How to Use isna in pandas to Detect Missing Data

Use the isna() function in pandas to detect missing values (NaN) in a DataFrame or Series. It returns a boolean object of the same shape, where True indicates a missing value and False means data is present.

Syntax

The isna() function can be called on a pandas DataFrame or Series. It returns a boolean object showing True for missing values and False otherwise.

• DataFrame.isna(): Checks each cell in the DataFrame.
• Series.isna(): Checks each element in the Series.

python

DataFrame.isna()
Series.isna()

Example

This example shows how to use isna() on a DataFrame to find missing values. The output is a DataFrame of booleans where True marks missing data.

python

import pandas as pd
import numpy as np

data = {'Name': ['Alice', 'Bob', None, 'David'],
        'Age': [25, np.nan, 30, 22],
        'City': ['New York', 'Los Angeles', 'Chicago', None]}
df = pd.DataFrame(data)

missing = df.isna()
print(missing)

Output

    Name    Age   City
0  False  False  False
1  False   True  False
2   True  False  False
3  False  False   True

Common Pitfalls

One common mistake is confusing isna() with isnull(). They are actually the same in pandas, so either works. Another pitfall is expecting isna() to remove missing values; it only detects them.

Also, calling isna() on a non-pandas object will cause an error.

python

import pandas as pd

s = pd.Series([1, None, 3])

# Wrong: expecting isna() to drop missing values
print(s.isna())  # Shows True/False, does NOT drop

# Right: use dropna() to remove missing values
print(s.dropna())

Output

0    False
1     True
2    False
dtype: bool
0    1.0
2    3.0
dtype: float64

Quick Reference

Function	Description
isna()	Returns boolean mask of missing values (NaN)
isnull()	Alias for isna(), same behavior
notna()	Returns boolean mask of non-missing values
dropna()	Removes missing values from data

Key Takeaways

Use pandas isna() to find missing values; it returns True where data is missing.

isna() works on both DataFrames and Series, giving a boolean mask of missing data.

isna() does not remove missing values; use dropna() to remove them.

isna() and isnull() are interchangeable in pandas.

Always call isna() on pandas objects to avoid errors.