Python: create a confusion matrix across two columns in a Pandas dataframe having only categorical data

confusion_matrix.py

import pandas as pd

def confusion_matrix(df: pd.DataFrame, col1: str, col2: str):
    """
    Given a dataframe with at least
    two categorical columns, create a 
    confusion matrix of the count of the columns
    cross-counts
    
    use like:
    
    >>> confusion_matrix(test_df, 'actual_label', 'predicted_label')
    """
    return (
            df
            .groupby([col1, col2])
            .size()
            .unstack(fill_value=0)
            )

Very nice. I came up with

df.groupby(col1)[col2].value_counts()

and was looking for a way to turn the resulting multi-index Series into a DataFrame, but I like your solution much better!