Pandas Series: product() function

Last update on September 15 2022 12:58:09 (UTC/GMT +8 hours)

Product of the values for the requested Pandas axis

The product() function is used to get the product of the values for the requested axis.

Syntax:

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

Parameters:

Name	Description	Type/Default Value	Required / Optional
axis	Axis for the function to be applied on.	{index (0)}	Required
skipna	Exclude NA/null values when computing the result.	bool Default Value : True	Required
level	If the axis is a MultiIndex (hierarchical), count along a particular level, collapsing into a scalar.	int or level name Default Value: None	Required
numeric_only	Include only float, int, boolean columns. If None, will attempt to use everything, then use only numeric data. Not implemented for Series	bool Default Value: None	Required
min_count	The required number of valid values to perform the operation. If fewer than min_count non-NA values are present the result will be NA. New in version 0.22.0: Added with the default being 0. This means the sum of an all-NA or empty Series is 0, and the product of an all-NA or empty Series is 1.	int Default Value: 0	Required
kwargs	Additional keyword arguments to be passed to the function.		Required

Returns: scalar or Series (if level specified)

Example - By default, the product of an empty or all-NA Series is 1:

Python-Pandas Code:

import numpy as np
import pandas as pd
pd.Series([]).prod()

Output:

1.0

Example - This can be controlled with the min_count parameter:

Python-Pandas Code:

import numpy as np
import pandas as pd
pd.Series([]).prod(min_count=1)

Output:

nan

Thanks to the skipna parameter, min_count handles all-NA and empty series identically.

Python-Pandas Code:

import numpy as np
import pandas as pd
pd.Series([np.nan]).prod()

Output:

1.0

Python-Pandas Code:

import numpy as np
import pandas as pd
pd.Series([np.nan]).prod(min_count=1)

Output:

nan

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