Count unique occurrences within data frame

Question

Let the table be as follows:

v1	v2	v3
A	B	A
B	B	A
	A	C
D	C	D

What i want R to create a table for number of occurences of unique values for each column:

v1	v2	v3
A	1	1
B	1	2
C	0	1
D	1	0

Answer 1

Try table like this

> table(unlist(df),names(df)[col(df)])

    V1 v2 v3
  A  1  1  2
  B  1  2  0
  C  0  1  1
  D  1  0  1

Data

> dput(df)
structure(list(V1 = c("A", "B", NA, "D"), v2 = c("B", "B", "A", 
"C"), v3 = c("A", "A", "C", "D")), class = "data.frame", row.names = c(NA,
-4L))

Answer 2

One option could be:

sapply(df, function(x) table(factor(x, levels = unique(unlist(df)))))

  V1 v2 v3
A  1  1  2
B  1  2  0
D  1  0  1
C  0  1  1

Answer 3

To add to the set, a tidyverse version.

library(tidyverse)

df %>% 
  pivot_longer(
    everything(), 
    values_to="Value", 
    names_to="Variable"
  ) %>% 
  group_by(Variable, Value) %>% 
  summarise(N=n(), .groups="drop") %>% 
  filter(!is.na(Value)) %>% 
  pivot_wider(values_from=N, names_from=Variable, values_fill=0) %>% 
  arrange(Value)
# A tibble: 4 x 4
  Value    v1    v2    v3
  <chr> <int> <int> <int>
1 A         1     1     2
2 B         1     2     0
3 C         0     1     1
4 D         1     0     1

Answer 4

For the sake of completeness, here is an approach which uses a combination of melt() and dcast():

library(data.table)
dcast(melt(setDT(df1), measure.vars = patterns("^v"))[value != ""], value ~ variable)

   value v1 v2 v3
1:     A  1  1  2
2:     B  1  2  0
3:     C  0  1  1
4:     D  1  0  1

The approach is similar to Limey's answer in reshaping the data from wide to long and back to wide but less verbose.

Edit

Instead of dcast(), table() can be called after reshaping from wide to long:

melt(setDT(df1), measure.vars = patterns("^v"))[value != ""][
  , table(value, variable)]

     variable
value v1 v2 v3
    A  1  1  2
    B  1  2  0
    C  0  1  1
    D  1  0  1

Note that data.table chaining is used here.

And, to save a few keystrokes:

melt(setDT(df1), measure.vars = names(df1))[value != ""][, table(rev(.SD))]

Data

df1 <- fread("
|v1|v2|v3|
|A |B | A|
|B |B | A|
|  |A | C|
|D |C | D|", 
drop = c(1,5), header = TRUE)

Answer 5

We can use mtabulate

library(qdapTools)
 t(mtabulate(df))
  V1 v2 v3
A  1  1  2
B  1  2  0
C  0  1  1
D  1  0  1

data

df <- structure(list(V1 = c("A", "B", NA, "D"), v2 = c("B", "B", "A", 
"C"), v3 = c("A", "A", "C", "D")), class = "data.frame", row.names = c(NA,
-4L))