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.first_valid_index() function returns the index for first non-NA/null value in the given series object.
Syntax: Series.first_valid_index()
Parameter : None
Returns : scalar : type of index
Example #1: Use Series.first_valid_index() function to find the first valid index in the given series object.
# importing pandas as pd import pandas as pd   # Creating the Series sr = pd.Series([None, 25, 3, 25, 24, 6])   # Create the Index index_ = ['Coca Cola', 'Sprite', 'Coke', 'Fanta', 'Dew', 'ThumbsUp']   # set the index sr.index = index_   # Print the series print(sr) |
Output :
Now we will use Series.first_valid_index() function to find the first valid index in the given series object.
# return the first valid index result = sr.first_valid_index() Â Â # Print the result print(result) |
Output :
As we can see in the output, the Series.first_valid_index() function has successfully returned the first valid index of the given series object.
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Example #2 : Use Series.first_valid_index() function to find the first valid index in the given series object.
# importing pandas as pd import pandas as pd   # Creating the Series sr = pd.Series([None, None, None, 18, 65, None, 32, 10, 5, 24, None])   # Create the Index index_ = pd.date_range('2010-10-09', periods = 11, freq ='M')   # set the index sr.index = index_   # Print the series print(sr) |
Output :
Now we will use Series.first_valid_index() function to find the first valid index in the given series object.
# return the first valid index result = sr.first_valid_index() Â Â # Print the result print(result) |
Output :
As we can see in the output, the Series.first_valid_index() function has successfully returned the first valid index of the given series object.
