R - Replace NA with Empty String in a DataFrame

How to replace NA (missing values) with blank space or an empty string in an R dataframe? You can replace NA values with blank spaces on columns of the R dataframe (data.frame) using is.na(), replace() methods. And use dplyr::mutate_if() to replace only character columns when you have mixed numeric and character columns, use dplyr::mutate_at() to replace multiple selected columns by index and name.

R base is.na() function
R base replace() function
dplyr::mutate_if() and tidyr::replace_na()
dplyr::mutate_at() and tidyr::replace_na()

Typically, NA values are treated as missing data, and performing operations on them can lead to inconsistent results. Therefore, it is advisable to address these missing values before processing the data. Similarly, using these you can also replace NA with zero (0) in R.

1. Quick Examples of Replacing NA’s with Empty String

Following are quick examples of replacing NA values with an empty string in R.


# Quick Examples

#Example 1 - Replace na values with blank using is.na()
my_dataframe[is.na(my_dataframe)] <- ""

#Example 2 - By using replace() & is.na()
my_dataframe <- replace(my_dataframe, is.na(my_dataframe), "")

# All below examples need to load these libraries
library("dplyr")
library("tidyr")

#Example 3 - Replace only string columns
my_dataframe <- my_dataframe %>% 
      mutate_if(is.character, ~replace_na(.,""))

# Example 4 - Replace on selected columns by Name
my_dataframe <- my_dataframe %>%
  mutate_at(c('name','gender'), ~replace_na(.,""))

# Example 5 - Replace on selected columns by Index
my_dataframe <- my_dataframe %>% 
  mutate_at(c(1,2), ~replace_na(.,""))

Let’s create a dataframe having NA values,


#Create dataframe
my_dataframe=data.frame(
  name=c('sravan',NA,'chrisa','shivgami',NA),
  gender=c(NA,'m',NA,'f',NA))

#Display dataframe
print(my_dataframe)

Output:


#Output
      name gender
1   sravan   <NA>
2     <NA>      m
3   chrisa   <NA>
4 shivgami      f
5     <NA>   <NA>

2. Replace NA’s with Empty String

The is.na() function in R determines if a particular data frame column value equals NA. When a value is NA, it generates TRUE, otherwise FALSE. So by specifying it within square brackets, it replaces NA with an empty string. This method facilitates the replacement of NA values with an empty string in an R data frame.

Syntax:


#Syntax
df[is.na(df)] = "value to replace"

where my_dataframe is the input dataframe. Let’s run an example to update NA values with blank space in R dataframe.


#Replace na values with blank using is.na()
my_dataframe[is.na(my_dataframe)] <- ""

#Display the dataframe
print(my_dataframe)

Output:


#Output
      name gender
1   sravan       
2               m
3   chrisa       
4 shivgami      f
5

In the above output, we can see that NA values are replaced with blank spaces.

3. Replace NA values with Blank Space using replace()

Let’s explore another method to replace NA values with empty string using the replace() function, which requires three parameters.

Syntax:


#Syntax
replace(df,is.na(df),"value to replace")

Parameters:

The first parameter is the input data frame.
The second parameter uses the is.na() method to check for missing values (NA).
The final parameter specifies the value “”, which will replace any missing values identified by the second parameter.

Example: Replace NA with blank space in the dataframe using replace()


#By using replace() & is.na()
my_dataframe <- replace(my_dataframe, is.na(my_dataframe), "")

#Display dataframe
print(my_dataframe)

Yields the same output as above.

Alternatively, you can also write the above statement using %>% operator. To use this, load the library dplyr.


#Example 2 - Using %>% 
library("dplyr")
my_dataframe <- my_dataframe %>% 
     replace(is.na(my_dataframe), "")
print(my_dataframe)

4. Replace NA with Empty String only on Character Columns

All examples above use dataframe with only characters hence renaming NA with an empty string is straight forward but, in real-time we would get a mix of numeric and character columns, and running the above examples results in an error hence, we need to use qualifiers to apply the change only on character columns ignoring numeric columns.

You can apply conditions by using dplyr::mutate_if() and is.character is used to check if the column is a character or not and apply tidyr::replace_na() only on character columns.


#Create dataframe
my_dataframe=data.frame(
  id=c(2,1,3,4,NA),
  name=c('sravan',NA,'chrisa','shivgami',NA),
  gender=c(NA,'m',NA,'f',NA))

#Load library
library("dplyr")
library("tidyr")

#Replace only character columns
my_dataframe <- my_dataframe %>%
       mutate_if(is.character, ~replace_na(., ""))
print(my_dataframe)

Yields below output. Notice that colid id still have NA values as it’s been ignored because it holds numeric values.


#Output
  id     name gender
1  2   sravan       
2  1               m
3  3   chrisa       
4  4 shivgami      f
5 NA

5. Replace NA with Empty String on Selected Multiple Columns

To replace NA with an empty string on selected multiple columns by name use mutate_at() function with vector c() of column names.


# Replace on selected multiple columns
library("dplyr")
library("tidyr")
my_dataframe <- my_dataframe %>% 
    mutate_at(c('name','gender'), ~replace_na(.,""))
print(my_dataframe)

Yields the same output as above.

6. Replace NA with Empty String on Selected Multiple Index

Finally, if you wanted to replace NA with an empty string on selected multiple r dataframe columns by index use mutate_at() function with vector c() of index values.


# Replace on selected multiple index
library("dplyr")
library("tidyr")
my_dataframe <- my_dataframe %>% 
     mutate_at(c(2,3), ~replace_na(.,""))
print(my_dataframe)

Yields the same output as above. You can find more details on the mutate() function and its variants in the R Documentation.

6. Conclusion

In this article, I have explained multiple ways to replace NA also called missing values with blank space or an empty string in the R dataframe by using is.na(), replace() methods. And use dplyr::mutate_if() to replace only on character columns when you have mixed numeric and character columns, use dplyr::mutate_at() to replace on multiple selected columns by index and name.