331.0 FR France \n",
- "8 269.0 301.0 FR France \n",
- "9 173.0 199.0 FR France \n",
- "10 108.0 130.0 FR France \n",
- "11 72.0 90.0 FR France \n",
- "12 48.0 64.0 FR France \n",
- "13 36.0 50.0 FR France \n",
- "14 38.0 52.0 FR France \n",
- "15 44.0 60.0 FR France \n",
- "16 33.0 45.0 FR France \n",
- "17 27.0 41.0 FR France \n",
- "18 22.0 34.0 FR France \n",
- "19 19.0 29.0 FR France \n",
- "20 10.0 20.0 FR France \n",
- "21 8.0 16.0 FR France \n",
- "22 9.0 19.0 FR France \n",
- "23 8.0 16.0 FR France \n",
- "24 7.0 15.0 FR France \n",
- "25 9.0 17.0 FR France \n",
- "26 7.0 15.0 FR France \n",
- "27 4.0 10.0 FR France \n",
- "28 2.0 8.0 FR France \n",
- "29 1.0 5.0 FR France \n",
- "... ... ... ... ... \n",
- "1818 35.0 59.0 FR France \n",
- "1819 38.0 64.0 FR France \n",
- "1820 59.0 97.0 FR France \n",
- "1821 55.0 93.0 FR France \n",
- "1822 44.0 80.0 FR France \n",
- "1823 66.0 116.0 FR France \n",
- "1824 83.0 149.0 FR France \n",
- "1825 207.0 281.0 FR France \n",
- "1826 319.0 395.0 FR France \n",
- "1827 405.0 485.0 FR France \n",
- "1828 458.0 544.0 FR France \n",
- "1829 591.0 689.0 FR France \n",
- "1830 618.0 722.0 FR France \n",
- "1831 652.0 762.0 FR France \n",
- "1832 784.0 926.0 FR France \n",
- "1833 939.0 1113.0 FR France \n",
- "1834 1074.0 1236.0 FR France \n",
- "1835 708.0 832.0 FR France \n",
- "1836 317.0 459.0 FR France \n",
- "1837 147.0 207.0 FR France \n",
- "1838 120.0 190.0 FR France \n",
- "1839 110.0 198.0 FR France \n",
- "1840 146.0 224.0 FR France \n",
- "1841 184.0 266.0 FR France \n",
- "1842 149.0 219.0 FR France \n",
- "1843 110.0 176.0 FR France \n",
- "1844 99.0 163.0 FR France \n",
- "1845 123.0 195.0 FR France \n",
- "1846 184.0 308.0 FR France \n",
- "1847 37.0 213.0 FR France \n",
+ " inc100 inc100_low inc100_up geo_insee geo_name \n",
+ "period \n",
+ "1990-12-03/1990-12-09 2 0 5 FR France \n",
+ "1990-12-10/1990-12-16 20 12 28 FR France \n",
+ "1990-12-17/1990-12-23 34 25 43 FR France \n",
+ "1990-12-24/1990-12-30 34 23 45 FR France \n",
+ "1990-12-31/1991-01-06 27 18 36 FR France \n",
+ "1991-01-07/1991-01-13 29 20 38 FR France \n",
+ "1991-01-14/1991-01-20 27 18 36 FR France \n",
+ "1991-01-21/1991-01-27 14 8 20 FR France \n",
+ "1991-01-28/1991-02-03 18 11 25 FR France \n",
+ "1991-02-04/1991-02-10 19 12 26 FR France \n",
+ "1991-02-11/1991-02-17 22 15 29 FR France \n",
+ "1991-02-18/1991-02-24 23 15 31 FR France \n",
+ "1991-02-25/1991-03-03 24 15 33 FR France \n",
+ "1991-03-04/1991-03-10 29 20 38 FR France \n",
+ "1991-03-11/1991-03-17 27 19 35 FR France \n",
+ "1991-03-18/1991-03-24 19 13 25 FR France \n",
+ "1991-03-25/1991-03-31 17 11 23 FR France \n",
+ "1991-04-01/1991-04-07 22 14 30 FR France \n",
+ "1991-04-08/1991-04-14 25 18 32 FR France \n",
+ "1991-04-15/1991-04-21 26 18 34 FR France \n",
+ "1991-04-22/1991-04-28 24 16 32 FR France \n",
