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Reshaping Data

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Transcript

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Your Turn

  1. Start with the enrollment_18_19 data frame

  2. select() the district_id variable as well as those about number of students by race/ethnicity and get rid of all others (hint: use the contains() helper function within select())

  3. Use pivot_longer() to convert all of the race/ethnicity variables into one variable

  4. Within pivot_longer(), use the names_to argument to call that variable race_ethnicity

  5. Within pivot_longer(), use the values_to argument to call that variable number_of_students

Learn More

The best place to learn more about pivot_longer() and pivot_wider() is the pivoting vignette from the tidyr package.

There’s also a nice article by Gavin Simpson of University College, London about pivoting. That article includes the animations below, made by Garrick Aden-Buie and Mara Averick, that gave a visual demonstration of pivoting.

RStudio has a nice primer on reshaping data, complex with a few exercises.

Finally, a heads up: if you ever see references to the functions gather() and spread(), these are the previous iterations of the pivot functions. They still work (as the tweet below from tidyverse developer Hadley Wickham indicates), but the pivot functions are, in my view (and the view of many others), much easier to use.

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

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IBRAH SENINDE

IBRAH SENINDE

April 22, 2021

Hi David, I typed the following code, but the new data frame still the original structure. What could be the problem? enrollment_by_race_ethnicity_18_19 % select(-contains("grade")) %>% select(-contains("kindergarten")) %>% select(-contains("percent")) %>% pivot_longer(cols = "district_id", names_to = "race_ethnicity", values_to = "number_of_students")

Harold Stanislaw

Harold Stanislaw

April 22, 2021

Hi IIbrah. Try changing pivot_longer(cols = “district_id”, to pivot_longer(-district_id , The code you entered was pivoting the district ID in addition to the other columns.

Harold Stanislaw

Harold Stanislaw

April 22, 2021

I used select(!contains ("percent")) instead of select(-contains ("percent")), mainly because the helper page listed the exclamation option rather than the minus sign. Are there any differences between the two?

David Keyes

David Keyes

April 22, 2021

I don't know the answer to that! Does it give the same result?

Harold Stanislaw

Harold Stanislaw

April 22, 2021

Looks like it gives the same answer.

David Keyes

David Keyes

April 22, 2021

Ok, I guess it does do the same thing then. Thanks for teaching me something new!

Matt M

I only have enrollment_17_18 and enrollment_18_19 files. Where did the math scores files come from that is shown at 5:40 of this lesson? My code matches what's in the Solutions for the Importing Data lesson and I don't think there was anything we downloaded in the Tidy Data lesson.

Matt M

I now see that we don't need for (Y)our turn. was just trying to follow along

Alberto Espinoza

Alberto Espinoza

September 10, 2022

Hi David, is there a way to enter the name of each column we want to remove within one select(-contains(" ")) argument rather than writing each one separately?

David Keyes

Do you mean like doing select(-c(column1, column2))?

Alberto Espinoza

Alberto Espinoza

September 27, 2022

Yes! Thank you, that worked.

Nadia Chang

Hi David! by using pivot_longer it means that it will always arrange the data by 3 columns?

David Keyes

I'm not sure I quite understand your question. Can you explain a bit more?

Nadia Chang

What I understand from pivot_longer documentation page is that it will rearrange the data by decreasing the number of columns, so my question is: if pivot longer will always tidy the data into 3 columns? In this case there is just one column for "the values", one column for "the names or columns that have characters" and "id column" (this last one we kept it by adding the "-").

David Keyes

David Keyes

December 1, 2022

It will be 3 columns if you only have 1 column that you are not pivoting (in this case, the id column). However, if you are not pivoting multiple columns then you will have more than 3. Does that make sense?