Closed TomFranklin closed 5 years ago
Yep.
dplyr::if_else()
and dplyr::case_when()
would be very useful.dplyr::rename()
and dplyr::select()
were discussed in the recent sessions (from line 135 here)dplyr::arrange()
was discussed in the last session and I think makes most sense in the context of dplyr::summarise()
(line 218 here) for organising data to find 'the largest x value' or whatever.What about the *_at()
, *_if()
variants of mutate
, etc? Too much to handle this early on? Maybe put it in a tip box.
Yes agree with all the above, to be honest, I've never used _at()
or _if()
! I could use a tip with those haha
At and if are really useful! One reference and an quick example could save people loads of time going forward!
See here for some code for ideas on tidyverse functions with the SWFC data, covering select
, mutate
, filter
, *_join
, group_by
, summarise
: https://github.com/matt-dray/r-training-eyssar/blob/master/180618_training-doc.R
I think it'd be helpful for data manipulation to be just kept in one chapter and to include additional functionality such as: