Computes a pair-wise frequency table of the given columns

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.

Usage

# S4 method for class 'SparkDataFrame,character,character'
crosstab(x, col1, col2)

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.

Note

crosstab since 1.5.0

See also

Other stat functions: approxQuantile(), corr(), cov(), freqItems(), sampleBy()

Examples

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