Python | Pandas Series.itemsize
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.itemsize
attribute return the size of the dtype of the item of the underlying data for the given Series object.
Syntax:Series.itemsize
Parameter : None
Returns : size
Example #1: Use Series.itemsize
attribute to check the size of the underlying data for 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.itemsize
attribute to check the size of the underlying data in the given Series object.
Output :
As we can see in the output, the Series.itemsize
attribute has returned 8 indicating that the size of the underlying data for the given Series object is 8 bytes.
Example #2 : Use Series.itemsize
attribute to check the size of the underlying data for 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.itemsize
attribute to check the size of the underlying data in the given Series object.
Output :
As we can see in the output, the Series.itemsize
attribute has returned 8 indicating that the size of the underlying data for the given Series object is 8 bytes.
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