Based on the data you provided and the code you wrote, it seems like you’re trying to perform a pivot table operation on your DataFrame h3.

Here’s how you can achieve what you want:

import pandas as pd

# assuming h3 is your DataFrame
pivot_table = h3.pivot_table(values='ssno', index='nat_actn_2_3', columns='fy', aggfunc=len, fill_value=0)

In this code, h3.pivot_table creates a pivot table where the rows are the unique values in the ’nat_actn_2_3’ column and the columns are the unique values in the ‘fy’ column. The values in each cell of the resulting DataFrame are the counts (i.e., the number of occurrences) of the corresponding value in the ‘ssno’ column.

If you want to add more columns or perform calculations on these pivot table results, you can use the groupby function like this:

pivot_table.groupby('fy').sum()

This will group the rows by the values in the ‘fy’ column and calculate the sum of all other columns (i.e., the counts from the original pivot table) for each group.

Note: The fill_value=0 parameter is used to replace NaN values with 0. If you want to keep these values as they are, just remove this parameter.

Last modified on 2024-01-10