# pandas.Series.prod¶

Return the product of the values for the requested axis.

- param axis
- {index (0)}
Axis for the function to be applied on.

- param skipna
- bool, default True
Exclude NA/null values when computing the result.

- param level
- int or level name, default None
If the axis is a MultiIndex (hierarchical), count along a particular level, collapsing into a scalar.

- param numeric_only
- bool, default None
Include only float, int, boolean columns. If None, will attempt to use everything, then use only numeric data. Not implemented for Series.

- param min_count
- int, default 0
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. **kwargs Additional keyword arguments to be passed to the function.

- return
scalar or Series (if level specified)

## Limitations¶

Parameters

`axis`

,`level`

,`numeric_only`

and`min_count`

are currently unsupported by Intel Scalable Dataframe Compiler

## Examples¶

```
import numpy as np
import pandas as pd
from numba import njit
@njit
def series_prod():
series = pd.Series([3.2, -10, np.nan, 0.23, 9.2])
return series.prod() # Expect value: -67.712
print(series_prod())
```

```
$ python ./series/series_prod.py
-67.712
```