Sum of column based on a condition a R - r

Question

I would like to print out total amount for each date so that my new dataframe will have date and and total amount columns.
My data frame looks like this
permitnum
amount
6/1/2022
na
ascas
30.00
olic
40.41
6/2/2022
na
avrey
17.32
fev
32.18
grey
12.20
any advice on how to go about this will be appreciated

Answer 1

Here is another tidyverse option, where I convert to date (and then reformat), then we can fill in the date, so that we can use that to group. Then, get the sum for each date.
library(tidyverse)
df %>%
mutate(permitnum = format(as.Date(permitnum, "%m/%d/%Y"), "%m/%d/%Y")) %>%
fill(permitnum, .direction = "down") %>%
group_by(permitnum) %>%
summarise(total_amount = sum(as.numeric(amount), na.rm = TRUE))
Output
permitnum total_amount
<chr> <dbl>
1 06/01/2022 70.4
2 06/02/2022 61.7
Data
df <- structure(list(permitnum = c("6/1/2022", "ascas", "olic", "6/2/2022",
"avrey", "fev", "grey"), amount = c("na", "30.00", "40.41", "na",
"17.32", "32.18", "12.20")), class = "data.frame", row.names = c(NA,
-7L))

Answer 2

Here is an option. Split the data by the date marked by a row with a number, then summarize the total in amount and combine the date and all rows.
library(tidyverse)
dat <- read_table("permitnum amount
6/1/2022 na
ascas 30.00
olic 40.41
6/2/2022 na
avrey 17.32
fev 32.18
grey 12.20")
dat |>
group_split(id = cumsum(grepl("\\d", permitnum))) |>
map_dfr(\(x){
date <- x$permitnum[[1]]
x |>
slice(-1) |>
summarise(date = date,
total_amount = sum(as.numeric(amount)))
})
#> # A tibble: 2 x 2
#> date total_amount
#> <chr> <dbl>
#> 1 6/1/2022 70.4
#> 2 6/2/2022 61.7