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Documentation improvements (#3328)
* Add examples for full_like, zeros_like, ones_like * Add examples for xr.align * Add examples for xr.merge * Update xr.where docstring * Update xr.dot docstring * Update xarray/core/common.py Co-Authored-By: Deepak Cherian <[email protected]> * Update xarray/core/common.py Co-Authored-By: Deepak Cherian <[email protected]> * Update xr.combine_by_coords docstring * Apply black formatting only * More black formatting * Remove unnecessary pandas bits * Fix indentation issues * Update assign and pipe * Update `Dataset.reindex` with examples * Update `Dataset.fillna` with examples * Address styling issues * Update docstring Co-Authored-By: Deepak Cherian <[email protected]>
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‎doc/whats-new.rst‎

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@@ -32,7 +32,10 @@ Documentation
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~~~~~~~~~~~~~
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- Add examples for :py:meth:`Dataset.swap_dims` and :py:meth:`DataArray.swap_dims`.
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By `Justus Magin <https://github.com/keewis>`_.
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- Add examples for :py:meth:`align`, :py:meth:`merge`, :py:meth:`combine_by_coords`,
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:py:meth:`full_like`, :py:meth:`zeros_like`, :py:meth:`ones_like`, :py:meth:`Dataset.pipe`,
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:py:meth:`Dataset.assign`, :py:meth:`Dataset.reindex`, :py:meth:`Dataset.fillna`.
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By `Anderson Banihirwe <https://github.com/andersy005>`_.
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- Fixed documentation to clean up an unwanted file created in ``ipython`` example
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(:pull:`3353`).
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By `Gregory Gundersen <https://github.com/gwgundersen/>`_.

‎xarray/core/alignment.py‎

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@@ -116,6 +116,136 @@ def align(
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ValueError
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If any dimensions without labels on the arguments have different sizes,
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or a different size than the size of the aligned dimension labels.
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Examples
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--------
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>>> import xarray as xr
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>>> x = xr.DataArray([[25, 35], [10, 24]], dims=('lat', 'lon'),
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... coords={'lat': [35., 40.], 'lon': [100., 120.]})
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>>> y = xr.DataArray([[20, 5], [7, 13]], dims=('lat', 'lon'),
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... coords={'lat': [35., 42.], 'lon': [100., 120.]})
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>>> x
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<xarray.DataArray (lat: 2, lon: 2)>
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array([[25, 35],
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[10, 24]])
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Coordinates:
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* lat (lat) float64 35.0 40.0
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* lon (lon) float64 100.0 120.0
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>>> y
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<xarray.DataArray (lat: 2, lon: 2)>
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array([[20, 5],
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[ 7, 13]])
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Coordinates:
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* lat (lat) float64 35.0 42.0
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* lon (lon) float64 100.0 120.0
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>>> a, b = xr.align(x, y)
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>>> a
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<xarray.DataArray (lat: 1, lon: 2)>
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array([[25, 35]])
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Coordinates:
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* lat (lat) float64 35.0
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* lon (lon) float64 100.0 120.0
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>>> b
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<xarray.DataArray (lat: 1, lon: 2)>
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array([[20, 5]])
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Coordinates:
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* lat (lat) float64 35.0
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* lon (lon) float64 100.0 120.0
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>>> a, b = xr.align(x, y, join='outer')
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>>> a
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<xarray.DataArray (lat: 3, lon: 2)>
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array([[25., 35.],
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[10., 24.],
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[nan, nan]])
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Coordinates:
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* lat (lat) float64 35.0 40.0 42.0
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* lon (lon) float64 100.0 120.0
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>>> b
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<xarray.DataArray (lat: 3, lon: 2)>
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array([[20., 5.],
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[nan, nan],
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[ 7., 13.]])
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Coordinates:
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* lat (lat) float64 35.0 40.0 42.0
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* lon (lon) float64 100.0 120.0
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>>> a, b = xr.align(x, y, join='outer', fill_value=-999)
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>>> a
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<xarray.DataArray (lat: 3, lon: 2)>
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array([[ 25, 35],
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[ 10, 24],
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[-999, -999]])
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Coordinates:
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* lat (lat) float64 35.0 40.0 42.0
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* lon (lon) float64 100.0 120.0
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>>> b
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<xarray.DataArray (lat: 3, lon: 2)>
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array([[ 20, 5],
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[-999, -999],
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[ 7, 13]])
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Coordinates:
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* lat (lat) float64 35.0 40.0 42.0
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* lon (lon) float64 100.0 120.0
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>>> a, b = xr.align(x, y, join='left')
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>>> a
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<xarray.DataArray (lat: 2, lon: 2)>
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array([[25, 35],
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[10, 24]])
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Coordinates:
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* lat (lat) float64 35.0 40.0
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* lon (lon) float64 100.0 120.0
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>>> b
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<xarray.DataArray (lat: 2, lon: 2)>
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array([[20., 5.],
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[nan, nan]])
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Coordinates:
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* lat (lat) float64 35.0 40.0
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* lon (lon) float64 100.0 120.0
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>>> a, b = xr.align(x, y, join='right')
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>>> a
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<xarray.DataArray (lat: 2, lon: 2)>
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array([[25., 35.],
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[nan, nan]])
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Coordinates:
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* lat (lat) float64 35.0 42.0
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* lon (lon) float64 100.0 120.0
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>>> b
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<xarray.DataArray (lat: 2, lon: 2)>
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array([[20, 5],
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[ 7, 13]])
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Coordinates:
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* lat (lat) float64 35.0 42.0
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* lon (lon) float64 100.0 120.0
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>>> a, b = xr.align(x, y, join='exact')
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Traceback (most recent call last):
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...
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"indexes along dimension {!r} are not equal".format(dim)
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ValueError: indexes along dimension 'lat' are not equal
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>>> a, b = xr.align(x, y, join='override')
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>>> a
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<xarray.DataArray (lat: 2, lon: 2)>
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array([[25, 35],
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[10, 24]])
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Coordinates:
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* lat (lat) float64 35.0 40.0
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* lon (lon) float64 100.0 120.0
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>>> b
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<xarray.DataArray (lat: 2, lon: 2)>
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array([[20, 5],
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[ 7, 13]])
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Coordinates:
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* lat (lat) float64 35.0 40.0
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* lon (lon) float64 100.0 120.0
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"""
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if indexes is None:
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indexes = {}

