CODEWITHSUNDEEP
r
PKumar
PKumar

Reputation: 11128

is.numeric and is.numeric option in apply showing different result

I have a dataset which contain some 200 fields and 1000000 of records as per below format:

Acc Field1 Field2 Field3 .....    
101   23   34   78    
102   6    1.2  89    
.
.
.

When I enter command 

apply(dat3[varlist[9]],2,is.numeric)

I get confirmation of field name with TRUE as a result, but when I try to test as is.numeric(dat3[varlist[9]]), I receive a FALSE as a result.

where dat3 is the dataframe on which I am working on and varlist is created using command: 

varlist <- names(dat3)

varlist contains all the list of variables in the data frame.

Attached is the real time screenshot.

I don't understand what I am doing wrong over here.

Any help from anybody is appreciated.

enter image description here

Upvotes: 0

Views: 153

Answers (3)

Jonas Tundo
Jonas Tundo

Reputation: 6207

If you do

varlist <- names(iris)
iris[varlist[1]]

you are defining a new dataframe with the selected column and not the variable itself.

do

iris[,colnames(iris) %in% varlist[1]]
is.numeric( iris[,colnames(iris) %in% varlist[1]])
#[1] TRUE

And try to make a reproducible example next time please

Upvotes: 1

Richie Cotton
Richie Cotton

Reputation: 121187

The standard way to perform tests column by column on a data frame is to use sapply.

sapply(mtcars, is.numeric)
sapply(CO2, is.numeric)

(Try swapping is.numeric for class as well.)

Upvotes: 4

James
James

Reputation: 66874

Using [ on a data.frame in this way will return another (smaller data frame). You need to use [[, or use the multi-index version of [ so that dropping is applied. For example:

class(mtcars[3])
[1] "data.frame"
is.numeric(mtcars[3])
[1] FALSE
is.numeric(mtcars[[3]])
[1] TRUE
is.numeric(mtcars[,3])
[1] TRUE

Upvotes: 2

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