Pipes are great, but if they are used outside dplyr where the syntax is optimized, e.g. for manipulating elements of a list of rows of data.frame code quickly gets more complex (and less readable) than it should be. The names are in my opinion self-explanatory enough that someone who does not know them could still understand what is happening, maybe more easily than the alternative that only uses standard R.
This is a proposal for introducing 3 new pipe operators to address this.
Element-wise pipes (could e.g. also replace df/add_name_col to reduce complexity):
# this is too verbose for what it does - and sapply's defaults are stupid
list_obj %>%
sapply(function(x) myfun(x, some_arg=3), simplify=FALSE, USE.NAMES=TRUE)
# or: sapply(myfun, some_arg=3, simplify=FALSE, USE.NAMES=TRUE)
list_obj %elm>%
myfun(some_arg=3)Row- and column-wise call pipes: Use each row (or column) of a data.frame/matrix as arguments to call an arbitrary function with. This could support #63 (and at the same time make code that is based on it easier to debug):
# not sure if this even works with named arguments
mat_obj %>%
apply(1, function(..., additional_arg=5) do.call(myfun, c(list(...),
list(additional_arg=additional_arg))))
mat_obj %row>% # or %col>%
myfun(additional_arg=5)
Pipes are great, but if they are used outside
dplyrwhere the syntax is optimized, e.g. for manipulating elements of alistof rows ofdata.framecode quickly gets more complex (and less readable) than it should be. The names are in my opinion self-explanatory enough that someone who does not know them could still understand what is happening, maybe more easily than the alternative that only uses standard R.This is a proposal for introducing 3 new pipe operators to address this.
Element-wise pipes (could e.g. also replace
df/add_name_colto reduce complexity):Row- and column-wise call pipes: Use each row (or column) of a
data.frame/matrixas arguments to call an arbitrary function with. This could support #63 (and at the same time make code that is based on it easier to debug):