tibble(
A = c("A","A","B","B"),
x = c(NA,NA,NA,1),
y = c(1,2,3,4),
) %>% group_by(A) -> df
desired output:
tibble(
A = c("B","B"),
x = c(NA,1)
y = c(3,4),
)
I want to find all groups for which all elements of x
and x
only are all NA
, then remove those groups. "B"
is filtered in because it has at least 1 non NA
element.
I tried:
df %>%
filter(all(!is.na(x)))
but it seems that filters out if it finds at least 1 NA; I need the correct word, which is not all
.
>Solution :
This will remove groups of column A
if all elements of x
are NA
:
library(dplyr)
df %>%
group_by(A) %>%
filter(! all(is.na(x)))
# A tibble: 2 × 3
# Groups: A [1]
# A x y
# <chr> <dbl> <dbl>
#1 B NA 3
#2 B 1 4
Note that group "A"
was removed because both cells in the column x
are not defined.