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sequential row selection in dataframe

3 messages · Pedro Mardones, Michael Kubovy, Greg Snow

Pedro Mardones
# 
Dear all;

I'm wondering if there is any 'efficient' approach for selecting a
sample of 'every nth rows'  from a dataframe. For example, let's use
the dataframe GAGurine in MASS library:
[1] 314

# select an 75% of the dataset, i.e. = 236 rows, every 2 rows starting
from row 1
[1] 157

# so, I still need another 79 rows, one way could be:
test2<-GAGurine[-seq(1,314,2),]
[1] 157
# and then
final<-rbind(test2,test3)
[1] 236

Does anyone have a better idea to get the same results but without
creating different datasets like test2 and test3?

Thanks
PM
Michael Kubovy
#
On Dec 26, 2006, at 12:07 AM, Pedro Mardones wrote:

            

      
      
      
    

        
A probabilistic approach:

len <- length(GAGurine[,1])
GAGu <- GAGurine[sample(1:len, round(.75 * len)), ] # 236 rows

A deterministic one:

nr <- 1 #or 2
GAGu2 <- GAGurine[-seq(nr, len, 4),] # drop every 4th, giving 235 rows
nr <- 3 # or 4
will give 236 rows.
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