Question

I have a data.frame, d1, that has 7 columns, the 5th through 7th column are supposed to be numeric:

str(d1[5])
'data.frame':   871 obs. of  1 variable:
 $ Latest.Assets..Mns.: num  14008 1483 11524 1081 2742 ... 

is.numeric(d1[5])
[1] FALSE

as.numeric(d1[5])
Error: (list) object cannot be coerced to type 'double'

How can this be? If str identifies it as numeric, how can it not be numeric? I’m importing from CSV.

Answer 1

> is.numeric_data.frame=function(x)all(sapply(x,is.numeric))

> is.numeric_data.frame(d1[[5]])
[1] TRUE 

Why

d1 is a list, hence d1[5] is a list of length 1, and in this case contains a data.frame. to get the data frame, use d1[[5]].

Even if a data frame contains numeric data, it isn’t numeric itself:

> x = data.frame(1:5,6:10)
> is.numeric(x)
[1] FALSE

Individual columns in a data frame are either numeric or not numeric. For instance:

> z <- data.frame(1:5,letters[1:5])

> is.numeric(z[[1]])
[1] TRUE
> is.numeric(z[[2]])
[1] FALSE

If you want to know if ALL columns in a data frame are numeric, you can use all and sapply:

> sapply(z,is.numeric)
    X1.5 letters.1.5. 
    TRUE        FALSE 

> all(sapply(z,is.numeric))
[1] FALSE

> all(sapply(x,is.numeric))
[1] TRUE

You can wrap this all up in a convenient function:

> is.numeric_data.frame=function(x)all(sapply(x,is.numeric))

> is.numeric_data.frame(d1[[5]])
[1] TRUE