问题
I am working on data that contains more than 300 categorical features that I have factored into 0s and 1s. Now, i need to create a matrix of the features to with frequency of joint occurrence in each cell.
In the end , I am looking to create a heatmap of this frequency matrix.
So, my dataframe in R looks like this:
id cat1 cat2 cat3 cat4
156 0 0 1 1
465 1 1 1 0
573 0 1 1 0
The output I want is:
cat1 cat2 cat3 ...
cat1 0 1 0
cat2 1 0 2
cat3 1 2 0
.
.
where each cell value denotes the number of times the two categorical variables have appeared together.
回答1:
We can use outer
#Since we have only 0's and 1's in column we can directly use &
fun <- function(x, y) sum(df[, x] & df[, y])
#Get all the cat columns
n <- seq_along(df)[-1]
#Apply function to every combination of columns
mat <- outer(n, n, Vectorize(fun))
#Turn diagonals to 0
diag(mat) <- 0
#Assign rownames and column names
dimnames(mat) <- list(names(df)[n], names(df[n]))
# cat1 cat2 cat3 cat4
#cat1 0 1 1 0
#cat2 1 0 2 0
#cat3 1 2 0 1
#cat4 0 0 1 0
回答2:
we can use table
with crossprod
from base R
i1 <- as.logical(unlist(df1[-1]))
out <- crossprod(table(df1$id[row(df1[-1])][i1],
names(df1)[-1][col(df1[-1])]. [i1]))
diag(out) <- 0
out
# cat1 cat2 cat3 cat4
# cat1 0 1 1 0
# cat2 1 0 2 0
# cat3 1 2 0 1
# cat4 0 0 1 0
data
df1 <- structure(list(id = c(156L, 465L, 573L), cat1 = c(0L, 1L, 0L),
cat2 = c(0L, 1L, 1L), cat3 = c(1L, 1L, 1L), cat4 = c(1L,
0L, 0L)), class = "data.frame", row.names = c(NA, -3L))
来源:https://stackoverflow.com/questions/58201529/program-to-obtain-frequency-matrix-of-categorical-data