Python | Pandas Series.isin()
Last Updated :
01 Oct, 2021
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.isin() function check whether values are contained in Series. It returns a boolean Series showing whether each element in the Series matches an element in the passed sequence of values exactly.
Syntax: Series.isin(values)
Parameter :
values : The sequence of values to test.
Returns : isin : Series (bool dtype)
Example #1: Use Series.isin() function to check if the passed values in the list are contained in the series object.
Python3
import pandas as pd
sr = pd.Series([ 10 , 25 , 3 , 25 , 24 , 6 ])
index_ = [ 'Coca Cola' , 'Sprite' , 'Coke' , 'Fanta' , 'Dew' , 'ThumbsUp' ]
sr.index = index_
print (sr)
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Output :
Now we will use Series.isin() function to check whether the passed values are contained in the series object.
Python3
result = sr.isin([ 25 ])
print (result)
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Output :
As we can see in the output, the Series.isin() function has returned an object containing boolean values. All values have been mapped to True if it is present in the list else False.
Example #2 : Use Series.isin() function to check if the passed values in the list are contained in the series object.
Python3
import pandas as pd
sr = pd.Series([ 11 , 21 , 8 , 18 , 65 , 84 , 32 , 10 , 5 , 24 , 32 ])
index_ = pd.date_range( '2010-10-09' , periods = 11 , freq = 'M' )
sr.index = index_
print (sr)
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Output :
Now we will use Series.isin() function to check whether the passed values are contained in the series object.
Python3
result = sr.isin([ 21 , 10 ])
print (result)
|
Output :
As we can see in the output, the Series.isin() function has returned an object containing boolean values. All values have been mapped to True if it is present in the list else False.
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