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Docstring examples (#7881)
* add examples * changes done to dataset.isel * Changes done on isel and reduce * xarray.dataset.tail * xarray.dataset.head * xarray.dataset.dropna * xarray.dataset.ffill * xarray.dataset.bfill * xarray.dataset.set_Coords * xarray.dataset.reset_coords * Revert "xarray.dataset.reset_coords" This reverts commit 7575a12. * Revert "xarray.dataset.tail" This reverts commit ee8ba41. * Revert "xarray.dataset.head" This reverts commit 82e1161. * Revert "xarray.dataset.dropna" This reverts commit 760aa4a. * Revert "xarray.dataset.ffill" This reverts commit 848a5fd. * Revert "xarray.dataset.bfill" This reverts commit eb7514e. * Revert "xarray.dataset.set_Coords" This reverts commit 5ecfd63. * check pre-commit * changes * argmin_indices * Try adding blank lines * indentation change * indentation * removed dataset.reduce 'skew' example * doctests * change * argmin * Update xarray/core/dataset.py Co-authored-by: Tom Nicholas <thomas.nicholas@columbia.edu> * what's new.rst updated * Move whatsnew entry to unreleased version --------- Co-authored-by: Tom Nicholas <thomas.nicholas@columbia.edu>
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‎doc/whats-new.rst

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@@ -40,6 +40,10 @@ Documentation
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- Expanded the page on wrapping numpy-like "duck" arrays.
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(:pull:`7911`) By `Tom Nicholas <https://github.com/TomNicholas>`_.
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- Added examples to docstrings of :py:meth:`Dataset.isel`, :py:meth:`Dataset.reduce`, :py:meth:`Dataset.argmin`,
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:py:meth:`Dataset.argmax` (:issue:`6793`, :pull:`7881`)
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By `Harshitha <https://github.com/harshitha1201>`_ .
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Internal Changes
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~~~~~~~~~~~~~~~~

