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.
