Reduce this NamedArray's data by applying ``mean`` along some dimension(s). Parameters ---------- dim : str, Iterable of Hashable, "..." or None, default: None Name of dimension[s] along which to apply ``mean``. For e.g. ``dim="x"`` or ``dim=
(
self,
dim: Dims = None,
*,
skipna: bool | None = None,
**kwargs: Any,
)
| 313 | ) |
| 314 | |
| 315 | def mean( |
| 316 | self, |
| 317 | dim: Dims = None, |
| 318 | *, |
| 319 | skipna: bool | None = None, |
| 320 | **kwargs: Any, |
| 321 | ) -> Self: |
| 322 | """ |
| 323 | Reduce this NamedArray's data by applying ``mean`` along some dimension(s). |
| 324 | |
| 325 | Parameters |
| 326 | ---------- |
| 327 | dim : str, Iterable of Hashable, "..." or None, default: None |
| 328 | Name of dimension[s] along which to apply ``mean``. For e.g. ``dim="x"`` |
| 329 | or ``dim=["x", "y"]``. If "..." or None, will reduce over all dimensions. |
| 330 | skipna : bool or None, optional |
| 331 | If True, skip missing values (as marked by NaN). By default, only |
| 332 | skips missing values for float dtypes; other dtypes either do not |
| 333 | have a sentinel missing value (int) or ``skipna=True`` has not been |
| 334 | implemented (object, datetime64 or timedelta64). |
| 335 | **kwargs : Any |
| 336 | Additional keyword arguments passed on to the appropriate array |
| 337 | function for calculating ``mean`` on this object's data. |
| 338 | These could include dask-specific kwargs like ``split_every``. |
| 339 | |
| 340 | Returns |
| 341 | ------- |
| 342 | reduced : NamedArray |
| 343 | New NamedArray with ``mean`` applied to its data and the |
| 344 | indicated dimension(s) removed |
| 345 | |
| 346 | See Also |
| 347 | -------- |
| 348 | numpy.mean |
| 349 | dask.array.mean |
| 350 | Dataset.mean |
| 351 | DataArray.mean |
| 352 | :ref:`agg` |
| 353 | User guide on reduction or aggregation operations. |
| 354 | |
| 355 | Examples |
| 356 | -------- |
| 357 | >>> from xarray.namedarray.core import NamedArray |
| 358 | >>> na = NamedArray("x", np.array([1, 2, 3, 0, 2, np.nan])) |
| 359 | >>> na |
| 360 | <xarray.NamedArray (x: 6)> Size: 48B |
| 361 | array([ 1., 2., 3., 0., 2., nan]) |
| 362 | |
| 363 | >>> na.mean() |
| 364 | <xarray.NamedArray ()> Size: 8B |
| 365 | array(1.6) |
| 366 | |
| 367 | Use ``skipna`` to control whether NaNs are ignored. |
| 368 | |
| 369 | >>> na.mean(skipna=False) |
| 370 | <xarray.NamedArray ()> Size: 8B |
| 371 | array(nan) |
| 372 | """ |