Recoding Categorical Variable

[Kayla]

I have a mutated categorical variable to perform an ANOVA. It is a factor with 6 levels. I am trying to make those 6 levels be only 2 levels: "Low" and "High" or 1 and 2.

sleepdata_complete <- mutate(sleepdata_complete,
qualslp = as.factor(qualslp),
qualslp = fct_recode(qualslp,
"V Poor" = "1",
"Poor" = "2",
"Fair" = "3",
"Good" = "4",
"V Good" = "5",
"Excel" = "6"))

This is what I currently have. Is there any way to change this? thank you!

[williaml]

Hi, you could use case_when. It would be something like this. To make it easier for everyone, you should provide a reproducible example next time.

library(dplyr)

sleepdata_complete <- mutate(sleepdata_complete,
                             qualslp = as.factor(qualslp),
                             qualslp2 = case_when(qualslp %in% c("V Poor", "Poor", "Fair") ~ "Low",
                                                  TRUE ~ "High")) %>%
  mutate(qualslp2 = factor(qualslp2, levels = c("Low", "High")))
  

FAQ: How to do a minimal reproducible example ( reprex ) for beginners

A minimal reproducible example consists of the following items: A minimal dataset, necessary to reproduce the issue The minimal runnable code necessary to reproduce the issue, which can be run on the given dataset, and including the necessary information on the used packages. Let's quickly go over each one of these with examples: Minimal Dataset (Sample Data) You need to provide a data frame that is small enough to be (reasonably) pasted on a post, but big enough to reproduce your issue. Let's say, as an example, that you are working with the iris data frame head(iris) #> Sepal.Length Sepal.Width Petal.Length Petal.Width Species #> 1 5.1 3.5 1.4 0.…

A general vectorised if — case_when