Reshape R data with user entries in rows, collapsing for each user

Question

Pardon my new-ness to the R world, thank you kindly in advance for your help.

I would like to analyze the data from an experiment.

The data comes in in Long

Answer 1

There’s a package called tidyr that makes melting and reshaping data frames much easier. In your case, you can use tidyr::spread straightforwardly:

result = spread(df, Item, Resp)

This will however fill missing entries with NA:

  User_id location age gender  A  B  C  D  E  G  H
1       1       CA  22      M  1 -1 -1  1 -1 NA NA
2       2       MD  27      F -1  1  1 NA  1 -1 -1

You can fix this by replacing them:

result[is.na(result)] = 0
result
#   User_id location age gender  A  B  C  D  E  G  H
# 1       1       CA  22      M  1 -1 -1  1 -1  0  0
# 2       2       MD  27      F -1  1  1  0  1 -1 -1

… or by using the fill argument:

result = spread(df, Item, Resp, fill = 0)

For completeness’ sake, the other way round (i.e. reproducing the original data.frame) works via gather (this is usually known as “melting”):

gather(result, Item, Resp, A : H)

— The last argument here tells gather which columns to gather (and it supports the concise range syntax).