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# A tibble: 31 x 13
Tanggal Nama_provinsi POSITIF Dirawat Sembuh Meninggal
<dttm> <chr> <dbl> <dbl> <dbl> <dbl>
1 2020-05-01 00:00:00 DKI Jakarta 4283 2151 427 393
2 2020-05-02 00:00:00 DKI Jakarta 4355 2089 562 400
3 2020-05-03 00:00:00 DKI Jakarta 4417 2062 622 410
4 2020-05-04 00:00:00 DKI Jakarta 4472 2080 650 412
5 2020-05-05 00:00:00 DKI Jakarta 4641 2146 711 414
6 2020-05-06 00:00:00 DKI Jakarta 4709 2195 713 420
7 2020-05-07 00:00:00 DKI Jakarta 4775 2196 718 430
8 2020-05-08 00:00:00 DKI Jakarta 4901 2281 763 431
9 2020-05-09 00:00:00 DKI Jakarta 4958 2312 767 437
10 2020-05-10 00:00:00 DKI Jakarta 5140 2360 803 444
# ... with 21 more rows, and 7 more variables: `Self Isolation` <dbl>,
# retail_and_recreation_percent_change_from_baseline <dbl>,
# grocery_and_pharmacy_percent_change_from_baseline <dbl>,
# parks_percent_change_from_baseline <dbl>,
# transit_stations_percent_change_from_baseline <dbl>,
# workplaces_percent_change_from_baseline <dbl>,
# residential_percent_change_from_baseline <dbl>
# A tibble: 31 x 9
Tanggal Nama_provinsi Sembuh retail_and_recreat~ grocery_and_pha~
<dttm> <chr> <dbl> <dbl> <dbl>
1 2020-05-01 00:00:00 DKI Jakarta 427 -61 -28
2 2020-05-02 00:00:00 DKI Jakarta 562 -62 -29
3 2020-05-03 00:00:00 DKI Jakarta 622 -64 -34
4 2020-05-04 00:00:00 DKI Jakarta 650 -56 -31
5 2020-05-05 00:00:00 DKI Jakarta 711 -57 -29
6 2020-05-06 00:00:00 DKI Jakarta 713 -57 -31
7 2020-05-07 00:00:00 DKI Jakarta 718 -61 -29
8 2020-05-08 00:00:00 DKI Jakarta 763 -56 -24
9 2020-05-09 00:00:00 DKI Jakarta 767 -60 -25
10 2020-05-10 00:00:00 DKI Jakarta 803 -63 -31
# ... with 21 more rows, and 4 more variables:
# parks_percent_change_from_baseline <dbl>,
# transit_stations_percent_change_from_baseline <dbl>,
# workplaces_percent_change_from_baseline <dbl>,
# residential_percent_change_from_baseline <dbl>
