Calculate the rate of the jth column given the ith column is true

conditional_rate.py

def conditional_rate(df):
    """
    Given a dataframe whose columns are all boolean
    valued, return a data frame of size:
    n_columns * n_columns
    where the ith row and the jth column represents
    the rate at which the jth variable is true
    given that the ith variable is true.
    """
    
    res = pandas.DataFrame(columns=df.columns, index=df.columns)
 
    for row_var in df.columns:
        for column_var in df.columns:               

            # All rows where the given "row" variable is true
            row_true = df[df[row_var]]
 
            # If there are no values where row_var is true or
            # if for all rows where row_var is true, column_var
            # is false, add a 0 entry
            if (len(row_true)==0 or sum(row_true[column_var])==0):
                res[column_var][row_var] = column_true_rate_given_row_true = 0
            
            else:                
                column_true_rate_given_row_true = row_true[column_var].value_counts(normalize=True)[True]        
                res[column_var][row_var] = column_true_rate_given_row_true
                
    return res