# xarray.DataArray.all

#### DataArray.all(dim=None, , keep_attrs=None, \*\*kwargs)[[source]](https://github.com/pydata/xarray/blob/main/xarray/core/_aggregations.py#L2672-L2737)

Reduce this DataArray’s data by applying `all` along some dimension(s).

* **Parameters:**
  * **dim** ([`str`](xarray.DataArray.str.html.md#xarray.DataArray.str), `Iterable` of `Hashable`, `"..."` or [`None`](https://docs.python.org/3/builtins/constants.html#None), *default*: [`None`](https://docs.python.org/3/builtins/constants.html#None)) – Name of dimension[s] along which to apply `all`. For e.g. `dim="x"`
    or `dim=["x", "y"]`. If “…” or None, will reduce over all dimensions.
  * **keep_attrs** ([`bool`](https://docs.python.org/3/builtins/functions.html#bool) or [`None`](https://docs.python.org/3/builtins/constants.html#None), *optional*) – If True, `attrs` will be copied from the original
    object to the new one.  If False, the new object will be
    returned without attributes.
  * **\*\*kwargs** (`Any`) – Additional keyword arguments passed on to the appropriate array
    function for calculating `all` on this object’s data.
    These could include dask-specific kwargs like `split_every`.
* **Returns:**
  **reduced** ([`DataArray`](xarray.DataArray.html.md#xarray.DataArray)) – New DataArray with `all` applied to its data and the
  indicated dimension(s) removed

#### SEE ALSO
[`numpy.all`](https://numpy.org/doc/stable/reference/generated/numpy.all.html#numpy.all), [`dask.array.all`](https://docs.dask.org/en/latest/generated/dask.array.all.html#dask.array.all), [`Dataset.all`](xarray.Dataset.all.html.md#xarray.Dataset.all)

[Aggregation](../user-guide/computation.html.md#agg)
: User guide on reduction or aggregation operations.

### Examples

<div class="try_examples_button_container"><button class="try_examples_button" onclick="window.tryExamplesShowIframe('1f68ff6f-8765-4fa2-91a7-0592d5afeb2d','7309c524-02fa-466a-bf29-041384aa2a54','5c4c795e-8594-482a-8cf3-9efed64f961c','../lite/tree/../notebooks/index.html?path=5866b09f_5485_4f38_8dd2_840879232af4.ipynb','None')">Try it in your browser!</button></div>
```pycon
>>> da = xr.DataArray(
...     np.array([True, True, True, True, True, False], dtype=bool),
...     dims="time",
...     coords=dict(
...         time=("time", pd.date_range("2001-01-01", freq="ME", periods=6)),
...         labels=("time", np.array(["a", "b", "c", "c", "b", "a"])),
...     ),
... )
>>> da
<xarray.DataArray (time: 6)> Size: 6B
array([ True,  True,  True,  True,  True, False])
Coordinates:
  * time     (time) datetime64[us] 48B 2001-01-31 2001-02-28 ... 2001-06-30
    labels   (time) <U1 24B 'a' 'b' 'c' 'c' 'b' 'a'
```

```pycon
>>> da.all()
<xarray.DataArray ()> Size: 1B
array(False)
```

<div id="5c4c795e-8594-482a-8cf3-9efed64f961c" class="try_examples_outer_iframe  hidden"><div class="try_examples_button_container"><button class="try_examples_button" onclick="window.tryExamplesHideIframe('1f68ff6f-8765-4fa2-91a7-0592d5afeb2d','5c4c795e-8594-482a-8cf3-9efed64f961c')">Go Back</button><button class="try_examples_button" onclick="window.openInNewTab('1f68ff6f-8765-4fa2-91a7-0592d5afeb2d','5c4c795e-8594-482a-8cf3-9efed64f961c')">Open In Tab</button></div><div id="7309c524-02fa-466a-bf29-041384aa2a54" class="jupyterlite_sphinx_iframe_container"></div></div><script>document.addEventListener("DOMContentLoaded", function() {window.loadTryExamplesConfig("../try_examples.json");});</script>
