Comments (4)
In the hypothetical code in the last line of your comment, it would just check cyl
for each column that is numeric.
If there were a function for that, it couldn't be a form of verify
. verify
is more flexible than the other assertions and doesn't have to work on data.frames at all. Is assert
not ok for this use case?
is_int <- function(x) x == floor(x)
df %>% assert(is_int, cyl, vs:carb)
or
df %>% assert_(is_int, names(df)[sapply(df, is.numeric)])
from assertr.
My hypothetical code is nonsense of course since it wasn't my intention to just check cyl
, but all numeric columns in the data_frame
(of which I ideally do not want to provide the names).
So my use-case would be to check if all numeric columns (which are currently e.g. stored as double) are really all integers before converting them to integers. And all that without providing the column names.
The column name part disqualifies your first solution. Your second solution is fine. It just does not completely adhere to the tidyverse
(or magrittr
pipe) conventions of not having to specify the data_frame
several times, I guess. So what about:
df %>% assert_if(is.numeric, is_int)
But really,
df %>% assert_(is_int, names(df)[sapply(df, is.numeric)])
is fine!
from assertr.
Here are some other alternatives!
df %>% assert_(., is_int, names(.)[sapply(., is.numeric)])
and
df %>% select_if(., is.numeric) %>% assert(is_int, everything())
By careful with the last one, though–it'll make data
the new smaller data frame with only numeric columns.
I consider this good enough for now because we're working on some other cool features. I'll reinvestigate potentially adding *_if functions afterwards. Is it ok with you if I close this issue for now?
from assertr.
Of course, this certainly isn't mission-critical.
Thanks for considering it!
from assertr.
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from assertr.