mutate

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This lesson is called mutate, part of the Fundamentals of R course. This lesson is called mutate, part of the Fundamentals of R course.

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# mutate

![](slides/images/mutate.png)

We use `mutate` we make new variables or change existing ones. 

Create a **new variable with a specific value**

Create a new variable called `completed_survey` and make all responses to it "Yes".

```{r}
nhanes %>%
  mutate(completed_survey = "Yes")
```

Copy your code from above and then add a line where you select only the `completed_survey` variable. Don't forget the pipe (%>%)!

```{r}
nhanes %>%
  mutate(completed_survey = "Yes") %>% 
  select(completed_survey)
```

Create a **new variable based on other variables**

Create a new variable called `pct_days_phys_health_bad` and calculate it as the percentage of self-reported days of bad physical health in the last 30 days. Remember that the `days_phys_hlth_bad` variable is a measure of the **number** of self-reported days of bad physical health in the last 30 days. Then, use `select` to show the `days_phys_hlth_bad` and `pct_days_phys_health_bad` variables.

```{r}
nhanes %>% 
  mutate(pct_days_phys_health_bad = days_phys_hlth_bad / 30) %>% 
  select(days_phys_hlth_bad, pct_days_phys_health_bad)
```

Change an **existing variable**

Round the `height` variable to a whole number. Then, use `select` to show only the `height` variable.

```{r}
nhanes %>%
  mutate(height = round(height, digits = 0)) %>% 
  select(height)
```

Complete the mutate sections of the data-wrangling-and-analysis-exercises.Rmd file.

Learn More

General Data Wrangling and Analysis Resources

Because most material that discusses data wrangling and analysis with the dplyr packges does so in a way that covers all of the verbs discussed in this course, I have chosen not to separate them by lesson. Instead, here are some helpful resources for learning more about all of the tidyverse verbs discussed in this course:

Chapter 5 of R for Data Science

RStudio Cloud primer on working with data

Tidyverse for Beginners by Danielle Navarro

Learning Statistics with R by Danielle Navarro

Introduction to the Tidyverse by Alison Hill

A gRadual intRoduction to data wRangling by Chester Ismay and Ted Laderas

Working in the Tidyverse by Desi Quintans and Jeff Powell

Christine Monnier video tutorials on dplyr

Have any questions? Put them below and we will help you out!

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Bohdanna Kinasevych

March 27, 2021

how do I add multiple columns together to create a new variable without having to write out each existing variable in the mutate function. For example if I have 10 questions on a survey and I want to create a composite score based on a sum of these 10 questions, is there a way to do this without having to write out: var1 + var2 + var3 .... + var10?

David Keyes

March 29, 2021

Great question, Bo! The best way to handle this is to tidy your data. Take a look at the tidy data and reshaping data lessons, which deal with this exxact issue. If you still have questions, let me know!

Eduardo Rodriguez

March 30, 2021

Hi David, how do I change a value format? For example, in the course assignment we divide by 30 and get a long decimal value. How would I format it so that it only shows two decimal places or even, out of curiosity, as a percentage?

Eduardo Rodriguez

March 30, 2021

Scratch the first part of the question. I could just wrap it in the round function. But how would I show a decimal as a percentage?

David Keyes

March 30, 2021

Yup, here's a video for you explaining this!

Eduardo Rodriguez

March 31, 2021

Whoa. More than helpful! The scales package is great and the round_half_up call is good to know. In Canada we also round up when it is a 5. Thanks again, David.

Harold Stanislaw

March 31, 2021

Question regarding overwriting a variable with itself. I'm always nervous about doing this, in case I mess up. On the other hand, I can see where creating new variables and keeping the old ones can easily get out of hand and/or require using the drop pipe a lot. If I want to overwrite a variable onto itself is there an easy way to undo the mutate if I make a mistake?

David Keyes

March 31, 2021

Yup! The easiest way is to just remove the line where you overwrite the variable and then rerun your code. That will bring your data frame back to the state where it was previously. Let me know if that makes sense!