+ "1991-04-29/1991-05-05 38 25 51 FR France \n",
+ "1991-05-06/1991-05-12 29 19 39 FR France \n",
+ "1991-05-13/1991-05-19 34 23 45 FR France \n",
+ "1991-05-20/1991-05-26 26 16 36 FR France \n",
+ "1991-05-27/1991-06-02 27 17 37 FR France \n",
+ "1991-06-03/1991-06-09 21 13 29 FR France \n",
+ "1991-06-10/1991-06-16 28 17 39 FR France \n",
+ "1991-06-17/1991-06-23 28 18 38 FR France \n",
+ "1991-06-24/1991-06-30 31 20 42 FR France \n",
+ "... ... ... ... ... ... \n",
+ "2019-09-02/2019-09-08 2 0 4 FR France \n",
+ "2019-09-09/2019-09-15 1 0 2 FR France \n",
+ "2019-09-16/2019-09-22 5 2 8 FR France \n",
+ "2019-09-23/2019-09-29 5 2 8 FR France \n",
+ "2019-09-30/2019-10-06 6 3 9 FR France \n",
+ "2019-10-07/2019-10-13 6 3 9 FR France \n",
+ "2019-10-14/2019-10-20 10 7 13 FR France \n",
+ "2019-10-21/2019-10-27 7 4 10 FR France \n",
+ "2019-10-28/2019-11-03 9 6 12 FR France \n",
+ "2019-11-04/2019-11-10 7 4 10 FR France \n",
+ "2019-11-11/2019-11-17 4 2 6 FR France \n",
+ "2019-11-18/2019-11-24 11 7 15 FR France \n",
+ "2019-11-25/2019-12-01 8 5 11 FR France \n",
+ "2019-12-02/2019-12-08 10 7 13 FR France \n",
+ "2019-12-09/2019-12-15 10 7 13 FR France \n",
+ "2019-12-16/2019-12-22 9 6 12 FR France \n",
+ "2019-12-23/2019-12-29 12 8 16 FR France \n",
+ "2019-12-30/2020-01-05 15 11 19 FR France \n",
+ "2020-01-06/2020-01-12 10 7 13 FR France \n",
+ "2020-01-13/2020-01-19 9 6 12 FR France \n",
+ "2020-01-20/2020-01-26 12 9 15 FR France \n",
+ "2020-01-27/2020-02-02 13 10 16 FR France \n",
+ "2020-02-03/2020-02-09 14 10 18 FR France \n",
+ "2020-02-10/2020-02-16 14 10 18 FR France \n",
+ "2020-02-17/2020-02-23 16 12 20 FR France \n",
+ "2020-02-24/2020-03-01 21 16 26 FR France \n",
+ "2020-03-02/2020-03-08 14 10 18 FR France \n",
+ "2020-03-09/2020-03-15 15 11 19 FR France \n",
+ "2020-03-16/2020-03-22 12 8 16 FR France \n",
+ "2020-03-23/2020-03-29 11 8 14 FR France \n",
"\n",
- "[1847 rows x 11 columns]"
+ "[1530 rows x 11 columns]"
]
},
- "execution_count": 6,
+ "execution_count": 8,
"metadata": {},
"output_type": "execute_result"
}
],
"source": [
- "data = raw_data.dropna().copy()\n",
- "data"
- ]
- },
- {
- "cell_type": "markdown",
- "metadata": {},
- "source": [
- "Nos données utilisent une convention inhabituelle: le numéro de\n",
- "semaine est collé à l'année, donnant l'impression qu'il s'agit\n",
- "de nombre entier. C'est comme ça que Pandas les interprète.\n",
- " \n",
- "Un deuxième problème est que Pandas ne comprend pas les numéros de\n",
- "semaine. Il faut lui fournir les dates de début et de fin de\n",
- "semaine. Nous utilisons pour cela la bibliothèque `isoweek`.\n",
- "\n",
- "Comme la conversion des semaines est devenu assez complexe, nous\n",
- "écrivons une petite fonction Python pour cela. Ensuite, nous\n",
- "l'appliquons à tous les points de nos donnés. Les résultats vont\n",
- "dans une nouvelle colonne 'period'."
