getting count of missing values in summary

[str_guru]

i want to get the count of NA's in column with max and min. is there any way in expss already to get a count in below example

library(expss)
library(dplyr)

example <- data.frame(org = c("A", "B", "C", "D", "E", "F", "G"),
                      q1 = c("apple", "apple", NA, "apple", "apple", "apple", NA),
                      q2 = c(NA, NA, NA, "banana", "banana", "banana", NA),
                      q3 = c("orange", NA, "orange", "orange", NA, "orange", NA),
                      region = c("1", "1", "2", "3", "3", "2", "2"))





pct_all <- cross_cpct(example, mrset(q1 %to% q3), region)](https://)

output should be look like

[BLukomski]

To count up the missing values in each of your columns, I would use the below code (In this case, for q1):

sum(is.na(example$q1))

The is.na part of this function will return 1 for missing values and 0 for non-missing values. The sum function will then return the sum of these binary values, giving you the total number of missing values in the column of your choosing.

[str_guru]

thats is for one variable but i want to do it for mrset(q1 %to% q3)

[nirgrahamuk]

I'm guessing it might be

library(expss)
library(dplyr)

example <- data.frame(org = c("A", "B", "C", "D", "E", "F", "G"),
                      q1 = c("apple", "apple", NA, "apple", "apple", "apple", NA),
                      q2 = c(NA, NA, NA, "banana", "banana", "banana", NA),
                      q3 = c("orange", NA, "orange", "orange", NA, "orange", NA),
                      region = c("1", "1", "2", "3", "3", "2", "2"))

na_replace_string <- "z_na"

(solid_example <- mutate(example,
                        across(starts_with("q"),
                               \(x)ifelse(is.na(x),na_replace_string,x))))

(pct_all <- cross_cpct(solid_example,
                       mrset(q1 %to% q3), region))

pct_all$row_labels[which(pct_all$row_labels==na_replace_string)] <- "#missing vals"

pct_all

 |               | region |       |     |
 |               |      1 |     2 |   3 |
 | ------------- | ------ | ----- | --- |
 |         apple |    100 |  33.3 | 100 |
 |        banana |        |  33.3 | 100 |
 |        orange |     50 |  66.7 |  50 |
 | #missing vals |    150 | 166.7 |  50 |
 |  #Total cases |      2 |   3.0 |   2 |