Fill NaN Values with Specified Value in Pandas Index Object

To fill NaN values with the specified value in an Index object, use the index.fillna() method in Pandas. At first, import the required libraries −

import pandas as pd
import numpy as np

Creating Pandas index with some NaN values as well −

index = pd.Index([50, 10, 70, np.nan, 90, 50, np.nan, np.nan, 30])

Display the Pandas index −

print("Pandas Index...\n",index)

Fill the NaN with some specific value −

print("\nIndex object after filling NaN value...\n",index.fillna('Amit'))

Example

Following is the code −

import pandas as pd
import numpy as np

# Creating Pandas index with some NaN values as well
index = pd.Index([50, 10, 70, np.nan, 90, 50, np.nan, np.nan, 30])

# Display the Pandas index
print("Pandas Index...\n",index)

# Return the number of elements in the Index
print("\nNumber of elements in the index...\n",index.size)

# Return the dtype of the data
print("\nThe dtype object...\n",index.dtype)

# Fill the NaN with some specific value
print("\nIndex object after filling NaN value...\n",index.fillna('Amit'))

Output

This will produce the following output −

Pandas Index...
Float64Index([50.0, 10.0, 70.0, nan, 90.0, 50.0, nan, nan, 30.0], dtype='float64')

Number of elements in the index...
9

The dtype object...
float64

Index object after filling NaN value...
Index([50.0, 10.0, 70.0, 'Amit', 90.0, 50.0, 'Amit', 'Amit', 30.0], dtype='object')