How can I use the aggregate function in a Pandas DataFrame?

How can I use the aggregate function in a Pandas DataFrame?

You can use the aggregate() function to apply multiple functions to your DataFrame. For example, you can summarize data by groups.

Can you show me a code example?

Sure! Here's a simple example:

import pandas as pd

data = {'A': ['foo', 'bar', 'foo', 'bar'], 'B': [1, 2, 3, 4]}

df = pd.DataFrame(data)

result = df.groupby('A').aggregate({'B': 'sum'})
print(result)

This will sum the values in column 'B' for each group in column 'A'.

What if I want to apply different functions to different columns?

You can pass a dictionary to the aggregate() function where keys are column names and values are the functions you want to apply. For example:

result = df.aggregate({'B': 'sum', 'C': 'mean'})