Open nehamoopen opened 1 year ago
These were comments made after following the very first course in R, comments are organised by session (corresponding to videos):
Intro to Tidyverse
Import Data
Hello! I haven't gone through the afternoon session materials (and will not manage before the end of this month). I had only noticed so far that the slides link to uu.nl/rdm
, that should be https://uu.nl/rdm
, because otherwise the link does not work. Sorry, not super useful feedback ;)
Notes from @Mish-JPFD:
penguins
dataset (raw) - there are column names with whitespaces, these should be renamed with underscores.
During session notes:
../data/penguins_raw.tsv
, when run from the entire environment it should be data/penguins_raw.tsv
. I think this is a something that we can set in the Rmd or in the settings chunk or something. This goes for all reading and writing of filespenguins_subset <- filter(penguins, ???)
> when manually importing the dataset, the dataset is not named penguins
, but penguins_raw
> This is the case for many exercises, needs check!penguins_subset
is overwritten here, should probably just be a new version of the dataset just in case people get stuck here because the selected columns cannot be found while testing
penguins_subset <- select(penguins_subset, ???)
with for example penguins_subset_select <- select(penguins_subset, ???)
|>
which does not rely on the magrittr
package. Perhaps that should be mentioned somehow, for people not using tidyverse in the future. Within the tidyverse the %>%
and |>
are interchangeable (source)Use the code you wrote during exercises 4 and 5, and make a workflow that starts with the data
penguins
, and subsequently applies yourfilter
andselect
operations.
should become
Use the code you wrote during exercises 5 and 6, and make a workflow that starts with the data
penguins_raw
, and subsequently applies yourfilter
andselect
operations.
penguins_subset_piping <- penguins_raw %>% ???
penguins_subset <- penguins_subset %>% mutate(culmen_ratio = ???)
> penguins_subset_mutate <- penguins_subset_piping %>% mutate(culmen_ratio = ???)
Exercise 9 combines two functions: rename and pivot_wider, I would perhaps just split them...maybe do the renaming earlier in the script as well
[ ] Importing data could be done with a simple read_tsv
and read_excel
, instead of having to go through the import menu -> copying the code -> having to figure out the concept of delimiters + how to specify them in arguments with (for example) /t
-> reformatting the date...
[ ] After a cleaner section on importing data, you could have a section on some basic cleaning/tidying operations which includes formatting dates (currently combined with importing data) and renaming columns (currently combined with pivoting data).
[ ] After the above two sections are done with simple, clean functions - we can introduce the participants to piping and have them chain all the three together (import, rename, reformat). Then moving onto the rest of the exercises will be easier...
[ ] The ggplot section could be simplified significantly. The section could start with introducing participants to the different layers involved in ggplot. There's an image of a pyramid which starts with the data as the base and then you add things like aesthetics and facets etc. on top. Thereafter, you could show participants something like the ggplot flipbook: https://evamaerey.github.io/ggplot_flipbook/ggplot_flipbook_xaringan.html and we could structure our exercises to follow this layered way of working (or at least demo it that way).
Please leave your feedback for the
tidyverse
component (afternoon session) in this issue, thaaaanks!