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Merged
jsignell merged 6 commits into from
Jan 20, 2026
Merged

Better ordering of coords in repr #11091

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42c6ce9
Updating coords ordering to keep matching dims together based on @ian…
jsignell Jan 16, 2026
9898f1c
Update tests to match new order
jsignell Jan 16, 2026
9ef813e
Update docstring examples with new coord order
jsignell Jan 16, 2026
76bf15b
Try to make the comments clearer
jsignell Jan 20, 2026
24039b7
Merge branch 'main' into ordered-coords
jsignell Jan 20, 2026
6b245e3
Update what's new
jsignell Jan 20, 2026
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2 changes: 2 additions & 0 deletions doc/whats-new.rst
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Expand Up @@ -36,6 +36,8 @@ New Features
of the same name are compared for potential conflicts when performing binary operations. The default for it is
``arithmetic_compat='minimal'`` which matches the existing behaviour.
By `Matthew Willson <https://github.com/mjwillson>`_.
- Better ordering of coordinates when displaying Xarray objects. (:pull:`11098`).
By `Ian Hunt-Isaak <https://github.com/ianhi>`_, `Julia Signell <https://github.com/jsignell>`_.

Breaking Changes
~~~~~~~~~~~~~~~~
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4 changes: 2 additions & 2 deletions xarray/core/common.py
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Expand Up @@ -619,9 +619,9 @@ def assign_coords(
<xarray.Dataset> Size: 360B
Dimensions: (x: 2, y: 2, time: 4)
Coordinates:
* time (time) datetime64[ns] 32B 2014-09-06 ... 2014-09-09
lon (x, y) float64 32B 260.2 260.7 260.2 260.8
lat (x, y) float64 32B 42.25 42.21 42.63 42.59
* time (time) datetime64[ns] 32B 2014-09-06 ... 2014-09-09
reference_time datetime64[ns] 8B 2014-09-05
Dimensions without coordinates: x, y
Data variables:
Expand All @@ -633,9 +633,9 @@ def assign_coords(
<xarray.Dataset> Size: 360B
Dimensions: (x: 2, y: 2, time: 4)
Coordinates:
* time (time) datetime64[ns] 32B 2014-09-06 ... 2014-09-09
lon (x, y) float64 32B -99.83 -99.32 -99.79 -99.23
lat (x, y) float64 32B 42.25 42.21 42.63 42.59
* time (time) datetime64[ns] 32B 2014-09-06 ... 2014-09-09
reference_time datetime64[ns] 8B 2014-09-05
Dimensions without coordinates: x, y
Data variables:
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8 changes: 4 additions & 4 deletions xarray/core/dataarray.py
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Expand Up @@ -369,9 +369,9 @@ class DataArray(
[[22.60070734, 13.78914233, 14.17424919],
[18.28478802, 16.15234857, 26.63418806]]])
Coordinates:
* time (time) datetime64[ns] 24B 2014-09-06 2014-09-07 2014-09-08
lon (x, y) float64 32B -99.83 -99.32 -99.79 -99.23
lat (x, y) float64 32B 42.25 42.21 42.63 42.59
* time (time) datetime64[ns] 24B 2014-09-06 2014-09-07 2014-09-08
reference_time datetime64[ns] 8B 2014-09-05
Dimensions without coordinates: x, y
Attributes:
Expand Down Expand Up @@ -2807,8 +2807,8 @@ def set_index(
[1., 1., 1.]])
