How to form groups for this specific problem?

Satish,

If you rearrange your data into a network of nodes and edges, you can use
the igraph package to identify disconnected (mutually exclusive) groups.

# example data
df <- data.frame(
  Component = c("C1", "C2", "C1", "C3", "C4", "C5"),
  TLA = c("TLA1", "TLA1", "TLA2", "TLA2", "TLA3", "TLA3")
)

# characterize data as a network of nodes and edges
nodes <- levels(unlist(df))
edges <- apply(df, 2, match, nodes)

# use the igraph package to identify disconnected groups
library(igraph)
g <- graph(edges)
ngroup <- clusters(g)$membership
df$Group <- ngroup[match(df$Component, nodes)]
df

  Component  TLA Group
1        C1 TLA1     1
2        C2 TLA1     1
3        C1 TLA2     1
4        C3 TLA2     1
5        C4 TLA3     2
6        C5 TLA3     2

Jean

On Sun, Mar 27, 2016 at 7:56 PM, Satish Vadlamani <

Hello All:
I would like to get some help with the following problem and understand how
this can be done in R efficiently. The header is given in the data frame.

*Component, TLA*
C1, TLA1
C2, TLA1
C1, TLA2
C3, TLA2
C4, TLA3
C5, TLA3

Notice that C1 is a component of TLA1 and TLA2.

I would like to form groups of mutually exclusive subsets and create a new
column called group for this subset. For the above data, the subsets and
the new group column value will be like so:

*Component, TLA, Group*
C1, TLA1, 1
C2, TLA1, 1
C1, TLA2, 1
C3, TLA2, 1
C4, TLA3, 2
C5, TLA3, 2

Appreciate any help on this. I could have looped through the observations
and tried some logic but I did not try that yet.

--

Satish Vadlamani

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