Python Pandas - Return a Series containing counts of unique values from Index object considering NaN values as well

To return a Series containing counts of unique values from Index object considering NaN values as well with the index.value_counts() method. Set the parameter dropna with value False.

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)

Count of unique values using value_counts(). Considering NaN as well using the "False" value of the "dropna" parameter −

index.value_counts(dropna=False) 

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) # count of unique values using value_counts() # considering NaN as well using the "False" value of the "dropna" parameter print("\nGet the count of unique values with NaN...\n",index.value_counts(dropna=False))

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 Get the count of unique values with NaN... NaN 3 50.0 2 10.0 1 70.0 1 90.0 1 30.0 1 dtype: int64