How to declare this R CSV data as numerical? I added spaces around my fields in CSV file in Vim csv.vim plugin. Now, I am having difficulties in declaring the column classes as numerical (`num` etc). Having negative values there also cause problems in the following columns The data can have empty fields. Data `data.csv` Test, test2, test3 , 1 , 1 10.8, -1 , 1 1.1 , 2 , 2 Code library('methods') DF <- read.csv("/home/masi/Data/data.csv", header = T, sep = ",", colClasses=c('num','num')) DF Output Error in methods::as(data[[i]], colClasses[i]) : no method or default for coercing “character” to “num” Calls: read.csv -> read.table -> <Anonymous> Execution halted * Casting to numerical fails when doing `colClasses=c('num','num')`. * Output in Column 3 is considered as `NA` because of one minus mark (`-1`) in the second column. R: 3.3.3

AFAIK `num` is not a valid _atomic vector class_ in `R`:

> Possible values are NA (the default, when type.convert is used), "NULL" (when the column is skipped), **one of the atomic vector classes (logical, integer, numeric, complex, character, raw)** , or "factor", "Date" or "POSIXct". Otherwise there needs to be an as method (from package methods) for conversion from "character" to the specified formal class.

Your code should work if you replace it by `numeric`:


> DF <- read.csv("data.csv", header = T, sep = ",", colClasses=c('num','num'))Error in methods::as(data[[i]], colClasses[i]) :
no method or default for coercing “character” to “num”


whereas


> DF <- read.csv("data.csv", header = T, sep = ",", colClasses=c('numeric','numeric'))
>
> DF
Test test2 test3
1 NA 1 1
2 10.8 -1 1
3 1.1 2 2
>