On Wed, 28 Jan 2009, Mark Na wrote:
Hi R-helpers,
I've been struggling with a problem for most of the day (!) so am finally
resorting to R-help.
I would like to subset the columns of my dataframe based on the frequency
with which the columns contain non-zero values. For example, let's say that
I want to retain only those columns which contain non-zero values in at
least 1% of their rows.
In Excel I would calculate a row at the bottom of my data sheet and use the
following function
=countif(range,">0")
to identify the number of non-zero cells in each column. Then, I would
divide that by the number of rows to obtain the frequency of non-zero values
in each column. Then, I would delete those columns with frequencies < 0.01.
But, I'd like to do this in R. I think the missing link is an analog to
Excel's countif function. Any ideas?
Use something like
DF[sapply(DF, function(x) mean(x) >= 0.01)]
Since logical values are converted to 0/1, mean() gives the frequency
(and sum() the count).
Thanks! Mark
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Brian D. Ripley, rip...@stats.ox.ac.uk
Professor of Applied Statistics, http://www.stats.ox.ac.uk/~ripley/
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