.isna()

The .isna() method checks whether the objects of a Dataframe or a Series contain missing or null values (NA, NaN) and returns a new object with the same shape as the original but with boolean values True or False as the elements. True indicates the presence of null or missing values and False indicates otherwise. The original DataFrame object, used to call the method, remains unchanged.

Syntax

# Check for NA values.
df.isna()

Example

Here are some examples for using the .isna() method on both DataFrame and Series objects:

Example 1: .isna() with a DataFrame

import pandas as pd

# Create a DataFrame with missing values
df = pd.DataFrame({
    'A': [1, 2, None, 4],
    'B': [5, None, 7, 8],
    'C': ['a', 'b', None, 'd']
})

# Check for missing values in the DataFrame
missing_values = df.isna()

print(missing_values)

The code above results in the following output:

       A      B      C
0  False  False  False
1  False   True  False
2   True  False   True
3  False  False  False

Example 2: .isna() with a Series

import pandas as pd

# Create a Series with missing values
s = pd.Series([1, None, 3, None, 5])

# Check for missing values in the Series
missing_values = s.isna()

print(missing_values)

The code above results in the following output:

0    False
1     True
2    False
3     True
4    False