Converting R contingency tables to data frames

August 11, 2010
By

(This article was first published on Computational Ecology, and kindly contributed to R-bloggers)

A contingency table presents the joint density of one or more
categorical variables. Each entry in a contingency table is a count
of the number of times a particular set of factors levels occurs in
the dataset. For example, consider a list of plant species where
each species is assigned a relative seed size (small, medium, or
large) and a growth form (tree, shrub, or herb).

seed.sizes <- c("small", "medium", "large")
growth.forms <- c("tree", "shrub", "herb")
species.traits <- data.frame(
  seed.size = seed.sizes,
  growth.form = growth.forms
)
seed.size growth.form
small herb
small herb
small shrub
small shrub
small tree
medium shrub
medium shrub
medium herb
medium tree
large tree
large tree
large tree

A contingency table will tell us how many times each combination of
seeds.sizes and growth.forms occur.

tbl <- table(species.traits)
herb shrub tree
0 0 3
1 2 1
2 2 1

The output contingency table are of class table. The behaviour of
these objects is not quite like a data frame. In fact, trying to
convert them to a data frame gives a non-intuitive result.

as.data.frame(tbl)
seed.size growth.form Freq
large herb 0
medium herb 1
small herb 2
large shrub 0
medium shrub 2
small shrub 2
large tree 3
medium tree 1
small tree 1

Coercion of the table into a data frame puts each factor of the
contingency table into its own column along with the frequency,
rather than keeping the same structure as original table object.
If we wanted to turn the table into a data frame keeping the
original structure we use as.data.frame.matrix. This function is
not well-documented in R, and this is probably the only situation in
which it would be used. But, it works.

as.data.frame.matrix(tbl)
herb shrub tree
0 0 3
1 2 1
2 2 1

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