我的函数中的循环不会改变我的数据类型（在 R 中）

Question

I intend to use a function to save me typing work for repetitive procedures. Many things are already working but not everything is working yet. Here is the code:

quicky <- function(df, factors){
      output <- as.character(substitute(factors)[-1])
      print(output)
      df[,output]
      for(i in names(df[,output])){
        hist(df[,as.character(i)])
        df[,as.character(i)] <- as.factor(df[,as.character(i)])#<- Why does this not work?
      }
    }

quicky(mtcars, c(cyl,hp,drat))

Request for help and explanation! Thanks in advance.

Answer 1

As we are looping over the column names created from 'output', just looping over those instead of further subsetting the data and getting te names . Also, in the function, return the dataset at the end

quicky <- function(df, factors){
      output <- as.character(substitute(factors)[-1])
      print(output)
     for(i in output){               
          df[[i]] <- as.factor(df[[i]])
           }

           df

    }

out <- quicky(mtcars, c(cyl,hp,drat))
str(out)
#'data.frame':  32 obs. of  11 variables:
# $ mpg : num  21 21 22.8 21.4 18.7 18.1 14.3 24.4 22.8 19.2 ...
# $ cyl : Factor w/ 3 levels "4","6","8": 2 2 1 2 3 2 3 1 1 2 ...  ###
# $ disp: num  160 160 108 258 360 ...
# $ hp  : Factor w/ 22 levels "52","62","65",..: 11 11 6 11 15 9 20 2 7 13 ...###
# $ drat: Factor w/ 22 levels "2.76","2.93",..: 16 16 15 5 6 1 7 11 17 17 ...###
# $ wt  : num  2.62 2.88 2.32 3.21 3.44 ...
# $ qsec: num  16.5 17 18.6 19.4 17 ...
# $ vs  : num  0 0 1 1 0 1 0 1 1 1 ...
# $ am  : num  1 1 1 0 0 0 0 0 0 0 ...
# $ gear: num  4 4 4 3 3 3 3 4 4 4 ...
# $ carb: num  4 4 1 1 2 1 4 2 2 4 ...

NOTE: Changed the [ to [[ so that it works with data.table and tbl_df

Answer 2

The reason quickly is failing to return the results of assignments to the columns of df is a peculiar feature of an R for -loop. It returns NULL. And the last function that was evaluated within your quicky function was for . So all you need to do is add a call to the value of df outside of the loop:

quicky <- function(df, factors){
    output <- as.character(substitute(factors)[-1])
    print(output)
    df[,output]
    for(i in names(df[,output])){
        hist(df[,as.character(i)])
        df[, i] <- as.factor(df[, i ])
    }; df  # add a call to evaluate `df` 
}

str( quicky(mtcars, c(cyl,hp,drat)) )
#-------
[1] "cyl"  "hp"   "drat"
'data.frame':   32 obs. of  11 variables:
 $ mpg : num  21 21 22.8 21.4 18.7 18.1 14.3 24.4 22.8 19.2 ...
 $ cyl : Factor w/ 3 levels "4","6","8": 2 2 1 2 3 2 3 1 1 2 ...
 $ disp: num  160 160 108 258 360 ...
 $ hp  : Factor w/ 22 levels "52","62","65",..: 11 11 6 11 15 9 20 2 7 13 ...
 $ drat: Factor w/ 22 levels "2.76","2.93",..: 16 16 15 5 6 1 7 11 17 17 ...
 $ wt  : num  2.62 2.88 2.32 3.21 3.44 ...
 $ qsec: num  16.5 17 18.6 19.4 17 ...
 $ vs  : num  0 0 1 1 0 1 0 1 1 1 ...
 $ am  : num  1 1 1 0 0 0 0 0 0 0 ...
 $ gear: num  4 4 4 3 3 3 3 4 4 4 ...
 $ carb: num  4 4 1 1 2 1 4 2 2 4 ..

This behavior of for is in contrast to most other functions in R. With a for-loop, the evaluations and assignments done within it typically become effective outside the for -loop body, ie in the calling environment, but the function call itself returns NULL. Most other functions have no effect outside their function body environments which then requires the programmer to assign the returned value to a named object if any lasting effect is desired. (You should, of course, not expect the value of mtcars to be affected by that action.)