Dear Hadley:
your request for evidence for my observation seems to have paved the way
to solve this issue. As it turns out, the effect I described only occurs
with "data.frames" read in with readxl. Clearly, I missed that these are
tbl_df. And that explains the differential behavior depending on whether
dplyr is loaded or not. Also, I realize that this latter effect can be
avoided by explicitly converting objects read in with readxl to a
data.frame.
Well, I should have known that if i had carefully read the README stuff
for readxl. But then, readxl is so much of an every-day tool for me that
I didn't even think of its involvement in my problem, all the more as
the reference manual does not mention the format/class of objects read
in with readxl.
So my apologies for any confusion I may have caused - and I certainly
did not mean my observation as a charge against dplyr or its authors.
Quite to the contrary, i appreciate thees tools, and as you may see,
tray to understand and use them.
Thank you so much again
Karl
On 04.08.2015 13:14, Hadley Wickham wrote:
No, the effect I described has nothing to do wit USING dplyr. It occurs with
>any (preexisting) data.frame once dplyr is LOADED (require(dplyr). It is
>this silent, sort of "backward acting" effect that disturbs me.
You're going to need to provide some evidence for that charge: dplyr
does not affect the behaviour of data.frames (only tbl_dfs)
Hadley
--
Karl Schilling
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