Prevent a numeric from being converted into a factor

Question

I'm building a table from a CSV file. When the file is initially loaded I need to load as characters.

datset <- read.csv("outcome-of-care-measures.csv", colClasses = "character")

I have function to convert a factor containing number (from other stack q)

as.numeric.factor <- function(x) {as.numeric(levels(x))[x]}

I clean up the file with

i<-17
datset[datset=="Not Available"]<-NA
datset<-datset[complete.cases(datset[,i]),]
x<- as.numeric.factor(datset[, i])

The datset table contains lots of columns I don't need so I build a new table :

dat <- data.frame(cbind("HospitalName"= datset[,2], "State"= datset[,7],"Rating" = x))

My problem is that even though x is numeric, it gets turned into a factor when loaded to the dataframe. I can verify this from debug mode with :

class(x)
"Numeric"

class(dat[,3])
"Factor"

In later code I'm trying to sort the Rating column but it's failing due it being a factor - I guess.

I've even tried appending stringsAsFactors = FALSE to read.csv but this has no effect.

How can I prevent x from being converted into a factor when loading to a DF?

Why don't you use the appropriate arguments in read.csv instead? There is an na.strings argument and you could import the column as numeric. — Roland
– Roland, Commented Aug 22, 2014 at 15:21
I am not able to reproduce the error when x <- factor(1:10): after transformation with as.numeric.factor and putting it in a data frame, it remains a numeric. @Henrik's comment is, I think, right on where there is a problem: what happens when you remove cbind? — Vincent Guillemot
– Vincent Guillemot, Commented Aug 22, 2014 at 15:24
In addition to the comment of @Roland, I think the data.frame(cbind step is problematic. The cbind step results in a matrix. A matrix can only hold type of values (see coercion hierarchy in the Value section of ?matrix). When you then apply data.frame on a character matrix, values are converted to factor (see stringsAsFactors argument in ?data.frame). See also options; stringsAsFactors. — Henrik
– Henrik, Commented Aug 22, 2014 at 15:24
Pay attention to Henrik. Note the examples in ?data.frame, which allow for constructs like data.frame(x = ...,y = ...), which is how you should be using the function. data.frame(cbind()) is a very bad habit. — joran
– joran, Commented Aug 22, 2014 at 15:27
@LeeH You don't have to specify the col classes (read.csv can do this automatically), but you could: colclasses <- rep("character, 40); colclasses[7] <- "numeric" — Roland
– Roland, Commented Aug 22, 2014 at 15:28

joran · Accepted Answer · 2014-08-22 15:48:45Z

1

As Henrik explained in his comment, this:

dat <- data.frame(cbind("HospitalName"= datset[,2], "State"= datset[,7],"Rating" = x))

is a poor way to construct a data frame. cbind converts everything to a matrix, which can only hold a single data type. Hence the coercion.

It would be better to do:

dat <- data.frame(HospitalName = dataset[,2],state = dataset[,7],rating = x)

However, it is also true as Roland mentioned that you should be able to specify this one column to be numeric when reading the data in via:

colclasses <- rep("character", 40)
colclasses[7] <- "numeric"

and then passing that in read.csv.

answered Aug 22, 2014 at 15:48

joran

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1 Comment

Thanks @joran. I'm still getting to grips with the class system in R. I understand completely where I was going wrong thanks to eloquent explanation