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Python | Pandas Series.data
  • Last Updated : 28 Jan, 2019

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.data attribute returns the data pointer of the underlying data for the given Series object.

Syntax:Series.data

Parameter : None



Returns : data pointer

Example #1: Use Series.data attribute to find the data pointer 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)

Output :

Now we will use Series.data attribute to return the data pointer for the given Series object.




# return the data pointer
sr.data

Output :

As we can see in the output, the Series.data attribute has returned the data pointer of the given Series object. It is the location where the object is stored.
 
Example #2 : Use Series.data attribute to find the data pointer 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.data attribute to return the data pointer for the given Series object.




# return the data pointer
sr.data

Output :

As we can see in the output, the Series.data attribute has returned the data pointer of the given Series object. It is the location where the object is stored.

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