crosstab() method in Python Pandas is used to compute a simple cross tabulation of two or more factors. It computes computes a frequency table of the factors unless an array of values and an aggregation function are passed, by default.

What Parameters can be used in crosstab() method of Python Pandas

index

It should be array-like, Series, or list of arrays/Series

It is used for Values to group by in the rows.

columns

It should be array-like, Series, or list of arrays/Series

It is used for Values to group by in the columns.

values

array-like, optional

Array of values to aggregate according to the factors. Requires aggfunc be specified.

rownames

sequence, default None

If passed, must match number of row arrays passed.

colnames

sequence, default None

If passed, must match number of column arrays passed.

aggfunc

function, optional

If specified, requires values be specified as well.

margins

bool, default False

Add row/column margins (subtotals).

margins_name

str, default ‘All’

Name of the row/column that will contain the totals when margins is True.

dropna

bool, default True

To drop columns whose entries are all NaN.

normalize

bool, {‘all’, ‘index’, ‘columns’}, or {0,1}, default False

Normalize by dividing all values by the sum of values.

• If passed ‘all’ or True, will normalize over all values.
• If passed ‘index’ will normalize over each row.
• If passed ‘columns’ will normalize over each column.
• If margins is True, will also normalize margin values.