Coordinates:
* x (x) int64 16B 0 1
* y (y) int64 24B 0 1 2
a (x) int64 16B 3 4
* y (y) int64 24B 0 1 2
>>> arr.set_index(x="a")
<xarray.DataArray (x: 2, y: 3)> Size: 48B
array([[1., 1., 1.],
Expand Down Expand Up @@ -5964,8 +5964,8 @@ def pad(
[nan, nan, nan, nan]])
Coordinates:
* x (x) float64 32B nan 0.0 1.0 nan
* y (y) int64 32B 10 20 30 40
z (x) float64 32B nan 100.0 200.0 nan
* y (y) int64 32B 10 20 30 40

Careful, ``constant_values`` are coerced to the data type of the array which may
lead to a loss of precision:
Expand All @@ -5978,8 +5978,8 @@ def pad(
[ 1, 1, 1, 1]])
Coordinates:
* x (x) float64 32B nan 0.0 1.0 nan
* y (y) int64 32B 10 20 30 40
z (x) float64 32B nan 100.0 200.0 nan
* y (y) int64 32B 10 20 30 40
"""
ds = self._to_temp_dataset().pad(
pad_width=pad_width,
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10 changes: 5 additions & 5 deletions xarray/core/dataset.py
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Expand Up @@ -322,10 +322,10 @@ class Dataset(
<xarray.Dataset> Size: 552B
Dimensions: (loc: 2, instrument: 3, time: 4)
Coordinates:
* instrument (instrument) <U8 96B 'manufac1' 'manufac2' 'manufac3'
* time (time) datetime64[ns] 32B 2014-09-06 ... 2014-09-09
lon (loc) float64 16B -99.83 -99.32
lat (loc) float64 16B 42.25 42.21
* instrument (instrument) <U8 96B 'manufac1' 'manufac2' 'manufac3'
* time (time) datetime64[ns] 32B 2014-09-06 ... 2014-09-09
reference_time datetime64[ns] 8B 2014-09-05
Dimensions without coordinates: loc
Data variables:
Expand Down Expand Up @@ -4733,8 +4733,8 @@ def set_index(
Dimensions: (x: 2, y: 3)
Coordinates:
* x (x) int64 16B 0 1
* y (y) int64 24B 0 1 2
a (x) int64 16B 3 4
* y (y) int64 24B 0 1 2
Data variables:
v (x, y) float64 48B 1.0 1.0 1.0 1.0 1.0 1.0
>>> ds.set_index(x="a")
Expand Down Expand Up @@ -8713,9 +8713,9 @@ def filter_by_attrs(self, **kwargs) -> Self:
<xarray.Dataset> Size: 192B
Dimensions: (x: 2, y: 2, time: 3)
Coordinates:
* time (time) datetime64[ns] 24B 2014-09-06 2014-09-07 2014-09-08
lon (x, y) float64 32B -99.83 -99.32 -99.79 -99.23
lat (x, y) float64 32B 42.25 42.21 42.63 42.59
* time (time) datetime64[ns] 24B 2014-09-06 2014-09-07 2014-09-08
reference_time datetime64[ns] 8B 2014-09-05
Dimensions without coordinates: x, y
Data variables:
Expand All @@ -8728,9 +8728,9 @@ def filter_by_attrs(self, **kwargs) -> Self:
<xarray.Dataset> Size: 288B
Dimensions: (x: 2, y: 2, time: 3)
Coordinates:
* time (time) datetime64[ns] 24B 2014-09-06 2014-09-07 2014-09-08
lon (x, y) float64 32B -99.83 -99.32 -99.79 -99.23
lat (x, y) float64 32B 42.25 42.21 42.63 42.59
* time (time) datetime64[ns] 24B 2014-09-06 2014-09-07 2014-09-08
reference_time datetime64[ns] 8B 2014-09-05
Dimensions without coordinates: x, y
Data variables:
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28 changes: 27 additions & 1 deletion xarray/core/formatting.py
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Expand Up @@ -443,12 +443,38 @@ def _mapping_repr(
)


def _coord_sort_key(coord, dims):
"""Sort key for coordinate ordering.

Orders by:
1. Primary: index of the matching dimension in dataset dims.
2. Secondary: dimension coordinates (name == dim) come before non-dimension coordinates

This groups non-dimension coordinates right after their associated dimension
coordinate.
