w3resource

Pandas: Series - prod() function

Product of the values for the requested Pandas axis

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

Syntax:

Series.prod(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

Example - 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

Previous: Percentage change between the current and a prior element
Next: Value at the given quantile



Become a Patron!

Follow us on Facebook and Twitter for latest update.

It will be nice if you may share this link in any developer community or anywhere else, from where other developers may find this content. Thanks.

https://w3resource.com/pandas/series/series-prod.php