- ]
- },
- {
- "cell_type": "code",
- "execution_count": 7,
- "metadata": {},
- "outputs": [],
- "source": [
- "def convert_week(year_and_week_int):\n",
- " year_and_week_str = str(year_and_week_int)\n",
- " year = int(year_and_week_str[:4])\n",
- " week = int(year_and_week_str[4:])\n",
- " w = isoweek.Week(year, week)\n",
- " return pd.Period(w.day(0), 'W')\n",
- "\n",
- "data['period'] = [convert_week(yw) for yw in data['week']]"
- ]
- },
- {
- "cell_type": "markdown",
- "metadata": {},
- "source": [
- "Il restent deux petites modifications à faire.\n",
- "\n",
- "Premièrement, nous définissons les périodes d'observation\n",
- "comme nouvel index de notre jeux de données. Ceci en fait\n",
- "une suite chronologique, ce qui sera pratique par la suite.\n",
- "\n",
- "Deuxièmement, nous trions les points par période, dans\n",
- "le sens chronologique."
- ]
- },
- {
- "cell_type": "code",
- "execution_count": 8,
- "metadata": {},
- "outputs": [],
- "source": [
- "sorted_data = data.set_index('period').sort_index()"
+ "sorted_data = data.set_index('period').sort_index()\n",
+ "sorted_data"
]
},
{
@@ -2302,26 +2256,14 @@
"zéro, ou au moins très faible. Nous laissons une \"marge d'erreur\"\n",
"d'une seconde.\n",
"\n",
- "Ceci s'avère tout à fait juste sauf pour deux périodes consécutives\n",
- "entre lesquelles il manque une semaine.\n",
- "\n",
- "Nous reconnaissons ces dates: c'est la semaine sans observations\n",
- "que nous avions supprimées !"
+ "Ceci permet de vérifier qu'il n'y a pas de \"trou\" dans les données :"
]
},
{
"cell_type": "code",
"execution_count": 9,
"metadata": {},
- "outputs": [
- {
- "name": "stdout",
- "output_type": "stream",
- "text": [
- "1989-05-01/1989-05-07 1989-05-15/1989-05-21\n"
- ]
- }
- ],
+ "outputs": [],
"source": [
"periods = sorted_data.index\n",
"for p1, p2 in zip(periods[:-1], periods[1:]):\n",
@@ -2345,7 +2287,7 @@
{
"data": {
"text/plain": [
- ""
+ ""
]
},
"execution_count": 10,
@@ -2354,7 +2296,7 @@
},
{
"data": {
- "image/png": "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\n",
+ "image/png": "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\n",
"text/plain": [
""
]
@@ -2373,7 +2315,7 @@
"cell_type": "markdown",
"metadata": {},
"source": [
- "Un zoom sur les dernières années montre mieux la situation des pics en hiver. Le creux des incidences se trouve en été."
+ "Un zoom sur les dernières années montre mieux la situation, avec un creux des incidences chaque année en septembre."
]
},
{
@@ -2384,7 +2326,7 @@
{
"data": {
"text/plain": [
- ""
+ ""
]
},
"execution_count": 11,
@@ -2393,7 +2335,7 @@
},
{
"data": {
- "image/png": "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\n",
+ "image/png": "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\n",
"text/plain": [
""
]
@@ -2405,7 +2347,7 @@
}
],
"source": [
- "sorted_data['inc'][-200:].plot()"
+ "sorted_data['inc'][-100:].plot()"
]
},
{
@@ -2421,37 +2363,76 @@
"source": [
"Etant donné que le pic de l'épidémie se situe en hiver, à cheval\n",
"entre deux années civiles, nous définissons la période de référence\n",
- "entre deux minima de l'incidence, du 1er août de l'année $N$ au\n",
- "1er août de l'année $N+1$.\n",
+ "entre deux minima de l'incidence, du 1er septembre de l'année $N$ au\n",
+ "1er septembre de l'année $N+1$.\n",
"\n",
"Notre tâche est un peu compliquée par le fait que l'année ne comporte\n",
"pas un nombre entier de semaines. Nous modifions donc un peu nos périodes\n",
- "de référence: à la place du 1er août de chaque année, nous utilisons le\n",
+ "de référence: à la place du 1er septembre de chaque année, nous utilisons le\n",
"premier jour de la semaine qui contient le 1er août.\n",
"\n",
- "Comme l'incidence de syndrome grippal est très faible en été, cette\n",
- "modification ne risque pas de fausser nos conclusions.\n",
+ "Comme l'incidence de syndrome grippal est très faible en septembre, on limite ainsi le risque de fausser nos conclusions.\n",
"\n",
- "Encore un petit détail: les données commencent an octobre 1984, ce qui\n",
- "rend la première année incomplète. Nous commençons donc l'analyse en 1985."
