Recent changes to read.spss() in the foreign package return a dataframe
containing additional attributes. For example,
TEMP<-read.spss(choose.files(), to.data.frame=T,use.value.labels=F)
str(TEMP)
`data.frame': 780 obs. of 8 variables:
$ EXPOS01: atomic 1 1 2 1 2 3 2 4 2 1 ...
..- attr(*, "value.labels")= Named num 5 4 3 2 1
.. ..- attr(*, "names")= chr "Yes, experienced it with Extreme
Impact" "Yes, experienced it with Moderate Impact" "Yes, experienced it
with A Little Impact" "Yes, experienced it with No Impact" ...
$ EXPOS02: atomic 1 1 1 1 1 1 1 1 1 1 ...
..- attr(*, "value.labels")= Named num 5 4 3 2 1
.. ..- attr(*, "names")= chr "Yes, experienced it with Extreme
Impact" "Yes, experienced it with Moderate Impact" "Yes, experienced it
with A Little Impact" "Yes, experienced it with No Impact" ...
Unfortunately, these changes may be ahead of their time (certainly ahead
of several functions). For instance edit balks at the changes:
edit(TEMP)
Error in edit.data.frame(TEMP) : can only handle vector and factor
elements
It used to be that the command "as.data.frame" or "data.frame" would
return a fairly basic data.frame and "fix" the problem. However, this
does not work (obviously because TEMP is already a data.frame). For
example,
TEMP<-as.data.frame(TEMP)
edit(TEMP)
Error in edit.data.frame(TEMP) : can only handle vector and factor
elements
It is possible to use "as.matrix", and then "data.frame" the result of
"as.matrix", but this gets a bit cumbersome.
The question is: Is there a simple command to strip additional
attribute characteristics from a data.frame and get a simple, easy to
use, uncomplicated data.frame?
On a related note, do other users routinely use read.spss with the
defaults of "to.data.frame=F" or "use.value.labels=T"? My experience
is that I am always using the non-default values in which case it would
be helpful to change the defaults to "to.data.frame=T" and
"use.value.labels=F". It would also probably make sense to change the
default for "trim.factor.names=T". Interested in others' perspective.
Appreciate all the great work Saikat DebRoy has done...just trying to
improve an already useful function.
Paul
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