PandasHow-ToBeginner · 3 min read

How to Use len() for DataFrame in pandas: Simple Guide

Use len() on a pandas DataFrame to get the number of rows it contains. For example, len(df) returns the count of rows in the DataFrame df.

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Syntax

The syntax to use len() with a pandas DataFrame is simple:

len(dataframe): Returns the number of rows in the DataFrame.

This works because a DataFrame's length is defined as its number of rows.

python

len(dataframe)

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Example

This example shows how to create a DataFrame and use len() to find out how many rows it has.

python

import pandas as pd

data = {'Name': ['Alice', 'Bob', 'Charlie'], 'Age': [25, 30, 35]}
df = pd.DataFrame(data)

row_count = len(df)
print(row_count)

Output

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Common Pitfalls

Some common mistakes when using len() with DataFrames include:

Expecting len() to return the number of columns instead of rows.
Using len() on a DataFrame column (a Series) and confusing it with the DataFrame length.

To get the number of columns, use df.shape[1] instead.

python

import pandas as pd

data = {'Name': ['Alice', 'Bob'], 'Age': [25, 30]}
df = pd.DataFrame(data)

# Wrong: expecting columns count
wrong = len(df)  # This returns rows count, not columns

# Right: get columns count
right = df.shape[1]

print(f"Rows: {len(df)}")
print(f"Columns: {right}")

Output

Rows: 2 Columns: 2

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Key Takeaways

Use len(dataframe) to get the number of rows in a pandas DataFrame.

len() returns rows count, not columns count.

To get columns count, use dataframe.shape[1].

len() works because DataFrame length is defined as its row count.