At my previous internship, SAS was the software of choice for about 80% of the statistical work done; this rate was pulled down by me using/pushing for `R`

and another co-worker using/pushing for `Python`

.

One of the positive features of SAS is its `PROC FREQ`

command. It gives useful summaries for contingency tables, such as row and column summary statistics and tests of different types. `R`

‘s base function `table`

is not full of bells and whistles. To get similar statistics as SAS’s `PROC FREQ`

, check out `CrossTable`

from the `gmodels`

package or the base function `margin.table`

to get row/column totals. See this for examples.