R Assign (or copy) column classes from a data fram

问题:

I produced a large data frame (1700+obs,159 variables) with a function that collects info from a website. Usually, the function finds numeric values for some columns, and thus they're numeric. Sometimes, however, it finds some text, and converts the whole column to text. I have one df whose column classes are correct, and I would like to "paste" those classes to a new, incorrect df. Say, for example:

dfCorrect<-data.frame(x=c(1,2,3,4),y=as.factor(c("a","b","c","d")),z=c("bar","foo","dat","dot"),stringsAsFactors = F)
str(dfCorrect)
'data.frame':   4 obs. of  3 variables:
 $ x: num  1 2 3 4
 $ y: Factor w/ 4 levels "a","b","c","d": 1 2 3 4
 $ z: chr  "bar" "foo" "dat" "dot"

## now I have my "wrong" data frame:
dfWrong<-as.data.frame(sapply(dfCorrect,paste,sep=""))
str(dfWrong)
'data.frame':   4 obs. of  3 variables:
 $ x: Factor w/ 4 levels "1","2","3","4": 1 2 3 4
 $ y: Factor w/ 4 levels "a","b","c","d": 1 2 3 4
 $ z: Factor w/ 4 levels "bar","dat","dot",..: 1 4 2 3

I wanted to copy the classes of each column of dfCorrect into dfWrong, but haven't found how to do it properly. I've tested:

dfWrong1<-dfWrong
dfWrong1[0,]<-dfCorrect[0,]
str(dfWrong1) ## bad result
'data.frame':   4 obs. of  3 variables:
 $ x: Factor w/ 4 levels "1","2","3","4": 1 2 3 4
 $ y: Factor w/ 4 levels "a","b","c","d": 1 2 3 4
 $ z: Factor w/ 4 levels "bar","dat","dot",..: 1 4 2 3

dfWrong1<-dfWrong
str(dfWrong1)<-str(dfCorrect)
'data.frame':   4 obs. of  3 variables:
 $ x: num  1 2 3 4
 $ y: Factor w/ 4 levels "a","b","c","d": 1 2 3 4
 $ z: chr  "bar" "foo" "dat" "dot"
Error in str(dfWrong1) <- str(dfCorrect) : 
  could not find function "str<-"

With this small matrix I could go by hand, but what about larger ones? Is there a way to "copy" the classes from one df to another without having to know the individual classes (and indexes) of each column?

Expected final result (after properly "pasting" classes):

all.equal(sapply(dfCorrect,class),sapply(dfWrong,class))
[1] TRUE

Thanks,

回答1:

You could try this:

dfWrong[] <- mapply(FUN = as,dfWrong,sapply(dfCorrect,class),SIMPLIFY = FALSE)

...although my first instinct is to agree with Oliver that if it were me I'd try to ensure the correct class at the point you're reading the data.