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Jul 28, 2025
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DOC: Update documentation for using natural sort with sort_values #61979

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2a2cddf
Update documentation for sort_values and natural sorting
marc-jones Jul 28, 2025
713cc47
Remove natsort_keygen calls
marc-jones Jul 28, 2025
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50 changes: 29 additions & 21 deletions pandas/core/frame.py
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Original file line number Diff line number Diff line change
Expand Up @@ -7173,35 +7173,43 @@ def sort_values(
`natural sorting <https://en.wikipedia.org/wiki/Natural_sort_order>`__.
This can be done using
``natsort`` `package <https://github.com/SethMMorton/natsort>`__,
which provides sorted indices according
to their natural order, as shown below:
which provides a function to generate a key
to sort data in their natural order:

>>> df = pd.DataFrame(
... {
... "time": ["0hr", "128hr", "72hr", "48hr", "96hr"],
... "value": [10, 20, 30, 40, 50],
... "hours": ["0hr", "128hr", "0hr", "64hr", "64hr", "128hr"],
... "mins": [
... "10mins",
... "40mins",
... "40mins",
... "40mins",
... "10mins",
... "10mins",
... ],
... "value": [10, 20, 30, 40, 50, 60],
... }
... )
>>> df
time value
0 0hr 10
1 128hr 20
2 72hr 30
3 48hr 40
4 96hr 50
>>> from natsort import index_natsorted
>>> index_natsorted(df["time"])
[0, 3, 2, 4, 1]
hours mins value
0 0hr 10mins 10
1 128hr 40mins 20
2 0hr 40mins 30
3 64hr 40mins 40
4 64hr 10mins 50
5 128hr 10mins 60
>>> from natsort import natsort_keygen
>>> df.sort_values(
... by="time",
... key=lambda x: np.argsort(index_natsorted(x)),
... by=["hours", "mins"],
... key=natsort_keygen(),
... )
time value
0 0hr 10
3 48hr 40
2 72hr 30
4 96hr 50
1 128hr 20
hours mins value
0 0hr 10mins 10
2 0hr 40mins 30
4 64hr 10mins 50
3 64hr 40mins 40
5 128hr 10mins 60
1 128hr 40mins 20
"""
inplace = validate_bool_kwarg(inplace, "inplace")
axis = self._get_axis_number(axis)
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43 changes: 27 additions & 16 deletions pandas/core/generic.py
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Original file line number Diff line number Diff line change
Expand Up @@ -5004,27 +5004,38 @@ def sort_values(

>>> df = pd.DataFrame(
... {
... "time": ["0hr", "128hr", "72hr", "48hr", "96hr"],
... "value": [10, 20, 30, 40, 50],
... "hours": ["0hr", "128hr", "0hr", "64hr", "64hr", "128hr"],
... "mins": [
... "10mins",
... "40mins",
... "40mins",
... "40mins",
... "10mins",
... "10mins",
... ],
... "value": [10, 20, 30, 40, 50, 60],
... }
... )
>>> df
time value
0 0hr 10
1 128hr 20
2 72hr 30
3 48hr 40
4 96hr 50
>>> from natsort import index_natsorted
hours mins value
0 0hr 10mins 10
1 128hr 40mins 20
2 0hr 40mins 30
3 64hr 40mins 40
4 64hr 10mins 50
5 128hr 10mins 60
>>> from natsort import natsort_keygen
>>> df.sort_values(
... by="time", key=lambda x: np.argsort(index_natsorted(df["time"]))
... by=["hours", "mins"],
... key=natsort_keygen(),
... )
time value
0 0hr 10
3 48hr 40
2 72hr 30
4 96hr 50
1 128hr 20
hours mins value
0 0hr 10mins 10
2 0hr 40mins 30
4 64hr 10mins 50
3 64hr 40mins 40
5 128hr 10mins 60
1 128hr 40mins 20
"""
raise AbstractMethodError(self)

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