Ralf B wrote:
Hi,
I am a beginner in R and have only read a few chapters in the R book,
I was not able to find a solution for this simple problem.
I have an empty data frame:
a=data.frame(name="test")
which I would like to extend in a for-loop (with data extracted from a
database). Ideally I would like to extend the data frame like this:
a["new_1"] = 1:10
a["new_1"] = 1:12
a["new_1"] = 1:14
I would first read all the data into a list (maybe using lapply), where
the columns are the parts of the list. Then you can find out which one
is longest, and add NA's at the end of the other columns, and than use
do.call("cbind", list_of_columns) to get the resulting data.frame:
note that I use apply type of constructs a lot, it is sort of one line
for loop.
# Create a mockup list for this particular example
column_list = lapply(round(runif(5, 1, 10)), function(len_column) {
rep(len_column, times = len_column)
})
# Find the length of the columns in the list
len_columns = sapply(column_list, length)
# add the NA's
dum = lapply(column_list, function(col) {
c(col, rep(NA, max(len_columns) - length(col)))
})
# Make the dataframe
dat = data.frame(do.call("cbind", dum))
it is quite a manual way of doing it, maybe someone else knows of an
available R function to do it. But this is how I would do it.
cheers,
Paul
R now obviously complains about the changing length of the new
columns. However, I would like to have missing values being added
whenever columns are shorter than a newer (longer) column. How can I
do that?
Thanks,
Ralf
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Drs. Paul Hiemstra
Department of Physical Geography
Faculty of Geosciences
University of Utrecht
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