Python | Pandas Series.product ()

Python Methods and Functions

Series.product() Pandas Series.product() returns the product of the underlying data in a given Series object .

Syntax: Series.product (axis = None, skipna = None, level = None, numeric_only = None, min_count = 0, ** kwargs)

Parameter:
axis: Axis for the function to be applied on.
skipna: Exclude NA / null values ​​when computing the result.
level: If the axis is a MultiIndex (hierarchical), count along a particular level, collapsing into a scalar.
numeric_only: Include only float, int, boolean columns. If None, will attempt to use everything, then use only numeric data. Not implemented for Series.
min_count: The required number of valid values ​​to perform the operation.
** kwargs: Additional keyword arguments to be passed to the function.

Returns: prod: scalar or Series (if level specified)

Example # 1: Use Series.product () to find the underlying data product in a given Series object.

# import pandas as pd

import pandas as pd

 
# Create series

sr = pd.Series ([ 10 , 25 , 3 , 11 , 24 , 6 ])

 
# Create index

index_ = [ 'Coca Cola' , ' Sprite' , 'Coke' , ' Fanta' , 'Dew' , ' ThumbsUp ' ]

  
# set index

sr.index = index_

  
# Print series

print (sr)

Output:

We will now use Series.product () to find the product of the elements in a given series object.

Output:

As we can see in the output, Series.product () successfully returned the product of the underlying data in the given series object.

Example # 2: Use Series.product () to find the underlying data product in a given Series object. This series object contains some missing values.

# return the product of all elements

result = sr.product ()

  
# Print result

print (result)

# import pandas as pd

import pandas as pd

 
# Create series

sr = pd.Series ([ 19.5 , 16.8 , None , 22.78 , None , 20.124 , None , 18.1002 , None ])

 
# Print series

print (sr)

Output:

We will now use Series.product () to find the artwork elements in this series object. We're going to skip missing values.

# return the product of all elements

result = sr.product (skipna = True )

 
# Print result

print (result)

Output:

As we can see in the output, Series.product () has successfully returned the product of the underlying data in the given object series.