Dgdrxrt

I have a dataframe which consists of two columns with categorical variables (Better, Similar, Worse). I would like to come up with a table which counts the number of times that these categories appear in the two columns.
The dataframe I am using is as follows:

 Category.x Category.y
1 Better Better
2 Better Better
3 Similar Similar
4 Worse Similar

I would like to come up with a table like this:

 Category.x Category.y
Better 2 2
Similar 1 2
Worse 1 0

How would you go about it?

As mentioned in the comments, table is standard for this, like

table(stack(DT))

 ind
values Category.x Category.y
 Better 2 2
 Similar 1 2
 Worse 1 0

or

table(value = unlist(DT), cat = names(DT)[col(DT)])

 cat
value Category.x Category.y
 Better 2 2
 Similar 1 2
 Worse 1 0

or

with(reshape(DT, direction = "long", varying = 1:2), 
 table(value = Category, cat = time)
)

 cat
value x y
 Better 2 2
 Similar 1 2
 Worse 1 0

sapply(df1, function(x) sapply(unique(unlist(df1)), function(y) sum(y == x)))
# Category.x Category.y
#Better 2 2
#Similar 1 2
#Worse 1 0

One dplyr and tidyr possibility could be:

df %>%
 gather(var, val) %>%
 count(var, val) %>%
 spread(var, n, fill = 0)

 val Category.x Category.y
 <chr> <dbl> <dbl>
1 Better 2 2
2 Similar 1 2
3 Worse 1 0

It, first, transforms the data from wide to long format, with column "var" including the variable names and column "val" the corresponding values. Second, it counts per "var" and "val". Finally, it spreads the data into the desired format.

Or with dplyr and reshape2 you can do:

df %>%
 mutate(rowid = row_number()) %>%
 melt(., id.vars = "rowid") %>%
 count(variable, value) %>%
 dcast(value ~ variable, value.var = "n", fill = 0)

 value Category.x Category.y
1 Better 2 2
2 Similar 1 2
3 Worse 1 0