Python | Pandas Series.get_values()

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.get_values() function return an ndarray containing the underlying data of the given series object.

Syntax: Series.get_values()

Parameter : None

Returns : ndarray

Example #1: Use Series.get_values() function to return an array containing the underlying data of the given series object.

# importing pandas as pd
import pandas as pd

# Creating the Series
sr = pd.Series([10, 25, 3, 25, 24, 6])

# Create the Index
index_ = ['Coca Cola', 'Sprite', 'Coke', 'Fanta', 'Dew', 'ThumbsUp']

# set the index
sr.index = index_

# Print the series
print(sr)

Output :

Now we will use Series.get_values() function to return the underlying data of the given series object as an array.

# return an array
result = sr.get_values()

# Print the result
print(result)

Output :

As we can see in the output, the Series.get_values() function has returned the given series object as an array.

Example #2 : Use Series.get_values() function to return an array containing the underlying data of the given series object.

# importing pandas as pd
import pandas as pd

# Creating the Series
sr = pd.Series([11, 21, 8, 18, 65, 84, 32, 10, 5, 24, 32])

# Create the Index
index_ = pd.date_range('2010-10-09', periods = 11, freq ='M')

# set the index
sr.index = index_

# Print the series
print(sr)

Output :

Now we will use Series.get_values() function to return the underlying data of the given series object as an array.

# return an array
result = sr.get_values()

# Print the result
print(result)

Output :

As we can see in the output, the Series.get_values() function has returned the given series object as an array.