Pandas series is a One-dimensional ndarray with axis labels. The labels need not be unique but must be a hashable type. The object supports both integer- and label-based indexing and provides a host of methods for performing operations involving the index.
Pandas Series.last_valid_index() function return index for the last non-NA/null value in the given series object.
Syntax: Series.last_valid_index()
Parameter : None
Returns : scalar
Example #1: Use Series.last_valid_index() function to return the last valid index of the given series object.
# importing pandas as pd import pandas as pd # Creating the Series sr = pd.Series(['New York', 'Chicago', 'Toronto', None, 'Rio']) # Create the Index index_ = ['City 1', 'City 2', 'City 3', 'City 4', 'City 5'] # set the index sr.index = index_ # Print the series print(sr) |
Output :
Now we will use Series.last_valid_index() function to return the last valid index of the given series object.
# return the last valid index result = sr.last_valid_index() # Print the result print(result) |
Output :
As we can see in the output, the Series.last_valid_index() function has returned the last valid index in the given series object.
Example #2: Use Series.last_valid_index() function to return the last valid index of the given series object.
# importing pandas as pd import pandas as pd # Creating the Series sr = pd.Series([19.5, 16.8, None, 22.78, 16.8, 20.124, None, None, None]) # Print the series print(sr) |
Output :
Now we will use Series.last_valid_index() function to return the last valid index of the given series object.
# return the last valid index result = sr.last_valid_index() # Print the result print(result) |
Output :
As we can see in the output, the Series.last_valid_index() function has returned the last valid index in the given series object.
