防止将数字转换为因子

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?

Answer 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 .