Python – Pandas Series.shape



Python | Pandas Series.shape

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 Series.shape attribute returns a tuple of the shape of the underlying data for the given series objects.

Syntax:Series.shape

Parameter : None

Returns : shape

Example #1: Use Series.shape attribute to find the shape of the underlying data of the given series object.

# importing pandas as pd
import pandas as pd
 
# Creating the Series
sr = pd.Series(['New York', 'Chicago', 'Toronto', 'Lisbon', 'Rio'])
 
# Creating the row axis labels
sr.index = ['City 1', 'City 2', 'City 3', 'City 4', 'City 5'
 
# Print the series
print(sr)

Output :

Now we will use Series.shape attribute to find the shape of the underlying data of the given Series object.

# return the shape
sr.shape

Output :


As we can see in the output, the Series.shape attribute has returned a tuple indicating the shape of the underlying data of the given series object.

Example #2 : Use Series.shape attribute to find the shape of the underlying data 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)

Output :

Now we will use Series.shape attribute to find the shape of the underlying data of the given Series object.

# return the shape
sr.shape

Output :

As we can see in the output, the Series.shape attribute has returned a tuple indicating the shape of the underlying data of the given series object.

 

Last Updated on October 21, 2021 by admin

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