You signed in with another tab or window. Reload to refresh your session.You signed out in another tab or window. Reload to refresh your session.You switched accounts on another tab or window. Reload to refresh your session.Dismiss alert
it would be great if skimr's summary() reported counts and the names of columns under each type category, for example:
skim(iris) %>% summary()
## A skim object
##
## Name: iris
## Number of Rows: 150
## Number of Columns: 5
##
## Column types
## factor (N): fact_col_1, fact_col_2, ..., fact_col_N
## dbl (M): dbl_col_1, dbl_col_2, ..., dbl_col_M
## int (...)
## lgl (...)
## chr (...)
this way we could quickly assess type distributions. idea: identify column types with the 3-letter symbols in the purrr::map_* family
The text was updated successfully, but these errors were encountered:
dan-reznik
changed the title
please make the summary() function report _which_ columns are categorical and numerical
could summary() report _which_ columns are categorical and numerical
Sep 11, 2018
dan-reznik
changed the title
could summary() report _which_ columns are categorical and numerical
could summary() report _which_ columns are of a certain type as well?
Sep 11, 2018
dan-reznik
changed the title
could summary() report _which_ columns are of a certain type as well?
could summary() report *which* columns are of a certain type as well?
Sep 11, 2018
That's an interesting possibility, do you want to make a PR for it? I think I might want them in separate rows than the numbers, but I'm not sure. Keeping in mind that there could be 1000s of columns I might want to only display the first 5 (or something) names.
In version 2 there is a single column that contains the variable names (skim_variable) and one with the type (skim_type) so it's easy to get the the of variables for a given type as a vector or to make a named list e.g my_list$numeric etc if you use to_list (which is like skim_to_list in v2). I think we should document this in a vignette. But going forward it might be part of thinking about managing skim with very large data sets.
it would be great if skimr's summary() reported counts and the names of columns under each type category, for example:
this way we could quickly assess type distributions. idea: identify column types with the 3-letter symbols in the purrr::map_* family
The text was updated successfully, but these errors were encountered: