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BUG: Reindex with columns and method #14993

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2b5724b
BUG: Reindex with columns and method
Dec 26, 2016
fdbd901
BUG: Tests for reindex with columns and methods
Dec 26, 2016
9c9ad95
BUG: Add tests for sparse dataframe
Dec 27, 2016
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1 change: 1 addition & 0 deletions doc/source/whatsnew/v0.20.0.txt
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Original file line number Diff line number Diff line change
Expand Up @@ -285,6 +285,7 @@ Bug Fixes
- Bug in ``DataFrame(..).apply(to_numeric)`` when values are of type decimal.Decimal. (:issue:`14827`)
- Bug in ``describe()`` when passing a numpy array which does not contain the median to the ``percentiles`` keyword argument (:issue:`14908`)
- Bug in ``DataFrame.sort_values()`` when sorting by multiple columns where one column is of type ``int64`` and contains ``NaT`` (:issue:`14922`)
- Bug in ``DataFrame.reindex()`` when using ``columns`` and ``method`` (:issue:`14992`)
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say that when passingcolumns, method was ignored.



- Bug in ``pd.read_msgpack()`` in which ``Series`` categoricals were being improperly processed (:issue:`14901`)
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14 changes: 7 additions & 7 deletions pandas/core/frame.py
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Expand Up @@ -2710,8 +2710,8 @@ def _reindex_axes(self, axes, level, limit, tolerance, method, fill_value,

columns = axes['columns']
if columns is not None:
frame = frame._reindex_columns(columns, copy, level, fill_value,
limit, tolerance)
frame = frame._reindex_columns(columns, method, copy, level,
fill_value, limit, tolerance)

index = axes['index']
if index is not None:
Expand All @@ -2722,17 +2722,17 @@ def _reindex_axes(self, axes, level, limit, tolerance, method, fill_value,

def _reindex_index(self, new_index, method, copy, level, fill_value=NA,
limit=None, tolerance=None):
new_index, indexer = self.index.reindex(new_index, method, level,
limit=limit,
new_index, indexer = self.index.reindex(new_index, method=method,
level=level, limit=limit,
tolerance=tolerance)
return self._reindex_with_indexers({0: [new_index, indexer]},
copy=copy, fill_value=fill_value,
allow_dups=False)

def _reindex_columns(self, new_columns, copy, level, fill_value=NA,
def _reindex_columns(self, new_columns, method, copy, level, fill_value=NA,
limit=None, tolerance=None):
new_columns, indexer = self.columns.reindex(new_columns, level=level,
limit=limit,
new_columns, indexer = self.columns.reindex(new_columns, method=method,
level=level, limit=limit,
tolerance=tolerance)
return self._reindex_with_indexers({1: [new_columns, indexer]},
copy=copy, fill_value=fill_value,
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4 changes: 2 additions & 2 deletions pandas/sparse/frame.py
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Expand Up @@ -571,8 +571,8 @@ def _reindex_index(self, index, method, copy, level, fill_value=np.nan,
new_series, index=index, columns=self.columns,
default_fill_value=self._default_fill_value).__finalize__(self)

def _reindex_columns(self, columns, copy, level, fill_value, limit=None,
takeable=False):
def _reindex_columns(self, columns, method, copy, level, fill_value,
limit=None, takeable=False):
if level is not None:
raise TypeError('Reindex by level not supported for sparse')

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29 changes: 29 additions & 0 deletions pandas/tests/frame/test_axis_select_reindex.py
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Expand Up @@ -297,6 +297,35 @@ def test_reindex_columns(self):
newFrame = self.frame.reindex(columns=[])
self.assertTrue(newFrame.empty)

# GH 14992, reindexing over columns ignored method
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you can make it a new test

df = DataFrame(data=[[11, 12, 13], [21, 22, 23], [31, 32, 33]],
index=[1, 2, 4],
columns=[1, 2, 4],
dtype=float)
expected_def = DataFrame(data=[[np.nan, 11, 12, np.nan, 13, np.nan],
[np.nan, 21, 22, np.nan, 23, np.nan],
[np.nan, 31, 32, np.nan, 33, np.nan]],
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you can just do these as:

result = ....
expected = ...
assert_frame_equal(result, expected)

easier to read this way

index=[1, 2, 4],
columns=range(6),
dtype=float)
expected_ffill = DataFrame(data=[[np.nan, 11, 12, 12, 13, 13],
[np.nan, 21, 22, 22, 23, 23],
[np.nan, 31, 32, 32, 33, 33]],
index=[1, 2, 4],
columns=range(6),
dtype=float)
expected_bfill = DataFrame(data=[[11, 11, 12, 13, 13, np.nan],
[21, 21, 22, 23, 23, np.nan],
[31, 31, 32, 33, 33, np.nan]],
index=[1, 2, 4],
columns=range(6),
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add similar tests for sparse as well.

dtype=float)
assert_frame_equal(df.reindex(columns=range(6)), expected_def)
assert_frame_equal(df.reindex(columns=range(6), method='ffill'),
expected_ffill)
assert_frame_equal(df.reindex(columns=range(6), method='bfill'),
expected_bfill)

def test_reindex_axes(self):
# GH 3317, reindexing by both axes loses freq of the index
df = DataFrame(np.ones((3, 3)),
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