Readable code with base R (part 1)

startsWith and endsWith for string-matching

There are special base functions for pre- or postfix matching.

# Basic usage:
w <- "Hello World!"
startsWith(w, "Hell")
## [1] TRUE
startsWith(w, "Helo")
## [1] FALSE
endsWith(w, "!")
## [1] TRUE

Of course, it also works with vectors. Can’t remember the exact name of a base function? Try this… 😉

base_funcs <- ls("package:base")

base_funcs[startsWith(base_funcs, "row")]
##  [1] "row"                    "row.names"             
##  [3] "row.names.data.frame"   "row.names.default"     
##  [5] "row.names<-"            "row.names<-.data.frame"
##  [7] "row.names<-.default"    "rowMeans"              
##  [9] "rownames"               "rownames<-"            
## [11] "rowsum"                 "rowsum.data.frame"     
## [13] "rowsum.default"         "rowSums"

The ‘readable’ property really shines when combined with control-flow.

tell_file_type <- function(fn) {
    # Check different file endings
    if (endsWith(fn, "txt")) {
        print("A text file.")
    }
    if (any(endsWith(fn, c("xlsx", "xls")))) {
        print("An Excel file.")
    }
}
tell_file_type("A.txt")
## [1] "A text file."
tell_file_type("B.xls")
## [1] "An Excel file."

The resulting code reads very well.

Filter

Using another nice base function, Filter, the above code can be further improved.

get_file_type <- function(fn) {
  file_endings <- c(text="txt", Excel="xls", Excel="xlsx")  
  Filter(file_endings, f = function(x) endsWith(fn, x))
}

get_file_type("C.xlsx")
##  Excel 
## "xlsx"

Again, very readable to my eyes. It should be noted that for this particular problem using tools::file_ext is even more appropriate, but I think the point has been made.

Last but not least, since Filter works on lists, you can use it on a data.frame as well.

dat <- data.frame(A=1:3, B=5:3, L=letters[1:3])
dat
##   A B L
## 1 1 5 a
## 2 2 4 b
## 3 3 3 c
Filter(dat, f = is.numeric)
##   A B
## 1 1 5
## 2 2 4
## 3 3 3
Filter(dat, f = Negate(is.numeric))  # or Filter(dat, f = function(x) !is.numeric(x))
##   L
## 1 a
## 2 b
## 3 c

That’s it for now – see you in part 2.