‎xarray/core/combine.py‎

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@@ -393,7 +393,7 @@ def combine_nested(
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--------
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A common task is collecting data from a parallelized simulation in which
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each processor wrote out to a separate file. A domain which was decomposed
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each process wrote out to a separate file. A domain which was decomposed
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into 4 parts, 2 each along both the x and y axes, requires organising the
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datasets into a doubly-nested list, e.g:
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@@ -505,8 +505,7 @@ def combine_by_coords(
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----------
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datasets : sequence of xarray.Dataset
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Dataset objects to combine.
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compat : {'identical', 'equals', 'broadcast_equals',
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'no_conflicts', 'override'}, optional
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compat : {'identical', 'equals', 'broadcast_equals', 'no_conflicts', 'override'}, optional
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String indicating how to compare variables of the same name for
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potential conflicts:
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@@ -520,9 +519,21 @@ def combine_by_coords(
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of all non-null values.
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- 'override': skip comparing and pick variable from first dataset
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data_vars : {'minimal', 'different', 'all' or list of str}, optional
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Details are in the documentation of concat
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These data variables will be concatenated together:
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* 'minimal': Only data variables in which the dimension already
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appears are included.
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* 'different': Data variables which are not equal (ignoring
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attributes) across all datasets are also concatenated (as well as
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all for which dimension already appears). Beware: this option may
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load the data payload of data variables into memory if they are not
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already loaded.
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* 'all': All data variables will be concatenated.
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* list of str: The listed data variables will be concatenated, in
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addition to the 'minimal' data variables.
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If objects are DataArrays, `data_vars` must be 'all'.
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coords : {'minimal', 'different', 'all' or list of str}, optional
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Details are in the documentation of concat
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As per the 'data_vars' kwarg, but for coordinate variables.
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fill_value : scalar, optional
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Value to use for newly missing values
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join : {'outer', 'inner', 'left', 'right', 'exact'}, optional
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they are concatenated based on the values in their dimension coordinates,
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not on their position in the list passed to `combine_by_coords`.
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>>> import numpy as np
571+
>>> import xarray as xr
572+
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>>> x1 = xr.Dataset(
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... {
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... "temperature": (("y", "x"), 20 * np.random.rand(6).reshape(2, 3)),
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... "precipitation": (("y", "x"), np.random.rand(6).reshape(2, 3)),
577+
... },
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... coords={"y": [0, 1], "x": [10, 20, 30]},
579+
... )
580+
>>> x2 = xr.Dataset(
581+
... {
582+
... "temperature": (("y", "x"), 20 * np.random.rand(6).reshape(2, 3)),
583+
... "precipitation": (("y", "x"), np.random.rand(6).reshape(2, 3)),
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... },
