Map functions in purrr (R Tidyverse)

[@loganbunch3561]

Thank the gods for this man. After hours of searching and trial and error, I finally found a youtube channel worth a damn. Thank you for making my life a little easier..

[@mashfintech]

Nice and simple. Gives a lot of clarity.

[@tahadinc1302]

I really like the way you explained the concept, thank you for the great video

[@krakenworks7702]

To the point and a clear explanation. Thank you.

[@ZomnY449]

what does the tilde stand for in the manual function of the map?

[@larissacury7714]

thank you very much! What does the ~ stand for before the . ?

[@vrajtalati5300]

how did you just kept the console and script in dark mode and everything else in light mode?

[@oriolverdenyvilalta85]

Perfectly explained

[@n00dle25]

Thank you! Very good video and explanation.

[@riverland0072]

nice...which keyboard do you use please...I like the sound

[@DividedStates]

Q: You have a tibble a1 and you write a1 * 2, it returns you are base R data.frame instead of a tibble. Why is that?

[@DimitrisPatikas]

nice. is there any difference from the build-in lapply() or sapply() commands?

[@TrentTube]

The nomenclature of base R isn't consistent with the tidyverse. Also, map functions are more feature-rich than the base R alternatives.

[@c0f2a]

Why we need to use map function from another package? I found lapply/sapply/mapply in the base R makes perfect sense to me.

[@TrentTube]

The nomenclature of base R isn't consistent with the tidyverse. Also, map functions are more feature-rich than the base R alternatives.

[@MannISNOR]

Thank you Ben!

[@brendenmorley2643]

Thank you. Great instruction

[@harrisonooi296]

good video, but i needed something more complex lmao ! but thank you :D

[@marlonfermat8115]

nice video, Also , it is not clear why not use apply, lapply ...etc

[@DividedStates]

Ok, let's talk about real world problems again. I mean, you seldom have a table with some easy numbers and maybe you maybe want to do more than multipling with 2. Let's say: You have a chromatography system which gives you .tsv or .csv files of a specific format. So, you want to transform a number of complex list elements in the same way. Could you make a list of data.frames (e.g. the files saved in the output folder of that instrument) pipe this list of data.frames into map? What if you want to do more then just one operation/function? How would you address specific elements of the data.frames, when piped?

[@TrentTube]

Nest and unnest can help separate out different elements of a list of dataframes, in the process of applying mapping functions to them. The .tsv vs .csv are usually handled with readr. See the following cheatsheet for help on more complicated, layered mapping: github.com/rstudio/cheatsheets/blob/master/purrr.pdf