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Reformatting a data table to enter column names in row names

I have data.table in R

 > dt SAMPLE junction count 1: R1 a 1 2: R2 a 1 3: R3 b 1 4: R3 a 1 5: R1 c 2

Now I want to "reformat" the data table to form the data frame m (basically, going through the selection matrix with an index for the corresponding counter value). Also note that for pairs (SAMPLE,junction) that do not exist in dt , I assume that the corresponding count value is zero . Can someone help me how to achieve this?

 > m R1 R2 R3 a 1 1 1 b 0 0 1 c 2 0 0
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2 answers

dcast from data.table changes the data set from the format "long" to "wide".

 library(data.table)#v1.9.5+ dcast(dt, junction~SAMPLE, value.var='count', fill=0) # junction R1 R2 R3 #1: a 1 1 1 #2: b 0 0 1 #3: c 2 0 0

If you need matrix output

 library(reshape2) acast(dt, junction~SAMPLE, value.var='count', fill=0) # R1 R2 R3 #a 1 1 1 #b 0 0 1 #c 2 0 0

Or xtabs from base R

  xtabs(count~junction+SAMPLE, dt)
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Alternative approach using spread from tidyr :

 library(tidyr) spread(dt, SAMPLE, count, fill=0) # junction R1 R2 R3 #1: a 1 1 1 #2: b 0 0 1 #3: c 2 0 0

Or an old school solution with reshape from stats :

 reshape(dt, timevar='SAMPLE', idvar=c('junction'), direction='wide') # junction count.R1 count.R2 count.R3 #1: a 1 1 1 #2: b NA NA 1 #3: c 2 NA NA

Data:

 dt = structure(list(SAMPLE = c("R1", "R2", "R3", "R3", "R1"), junction = c("a", "a", "b", "a", "c"), count = c(1, 1, 1, 1, 2)), .Names = c("SAMPLE", "junction", "count"), row.names = c(NA, -5L), class = c("data.table", "data.frame"), .internal.selfref = <pointer: 0x05e924a0>)
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