Extracting Rows with Missing Values in R
This article illustrates how to filter data set rows with NA in the R programming language.
Constructing Example Data
my_df <- data.frame(x = c(1:5, NA), # Our data frame y = c(NA, 1:5), z = c(NA, NA, 2:5)) my_df # x y z # 1 1 NA NA # 2 2 1 NA # 3 3 2 2 # 4 4 3 3 # 5 5 4 4 # 6 NA 5 5 |
my_df <- data.frame(x = c(1:5, NA), # Our data frame y = c(NA, 1:5), z = c(NA, NA, 2:5)) my_df # x y z # 1 1 NA NA # 2 2 1 NA # 3 3 2 2 # 4 4 3 3 # 5 5 4 4 # 6 NA 5 5
Example 1: Returning Rows with Missing Values in Any Variable of the Data Frame
my_df[rowSums(is.na(my_df)) > 0, ] # All NA-rows # x y z # 1 1 NA NA # 2 2 1 NA # 6 NA 5 5 |
my_df[rowSums(is.na(my_df)) > 0, ] # All NA-rows # x y z # 1 1 NA NA # 2 2 1 NA # 6 NA 5 5
Example 2: Selecting Rows with Missing Values in a Certain Variable of the Data Frame
my_df[is.na(my_df$x), ] # NA in variable x # x y z # 6 NA 5 5 |
my_df[is.na(my_df$x), ] # NA in variable x # x y z # 6 NA 5 5