Python | Pandas Series.axes
Last Updated :
28 Jan, 2019
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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 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
Python3
Output :
Now we will use
Python3 1==
Output :
As we can see in the output, the
Python3
Output :
Now we will use
Python3 1==
Output :
As we can see in the output, the
Series.axes
attribute returns a list of row axis labels of the given Series object.
Syntax:Series.axes Parameter : None Returns : list of row axis labelsExample #1: Use
Series.axes
attribute to return the row axis labels of the given Series object.
# importing pandas as pd
import pandas as pd
# Creating the Series
sr = pd.Series(['New York', 'Chicago', 'Toronto', 'Lisbon'])
# Creating the row axis labels
sr.index = ['City 1', 'City 2', 'City 3', 'City 4']
# Print the series
print(sr)

Series.axes
attribute to return a list of row axis labels for the given Series object.
# return the element at the first position
sr.axes

Series.axes
attribute has returned a list containing the labels of the row axes for the given Series object.
Example #2 : Use Series.axes
attribute to return the row axis labels of the given Series object.
# importing pandas as pd
import pandas as pd
# Creating the Series
sr = pd.Series(['1/1/2018', '2/1/2018', '3/1/2018', '4/1/2018'])
# Creating the row axis labels
sr.index = ['Day 1', 'Day 2', 'Day 3', 'Day 4']
# Print the series
print(sr)

Series.axes
attribute to return a list of row axis labels for the given Series object.
# return the element at the first position
sr.axes

Series.axes
attribute has returned a list containing the labels of the row axes for the given Series object.