How to form groups for this specific problem?

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

        [[alternative HTML version deleted]]

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

        [[alternative HTML version deleted]]

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 <
satish.vadlamani at gmail.com> wrote:

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

        [[alternative HTML version deleted]]

Jean:
Wow. Thank you so much for this. I will read up igraph and then see if
this is going to work for me for the larger dataset.

Thanks for the wonderful snippet code you wrote. Basically, the
requirement is this:
TLA1 (Top Level Assembly) and its components should belong to the same
group. If a component belongs to a different TLA (say TLA2), then that TLA1
and all of its components should belong to the same as that of TLA1.

Are these types of questions appropriate for this group?

Thanks,
Satish


On Mar 28, 2016 9:10 AM, "Adams, Jean" <jvadams at usgs.gov> wrote:

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 <
satish.vadlamani at gmail.com> wrote:

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

        [[alternative HTML version deleted]]