585+
... coords={"y": [2, 3], "x": [10, 20, 30]},
586+
... )
587+
>>> x3 = xr.Dataset(
588+
... {
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... "temperature": (("y", "x"), 20 * np.random.rand(6).reshape(2, 3)),
590+
... "precipitation": (("y", "x"), np.random.rand(6).reshape(2, 3)),
591+
... },
592+
... coords={"y": [2, 3], "x": [40, 50, 60]},
593+
... )
594+
559595
>>> x1
560596
<xarray.Dataset>
561-
Dimensions: (x: 3)
562-
Coords:
563-
* position (x) int64 0 1 2
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Dimensions: (x: 3, y: 2)
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Coordinates:
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* y (y) int64 0 1
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* x (x) int64 10 20 30
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Data variables:
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temperature (x) float64 11.04 23.57 20.77 ...
602+
temperature (y, x) float64 1.654 10.63 7.015 2.543 13.93 9.436
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precipitation (y, x) float64 0.2136 0.9974 0.7603 0.4679 0.3115 0.945
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>>> x2
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<xarray.Dataset>
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Dimensions: (x: 3)
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Coords:
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* position (x) int64 3 4 5
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Dimensions: (x: 3, y: 2)
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Coordinates:
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* y (y) int64 2 3
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* x (x) int64 10 20 30
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Data variables:
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temperature (y, x) float64 9.341 0.1251 6.269 7.709 8.82 2.316
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precipitation (y, x) float64 0.1728 0.1178 0.03018 0.6509 0.06938 0.3792
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>>> x3
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<xarray.Dataset>
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Dimensions: (x: 3, y: 2)
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Coordinates:
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* y (y) int64 2 3
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* x (x) int64 40 50 60
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Data variables:
573-
temperature (x) float64 6.97 8.13 7.42 ...
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temperature (y, x) float64 2.789 2.446 6.551 12.46 2.22 15.96
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precipitation (y, x) float64 0.4804 0.1902 0.2457 0.6125 0.4654 0.5953
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>>> combined = xr.combine_by_coords([x2, x1])
625+
>>> xr.combine_by_coords([x2, x1])
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<xarray.Dataset>
577-
Dimensions: (x: 6)
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Coords:
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* position (x) int64 0 1 2 3 4 5
627+
Dimensions: (x: 3, y: 4)
628+
Coordinates:
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* x (x) int64 10 20 30
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* y (y) int64 0 1 2 3
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Data variables:
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temperature (x) float64 11.04 23.57 20.77 ...
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temperature (y, x) float64 1.654 10.63 7.015 2.543 ... 7.709 8.82 2.316
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precipitation (y, x) float64 0.2136 0.9974 0.7603 ... 0.6509 0.06938 0.3792
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635+
>>> xr.combine_by_coords([x3, x1])
636+
<xarray.Dataset>
637+
Dimensions: (x: 6, y: 4)
638+
Coordinates:
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* x (x) int64 10 20 30 40 50 60
640+
* y (y) int64 0 1 2 3
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Data variables:
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temperature (y, x) float64 1.654 10.63 7.015 nan ... nan 12.46 2.22 15.96
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precipitation (y, x) float64 0.2136 0.9974 0.7603 ... 0.6125 0.4654 0.5953
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>>> xr.combine_by_coords([x3, x1], join='override')
646+
<xarray.Dataset>
647+
Dimensions: (x: 3, y: 4)
648+
Coordinates:
649+
* x (x) int64 10 20 30
650+
* y (y) int64 0 1 2 3
651+
Data variables:
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temperature (y, x) float64 1.654 10.63 7.015 2.543 ... 12.46 2.22 15.96
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precipitation (y, x) float64 0.2136 0.9974 0.7603 ... 0.6125 0.4654 0.5953
654+
582655
"""
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584657
# Group by data vars

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