# Computes a pair-wise frequency table of the given columns

`crosstab.Rd`

Computes a pair-wise frequency table of the given columns. Also known as a contingency table. The number of distinct values for each column should be less than 1e4. At most 1e6 non-zero pair frequencies will be returned.

## Arguments

- x
a SparkDataFrame

- col1
name of the first column. Distinct items will make the first item of each row.

- col2
name of the second column. Distinct items will make the column names of the output.

## Value

a local R data.frame representing the contingency table. The first column of each row
will be the distinct values of `col1`

and the column names will be the distinct
values of `col2`

. The name of the first column will be "`col1`

_`col2`

".
Pairs that have no occurrences will have zero as their counts.

## See also

Other stat functions:
`approxQuantile()`

,
`corr()`

,
`cov()`

,
`freqItems()`

,
`sampleBy()`

## Examples

```
if (FALSE) {
df <- read.json("/path/to/file.json")
ct <- crosstab(df, "title", "gender")
}
```