Python | Pandas Series.bfill() Last Updated : 17 Feb, 2019 Comments Improve Suggest changes Like Article Like Report 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.bfill() function is synonym for the backward fill method. This function is used to fill the missing values in the given series object. Syntax: Series.bfill(axis=None, inplace=False, limit=None, downcast=None) Parameter : axis : axis = 1 inplace : make changes to the same object limit : maximum number of consecutive missing values to fill Returns : Series Example #1: Use Series.bfill() function to fill the missing values in the given series object. Python3 # 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.bfill() function to fill the missing values in the given series object. Python3 1== # fill the missing values using backward fill method result = sr.bfill() # Print the result print(result) Output : As we can see in the output, the Series.bfill() function has successfully filled the missing values in the given series object using the backward fill method. Example #2 : Use Series.bfill() function to fill the missing values in the given series object. Python3 # importing pandas as pd import pandas as pd # Creating the Series sr = pd.Series([100, 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.bfill() function to fill the missing values in the given series object. Python3 1== # fill the missing values using backward fill method result = sr.bfill() # Print the result print(result) Output : As we can see in the output, the Series.bfill() function has successfully filled the missing values in the given series object using the backward fill method. Notice the last value has not been filled because there is no valid value in the series after that element. Comment More infoAdvertise with us Next Article Python | Pandas Series.iat S Shubham__Ranjan Follow Improve Article Tags : Pandas Python-pandas Python pandas-series-methods AI-ML-DS With Python Similar Reads Python | Pandas Series.ffill() 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.ffill() function is synonym f 2 min read Python | Pandas Series.isnull() 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.isnull() function detect missi 2 min read Python | Pandas Series.le() Python is a great language for doing data analysis, primarily because of the fantastic ecosystem of data-centric Python packages. Pandas is one of those packages and makes importing and analyzing data much easier. Pandas series.le() is used to compare every element of Caller series with passed serie 3 min read Python | Pandas Series.iloc Python is a great language for doing data analysis, primarily because of the fantastic ecosystem of data-centric python packages. Pandas is one of those packages and makes importing and analyzing data much easier. Pandas series is a One-dimensional ndarray with axis labels. The labels need not be un 2 min read Python | Pandas Series.iat Python is a great language for doing data analysis, primarily because of the fantastic ecosystem of data-centric python packages. Pandas is one of those packages and makes importing and analyzing data much easier. Pandas series is a One-dimensional ndarray with axis labels. The labels need not be un 2 min read Python | Pandas Series.div() Python is a great language for doing data analysis, primarily because of the fantastic ecosystem of data-centric Python packages. Pandas is one of those packages and makes importing and analyzing data much easier. Python Series.div() is used to divide series or list like objects with same length by 2 min read Like