+ "Encore un petit détail: les données commencent en décembre 1990, ce qui\n",
+ "rend la première année incomplète. Nous commençons donc l'analyse en 1991. L'année en cours, incomplète également, est aussi éliminée."
]
},
{
"cell_type": "code",
"execution_count": 12,
"metadata": {},
- "outputs": [],
+ "outputs": [
+ {
+ "data": {
+ "text/plain": [
+ "[Period('1991-08-26/1991-09-01', 'W-SUN'),\n",
+ " Period('1992-08-31/1992-09-06', 'W-SUN'),\n",
+ " Period('1993-08-30/1993-09-05', 'W-SUN'),\n",
+ " Period('1994-08-29/1994-09-04', 'W-SUN'),\n",
+ " Period('1995-08-28/1995-09-03', 'W-SUN'),\n",
+ " Period('1996-08-26/1996-09-01', 'W-SUN'),\n",
+ " Period('1997-09-01/1997-09-07', 'W-SUN'),\n",
+ " Period('1998-08-31/1998-09-06', 'W-SUN'),\n",
+ " Period('1999-08-30/1999-09-05', 'W-SUN'),\n",
+ " Period('2000-08-28/2000-09-03', 'W-SUN'),\n",
+ " Period('2001-08-27/2001-09-02', 'W-SUN'),\n",
+ " Period('2002-08-26/2002-09-01', 'W-SUN'),\n",
+ " Period('2003-09-01/2003-09-07', 'W-SUN'),\n",
+ " Period('2004-08-30/2004-09-05', 'W-SUN'),\n",
+ " Period('2005-08-29/2005-09-04', 'W-SUN'),\n",
+ " Period('2006-08-28/2006-09-03', 'W-SUN'),\n",
+ " Period('2007-08-27/2007-09-02', 'W-SUN'),\n",
+ " Period('2008-09-01/2008-09-07', 'W-SUN'),\n",
+ " Period('2009-08-31/2009-09-06', 'W-SUN'),\n",
+ " Period('2010-08-30/2010-09-05', 'W-SUN'),\n",
+ " Period('2011-08-29/2011-09-04', 'W-SUN'),\n",
+ " Period('2012-08-27/2012-09-02', 'W-SUN'),\n",
+ " Period('2013-08-26/2013-09-01', 'W-SUN'),\n",
+ " Period('2014-09-01/2014-09-07', 'W-SUN'),\n",
+ " Period('2015-08-31/2015-09-06', 'W-SUN'),\n",
+ " Period('2016-08-29/2016-09-04', 'W-SUN'),\n",
+ " Period('2017-08-28/2017-09-03', 'W-SUN'),\n",
+ " Period('2018-08-27/2018-09-02', 'W-SUN'),\n",
+ " Period('2019-08-26/2019-09-01', 'W-SUN')]"
+ ]
+ },
+ "execution_count": 12,
+ "metadata": {},
+ "output_type": "execute_result"
+ }
+ ],
"source": [
- "first_august_week = [pd.Period(pd.Timestamp(y, 8, 1), 'W')\n",
- " for y in range(1985,\n",
- " sorted_data.index[-1].year)]"
+ "first_week = [pd.Period(pd.Timestamp(y, 9, 1), 'W')\n",
+ " for y in range(1991,\n",
+ " sorted_data.index[-1].year)]\n",
+ "first_week"
]
},
{
"cell_type": "markdown",
"metadata": {},
"source": [
- "En partant de cette liste des semaines qui contiennent un 1er août, nous obtenons nos intervalles d'environ un an comme les périodes entre deux semaines adjacentes dans cette liste. Nous calculons les sommes des incidences hebdomadaires pour toutes ces périodes.\n",
+ "En partant de cette liste des semaines qui contiennent un 1er septembre, nous obtenons nos intervalles d'environ un an comme les périodes entre deux semaines adjacentes dans cette liste. Nous calculons les sommes des incidences hebdomadaires pour toutes ces périodes.\n",
"\n",
"Nous vérifions également que ces périodes contiennent entre 51 et 52 semaines, pour nous protéger contre des éventuelles erreurs dans notre code."
