GroupBy

What is groupby?

• A method to split data into groups based on some key(s).
• Perform aggregations, transformations, or custom functions on each group.
• Combine results into a new DataFrame or Series.

Basic Syntax

• by → column(s) or index level(s) to group on.
• operation → aggregation (sum, mean, count, etc.), transformation, or apply.

Aggregation

Common built-ins:

• .mean() → average per group
• .sum() → sum per group
• .count() → count non-NA entries per group
• .size() → group sizes (including NAs)
• .max() / .min() → extrema per group
• .median(), .std(), .var()

Example:

Output:

Multiple Aggregations

Use .agg() for flexibility:

Or custom names:

Grouping by Multiple Columns

This produces a MultiIndex.

Transformations

Unlike aggregation (reduces groups), transformations return the same shape as the original DataFrame.
Example: normalise salaries within departments:

Filtering Groups

Use .filter() to drop groups based on a condition:

Keeps only departments with an average salary above 60,000.

Iterating Over Groups

Returns multiple DataFrames:

• name → the group key (value of the column you grouped by).
• group → a DataFrame containing only the rows that belong to that group.

If you group by multiple columns, name becomes a tuple of keys.