Dear Jeff:
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.
Best,
Karl Schilling
On 04.08.2015 12:20, Jeff Newmiller wrote:
I
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
length(df[,1]).
Both commands will return n.
However, once dplyr is loaded,
length(df[,1]) will return a value of 1.
length(df$m1) and also length(df[[1]]) will correctly return n.
I know that using length() may not be the most elegant or efficient way to
get the value of n. However,
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 04 Aug 2015, at 10:50 , Karl Schilling karl.schill...@uni-bonn.de wrote:
Dear All,
I have an observation / question about how the function length() works once
package dplyr is loaded.
Say we have a data.frame df with n rows and m columns. Then a way to get the
number of rows is to
I can confirm that the drop default is different, but keep in mind that it is
only changed for a tbl_df so just convert back to data.frame at the end of your
dplr operations to get back to your familiar data.frame behavior.
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