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ENH: DataFrame sort columns by rows: sort_values(axis=1) #13622

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ENH: DataFrame sort columns by rows: sort_values(axis=1) #13622

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970e25b
DataFrame sort columns by rows: sort_values(axis=1)
IamJeffG Jun 21, 2016
0f23615
Whatsnew entry for DataFrame.sort_values by index (10806)
IamJeffG Jul 11, 2016
2773cdf
Tweak whatsnew entry
IamJeffG Jul 12, 2016
f43ab2e
Tweak whatsnew entry, once more
IamJeffG Jul 12, 2016
ea2d89e
More test cases. Clarify whatnew w/ example.
IamJeffG Jul 17, 2016
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1 change: 1 addition & 0 deletions doc/source/whatsnew/v0.19.0.txt
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Expand Up @@ -229,6 +229,7 @@ Other enhancements
- ``pd.read_html()`` has gained support for the ``decimal`` option (:issue:`12907`)
- A top-level function :func:`union_categorical` has been added for combining categoricals, see :ref:`Unioning Categoricals<categorical.union>` (:issue:`13361`)
- ``Series`` has gained the properties ``.is_monotonic``, ``.is_monotonic_increasing``, ``.is_monotonic_decreasing``, similar to ``Index`` (:issue:`13336`)
- ``DataFrame.sort_values()`` has gained support for re-ordering columns by index label (:issue:`10806`)
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this is not clear what actually you are changing. This is for axis 1 support for by

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Don't they mean the same thing? (by is always required sort_values, and axis 1 is equivalent to "columns".) See if the new wording in 2773cdf hits what you're getting at, otherwise can you please specify?

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The rewording in that commit is good! (exactly what I wanted to suggest to combine both :-))

Maybe just "with" after "columns"

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Done.


.. _whatsnew_0190.api:

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7 changes: 3 additions & 4 deletions pandas/core/frame.py
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Expand Up @@ -3127,9 +3127,8 @@ def sort_values(self, by, axis=0, ascending=True, inplace=False,
kind='quicksort', na_position='last'):

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can you update the .sort_values doc-string to look like others, e.g. look at sortlevel (for the axis arg)

axis = self._get_axis_number(axis)
other_axis = 0 if axis == 1 else 1

if axis != 0:
raise ValueError('When sorting by column, axis must be 0 (rows)')
if not isinstance(by, list):
by = [by]
if com.is_sequence(ascending) and len(by) != len(ascending):
Expand All @@ -3145,7 +3144,7 @@ def trans(v):

keys = []
for x in by:
k = self[x].values
k = self.xs(x, axis=other_axis).values
if k.ndim == 2:
raise ValueError('Cannot sort by duplicate column %s' %
str(x))
Expand All @@ -3157,7 +3156,7 @@ def trans(v):
from pandas.core.groupby import _nargsort

by = by[0]
k = self[by].values
k = self.xs(by, axis=other_axis).values
if k.ndim == 2:

# try to be helpful
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25 changes: 21 additions & 4 deletions pandas/tests/frame/test_sorting.py
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Expand Up @@ -84,7 +84,7 @@ def test_sort_values(self):
frame = DataFrame([[1, 1, 2], [3, 1, 0], [4, 5, 6]],
index=[1, 2, 3], columns=list('ABC'))

# by column
# by column (axis=0)
sorted_df = frame.sort_values(by='A')
indexer = frame['A'].argsort().values
expected = frame.ix[frame.index[indexer]]
Expand Down Expand Up @@ -116,9 +116,26 @@ def test_sort_values(self):
self.assertRaises(ValueError, lambda: frame.sort_values(
by=['A', 'B'], axis=2, inplace=True))

msg = 'When sorting by column, axis must be 0'
with assertRaisesRegexp(ValueError, msg):
frame.sort_values(by='A', axis=1)
# by row (axis=1): GH 10806
sorted_df = frame.sort_values(by=3, axis=1)
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throw in an axis='columns' instead of one of the axis=1

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Do you mean that the string columns should be supported as a valid axis value? That's neat. Can you point me to where that's documented though? I can't find reference to it.

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this is what _get_axis_number(..) does

the doc-string should be something like:

axis : {index (0), columns (1)}

which we programatically generate (this is from DataFrame.min for example), look in generic.py to see how

expected = frame
assert_frame_equal(sorted_df, expected)

sorted_df = frame.sort_values(by=3, axis=1, ascending=False)
expected = frame.reindex(columns=['C', 'B', 'A'])
assert_frame_equal(sorted_df, expected)

sorted_df = frame.sort_values(by=[1, 2], axis=1)
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add a test for the other options, na_position (also add some nas), and inplace.

expected = frame.reindex(columns=['B', 'A', 'C'])
assert_frame_equal(sorted_df, expected)

sorted_df = frame.sort_values(by=[1, 3], axis=1,
ascending=[True, False])
assert_frame_equal(sorted_df, expected)

sorted_df = frame.sort_values(by=[1, 3], axis=1, ascending=False)
expected = frame.reindex(columns=['C', 'B', 'A'])
assert_frame_equal(sorted_df, expected)

msg = r'Length of ascending \(5\) != length of by \(2\)'
with assertRaisesRegexp(ValueError, msg):
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