Replace 0 with NA in R (Example) | Changing Zero in Data Frame & Vector

In this article, I’ll illustrate how to substitute 0 with NA in the R programming language.

The tutorial will contain this:

Let’s dive into it!

Creation of Example Data

We’ll use the following data frame for the example of this R programming tutorial:

data <- data.frame(x1 = c(2, 0, 7, 4, 0, 5),    # Create example data
                   x2 = c(0, 0, 0, 1, 1, 0))
data                                            # Print example data
# x1 x2
# 1  2  0
# 2  0  0
# 3  7  0
# 4  4  1
# 5  0  1
# 6  5  0

Our example data consists of six rows and two variables x1 and x2. Some of the values of these two rows are zero.

Example: Replace 0 with NA

Replacing 0 by NA in R is a simple task. We simply have to run the following R code:

data[data == 0] <- NA                           # Replace 0 with NA
data                                            # Print updated data
#   x1 x2
# 1  2 NA
# 2 NA NA
# 3  7 NA
# 4  4  1
# 5 NA  1
# 6  5 NA

As you can see based on the RStudio console output, we replaced all 0 values with NA values. Note that we could apply the same code to a vector or a single data frame column.

Video, Further Resources & Summary

Do you want to learn more about the manipulation of data in R? Then you could have a look at the following video of my YouTube channel. I show the R code of this tutorial in the video.

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In addition, you might want to have a look at the other tutorials on https://statisticsglobe.com/. You can find a selection of tutorials below:

This article explained how to change zeros in a data frame or vector to not available values in the R programming language. Tell me about it in the comments section, in case you have any further questions and/or comments.

4 Comments. Leave new

Jessie
October 16, 2021 7:45 pm

But what if I only want to change the 0’s to NA in one column only of my data set?

Reply
- Joachim
  October 25, 2021 9:10 am
  Hey Jessie,
  
  You may access the values of a single column using the $ operator. Please try the following R code:
  data$x1[data$x1 == 0] <- NA
  data$x1[data$x1 == 0] <- NA
  Regards
  
  Joachim
  Reply
Scott Jackson
April 22, 2022 12:47 am
I like the answer, and it works, but I’m here searching for this right now because I have a string of magrittr pipes ‘%>%’ written, and I have to break out of it to use that convention above. I have a column in a dataframe where I have NAs that will stay NA, and other values that I want to be NAs.

This FAILS:
%>% mutate(Q4_spend = if_else((is.na(Q4_spend) | (Q4_spend < 100)), NA, Q4_spend)) %>%
%>% mutate(Q4_spend = if_else((is.na(Q4_spend) | (Q4_spend < 100)), NA, Q4_spend)) %>%
But this works (arbitrary 5 instead of NA):
%>% mutate(Q4_spend = if_else((is.na(Q4_spend) | (Q4_spend < 100)), 5, Q4_spend)) %>%
%>% mutate(Q4_spend = if_else((is.na(Q4_spend) | (Q4_spend < 100)), 5, Q4_spend)) %>%
Any thoughts on how to make the first case work without breaking off the pipe chain?
Reply
- Joachim
  April 22, 2022 8:10 am
  Hey Scott,
  
  Thank you, glad you found the tutorial helpful!
  
  I’m not sure why this code doesn’t work for you. However, would it be an alternative to use the Base R ifelse() function instead of the dplyr if_else function?
  
  For example:
  ifelse(is.na(c(1:10, NA)), NA, "xxx")
  ifelse(is.na(c(1:10, NA)), NA, "xxx")
  Regards,
  Joachim
  Reply