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.
import pandas as pd
sr = pd.Series([ 'New York' , 'Chicago' , 'Toronto' , 'Lisbon' ])
sr.index = [ 'City 1' , 'City 2' , 'City 3' , 'City 4' ]
print (sr)
|
Output :
Now we will use Series.data
attribute to return the data pointer for the given Series object.
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.
import pandas as pd
sr = pd.Series([ '1/1/2018' , '2/1/2018' , '3/1/2018' , '4/1/2018' ])
sr.index = [ 'Day 1' , 'Day 2' , 'Day 3' , 'Day 4' ]
print (sr)
|
Output :
Now we will use Series.data
attribute to return the data pointer for the given Series object.
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.
Share your thoughts in the comments
Please Login to comment...