Harold Stanislaw

March 31, 2021

Yes, it makes sense -- thanks!

Lina Khan

September 27, 2021

When the values are changed, like rounding values, how come it doesn't show in the dataset tab? Or, have I forgotten something? For example, the output still shows the rounded values when I select the variable. But other than clean_names, the changes don't appear in the dataset. Thanks!

David Keyes

September 28, 2021

Good question! This is something that confused me when I was learning R. Here's a quick explanation for you! Let me know if this is clear.

Ellen Wilson

October 6, 2022

This link no longer works

David Keyes

October 6, 2022

Sorry about that! We switched video hosts and that video didn't seem to get transferred over. We just talked about something similar yesterday in a training program we're doing for the Visitor Studies Association (VSA). You can see our discussion here where we talk about assigning objects vs displaying them. Let me know if that helps!

David Keyes

September 28, 2021

I typically keep both a numeric and a character variable. Here's a quick explanation of why.

Lindsay Quarles

October 21, 2021

Can you help me better understand the round function? I don't understand the digits part? Does it only apply to decimals? What if you want to round to the nearest whole number what would you put? Or to round to the nearest 10?

Lindsay Quarles

October 21, 2021

I figured it out. 0 for nearest whole number, -1 for nearest 10, and so on.

Yenn Lee

July 19, 2022

Hi, I have a column that I would like to split into three. The data in the existing column looks like the following, and I would like it to feed into three new columns: id, bio, and username.

{"id":"1234567","bio":"John Smith, first-year undergraduate in Physics","username":"JSAstronaut"}

All rows follow this exact format (although the bio part may be longer), so I feel there must be a simple way to do, and I was just wondering if anyone has suggestions. Or is this going to be covered at a later point in the courses? So far I have tried the separate function in tidyr, but it hasn't quite turned out to be the way I hoped.

I'd appreciate any pointers. Thank you!

Charlie Hadley

July 21, 2022

Hi Yenn!

This is a somewhat beyond basic problem to solve. Because it was a fun problem to solve I wrote a bit of custom code for you. There are two versions:

Using mutate() for each column
Using across() inside mutate(). This is far beyond the scope of this Getting Started Course.

Unfortunately, there's a limit to how much custom code I can write for folks on this course - and I've hit that limit. We have additional courses that might be useful to you, and the R in 3 Months program gives you 12 weeks of custom feedback videos for your data. However, of course there's no requirement for you to make any purchases from us.

I also need to tell you to be careful about quotations in programming. Most strings are contained within double quotation marks. But. These must be contained in straight quotes, curly quotes will break your code. Because your strings themselves contain double quotes there are two approaches:

Escape the quotes, "{"id":"1234567""
Use single quotes to contain the string, '{"id":"1234567"'

Hopefully this does help you. R is an awesome tool, but sometimes problem solving requires a few more steps than we can introduce in this course.

Cheers,

Charlie

Tatiana Bustos

July 27, 2022

Hi What if I wanted to create a new variable for a subset of groups with one type and then another set of groups with another For example, if I wanted to only create a new variable for "Females" with country = United States, but then select only "Males" with country = Canada. I tried to do the following as a best guess nhanes %>% mutate(completed_survey = "Yes") select(contains("female"))

David Keyes

July 28, 2022

Your best bet would be to use the case_when() function. I cover this in the Going Deeper course. Here's a video from the course showing how it works.

Fundamentals of R

RMarkdown

Data Wrangling and Analysis

Data Visualization

Wrapping Up

Fundamentals of R

mutate

This lesson is locked

Transcript

Your Turn

Solution

Learn More

Have any questions? Put them below and we will help you out!

Bohdanna Kinasevych

David Keyes

Eduardo Rodriguez

Eduardo Rodriguez

David Keyes

Eduardo Rodriguez

Harold Stanislaw

David Keyes

Harold Stanislaw

Lina Khan

David Keyes

Ellen Wilson

David Keyes

David Keyes

Lindsay Quarles

Lindsay Quarles

Yenn Lee

Charlie Hadley

Tatiana Bustos

David Keyes