10000 Handle New PyFlakes Issues by WillAyd · Pull Request #25697 · pandas-dev/pandas · GitHub
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Handle New PyFlakes Issues #25697

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986abb3
Fixed non-typing issues
WillAyd Mar 12, 2019
c7e3574
Modified pep8speaks
WillAyd Mar 12, 2019
2f2bffd
Replaced tab with newline
WillAyd Mar 12, 2019
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Fixed non-typing issues
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@WillAyd
WillAyd committed Mar 12, 2019
commit 986abb3d3b080ef74e90d49bfad8ddefcbd60176
2 changes: 1 addition & 1 deletion pandas/_libs/tslibs/nattype.pyx
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Expand Up @@ -353,7 +353,7 @@ class NaTType(_NaT):

.. versionadded:: 0.23.0
""")
day_name = _make_nan_func('day_name', # noqa:E128
day_name = _make_nan_func('day_name', # noqa:E128
"""
Return the day name of the Timestamp with specified locale.

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2 changes: 1 addition & 1 deletion pandas/core/dtypes/dtypes.py
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Expand Up @@ -937,7 +937,7 @@ def construct_from_string(cls, string):

if (string.lower() == 'interval' or
cls._match.search(string) is not None):
return cls(string)
return cls(string)

msg = ('Incorrectly formatted string passed to constructor. '
'Valid formats include Interval or Interval[dtype] '
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1 change: 0 additions & 1 deletion pandas/io/formats/format.py
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Expand Up @@ -440,7 +440,6 @@ def _chk_truncate(self):
max_rows = self.max_rows

if max_cols == 0 or max_rows == 0: # assume we are in the terminal
# (why else = 0)
(w, h) = get_terminal_size()
self.w = w
self.h = h
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5 changes: 3 additions & 2 deletions pandas/tests/frame/test_alter_axes.py
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Expand Up @@ -201,7 +201,8 @@ def test_set_index_pass_arrays_duplicate(self, frame_of_index_cols, drop,
# need to adapt first drop for case that both keys are 'A' --
# cannot drop the same column twice;
# use "is" because == would give ambiguous Boolean error for containers
first_drop = False if (keys[0] is 'A' and keys[1] is 'A') else drop
first_drop = False if (
keys[0] is 'A' and keys[1] is 'A') else drop # noqa: F632

# to test against already-tested behaviour, we add sequentially,
# hence second append always True; must wrap keys in list, otherwise
Expand Down Expand Up @@ -1272,7 +1273,7 @@ def test_rename_axis_style_raises(self):
df.rename(id, mapper=id)

def test_reindex_api_equivalence(self):
# equivalence of the labels/axis and index/columns API's
# equivalence of the labels/axis and index/columns API's
df = DataFrame([[1, 2, 3], [3, 4, 5], [5, 6, 7]],
index=['a', 'b', 'c'],
columns=['d', 'e', 'f'])
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2 changes: 1 addition & 1 deletion pandas/tests/groupby/test_apply.py
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Expand Up @@ -9,7 +9,7 @@


def test_apply_issues():
# GH 5788
# GH 5788

s = """2011.05.16,00:00,1.40893
2011.05.16,01:00,1.40760
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22 changes: 11 additions & 11 deletions pandas/tests/groupby/test_grouping.py
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Expand Up @@ -649,17 +649,17 @@ def test_groupby_with_single_column(self):
tm.assert_frame_equal(df.groupby('a').nth(1), exp)

def test_gb_key_len_equal_axis_len(self):
# GH16843
# test ensures that index and column keys are recognized correctly
# when number of keys equals axis length of groupby
df = pd.DataFrame([['foo', 'bar', 'B', 1],
['foo', 'bar', 'B', 2],
['foo', 'baz', 'C', 3]],
columns=['first', 'second', 'third', 'one'])
df = df.set_index(['first', 'second'])
df = df.groupby(['first', 'second', 'third']).size()
assert df.loc[('foo', 'bar', 'B')] == 2
assert df.loc[('foo', 'baz', 'C')] == 1
# GH16843
# test ensures that index and column keys are recognized correctly
# when number of keys equals axis length of groupby
df = pd.DataFrame([['foo', 'bar', 'B', 1],
['foo', 'bar', 'B', 2],
['foo', 'baz', 'C', 3]],
columns=['first', 'second', 'third', 'one'])
df = df.set_index(['first', 'second'])
df = df.groupby(['first', 'second', 'third']).size()
assert df.loc[('foo', 'bar', 'B')] == 2
assert df.loc[('foo', 'baz', 'C')] == 1


# groups & iteration
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2 changes: 1 addition & 1 deletion pandas/tests/indexes/interval/test_interval_tree.py
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Expand Up @@ -159,7 +159,7 @@ def test_is_overlapping_endpoints(self, closed, order):
left, right = np.arange(3), np.arange(1, 4)
tree = IntervalTree(left[order], right[order], closed=closed)
result = tree.is_overlapping
expected = closed is 'both'
expected = closed == 'both'
assert result is expected

