Frequency counts in R [duplicate]

This may seem like a very basic R question, but I'd appreciate an answer. I have a data frame in the form of:

col1    col2
a   g
a   h
a   g
b   i
b   g
b   h
c   i

I want to transform it into counts, so the outcome would be like this. I've tried using table () function, but seem to only be able to get the count for one column.

    a   b   c
g   2   1   0
h   1   1   0
i   0   1   1

How do I do it in R?

I'm not really sure what you used, but table works fine for me!

Here's a minimal reproducible example:

df <- structure(list(V1 = c("a", "a", "a", "b", "b", "b", "c"), 
                     V2 = c("g", "h", "g", "i", "g", "h", "i")), 
                .Names = c("V1", "V2"), class = "data.frame", 
                row.names = c(NA, -7L))
table(df)
#    V2
# V1  g h i
#   a 2 1 0
#   b 1 1 1
#   c 0 0 1

Notes:

• Try table(df[c(2, 1)]) (or table(df$V2, df$V1)) to swap the rows and columns.
• Use as.data.frame.matrix(table(df)) to get a data.frame as your output. (as.data.frame will create a long data.frame, not one in the same output format you desire).

Using f from @Ananda you can use dcast

library(reshape2)

> dcast(f, V1~V2)
Using V2 as value column: use value.var to override.
Aggregation function missing: defaulting to length
  V1  g  h  i
1 a   2  1  0
2 b   1  1  1
3 c   0  0  1

However, I'm writing this only in case you may need something more than just table (which for this case it's the simplest correct answer) in the future, like:

set.seed(1)
f$var <- rnorm(7)

> f
  V1 V2        var
1 a   g -0.6264538
2 a   h  0.1836433
3 a   g -0.8356286
4 b   i  1.5952808
5 b   g  0.3295078
6 b   h -0.8204684
7 c   i  0.4874291

> dcast(f, V1~V2, value.var="var", fun.aggregate=sum)
  V1          g          h         i
1 a  -1.4620824  0.1836433 0.0000000
2 b   0.3295078 -0.8204684 1.5952808
3 c   0.0000000  0.0000000 0.4874291