How to Report NA Values in a Data Frame in R Programming (Example Code)
In this tutorial, I’ll show how to visualize and count missing values in R programming.
Creating Example Data
my_df <- data.frame(v = c(1, 5, NA, 3, 1), w = 1:5, x = c("A", "C", NA, "C", "B"), y = c(0, 0, NA, NA, 0), z = c(9, 8, 7, 6, NA)) my_df # v w x y z # 1 1 1 A 0 9 # 2 5 2 C 0 8 # 3 NA 3 <NA> NA 7 # 4 3 4 C NA 6 # 5 1 5 B 0 NA |
my_df <- data.frame(v = c(1, 5, NA, 3, 1), w = 1:5, x = c("A", "C", NA, "C", "B"), y = c(0, 0, NA, NA, 0), z = c(9, 8, 7, 6, NA)) my_df # v w x y z # 1 1 1 A 0 9 # 2 5 2 C 0 8 # 3 NA 3 <NA> NA 7 # 4 3 4 C NA 6 # 5 1 5 B 0 NA
Example: Get Number of NA Values for Each Column
colSums(is.na(data)) # Counting missings # v w x y z # 1 0 1 2 1 |
colSums(is.na(data)) # Counting missings # v w x y z # 1 0 1 2 1