Convert data.frame column format from character to factor

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)