‎xarray/core/dataset.py

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@@ -2497,6 +2497,63 @@ def isel(
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in this dataset, unless vectorized indexing was triggered by using
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an array indexer, in which case the data will be a copy.
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Examples
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--------
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>>> dataset = xr.Dataset(
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... {
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... "math_scores": (
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... ["student", "test"],
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... [[90, 85, 92], [78, 80, 85], [95, 92, 98]],
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... ),
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... "english_scores": (
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... ["student", "test"],
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... [[88, 90, 92], [75, 82, 79], [93, 96, 91]],
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... ),
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... },
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... coords={
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... "student": ["Alice", "Bob", "Charlie"],
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... "test": ["Test 1", "Test 2", "Test 3"],
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... },
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... )
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# A specific element from the dataset is selected
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>>> dataset.isel(student=1, test=0)
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<xarray.Dataset>
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Dimensions: ()
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Coordinates:
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student <U7 'Bob'
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test <U6 'Test 1'
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Data variables:
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math_scores int64 78
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english_scores int64 75
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# Indexing with a slice using isel
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>>> slice_of_data = dataset.isel(student=slice(0, 2), test=slice(0, 2))
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>>> slice_of_data
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<xarray.Dataset>
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Dimensions: (student: 2, test: 2)
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Coordinates:
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* student (student) <U7 'Alice' 'Bob'
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* test (test) <U6 'Test 1' 'Test 2'
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Data variables:
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math_scores (student, test) int64 90 85 78 80
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english_scores (student, test) int64 88 90 75 82
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>>> index_array = xr.DataArray([0, 2], dims="student")
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>>> indexed_data = dataset.isel(student=index_array)
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>>> indexed_data
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<xarray.Dataset>
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Dimensions: (student: 2, test: 3)
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Coordinates:
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* student (student) <U7 'Alice' 'Charlie'
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* test (test) <U6 'Test 1' 'Test 2' 'Test 3'
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Data variables:
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math_scores (student, test) int64 90 85 92 95 92 98
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english_scores (student, test) int64 88 90 92 93 96 91
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See Also
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--------
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Dataset.sel
@@ -5922,6 +5979,38 @@ def reduce(
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reduced : Dataset
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Dataset with this object's DataArrays replaced with new DataArrays
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of summarized data and the indicated dimension(s) removed.
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Examples
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--------
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>>> dataset = xr.Dataset(
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... {
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... "math_scores": (
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... ["student", "test"],
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... [[90, 85, 92], [78, 80, 85], [95, 92, 98]],
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... ),
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... "english_scores": (
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... ["student", "test"],
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... [[88, 90, 92], [75, 82, 79], [93, 96, 91]],
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... ),
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... },
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... coords={
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... "student": ["Alice", "Bob", "Charlie"],
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... "test": ["Test 1", "Test 2", "Test 3"],
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... },
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... )
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# Calculate the 75th percentile of math scores for each student using np.percentile
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>>> percentile_scores = dataset.reduce(np.percentile, q=75, dim="test")
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>>> percentile_scores
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<xarray.Dataset>
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Dimensions: (student: 3)
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Coordinates:
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* student (student) <U7 'Alice' 'Bob' 'Charlie'
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Data variables:
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math_scores (student) float64 91.0 82.5 96.5
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english_scores (student) float64 91.0 80.5 94.5
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"""
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if kwargs.get("axis", None) is not None:
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raise ValueError(
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-------
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result : Dataset
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Examples
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--------
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>>> dataset = xr.Dataset(
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... {
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... "math_scores": (
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... ["student", "test"],
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... [[90, 85, 79], [78, 80, 85], [95, 92, 98]],
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... ),
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... "english_scores": (
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... ["student", "test"],
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... [[88, 90, 92], [75, 82, 79], [39, 96, 78]],
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... ),
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... },
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... coords={
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... "student": ["Alice", "Bob", "Charlie"],
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... "test": ["Test 1", "Test 2", "Test 3"],
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... },
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... )
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# Indices of the minimum values along the 'student' dimension are calculated
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>>> argmin_indices = dataset.argmin(dim="student")
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>>> min_score_in_math = dataset["student"].isel(
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... student=argmin_indices["math_scores"]
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... )
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>>> min_score_in_math
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<xarray.DataArray 'student' (test: 3)>
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array(['Bob', 'Bob', 'Alice'], dtype='<U7')
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Coordinates:
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student (test) <U7 'Bob' 'Bob' 'Alice'
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* test (test) <U6 'Test 1' 'Test 2' 'Test 3'
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>>> min_score_in_english = dataset["student"].isel(
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... student=argmin_indices["english_scores"]
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... )
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>>> min_score_in_english
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<xarray.DataArray 'student' (test: 3)>
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array(['Charlie', 'Bob', 'Charlie'], dtype='<U7')
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Coordinates:
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student (test) <U7 'Charlie' 'Bob' 'Charlie'
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* test (test) <U6 'Test 1' 'Test 2' 'Test 3'
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See Also
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--------
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Dataset.idxmin
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DataArray.argmin
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"""
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if dim is None:
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-------
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result : Dataset
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Examples
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--------
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>>> dataset = xr.Dataset(
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... {
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... "math_scores": (
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... ["student", "test"],
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... [[90, 85, 92], [78, 80, 85], [95, 92, 98]],
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... ),
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... "english_scores": (
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... ["student", "test"],
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... [[88, 90, 92], [75, 82, 79], [93, 96, 91]],
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... ),
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... },
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... coords={
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... "student": ["Alice", "Bob", "Charlie"],
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... "test": ["Test 1", "Test 2", "Test 3"],
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... },
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... )
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# Indices of the maximum values along the 'student' dimension are calculated
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>>> argmax_indices = dataset.argmax(dim="test")
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>>> argmax_indices
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<xarray.Dataset>
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Dimensions: (student: 3)
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Coordinates:
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* student (student) <U7 'Alice' 'Bob' 'Charlie'
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Data variables:
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math_scores (student) int64 2 2 2
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english_scores (student) int64 2 1 1
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See Also
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--------
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DataArray.argmax

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