What does the dot mean in R – personal preference, naming convention or more?

by

A dot in function name can mean any of the following:

  • nothing at all
  • a separator between method and class in S3 methods
  • to hide the function name

Possible meanings

1. Nothing at all

The dot in data.frame doesn’t separate data from frame, other than visually.

2. Separation of methods and classes in S3 methods

plot is one example of a generic S3 method. Thus plot.lm and plot.glm are the underlying function definitions that are used when calling plot(lm(...)) or plot(glm(...))

3. To hide internal functions

When writing packages, it is sometimes useful to use leading dots in function names because these functions are somewhat hidden from general view. Functions that are meant to be purely internal to a package sometimes use this.

In this context, “somewhat hidden” simply means that the variable (or function) won’t normally show up when you list object with ls(). To force ls to show these variables, use ls(all.names=TRUE). By using a dot as first letter of a variable, you change the scope of the variable itself. For example:

x <- 3
.x <- 4

ls()
[1] "x"

ls(all.names=TRUE)
[1] ".x" "x" 

x
[1] 3
.x
[1] 4

4. Other possible reasons

In Hadley’s plyr package, he uses the convention to use leading dots in function names. This as a mechanism to try and ensure that when resolving variable names, the values resolve to the user variables rather than internal function variables.

Complications

This mishmash of different uses can lead to very confusing situations, because these different uses can all get mixed up in the same function name.

For example, to convert a data.frame to a list you use as.list(..)

as.list(iris)

In this case as.list is a S3 generic method, and you are passing a data.frame to it. Thus the S3 function is called as.list.data.frame:

> as.list.data.frame
function (x, ...) 
{
    x <- unclass(x)
    attr(x, "row.names") <- NULL
    x
}
<environment: namespace:base>

And for something truly spectacular, load the data.table package and look at the function as.data.table.data.frame:

> library(data.table)

> methods(as.data.table)
[1] as.data.table.data.frame* as.data.table.data.table* as.data.table.matrix*    

   Non-visible functions are asterisked


> data.table:::as.data.table.data.frame
function (x, keep.rownames = FALSE) 
{
    if (keep.rownames) 
        return(data.table(rn = rownames(x), x, keep.rownames = FALSE))
    attr(x, "row.names") = .set_row_names(nrow(x))
    class(x) = c("data.table", "data.frame")
    x
}
<environment: namespace:data.table>

More Related Contents:

  1. Faster ways to calculate frequencies and cast from long to wide
  2. Reshape three column data frame to matrix (“long” to “wide” format) [duplicate]
  3. Why does summarize or mutate not work with group_by when I load `plyr` after `dplyr`?
  4. How to select the rows with maximum values in each group with dplyr? [duplicate]
  5. Group by multiple columns and sum other multiple columns
  6. How to create a lag variable within each group?
  7. Why are my dplyr group_by & summarize not working properly? (name-collision with plyr)
  8. Unique rows, considering two columns, in R, without order
  9. Remove group from data.frame if at least one group member meets condition
  10. Idiomatic R code for partitioning a vector by an index and performing an operation on that partition
  11. dplyr summarise: Equivalent of “.drop=FALSE” to keep groups with zero length in output
  12. dplyr: “Error in n(): function should not be called directly”
  13. Aggregate a data frame based on unordered pairs of columns
  14. Count number of rows by group using dplyr
  15. How to strsplit different number of strings in certain column by do function
  16. Change value of variable with dplyr
  17. Do you use attach() or call variables by name or slicing?
  18. How to get top n companies from a data frame in decreasing order
  19. Returning first row of group
  20. Split Data Frame into Rows of Fixed Size
  21. R: Split unbalanced list in data.frame column
  22. Get the means of sub groups of means in R
  23. meaning of ddply error: ‘names’ attribute [9] must be the same length as the vector [1]
  24. Standard error bars using stat_summary
  25. Replace missing values (NA) in one data set with values from another where columns match
  26. R use ddply or aggregate
  27. Sum of rows based on column value
  28. ddply for sum by group in R
  29. Can `ddply` (or similar) do a sliding window?
  30. R – Faster Way to Calculate Rolling Statistics Over a Variable Interval

Leave a Comment