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.get() function get item from object for given key (DataFrame column, Panel slice, etc.). Returns default value if not found.
Syntax: Series.get(key, default=None)
Parameter :
key : objectReturns : value : same type as items contained in object
Example #1: Use Series.get() function to get the value for the passed index label in the given series object.
# 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)
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Output :
Now we will use Series.get() function to return the value for the passed index label in the given series object.
# return the value corresponding to # the passe index label result = sr.get(key = 'City 3')
# Print the result print(result)
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Output :
As we can see in the output, the Series.get() function has returned the value corresponding to the passed index label.
Example #2 : Use Series.get() function to get the value for the passed index label in the given series object.
# importing pandas as pd import pandas as pd
# Creating the Series sr = pd.Series([11, 21, 8, 18, 65, 84, 32, 10, 5, 24, 32])
# 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)
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Output :
Now we will use Series.get() function to return the value for the passed index label in the given series object.
# return the value corresponding to # the passe index label result = sr.get(key = '2011-03-31')
# Print the result print(result)
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Output :
As we can see in the output, the Series.get() function has returned the value corresponding to the passed index label.