Is this what you mean?
library(dplyr)
# Sample data on a copy/paste friendly format, replace this with your own data frame
pa_new1 <- data.frame(
stringsAsFactors = FALSE,
Start.Date = c("1974-08-02","1974-07-12",
"1974-06-28","1974-06-21","1974-05-31","1974-05-17"),
End.Date = c("1974-08-05","1974-07-15",
"1974-07-01","1974-06-24","1974-06-03","1974-05-20"),
Approving = c(24, 24, 28, 26, 28, 26),
Disapproving = c(66, 63, 58, 61, 61, 61),
Unsure.NoData = c(10, 13, 14, 13, 11, 13),
Date = c("1974-08-02","1974-07-12",
"1974-06-28","1974-06-21","1974-05-31","1974-05-17"),
year = c("1974", "1974", "1974", "1974", "1974", "1974"),
month = c("08", "07", "06", "06", "05", "05")
)
# Relevant code
pa_new1 %>%
group_by(year, month) %>%
summarise(across(where(is.numeric), mean))
#> `summarise()` has grouped output by 'year'. You can override using the
#> `.groups` argument.
#> # A tibble: 4 × 5
#> # Groups: year [1]
#> year month Approving Disapproving Unsure.NoData
#> <chr> <chr> <dbl> <dbl> <dbl>
#> 1 1974 05 27 61 12
#> 2 1974 06 27 59.5 13.5
#> 3 1974 07 24 63 13
#> 4 1974 08 24 66 10
Created on 2022-05-07 by the reprex package (v2.0.1)
Note: Next time please provide a proper REPRoducible EXample (reprex) illustrating your issue.