How can I perform advanced aggregation in Pandas?

How can I perform advanced aggregation in Pandas?

You can use the groupby method along with aggregation functions like sum, mean, or custom functions. What specific aggregation are you looking to perform?

I want to calculate the average and total sales by product category.

You can do this by grouping your DataFrame by the product category and then using the agg function. Here's an example:

import pandas as pd

df.groupby('category').agg({'sales': ['sum', 'mean']})

Can I also include the count of sales in the same aggregation?

Yes, you can include the count by adding it to the agg function like this:

df.groupby('category').agg({'sales': ['sum', 'mean', 'count']})

That’s great! How do I rename the aggregated columns?

You can rename the columns by using the rename method after aggregation. For example:

df.groupby('category').agg({'sales': ['sum', 'mean', 'count']}).rename(columns={'sum': 'Total Sales', 'mean': 'Average Sales', 'count': 'Sales Count'})