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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 0.126359


I need to dispose of the x and y and convert it to a data frame that looks exactly equivalent to the over (three rows, four columns), however 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.
dataframe r-language
by

3 Answers

espadacoder11 


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.
sandhya6gczb
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.
pankajshivnani123
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)

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