How to Use Filter in pandas GroupBy: Syntax and Examples

Use filter on a pandas.DataFrameGroupBy object to keep groups that satisfy a condition. Pass a function to filter that returns True for groups you want to keep and False for those to drop.

Syntax

The filter method is called on a groupby object. It takes a function that receives each group as a DataFrame and returns True to keep the group or False to drop it.

• grouped.filter(func): Applies func to each group.
• func: A function that takes a DataFrame (group) and returns a boolean.

python

grouped = df.groupby('column_name')
filtered = grouped.filter(lambda x: condition_on_x)

Example

This example groups data by a category and keeps only groups with more than 2 rows.

python

import pandas as pd

data = {'Category': ['A', 'A', 'B', 'B', 'B', 'C'],
        'Value': [10, 15, 10, 20, 30, 40]}
df = pd.DataFrame(data)

grouped = df.groupby('Category')
filtered = grouped.filter(lambda x: len(x) > 2)
print(filtered)

Output

  Category  Value
2        B     10
3        B     20
4        B     30

Common Pitfalls

Common mistakes when using filter with groupby include:

• Returning a non-boolean value from the function.
• Using filter when you want to transform or aggregate data.
• Expecting filter to modify the original DataFrame instead of returning a filtered copy.

Always ensure your function returns a single boolean per group.

python

import pandas as pd

data = {'Category': ['A', 'A', 'B', 'B', 'B', 'C'],
        'Value': [10, 15, 10, 20, 30, 40]}
df = pd.DataFrame(data)

grouped = df.groupby('Category')

# Wrong: returns a non-boolean value
# filtered = grouped.filter(lambda x: x['Value'].mean())  # This will raise an error

# Right: returns boolean
filtered = grouped.filter(lambda x: x['Value'].mean() > 15)
print(filtered)

Output

  Category  Value
3        B     20
4        B     30
5        C     40

Quick Reference

• filter(func): Keep groups where func(group) is True.
• func: Function receiving group DataFrame, returns True/False.
• Use for selecting groups, not for modifying data.
• Returns a filtered DataFrame with original index preserved.

Key Takeaways

Use filter on a groupby object to keep groups based on a condition function.

The function passed to filter must return a boolean for each group.

Filter returns a new DataFrame with only the groups that meet the condition.

Do not use filter to modify data; use transform or apply for that.

Common error: returning non-boolean values from the filter function.