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.add_suffix()
function is used to add suffix at the end of the index labels in the given series object.
Syntax: Series.add_suffix(suffix)
Parameter :
suffix : The string to add after each label.Returns : Series or DataFrame
Example #1: Use Series.add_suffix()
function to add suffix at the end of each index labels in the given series object.
# importing pandas as pd import pandas as pd # Creating the Series sr = pd.Series([ 34 , 5 , 13 , 32 , 4 , 15 ]) # Create the Index index_ = [ 'Coca Cola' , 'Sprite' , 'Coke' , 'Fanta' , 'Dew' , 'ThumbsUp' ] # set the index sr.index = index_ # Print the series print (sr) |
Output :
Coca Cola 34 Sprite 5 Coke 13 Fanta 32 Dew 4 ThumbsUp 15 dtype: int64
Now we will use Series.add_suffix()
function to add the suffix ‘_IPL 2019’ at the end of each index labels in the given series object.
# add '_IPL 2019' to each index labels result = sr.add_suffix(suffix = '_IPL 2019' ) # Print the result print (result) |
Output :
Coca Cola_IPL 2019 34 Sprite_IPL 2019 5 Coke_IPL 2019 13 Fanta_IPL 2019 32 Dew_IPL 2019 4 ThumbsUp_IPL 2019 15 dtype: int64
As we can see in the output, the Series.add_suffix()
function has successfully added the passed suffix at the end of each index labels in the given series object.
Example #2 : Use Series.add_suffix()
function to add suffix at the end of each index labels in the given series object.
# importing pandas as pd import pandas as pd # Creating the Series sr = pd.Series([ 51 , 10 , 24 , 18 , 1 , 84 , 12 , 10 , 5 , 24 , 0 ]) # Create the Index # apply yearly frequency index_ = pd.date_range( '2010-10-09 08:45' , periods = 11 , freq = 'Y' ) # set the index sr.index = index_ # Print the series print (sr) |
Output :
2010-12-31 08:45:00 51 2011-12-31 08:45:00 10 2012-12-31 08:45:00 24 2013-12-31 08:45:00 18 2014-12-31 08:45:00 1 2015-12-31 08:45:00 84 2016-12-31 08:45:00 12 2017-12-31 08:45:00 10 2018-12-31 08:45:00 5 2019-12-31 08:45:00 24 2020-12-31 08:45:00 0 Freq: A-DEC, dtype: int64
Now we will use Series.add_suffix()
function to add the suffix ‘_Date’ at the end of each index labels in the given series object.
# add '_Date' to each index labels result = sr.add_suffix(suffix = '_Date' ) # Print the result print (result) |
Output :
2010-12-31 08:45:00_Date 51 2011-12-31 08:45:00_Date 10 2012-12-31 08:45:00_Date 24 2013-12-31 08:45:00_Date 18 2014-12-31 08:45:00_Date 1 2015-12-31 08:45:00_Date 84 2016-12-31 08:45:00_Date 12 2017-12-31 08:45:00_Date 10 2018-12-31 08:45:00_Date 5 2019-12-31 08:45:00_Date 24 2020-12-31 08:45:00_Date 0 dtype: int64
As we can see in the output, the Series.add_suffix()
function has successfully added the passed suffix at the end of each index labels in the given series object.