Using Min and max function inside a function

Question

I have created a function which uses 2 variables to do grouping and uses third variable to create min and max for each groups. But the min and max function gives wrong output. It gives the minimum and maximum for entire dataset and not for each group.

myfunction= function(x,a,b,column) {
  temp=group_by(x,x[[a]],x[[b]])
   Score=summarise(temp,Totals=n(),Mnscore=min(x[[c]]),Mxscore=max(x[[c]]))
 return(Score)
}

myfunction(dataset,"a","b","c")


Actual Results:
a b Totals  Min Max
1 1  10     15  50
1 2  20     15  50
1 3  30     15  50

Expected results:
a b Totals  Min Max
1 1  10     20  48
1 2  20     21  49
1 3  30     15  50

Answer 1

to write a function, you could do the following:

library(tidyverse)
myfunction= function(x,a,b,column) 
  {
  column <- enquo(column)
  vars <- enquos(a,b)
  x %>% 
    group_by(!!!vars) %>% 
    summarise(Totals=n(),Mnscore=min(!!c),Mxscore=max(!!column))
}

then call this inputing a,b,c as symbols and not characters

myfunction(dataset,a,b,column)

Answer 2

You can use the data.table package if you want a very effective way to solve your problem. Try the following minimal reproducible example.

library(data.table)
set.seed(20191011L)

data <- data.table(
  V1 = letters[sample(3, 20, TRUE)],
  V2 = letters[sample(3, 20, TRUE)],
  V3 = runif(20)
)

fun <- function(data, groups, target){

  data[, .(min=min(get(target)), max=max(get(target))), mget(groups)]

}

fun(data, c("V1", "V2"), "V3")

##     V1 V2        min       max
##  1:  b  c 0.20653948 0.4618063
##  2:  a  a 0.09560888 0.3347064
##  3:  b  b 0.75071480 0.7507148
##  4:  c  a 0.66410519 0.8258410
##  5:  c  c 0.01303751 0.7635212
##  6:  a  b 0.04770186 0.6332439
##  7:  b  a 0.25069813 0.9008885

Answer 3

Try this:

require(dplyr)

result = dataset %>% 
  dplyr::group_by(a,b) %>% 
  dplyr::summarise(Totals = n(),
                   Mnscore = min(c),
                   Mxscore = max(c))

Let me know if it works.