Tidying data in R with pivot_wider()

Let's learn how to use the pivot_wider() command from R's {dplyr} package to deal with observations that are spread across multiple rows of a data frame. Your life is about to get better!
If this vid helps you, please help me a tiny bit by mashing that 'like' button. For more #rstats joy, crush that 'subscribe' button!

[@EquitableEquations]

You can find materials from this vid (and others) at github.com/equitable-equations/youtube

[@TheJq32]

Couldn't find the blocks dataset in the link?

[@EquitableEquations]

@@TheJq32 It's included in the GLMsData package. The script on GitHub includes code to access the set. Enjoy!

[@jennanancarrow3007]

I spent hours stuck on a question for an assignment. I was completely in tears, and made a desperate pilgrimage to CZcams... and learned exactly how to do the thing in 5 minutes. THANK YOU!!!

[@EquitableEquations]

Yay! Glad it helped.

[@randomrants8294]

Very well explained without any clutter

[@sergiochavezlazo5362]

This is a great video! Thank you very much !

[@ivanalexandrov8752]

Thank you a lot! I understood it perfectly

[@nicolafierro1]

This was hella useful
Thanks !!

[@chitrabalu8280]

Thanks for this video.

[@EquitableEquations]

Glad it helped!

[@oscarrosalescorzo]

Thanks!

[@romanvasiura6705]

Thank you!

[@FlurinaB]

Thank you so much for this helpful video!! May I ask: After having converted the blocks dataframe into wide format: If i wanted to calculate the mean for time and for number of trial 1 and trial 2, how would that work?

[@EquitableEquations]

Hi! It's actually more natural to do those calculations before pivoting. Group_by() and summarize() are built for this!
czcams.com/video/owkZgyeNXSg/video.html

[@xiyaluo6891]

Thanks

[@CanDoSo_org]

Thanks, Andrew. It would be more helpful if you can attach the data you used.

[@EquitableEquations]

Done.

[@CanDoSo_org]

@@EquitableEquations Many thanks.

[@OlawaleQuadriOgunsola]

Pivot_wider and _longer are in the tidyr package, not dplyr.

[@vincenzo4259]

Thanks

[@EquitableEquations]

You're welcome!