# dask.dataframe.Series.prod

#### Series.prod(axis=0, skipna=True, numeric_only=False, min_count=0, split_every=False, \*\*kwargs)

Return the product of the values over the requested axis.

This docstring was copied from pandas.DataFrame.prod.

Some inconsistencies with the Dask version may exist.

* **Parameters:**
  **axis**
  : Axis for the function to be applied on.
    For Series this parameter is unused and defaults to 0.
    <br/>
    #### WARNING
    The behavior of DataFrame.prod with `axis=None` is deprecated,
    in a future version this will reduce over both axes and return a scalar
    To retain the old behavior, pass axis=0 (or do not pass axis).
    <br/>
    #### Versionadded
    Added in version 2.0.0.

  **skipna**
  : Exclude NA/null values when computing the result.

  **numeric_only**
  : Include only float, int, boolean columns. Not implemented for Series.

  **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.

  **\*\*kwargs**
  : Additional keyword arguments to be passed to the function.
* **Returns:**
  Series or scalar
  : The product of the values over the requested axis.

#### SEE ALSO
[`Series.sum`](dask.dataframe.Series.sum.html.md#dask.dataframe.Series.sum)
: Return the sum.

[`Series.min`](dask.dataframe.Series.min.html.md#dask.dataframe.Series.min)
: Return the minimum.

[`Series.max`](dask.dataframe.Series.max.html.md#dask.dataframe.Series.max)
: Return the maximum.

[`Series.idxmin`](dask.dataframe.Series.idxmin.html.md#dask.dataframe.Series.idxmin)
: Return the index of the minimum.

[`Series.idxmax`](dask.dataframe.Series.idxmax.html.md#dask.dataframe.Series.idxmax)
: Return the index of the maximum.

[`DataFrame.sum`](dask.dataframe.DataFrame.sum.html.md#dask.dataframe.DataFrame.sum)
: Return the sum over the requested axis.

[`DataFrame.min`](dask.dataframe.DataFrame.min.html.md#dask.dataframe.DataFrame.min)
: Return the minimum over the requested axis.

[`DataFrame.max`](dask.dataframe.DataFrame.max.html.md#dask.dataframe.DataFrame.max)
: Return the maximum over the requested axis.

[`DataFrame.idxmin`](dask.dataframe.DataFrame.idxmin.html.md#dask.dataframe.DataFrame.idxmin)
: Return the index of the minimum over the requested axis.

[`DataFrame.idxmax`](dask.dataframe.DataFrame.idxmax.html.md#dask.dataframe.DataFrame.idxmax)
: Return the index of the maximum over the requested axis.

### Examples

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

```pycon
>>> pd.Series([], dtype="float64").prod()
1.0
```

This can be controlled with the `min_count` parameter

```pycon
>>> pd.Series([], dtype="float64").prod(min_count=1)
nan
```

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

```pycon
>>> pd.Series([np.nan]).prod()
1.0
```

```pycon
>>> pd.Series([np.nan]).prod(min_count=1)
nan
```

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