README.md

NOTE: This is a toy package created for expository purposes by Jenny Bryan, and edited by Nivretta Thatra for Stat 545 2016. It is not meant to actually be useful. If you want a package for factor handling, please see forcats.

foofactors

Factors are a very useful type of variable in R, but they can also drive you nuts. This package provides some helper functions for the care and feeding of factors.

Installation

library(tidyverse)
library("devtools")
devtools::install_github("nivretta/foofactors")

Quick demo

Keeping order of levels via givenorder():

library(foofactors)
#> 
#> Attaching package: 'foofactors'
#> The following object is masked from 'package:base':
#> 
#>     character
z <- factor(c("b", "c", "a", "e", "b"))

Normally the levels will be ordered alphabetically.

factor(z)
#> [1] b c a e b
#> Levels: a b c e

Sometimes you'd like to maintain the order levels in which they appear in the data.

givenorder(z)
#> [1] b c a e b
#> Levels: b c a e

Change some factors to characters via character():

Check for factors where number of unique values = length, and change to character.

m <- factor(c("a", "b", "c", "d"))
class(m)
#> [1] "factor"

m_character <- character(m)
class(m_character)
#> [1] "character"

Otherwise print nochange.

n <- factor(c("a", "b", "c", "d", "a"))
class(n)
#> [1] "factor"

character(n)
#> [1] "NOCHANGE"

Jenny's given functions

Binding two factors via fbind():

a <- factor(c("character", "hits", "your", "eyeballs"))
b <- factor(c("but", "integer", "where it", "counts"))

Simply catenating two factors leads to a result that most don't expect.

c(a, b)
#> [1] 1 3 4 2 1 3 4 2

The fbind() function glues two factors together and returns factor.

fbind(a, b)
#> [1] character hits      your      eyeballs  but       integer   where it 
#> [8] counts   
#> Levels: but character counts eyeballs hits integer where it your

Often we want a table of frequencies for the levels of a factor. The base table() function returns an object of class table, which can be inconvenient for downstream work. Processing with as.data.frame() can be helpful but it's a bit clunky.

set.seed(1234)
x <- factor(sample(letters[1:5], size = 100, replace = TRUE))
table(x)
#> x
#>  a  b  c  d  e 
#> 25 26 17 17 15
as.data.frame(table(x))
#>   x Freq
#> 1 a   25
#> 2 b   26
#> 3 c   17
#> 4 d   17
#> 5 e   15

The freq_out() function returns a frequency table as a well-named tbl_df:

freq_out(x)
#> # A tibble: 5 × 2
#>        x     n
#>   <fctr> <int>
#> 1      a    25
#> 2      b    26
#> 3      c    17
#> 4      d    17
#> 5      e    15