How do I use groupby in pandas to analyze my DataFrame?

How do I use groupby in pandas to analyze my DataFrame?

You can use the groupby() function in pandas to group your DataFrame by one or more columns. This allows you to perform aggregate functions on the grouped data.

Can you show me an example of how to group by a column and calculate the mean?

Sure! Here's a simple example:

import pandas as pd

data = {'Category': ['A', 'B', 'A', 'B'], 'Values': [10, 20, 30, 40]}

df = pd.DataFrame(data)

result = df.groupby('Category').mean()
print(result)

This will give you the mean of 'Values' for each 'Category'.

What if I want to group by multiple columns?

You can pass a list of column names to groupby(). For example:

result = df.groupby(['Category', 'AnotherColumn']).sum()

This will group by both 'Category' and 'AnotherColumn' and calculate the sum.

Can I apply multiple aggregation functions at once?

Yes, you can use the agg() function to apply multiple aggregations. For example:

result = df.groupby('Category').agg({'Values': ['mean', 'sum']})

This will give you both the mean and sum of 'Values' for each 'Category'.