How to convert data.frame column from Factor to numeric [duplicate]

Answer 1

As an alternative to $dollarsign notation, use a within block:

breast <- within(breast, {
  class <- as.numeric(as.character(class))
})

Note that you want to convert your vector to a character before converting it to a numeric. Simply calling as.numeric(class) will not the ids corresponding to each factor level (1, 2) rather than the levels themselves.

Answer 2

From ?factor:

To transform a factor f to approximately its original numeric values, as.numeric(levels(f))[f] is recommended and slightly more efficient than as.numeric(as.character(f)).

Answer 3

breast$class <- as.numeric(as.character(breast$class))

If you have many columns to convert to numeric

indx <- sapply(breast, is.factor)
breast[indx] <- lapply(breast[indx], function(x) as.numeric(as.character(x)))

Another option is to use stringsAsFactors=FALSE while reading the file using read.table or read.csv

Just in case, other options to create/change columns

 breast[,'class'] <- as.numeric(as.character(breast[,'class']))

or

 breast <- transform(breast, class=as.numeric(as.character(breast)))

Answer 4

This is FAQ 7.10. Others have shown how to apply this to a single column in a data frame, or to multiple columns in a data frame. But this is really treating the symptom, not curing the cause.

A better approach is to use the colClasses argument to read.table and related functions to tell R that the column should be numeric so that it never creates a factor and creates numeric. This will put in NA for any values that do not convert to numeric.

Another better option is to figure out why R does not recognize the column as numeric (usually a non numeric character somewhere in that column) and fix the original data so that it is read in properly without needing to create NAs.

Best is a combination of the last 2, make sure the data is correct before reading it in and specify colClasses so R does not need to guess (this can speed up reading as well).