How to convert a table to a data frame

If you are using the tidyverse, you can use

as_data_frame(table(myvector))

to get a tibble (i.e. a data frame with some minor variations from the base class)

While the results vary in this case because the column names are numbers, another way I've used is data.frame(rbind(mytable)). Using the example from @X.X:

> freq_t = table(cyl = mtcars$cyl, gear = mtcars$gear)

> freq_t
   gear
cyl  3  4  5
  4  1  8  2
  6  2  4  1
  8 12  0  2

> data.frame(rbind(freq_t))
  X3 X4 X5
4  1  8  2
6  2  4  1
8 12  0  2

If the column names do not start with numbers, the X won't get added to the front of them.

Short answer: using as.data.frame.matrix(mytable), as @Victor Van Hee suggested.

Long answer: as.data.frame(mytable) may not work on contingency tables generated by table() function, even if is.matrix(your_table) returns TRUE. It will still melt you table into the factor1 factor2 factori counts format.

Example:

> freq_t = table(cyl = mtcars$cyl, gear = mtcars$gear)

> freq_t
   gear
cyl  3  4  5
  4  1  8  2
  6  2  4  1
  8 12  0  2

> is.matrix(freq_t)
[1] TRUE

> as.data.frame(freq_t)
  cyl gear Freq
1   4    3    1
2   6    3    2
3   8    3   12
4   4    4    8
5   6    4    4
6   8    4    0
7   4    5    2
8   6    5    1
9   8    5    2
> as.data.frame.matrix(freq_t)
   3 4 5
4  1 8 2
6  2 4 1
8 12 0 2

I figured it out already:

as.data.frame.matrix(mytable) 

does what I need -- apparently, the table needs to somehow be converted to a matrix in order to be appropriately translated into a data frame. I found more details on this as.data.frame.matrix() function for contingency tables at the Computational Ecology blog.