I have a categorical data set that looks similar to:
A < -data.frame(animal = c(\"cat\",\"cat\",\"cat\",\"dog\",\"dog\",\"dog\",\"elephant\",\"elephant\",
In a vein similar to how agstudy did it, I'd present the 'tidyverse' way of presenting the ordering:
A$animal <- factor(A$animal, levels = c("dog", "elephant","cat"))
A$color <- factor(A$color, levels = c("green", "blue", "red"))
Then we load dplyr
or the whole tidyverse
and can do
arrange(A, animal, color)
or simply
A %>% arrange(animal, color)
where %>%
is the 'pipe' operator in r, and can be accessed by using Ctrl
+ Shift
+ m
One other thing worth noting - you don't have to convert the class to do this. You can simply order by the factor of the variable. Thus preserving as eg character class within the existing data structure, if that is desired.
so eg, using the example above:
A[order(factor(A$animal, levels = c("dog", "elephant","cat")) ,factor(A$color, levels = c("green", "blue", "red"))),]
Depends on whether conservation of class is important. This would be a much more typical use case for me personally. HTH
The levels should be specified explicitly:
A$animal <- factor(A$animal, levels = c("dog", "elephant","cat"))
A$color <- factor(A$color, levels = c("green", "blue", "red"))
Then you order by the 2 columns simultaneously:
A[order(A$animal,A$color),]
# animal color
# 6 dog green
# 4 dog blue
# 5 dog red
# 9 elephant green
# 7 elephant blue
# 8 elephant red
# 3 cat green
# 1 cat blue
# 2 cat red
You can also use match
- you do not alter column class neither do a factor
transformation.
animalOrder = c("dog", "elephant","cat")
colorOrder = c("green", "blue", "red")
A[ order(match(A$animal, animalOrder), match(A$color, colorOrder)), ]
animal color
6 dog green
4 dog blue
5 dog red
9 elephant green
7 elephant blue
8 elephant red
3 cat green
1 cat blue
2 cat red