Python | Pandas Series.values
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.values attribute return Series as ndarray or ndarray-like depending on the dtype.
Syntax:Series.values
Parameter : None
Returns : ndarray
Example #1: Use Series.values attribute to return the values in the given series object as an ndarray.
import pandas as pd
sr = pd.Series(['New York', 'Chicago', 'Toronto', 'Lisbon', 'Rio'])
sr.index = ['City 1', 'City 2', 'City 3', 'City 4', 'City 5']
print(sr)
|
Output :
Now we will use Series.values attribute to return the values of the given Series object as an ndarray.
Output :
As we can see in the output, the Series.values attribute has returned an ndarray object containing the values of the given Series object.
Example #2 : Use Series.values attribute to return the values in the given series object as an ndarray.
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.values attribute to return the values of the given Series object as an ndarray.
Output :
As we can see in the output, the Series.values attribute has returned an ndarray object containing the values of the given Series object.
Like Article
Suggest improvement
Share your thoughts in the comments
Please Login to comment...