]
@@ -2464,8 +2445,8 @@
"source": [
"year = []\n",
"yearly_incidence = []\n",
- "for week1, week2 in zip(first_august_week[:-1],\n",
- " first_august_week[1:]):\n",
+ "for week1, week2 in zip(first_week[:-1],\n",
+ " first_week[1:]):\n",
" one_year = sorted_data['inc'][week1:week2-1]\n",
" assert abs(len(one_year)-52) < 2\n",
" yearly_incidence.append(one_year.sum())\n",
@@ -2488,7 +2469,7 @@
{
"data": {
"text/plain": [
- ""
+ ""
]
},
"execution_count": 14,
@@ -2497,7 +2478,7 @@
},
{
"data": {
- "image/png": "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\n",
+ "image/png": "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\n",
"text/plain": [
""
]
@@ -2516,7 +2497,7 @@
"cell_type": "markdown",
"metadata": {},
"source": [
- "Une liste triée permet de plus facilement répérer les valeurs les plus élevées (à la fin)."
+ "Une liste triée permet de plus facilement répérer les valeurs extrêmes."
]
},
{
@@ -2527,40 +2508,34 @@
{
"data": {
"text/plain": [
- "2014 1600941\n",
- "1991 1659249\n",
- "1995 1840410\n",
- "2012 2175217\n",
- "2003 2234584\n",
- "2019 2254386\n",
- "2006 2307352\n",
- "2017 2321583\n",
- "2001 2529279\n",
- "1992 2574578\n",
- "1993 2703886\n",
- "2018 2705325\n",
- "1988 2765617\n",
- "2007 2780164\n",
- "1987 2855570\n",
- "2016 2856393\n",
- "2011 2857040\n",
- "2008 2973918\n",
- "1998 3034904\n",
- "2002 3125418\n",
- "2009 3444020\n",
- "1994 3514763\n",
- "1996 3539413\n",
- "2004 3567744\n",
- "1997 3620066\n",
- "2015 3654892\n",
- "2000 3826372\n",
- "2005 3835025\n",
- "1999 3908112\n",
- "2010 4111392\n",
- "2013 4182691\n",
- "1986 5115251\n",
- "1990 5235827\n",
- "1989 5466192\n",
+ "2002 516689\n",
+ "2018 542312\n",
+ "2017 551041\n",
+ "1996 564901\n",
+ "2019 584066\n",
+ "2015 604382\n",
+ "2000 617597\n",
+ "2001 619041\n",
+ "2012 624573\n",
+ "2005 628464\n",
+ "2006 632833\n",
+ "2011 642368\n",
+ "1993 643387\n",
+ "1995 652478\n",
+ "1994 661409\n",
+ "1998 677775\n",
+ "1997 683434\n",
+ "2014 685769\n",
+ "2013 698332\n",
+ "2007 717352\n",
+ "2008 749478\n",
+ "1999 756456\n",
+ "2003 758363\n",
+ "2004 777388\n",
+ "2016 782114\n",
+ "2010 829911\n",
+ "1992 832939\n",
+ "2009 842373\n",
"dtype: int64"
]
},
@@ -2577,8 +2552,7 @@
"cell_type": "markdown",
"metadata": {},
"source": [
- "Enfin, un histogramme montre bien que les épidémies fortes, qui touchent environ 10% de la population\n",
- " française, sont assez rares: il y en eu trois au cours des 35 dernières années."
+ "Enfin, un histogramme montre une queue de distribution assez épaisse : les épidémies fortes sont assez fréquentes ; d'un autre côté, elles ne sont pas beaucoup plus fortes qu'une épidémie moyenne."
]
},
{
@@ -2589,7 +2563,7 @@
{
"data": {
"text/plain": [
- ""
+ ""
]
},
"execution_count": 16,
@@ -2598,7 +2572,7 @@
},
{
"data": {
- "image/png": "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\n",
+ "image/png": "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\n",
"text/plain": [
""
]
@@ -2615,10 +2589,31 @@
},
{
"cell_type": "code",
- "execution_count": null,
+ "execution_count": 17,
"metadata": {},
- "outputs": [],
- "source": []
+ "outputs": [
+ {
+ "data": {
+ "text/plain": [
+ "count 28.000000\n",
+ "mean 674186.607143\n",
+ "std 90193.127425\n",
+ "min 516689.000000\n",
+ "25% 618680.000000\n",
+ "50% 656943.500000\n",
+ "75% 751222.500000\n",
+ "max 842373.000000\n",
+ "dtype: float64"
+ ]
+ },
+ "execution_count": 17,
+ "metadata": {},
+ "output_type": "execute_result"
+ }
+ ],
+ "source": [
+ "yearly_incidence.describe()"
+ ]
}
],
"metadata": {