Using pmap function to check whether all values in a row are positive or negative

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I have this data frame and I would like to solely use pmap function to filter only rows where all values are either negative or positive. I am looking for a concise way of doing this as I thought about c(...) but we can only use it inside a function. It is achievable by this code:

df <- tibble(x = c("a", "b", "c"), y = c(1, -1, -1), z = c(1, -1, 1), 
             p = c(1, -1, -1))

df %>%
  filter(pmap_lgl(list(y, z, p), ~ ..1 > 0 & ..2 > 0 & ..3 > 0  | 
                    ..1 < 0 & ..2 < 0 & ..3 < 0))

# A tibble: 2 x 4
  x         y     z     p
  <chr> <dbl> <dbl> <dbl>
1 a         1     1     1
2 b        -1    -1    -1

So I am looking for a way that predicate applies on all values in case I had more than 3 columns that I don't want to name them or refer to them like this.

Any help would be highly appreciated and thank you in advance.

purrr r
1 Answers

We can use if_all

library(dplyr)
df %>% 
    filter(across(where(is.numeric), ~ . > 0)|
           if_all(where(is.numeric), ~ . < 0))

-output

# A tibble: 2 x 4
#  x         y     z     p
#  <chr> <dbl> <dbl> <dbl>
#1 a         1     1     1
#2 b        -1    -1    -1

Or with pmap by selecting the numeric columns, check whether all the values are less than 0 or | greater than 0

library(purrr)
df %>%
   filter(pmap_lgl(select(., where(is.numeric)), 
              ~ all(c(...) < 0)| all(c(...)> 0)))

-output

# A tibble: 2 x 4
#  x         y     z     p
#  <chr> <dbl> <dbl> <dbl>
#1 a         1     1     1
#2 b        -1    -1    -1
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