Hi @Aloysio, welcome to RStudio Community.
I would do it like this:
library(dplyr, warn.conflicts = FALSE)
a <- tribble(~ fecha, ~ provincia_deteccion, ~ n, ~ fa,
"2020-03-11", "Sancti Spíritus", 3L, 3L,
"2020-03-13", "Villa Clara", 1L, 1L,
"2020-03-16", "La Habana", 1L, 1L,
"2020-03-17", "Camagüey", 1L, 1L,
"2020-03-17", "La Habana", 1L, 2L,
"2020-03-18", "Holguín", 1L, 1L)
a <- mutate(a, fecha = as.POSIXct(fecha))
b <- tribble(~ fecha, ~ provincia_deteccion, ~ fallecidos, ~ faa_fallecidos,
"2020-03-12 00:00:00", "Sancti Spíritus", 1L, 1L,
"2020-03-26 00:00:00", "La Habana", 1L, 1L,
"2020-03-28 00:00:00", "Villa Clara", 1L, 1L,
"2020-03-29 00:00:00", "Ciego de Ávila", 1L, 1L,
"2020-03-29 00:00:00", "La Habana", 1L, 2L,
"2020-03-30 00:00:00", "La Habana", 1L, 3L)
b <- mutate(b, fecha = as.POSIXct(fecha))
a %>%
rename(fallecidos = n, faa_fallecidos = fa) %>%
bind_rows(b) %>%
group_by(fecha, provincia_deteccion) %>%
summarize(fallecidos = sum(fallecidos)) %>%
group_by(provincia_deteccion) %>%
mutate(faa_fallecidos = cumsum(fallecidos)) %>%
ungroup()
#> # A tibble: 12 x 4
#> fecha provincia_deteccion fallecidos faa_fallecidos
#> <dttm> <chr> <int> <int>
#> 1 2020-03-11 00:00:00 Sancti Spíritus 3 3
#> 2 2020-03-12 00:00:00 Sancti Spíritus 1 4
#> 3 2020-03-13 00:00:00 Villa Clara 1 1
#> 4 2020-03-16 00:00:00 La Habana 1 1
#> 5 2020-03-17 00:00:00 Camagüey 1 1
#> 6 2020-03-17 00:00:00 La Habana 1 2
#> 7 2020-03-18 00:00:00 Holguín 1 1
#> 8 2020-03-26 00:00:00 La Habana 1 3
#> 9 2020-03-28 00:00:00 Villa Clara 1 2
#> 10 2020-03-29 00:00:00 Ciego de Ávila 1 1
#> 11 2020-03-29 00:00:00 La Habana 1 4
#> 12 2020-03-30 00:00:00 La Habana 1 5
Created on 2020-04-19 by the reprex package (v0.3.0)