How to Use size in groupby in pandas: Simple Guide

In pandas, you can use groupby().size() to count the number of rows in each group. This returns a Series with group labels as the index and the size of each group as values.

Syntax

The basic syntax to use size with groupby is:

DataFrame.groupby(by).size()

Here:

• DataFrame is your data table.
• by is the column name(s) or list of columns to group by.
• size() counts the number of rows in each group.

python

df.groupby('column_name').size()

Example

This example shows how to group a DataFrame by a column and count the number of rows in each group using size().

python

import pandas as pd

data = {'Team': ['A', 'A', 'B', 'B', 'B', 'C'],
        'Points': [10, 15, 10, 20, 15, 10]}
df = pd.DataFrame(data)

# Group by 'Team' and count rows in each group
group_sizes = df.groupby('Team').size()
print(group_sizes)

Output

Team
A    2
B    3
C    1
dtype: int64

Common Pitfalls

One common mistake is confusing size() with count(). size() counts all rows including those with missing values, while count() counts only non-missing values in each column.

Also, size() returns a Series with group labels as index, not a DataFrame.

python

import pandas as pd

data = {'Team': ['A', 'A', 'B', 'B', 'B', 'C'],
        'Points': [10, None, 10, 20, None, 10]}
df = pd.DataFrame(data)

# Using size counts all rows
size_result = df.groupby('Team').size()

# Using count counts only non-NA values in 'Points'
count_result = df.groupby('Team')['Points'].count()

print('Size result:\n', size_result)
print('\nCount result:\n', count_result)

Output

Size result:
Team
A    2
B    3
C    1
dtype: int64

Count result:
Team
A    1
B    2
C    1
Name: Points, dtype: int64

Quick Reference

Method	Description	Returns
groupby().size()	Counts total rows in each group including missing values	Series with group sizes
groupby().count()	Counts non-missing values per column in each group	DataFrame or Series with counts
groupby().agg('size')	Alternative way to get group sizes	Series with group sizes

Key Takeaways

Use groupby().size() to count all rows in each group including missing values.

groupby().size() returns a Series with group labels as the index.

Do not confuse size() with count(); count() ignores missing values.

You can group by one or multiple columns using a list in groupby().

size() is a quick way to see how many items are in each group.