Boya-
table() is the function that does what you want:
cdat = data.frame(membership=rep(1:3,rep(3,3)),
+ label=as.character(c(0,0,1,0,1,1,1,1,1)))
table(cdat)
label
membership 0 1
1 2 1
2 1 2
3 0 3
From there, you can rearrange it in a variety of ways:
as.data.frame(table(cdat))
membership label Freq
1 1 0 2
2 2 0 1
3 3 0 0
4 1 1 1
5 2 1 2
6 3 1 3
Or, to conform with your request
reshape(as.data.frame(table(cdat)),idvar='membership',
+ v.names='Freq',timevar='label',direction='wide')
membership Freq.0 Freq.1
1 1 2 1
2 2 1 2
3 3 0 3
- Phil Spector
Statistical Computing Facility
Department of Statistics
UC Berkeley
spec...@stat.berkeley.edu
On Wed, 21 Jul 2010, Boya Sun wrote:
Dear R experts,
I have a labeled data set. Each data is assigned a binary label 0 or 1.
Assume that I use some clustering algorithm to group the data by clusters
(using some features of the data). Now I want to know how many data are
labeled as 0/1 in each cluster.
For example, assume that I have 9 labeled data grouped into three clusters.
The ids of the clusters are 1, 2, and 3. The dataset is represented by the
following matrix:
membership Label
d1 1 0
d2 1 0
d3 1 1
d4 2 0
d5 2 1
d6 2 1
d7 3 1
d8 3 1
d9 3 1
Now I want to get the following output, telling me how many data are labeled
as 0 and 1 in each cluster
cluster_id 0-data 1-data
1 2 1
2 1 2
3 0 3
The output does not have to be a matrix, it could be a summary of the
statistics.
How should I approach this problem? What R functions should I use to get
such information?
Thanks so much!
Boya
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