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complex table
2 messages · Michael Anyadike-Danes, Jacques VESLOT
it is not perfectly clear for me, but you could try :
DF[,1:72] <- as.data.frame(lapply(DF[,1:72], factor, levels=1:6))
lapply(split(DF, DF$cluster), function(x) apply(x[,-73], 2, table))
lapply(split(DF, DF$cluster), function(x) { x11() ;
barplot(apply(x[,-73], 2, table)) })
lapply(split(DF, DF$cluster), function(x) { x11() ;
barplot(apply(x[,-73], 2, table), beside=T) })
Michael Anyadike-Danes a Âécrit :
I have a data table with 712 cases (rows) describing young people’s activities for 72 months each case has been classified into one of 5 clusters. The first 72 columns are monthly activities coded 1 to 6 (e.g. school =1) and the 73rd column is the cluster number of the case. I wish to summarise the distribution of monthly activities by cluster e.g for cluster 1: 6 months school; 24 further education; etc. After looking through available resources my solution is quite complex involving – amongst other things a series of loops. I’m sure there is a quicker and simpler way (manipulating table or xtabs) but I just can’t see how to do it. Any advice? Michael Anyadike-Danes [[alternative HTML version deleted]] ------------------------------------------------------------------------
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