r - Using a global function to identify which subfunctions to run -
i have dataset categorical variable may take around 6 or 7 unique variables. depending upon variable is, need run several functions - each of different depending upon value of categorical variable.
i don't know how go programming things called correctly. keep in mind might simple here, in scenario more complicated lots of sub functions.
library(dplyr) func1_value_one = function(multiplication_value){ mtcars$check="value_one" mtcars$mpg =mtcars*multiplication_value filter(mtcars, mpg>60) } func0_value_zero = function(division_value){ mtcars$check="value_zero" mtcars$mpg =mtcars$mpg / division_value filter(mtcars, mpg <3) } help_function=function(category_p,change_p){ mtcars=return(filter(mtcars, vs==category_p)) data=ifelse(category_p==0,return(func0_value_zero(change_p)),return(func1_value_ one(change_p) )) return(data) } #i want filter values meet parameter passed in , perform update on values # right not able both filter values , perform correct function call. help_function(0,2)
so identifying_func(0,20) return only rows mtcars has vs==0, divide mpg values 20, , create new column called check values equal 'value_zero'
in broader context, dataset use flag determine many different table join combinations , depending upon data perform variety of calculations , adjustments.
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