@pytest.mark.parametrize('left, right', [
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4 changes: 2 additions & 2 deletions pandas/tests/io/test_pytables.py
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Expand Up @@ -2386,8 +2386,8 @@ def test_empty_series_frame(self):
@pytest.mark.parametrize(
'dtype', [np.int64, np.float64, np.object, 'm8[ns]', 'M8[ns]'])
def test_empty_series(self, dtype):
s = Series(dtype=dtype)
self._check_roundtrip(s, tm.assert_series_equal)
s = Series(dtype=dtype)
self._check_roundtrip(s, tm.assert_series_equal)

def test_can_serialize_dates(self):

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48 changes: 24 additions & 24 deletions pandas/tests/series/test_rank.py
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Expand Up @@ -421,10 +421,10 @@ def test_rank_modify_inplace(self):
([1, 1, 3, 3, 5, 5], [1. / 3, 1. / 3, 2. / 3, 2. / 3, 3. / 3, 3. / 3]),
([-5, -4, -3, -2, -1], [1. / 5, 2. / 5, 3. / 5, 4. / 5, 5. / 5])])
def test_rank_dense_pct(dtype, ser, exp):
s = Series(ser).astype(dtype)
result = s.rank(method='dense', pct=True)
expected = Series(exp).astype(result.dtype)
assert_series_equal(result, expected)
s = Series(ser).astype(dtype)
result = s.rank(method='dense', pct=True)
expected = Series(exp).astype(result.dtype)
assert_series_equal(result, expected)


@pytest.mark.parametrize('dtype', ['O', 'f8', 'i8'])
Expand All @@ -439,10 +439,10 @@ def test_rank_dense_pct(dtype, 8000 ser, exp):
([1, 1, 3, 3, 5, 5], [1. / 6, 1. / 6, 3. / 6, 3. / 6, 5. / 6, 5. / 6]),
([-5, -4, -3, -2, -1], [1. / 5, 2. / 5, 3. / 5, 4. / 5, 5. / 5])])
def test_rank_min_pct(dtype, ser, exp):
s = Series(ser).astype(dtype)
result = s.rank(method='min', pct=True)
expected = Series(exp).astype(result.dtype)
assert_series_equal(result, expected)
s = Series(ser).astype(dtype)
result = s.rank(method='min', pct=True)
expected = Series(exp).astype(result.dtype)
assert_series_equal(result, expected)


@pytest.mark.parametrize('dtype', ['O', 'f8', 'i8'])
Expand All @@ -457,10 +457,10 @@ def test_rank_min_pct(dtype, ser, exp):
([1, 1, 3, 3, 5, 5], [2. / 6, 2. / 6, 4. / 6, 4. / 6, 6. / 6, 6. / 6]),
([-5, -4, -3, -2, -1], [1. / 5, 2. / 5, 3. / 5, 4. / 5, 5. / 5])])
def test_rank_max_pct(dtype, ser, exp):
s = Series(ser).astype(dtype)
result = s.rank(method='max', pct=True)
expected = Series(exp).astype(result.dtype)
assert_series_equal(result, expected)
s = Series(ser).astype(dtype)
result = s.rank(method='max', pct=True)
expected = Series(exp).astype(result.dtype)
assert_series_equal(result, expected)


@pytest.mark.parametrize('dtype', ['O', 'f8', 'i8'])
Expand All @@ -476,10 +476,10 @@ def test_rank_max_pct(dtype, ser, exp):
[1.5 / 6, 1.5 / 6, 3.5 / 6, 3.5 / 6, 5.5 / 6, 5.5 / 6]),
([-5, -4, -3, -2, -1], [1. / 5, 2. / 5, 3. / 5, 4. / 5, 5. / 5])])
def test_rank_average_pct(dtype, ser, exp):
s = Series(ser).astype(dtype)
result = s.rank(method='average', pct=True)
expected = Series(exp).astype(result.dtype)
assert_series_equal(result, expected)
s = Series(ser).astype(dtype)
result = s.rank(method='average', pct=True)
expected = Series(exp).astype(result.dtype)
assert_series_equal(result, expected)


@pytest.mark.parametrize('dtype', ['f8', 'i8'])
Expand All @@ -494,16 +494,16 @@ def test_rank_average_pct(dtype, ser, exp):
([1, 1, 3, 3, 5, 5], [1. / 6, 2. / 6, 3. / 6, 4. / 6, 5. / 6, 6. / 6]),
([-5, -4, -3, -2, -1], [1. / 5, 2. / 5, 3. / 5, 4. / 5, 5. / 5])])
def test_rank_first_pct(dtype, ser, exp):
s = Series(ser).astype(dtype)
result = s.rank(method='first', pct=True)
expected = Series(exp).astype(result.dtype)
assert_series_equal(result, expected)
s = Series(ser).astype(dtype)
result = s.rank(method='first', pct=True)
expected = Series(exp).astype(result.dtype)
assert_series_equal(result, expected)


@pytest.mark.single
@pytest.mark.high_memory
def test_pct_max_many_rows():
# GH 18271
s = Series(np.arange(2**24 + 1))
result = s.rank(pct=True).max()
assert result == 1
# GH 18271
s = Series(np.arange(2**24 + 1))
result = s.rank(pct=True).max()
assert result == 1
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