How to convert a table to a data frame

I have a table in R that has str() of this:

 table [1:3, 1:4] 0.166 0.319 0.457 0.261 0.248 ...
 - attr(*, "dimnames")=List of 2
  ..$ x: chr [1:3] "Metro >=1 million" "Metro <1 million" "Non-Metro Counties"
  ..$ y: chr [1:4] "q1" "q2" "q3" "q4"

And looks like this when I print it:

                    y
x                           q1        q2        q3        q4
  Metro >=1 million  0.1663567 0.2612212 0.2670441 0.3053781
  Metro <1 million   0.3192857 0.2480012 0.2341030 0.1986102
  Non-Metro Counties 0.4570341 0.2044960 0.2121102 0.1263597

I want to get rid of the x and y and convert it to a data frame that looks exactly the same as the above (three rows, four columns), but without the x or y. If I use as.data.frame(mytable), instead I get this:

                    x  y      Freq
1   Metro >=1 million q1 0.1663567
2    Metro <1 million q1 0.3192857
3  Non-Metro Counties q1 0.4570341
4   Metro >=1 million q2 0.2612212
5    Metro <1 million q2 0.2480012
6  Non-Metro Counties q2 0.2044960
7   Metro >=1 million q3 0.2670441
8    Metro <1 million q3 0.2341030
9  Non-Metro Counties q3 0.2121102
10  Metro >=1 million q4 0.3053781
11   Metro <1 million q4 0.1986102
12 Non-Metro Counties q4 0.1263597

I probably fundamentally do not understand how tables relate to data frames.

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.

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

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)

This is deprecated:

as.data.frame(my_table)

Instead use this package:

library("quanteda")
convert(my_table, to="data.frame")