How to replace NA in a column with specific value

In this tutorial we will learn how to replace missing values/NA in a column with a specific value. We will replace NA in a column using two approaches. At first we will use dplyr function mutate and ifelse to identify the element(s) with NA and replace with a specific value. Next we will use base R approach to replace missing value(s) in a column.

To get started let us load the packages needed.

library(tidyverse)

And also create a simple dataframe from scratch. Here create tibble, tidyverse variant of data frame using tribble() function.

sales     
## 1 Q1       2000  6603
## 2 Q2       2000  7182
## 3 Q3       2000  8175
## 4      2000  9001

Replace NA in column with a specific value using tidyverse

Let us say we want to replace the missing value with a specific value “Q4”, we can use mutate() function to update the column with a new one. We use ifelse() function identify missing value element and replace it with the value we want.

sales %>%
  mutate(quarter=ifelse(is.na(quarter),"Q4",quarter))
## # A tibble: 4 × 3
##   quarter  year sales
##       
## 1 Q1       2000  6603
## 2 Q2       2000  7182
## 3 Q3       2000  8175
## 4 Q4       2000  9001

Replace NA in column with a specific value using base R

If were to use base R function to replace missing value in a column, we will first identify the index where there is NA in the column using is.na() function and assign the value of interest as shown below.

sales$quarter[is.na(sales$quarter)]     
## 1 Q1       2000  6603
## 2 Q2       2000  7182
## 3 Q3       2000  8175
## 4 Q4       2000  9001