Python | Pandas Series.add_prefix()
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_prefix()
function is used to add prefix to each index labels of the given series object.
Syntax: Series.add_prefix(prefix) Parameter : prefix : The string to add before each label. Returns : Series or DataFrame
Example #1:
Use
Series.add_prefix()
function to add prefix to 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_prefix()
function to add the string label ‘IPL 2019_’ before each index labels in the given series object.
# add 'IPL 2019_' before each index labels
result = sr.add_prefix(prefix = 'IPL 2019_')
# Print the result
print(result)
Output :
IPL 2019_Coca Cola 34
IPL 2019_Sprite 5
IPL 2019_Coke 13
IPL 2019_Fanta 32
IPL 2019_Dew 4
IPL 2019_ThumbsUp 15
dtype: int64
As we can see in the output, the
Series.add_prefix()
function has successfully added the passed string label before each index labels in the given series object.
Example #2 :
Use
Series.add_prefix()
function to add prefix to 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_prefix()
function to add the string label ‘Date_’ before each index labels in the given series object.
# add 'Date_' before each index labels
result = sr.add_prefix(prefix = 'Date_')
# Print the result
print(result)
Output :
Date_2010-12-31 08:45:00 51
Date_2011-12-31 08:45:00 10
Date_2012-12-31 08:45:00 24
Date_2013-12-31 08:45:00 18
Date_2014-12-31 08:45:00 1
Date_2015-12-31 08:45:00 84
Date_2016-12-31 08:45:00 12
Date_2017-12-31 08:45:00 10
Date_2018-12-31 08:45:00 5
Date_2019-12-31 08:45:00 24
Date_2020-12-31 08:45:00 0
dtype: int64
As we can see in the output, the
Series.add_prefix()
function has successfully added the passed string label before each index labels in the given series object.
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