"""
name, var = coord

# Dimension coordinates come first within their dim section
if name in dims:
return (dims.index(name), 0)

# Non-dimension coordinates come second within their dim section
# Check the var.dims list in backwards order to put (x, y) after (x) and (y)
for d in var.dims[::-1]:
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@jsignell jsignell Jan 16, 2026 •
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I switched this to look at dims in reverse order because this feels like the right order:

        >>> import numpy as np
        >>> import xarray as xr
        >>> temperature = np.arange(25).reshape(5, 5)
        >>> pressure = np.arange(50, 75).reshape(5, 5)
        >>> da = xr.DataArray(
        ...     data=temperature,
        ...     dims=["x", "y"],
        ...     coords=dict(
        ...         lon=("x", np.arange(10, 15)),
        ...         lat=("y", np.arange(20, 25)),
        ...         Pressure=(["x", "y"], pressure),
        ...     ),
        ...     name="Temperature",
        ... )
        >>> da
        <xarray.DataArray 'Temperature' (x: 5, y: 5)> Size: 200B
        array([[ 0,  1,  2,  3,  4],
               [ 5,  6,  7,  8,  9],
               [10, 11, 12, 13, 14],
               [15, 16, 17, 18, 19],
               [20, 21, 22, 23, 24]])
        Coordinates:
            lon       (x) int64 40B 10 11 12 13 14
            lat       (y) int64 40B 20 21 22 23 24
            Pressure  (x, y) int64 200B 50 51 52 53 54 55 56 57 ... 68 69 70 71 72 73 74
        Dimensions without coordinates: x, y

if d in dims:
return (dims.index(d), 1)

# Scalar coords or coords with dims not in dataset dims go at the end
return (len(dims), 1)


def coords_repr(coords: AbstractCoordinates, col_width=None, max_rows=None):
if col_width is None:
col_width = _calculate_col_width(coords)
dims = tuple(coords._data.dims)
dim_ordered_coords = sorted(
coords.items(), key=lambda x: dims.index(x[0]) if x[0] in dims else len(dims)
coords.items(), key=functools.partial(_coord_sort_key, dims=dims)
)
return _mapping_repr(
dict(dim_ordered_coords),
Expand Down
3 changes: 2 additions & 1 deletion xarray/core/formatting_html.py
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Expand Up @@ -11,6 +11,7 @@
from typing import TYPE_CHECKING

from xarray.core.formatting import (
_coord_sort_key,
filter_nondefault_indexes,
inherited_vars,
inline_index_repr,
Expand Down Expand Up @@ -120,7 +121,7 @@ def summarize_coords(variables) -> str:
li_items = []
dims = tuple(variables._data.dims)
dim_ordered_coords = sorted(
variables.items(), key=lambda x: dims.index(x[0]) if x[0] in dims else len(dims)
variables.items(), key=partial(_coord_sort_key, dims=dims)
)
for k, v in dim_ordered_coords:
li_content = summarize_variable(k, v, is_index=k in variables.xindexes)
Expand Down
4 changes: 2 additions & 2 deletions xarray/structure/concat.py
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Expand Up @@ -239,8 +239,8 @@ def concat(
array([[0, 1, 2],
[3, 4, 5]])
Coordinates:
* y (y) int64 24B 10 20 30
x (new_dim) <U1 8B 'a' 'b'
* y (y) int64 24B 10 20 30
Dimensions without coordinates: new_dim

>>> xr.concat(
Expand All @@ -253,8 +253,8 @@ def concat(
[3, 4, 5]])
Coordinates:
* new_dim (new_dim) int64 16B -90 -100
* y (y) int64 24B 10 20 30
x (new_dim) <U1 8B 'a' 'b'
* y (y) int64 24B 10 20 30

# Concatenate a scalar variable along a new dimension of the same name with and without creating a new index

Expand Down
4 changes: 2 additions & 2 deletions xarray/tests/test_dataset.py
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Expand Up @@ -294,8 +294,8 @@ def test_repr(self) -> None:
Coordinates:
* dim2 (dim2) float64 72B 0.0 0.5 1.0 1.5 2.0 2.5 3.0 3.5 4.0
* dim3 (dim3) {data["dim3"].dtype} 40B 'a' 'b' 'c' 'd' 'e' 'f' 'g' 'h' 'i' 'j'
* time (time) datetime64[ns] 160B 2000-01-01 2000-01-02 ... 2000-01-20
numbers (dim3) int64 80B 0 1 2 0 0 1 1 2 2 3
* time (time) datetime64[ns] 160B 2000-01-01 2000-01-02 ... 2000-01-20
Dimensions without coordinates: dim1
Data variables:
var1 (dim1, dim2) float64 576B -0.9891 -0.3678 1.288 ... -0.2116 0.364
Expand Down Expand Up @@ -875,8 +875,8 @@ def test_coords_properties(self) -> None:
"""\
Coordinates:
* x (x) int64 16B -1 -2
* y (y) int64 24B 0 1 2
a (x) int64 16B 4 5
* y (y) int64 24B 0 1 2
b int64 8B -10"""
)
actual = repr(coords)
Expand Down
2 changes: 1 addition & 1 deletion xarray/tests/test_datatree.py
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Expand Up @@ -644,8 +644,8 @@ def test_properties(self) -> None:
"""\
Coordinates:
* x (x) int64 16B -1 -2
* y (y) int64 24B 0 1 2
a (x) int64 16B 4 5
* y (y) int64 24B 0 1 2
b int64 8B -10"""
)
actual = repr(coords)
Expand Down
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