# xarray.computation.rolling.DatasetCoarsen.mean

#### DatasetCoarsen.mean(keep_attrs=None, \*\*kwargs)[[source]](https://github.com/pydata/xarray/blob/main/xarray/computation/rolling.py#L1232-L1237)

Reduce this object’s data by applying mean along some dimension(s).

* **Parameters:**
  * **skipna** ([`bool`](https://docs.python.org/3/builtins/functions.html#bool), *optional*) – If True, skip missing values (as marked by NaN). By default, only
    skips missing values for float dtypes; other dtypes either do not
    have a sentinel missing value (int) or skipna=True has not been
    implemented (object, datetime64 or timedelta64).
  * **keep_attrs** ([`bool`](https://docs.python.org/3/builtins/functions.html#bool), *optional*) – If True, the attributes (attrs) will be copied from the original
    object to the new one.  If False (default), the new object will be
    returned without attributes.
  * **\*\*kwargs** ([`dict`](https://docs.python.org/3/builtins/stdtypes.html#dict)) – Additional keyword arguments passed on to the appropriate array
    function for calculating mean on this object’s data.
* **Returns:**
  **reduced** (`same type as caller`) – New object with mean applied to its data and the
  indicated dimension(s) removed.