Convert data.frame column format from character to factor

I would like to change the format (class) of some columns of my data.frame object (mydf) from charactor to factor.

I don't want to do this when I'm reading the text file by read.table() function.

Any help would be appreciated.

Hi welcome to the world of R.

mtcars  #look at this built in data set
str(mtcars) #allows you to see the classes of the variables (all numeric)

#one approach it to index with the $ sign and the as.factor function
mtcars$am <- as.factor(mtcars$am)
#another approach
mtcars[, 'cyl'] <- as.factor(mtcars[, 'cyl'])
str(mtcars)  # now look at the classes

This also works for character, dates, integers and other classes

Since you're new to R I'd suggest you have a look at these two websites:

R reference manuals: http://cran.r-project.org/manuals.html

R Reference card: http://cran.r-project.org/doc/contrib/Short-refcard.pdf

# To do it for all names
df[] <- lapply( df, factor) # the "[]" keeps the dataframe structure

# to do it for some names in a vector named 'col_names'
col_names <- names(df)
df[col_names] <- lapply(df[col_names] , factor)

Explanation. All dataframes are lists and the results of [ used with multiple valued arguments are likewise lists, so looping over lists is the task of lapply. The above assignment will create a set of lists that the function data.frame.[<- should successfully stick back into into the dataframe, df

Another strategy would be to convert only those columns where the number of unique items is less than some criterion, let's say fewer than the log of the number of rows as an example:

cols.to.factor <- sapply( df, function(col) length(unique(col)) < log10(length(col)) )
df[ cols.to.factor] <- lapply(df[ cols.to.factor] , factor)

You could use dplyr::mutate_if() to convert all character columns or dplyr::mutate_at() for select named character columns to factors:

library(dplyr)

# all character columns to factor:
df <- mutate_if(df, is.character, as.factor)

# select character columns 'char1', 'char2', etc. to factor:
df <- mutate_at(df, vars(char1, char2), as.factor)

If you want to change all character variables in your data.frame to factors after you've already loaded your data, you can do it like this, to a data.frame called dat:

character_vars <- lapply(dat, class) == "character"
dat[, character_vars] <- lapply(dat[, character_vars], as.factor)

This creates a vector identifying which columns are of class character, then applies as.factor to those columns.

Sample data:

dat <- data.frame(var1 = c("a", "b"),
                  var2 = c("hi", "low"),
                  var3 = c(0, 0.1),
                  stringsAsFactors = FALSE
                  )

Another short way you could use is a pipe (%<>%) from the magrittr package. It converts the character column mycolumn to a factor.

library(magrittr)

mydf$mycolumn %<>% factor

I've doing it with a function. In this case I will only transform character variables to factor:

for (i in 1:ncol(data)){
	if(is.character(data[,i])){
		data[,i]=factor(data[,i])
	}
}

Unless you need to identify the columns automatically, I found this to be the simplest solution:

df$name <- as.factor(df$name)

This makes column name in dataframe df a factor.

You can use across with new dplyr 1.0.0

library(dplyr)

df <- mtcars 
#To turn 1 column to factor
df <- df %>% mutate(cyl = factor(cyl))

#Turn columns to factor based on their type. 
df <- df %>% mutate(across(where(is.character), factor))

#Based on the position
df <- df %>% mutate(across(c(2, 4), factor))

#Change specific columns by their name
df <- df %>% mutate(across(c(cyl, am), factor))