how to determine if a character vector is a valid numeric or integer vector

Posted by Andrew Barr on Stack Overflow See other posts from Stack Overflow or by Andrew Barr
Published on 2014-06-09T21:11:13Z Indexed on 2014/06/09 21:24 UTC
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I am trying to turn a nested list structure into a dataframe. The list looks similar to the following (it is serialized data from parsed JSON read in using the httr package).

  myList <- list(object1 = list(w=1, x=list(y=0.1, z="cat")), object2 = list(w=2, x=list(y=0.2, z="dog")))

unlist(myList) does a great job of recursively flattening the list, and I can then use lapply to flatten all the objects nicely.

  flatList <- lapply(myList, FUN= function(object) {return(as.data.frame(rbind(unlist(object))))}) 

And finally, I can button it up using plyr::rbind.fill

  myDF <- do.call(plyr::rbind.fill, flatList)
  str(myDF)

  #'data.frame':    2 obs. of  3 variables:
  #$ w  : Factor w/ 2 levels "1","2": 1 2
  #$ x.y: Factor w/ 2 levels "0.1","0.2": 1 2
  #$ x.z: Factor w/ 2 levels "cat","dog": 1 2

The problem is that w and x.y are now being interpreted as character vectors, which by default get parsed as factors in the dataframe. I believe that unlist() is the culprit, but I can't figure out another way to recursively flatten the list structure. A workaround would be to post-process the dataframe, and assign data types then. What is the best way to determine if a vector is a valid numeric or integer vector?

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