NA values in vectors passed to map_dfr - r

Question

I'm trying to pass vectors, each with a different number of NA values, through to a map() function but it's returning an error.
I have a tibble of N numeric columns and 1 categorical column. I want to compare the distributions for each of the numeric columns against the other split by the values of the categorical column. I use overlapping::overlap() to calculate the overlap of the distributions, and i feed the numeric columns into a map_dfr function for the iteration. For example:
require(overlapping)
require(dplyr)
require(purrr)
set.seed( 1 )
n <- 100
G1 <- sample( 0:30, size = n, replace = TRUE )
G2 <- sample( 0:30, size = n, replace = TRUE, prob = dbinom( 0:30, 31, .55 ))
G3 <- sample( 0:30, size = n, replace = TRUE, prob = dbinom( 0:30, 41, .65 ))
Data <- data.frame(y = G1, x = G2, z = G3, group = rep(c("G1","G2", "G3"), each = n), class = rep(c("C1","C2", "C3"), each = 1)) %>% as_tibble()
Data
overlap_fcn <- function(.x) {
## construct list of vectors
dist_list <- list(
"C1" = Data %>%
filter(class == 'C1', !is.na(.x)) %>%
pull(.x),
"C2" = Data %>%
filter(class == 'C2', !is.na(.x)) %>%
pull(.x),
"C3" = Data %>%
filter(class == 'C3', !is.na(.x)) %>%
pull(.x)
)
## calculate distribution overlaps
return(
enframe(
overlapping::overlap(dist_list)$OV*100
) %>%
mutate(value = paste0(round(value, 2), "%"),
class = .x) %>%
rename(comparison = name, overlap = value) %>%
relocate(class)
)
}
overlap_table <- purrr::map_dfr(
.x = c('y', 'x', "z"),
.f = ~overlap_fcn(.x))
overlap_table
The above works as intended. However, in practice I have different amounts of missingess in each of x, y, and z. I try to account for this with the filter on !is.na(.x) but it's not working. For example:
Data$x[1:3] <- NA
Data$y[10:20] <- NA
Data$z[100:150] <- NA
overlap_table <- purrr::map_dfr(
.x = c('x', 'y', "z"),
.f = ~overlap_fcn(.x))
returns this error:
Error in density.default(x[[j]], n = nbins, ...): 'x' contains missing values
Error in density.default(x[[j]], n = nbins, ...): 'x' contains missing values
Traceback:
1. purrr::map_dfr(.x = c("x", "y", "z"), .f = ~overlap_fcn(.x))
2. map(.x, .f, ...)
3. .f(.x[[i]], ...)
4. overlap_fcn(.x)
5. enframe(overlapping::overlap(dist_list)$OV * 100) %>% mutate(value = paste0(round(value,
. 2), "%"), class = .x) %>% rename(comparison = name, overlap = value) %>%
. relocate(class) # at line 25-33 of file <text>
6. relocate(., class)
7. rename(., comparison = name, overlap = value)
8. mutate(., value = paste0(round(value, 2), "%"), class = .x)
9. enframe(overlapping::overlap(dist_list)$OV * 100)
10. overlapping::overlap(dist_list)
11. density(x[[j]], n = nbins, ...)
12. density.default(x[[j]], n = nbins, ...)
13. stop("'x' contains missing values")
Can anyone help me out here please? I'm sure it's something super obvious i'm missing; i just can't see what!

Answer 1

Here, the .x is character class. We may need to convert to symbol and evaluate (!!)
overlap_fcn <- function(.x) {
## construct list of vectors
dist_list <- list(
"C1" = Data %>%
filter(class == 'C1', !is.na(!! rlang::sym(.x))) %>%
pull(.x),
"C2" = Data %>%
filter(class == 'C2', !is.na(!! rlang::sym(.x))) %>%
pull(.x),
"C3" = Data %>%
filter(class == 'C3', !is.na(!! rlang::sym(.x))) %>%
pull(.x)
)
## calculate distribution overlaps
return(
enframe(
overlapping::overlap(dist_list)$OV*100
) %>%
mutate(value = paste0(round(value, 2), "%"),
class = .x) %>%
rename(comparison = name, overlap = value) %>%
relocate(class)
)
}
-testing after creating the NAs in Data
> purrr::map_dfr(
+ .x = c('x', 'y', "z"),
+ .f = ~overlap_fcn(.x))
# A tibble: 9 × 3
class comparison overlap
<chr> <chr> <chr>
1 x C1-C2 98.61%
2 x C1-C3 97.46%
3 x C2-C3 97.5%
4 y C1-C2 95.47%
5 y C1-C3 96.22%
6 y C2-C3 97.14%
7 z C1-C2 90.17%
8 z C1-C3 94.9%
9 z C2-C3 89.24%