10000 Remove SharedItems from test_excel by WillAyd · Pull Request #26579 · pandas-dev/pandas · GitHub
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Remove SharedItems from test_excel #26579

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Merged
merged 15 commits into from
Jun 5, 2019
Merged

Remove SharedItems from test_excel #26579

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f80e015
Reused and reorged seriesd fixture
WillAyd May 30, 2019
d10b8f2
Removed frame fixtures
WillAyd May 30, 2019
cfbd1c4
Removed shareditems
WillAyd May 30, 2019
02a3aea
lint fixup
WillAyd May 30, 2019
27ce9fc
Cleaned up ambiguous frame references
WillAyd May 30, 2019
d395132
Merge remote-tracking branch 'upstream/master' into fixturize-excel
WillAyd Jun 3, 2019
407149f
Reverted changes to frame tests
WillAyd Jun 3, 2019
88d378e
Reverted errant merge fixup
WillAyd Jun 3, 2019
4996340
Reverted changes to frame conftest
WillAyd Jun 3, 2019
0586759
Cleaned up fixture usage
WillAyd Jun 3, 2019
c59602b
Reverted groupby conftest from master
WillAyd Jun 3, 2019
3b739df
Fixed up failures with mixed fixture usage
WillAyd Jun 3, 2019
2d0d3dc
Used tsframe fixture where appropriate
WillAyd Jun 3, 2019
5d0b631
style fixes
WillAyd Jun 3, 2019
199909a
Added copy to frame2 fixture
WillAyd Jun 4, 2019
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Cleaned up ambiguous frame references
  • Loading branch information
@WillAyd
WillAyd committed May 30, 2019
commit 27ce9fc281aa544e3bb7b4b68a58c2a999c90b73
90 changes: 44 additions & 46 deletions pandas/tests/io/test_excel.py
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Original file line number Diff line number Diff line change
Expand Up @@ -1217,24 +1217,24 @@ def test_basics_with_nan(self, merge_cells, engine, ext, frame):

@pytest.mark.parametrize("np_type", [
np.int8, np.int16, np.int32, np.int64])
def test_int_types(self, merge_cells, engine, ext, np_type, frame):
def test_int_types(self, merge_cells, engine, ext, np_type):
# Test np.int values read come back as int
# (rather than float which is Excel's format).
frame = DataFrame(np.random.randint(-10, 10, size=(10, 2)),
dtype=np_type)
frame.to_excel(self.path, "test1")
df = DataFrame(np.random.randint(-10, 10, size=(10, 2)),
dtype=np_type)
df.to_excel(self.path, "test1")

reader = ExcelFile(self.path)
recons = pd.read_excel(reader, "test1", index_col=0)

int_frame = frame.astype(np.int64)
int_frame = df.astype(np.int64)
tm.assert_frame_equal(int_frame, recons)

recons2 = pd.read_excel(self.path, "test1", index_col=0)
tm.assert_frame_equal(int_frame, recons2)

# Test with convert_float=False comes back as float.
float_frame = frame.astype(float)
float_frame = df.astype(float)
recons = pd.read_excel(self.path, "test1",
convert_float=False, index_col=0)
tm.assert_frame_equal(recons, float_frame,
Expand All @@ -1243,35 +1243,35 @@ def test_int_types(self, merge_cells, engine, ext, np_type, frame):

@pytest.mark.parametrize("np_type", [
np.float16, np.float32, np.float64])
def test_float_types(self, merge_cells, engine, ext, np_type, frame):
def test_float_types(self, merge_cells, engine, ext, np_type):
# Test np.float values read come back as float.
frame = DataFrame(np.random.random_sample(10), dtype=np_type)
frame.to_excel(self.path, "test1")
df = DataFrame(np.random.random_sample(10), dtype=np_type)
df.to_excel(self.path, "test1")

reader = ExcelFile(self.path)
recons = pd.read_excel(reader, "test1", index_col=0).astype(np_type)

tm.assert_frame_equal(frame, recons, check_dtype=False)
tm.assert_frame_equal(df, recons, check_dtype=False)

@pytest.mark.parametrize("np_type", [np.bool8, np.bool_])
def test_bool_types(self, merge_cells, engine, ext, np_type, frame):
def test_bool_types(self, merge_cells, engine, ext, np_type):
# Test np.bool values read come back as float.
frame = (DataFrame([1, 0, True, False], dtype=np_type))
frame.to_excel(self.path, "test1")
df = (DataFrame([1, 0, True, False], dtype=np_type))
df.to_excel(self.path, "test1")

reader = ExcelFile(self.path)
recons = pd.read_excel(reader, "test1", index_col=0).astype(np_type)

tm.assert_frame_equal(frame, recons)
tm.assert_frame_equal(df, recons)

def test_inf_roundtrip(self, frame, *_):
frame = DataFrame([(1, np.inf), (2, 3), (5, -np.inf)])
frame.to_excel(self.path, "test1")
def test_inf_roundtrip(self, *_):
df = DataFrame([(1, np.inf), (2, 3), (5, -np.inf)])
df.to_excel(self.path, "test1")

reader = ExcelFile(self.path)
recons = pd.read_excel(reader, "test1", index_col=0)

tm.assert_frame_equal(frame, recons)
tm.assert_frame_equal(df, recons)

def test_sheets(self, merge_cells, engine, ext, frame, tsframe):
frame['A'][:5] = nan
Expand Down Expand Up @@ -1428,54 +1428,54 @@ def test_excel_date_datetime_format(self, merge_cells, engine, ext):
# we need to use df_expected to check the result.
tm.assert_frame_equal(rs2, df_expected)

def test_to_excel_interval_no_labels(self, frame, *_):
def test_to_excel_interval_no_labels(self, *_):
# see gh-19242
#
# Test writing Interval without labels.
frame = DataFrame(np.random.randint(-10, 10, size=(20, 1)),
dtype=np.int64)
df = DataFrame(np.random.randint(-10, 10, size=(20, 1)),
dtype=np.int64)
expected = frame.copy()

frame["new"] = pd.cut(frame[0], 10)
df["new"] = pd.cut(frame[0], 10)
expected["new"] = pd.cut(expected[0], 10).astype(str)

frame.to_excel(self.path, "test1")
df.to_excel(self.path, "test1")
reader = ExcelFile(self.path)

recons = pd.read_excel(reader, "test1", index_col=0)
tm.assert_frame_equal(expected, recons)

def test_to_excel_interval_labels(self, frame, *_):
def test_to_excel_interval_labels(self, *_):
# see gh-19242
#
# Test writing Interval with labels.
frame = DataFrame(np.random.randint(-10, 10, size=(20, 1)),
dtype=np.int64)
expected = frame.copy()
df = DataFrame(np.random.randint(-10, 10, size=(20, 1)),
dtype=np.int64)
expected = df.copy()
intervals = pd.cut(frame[0], 10, labels=["A", "B", "C", "D", "E",
"F", "G", "H", "I", "J"])
frame["new"] = intervals
df["new"] = intervals
expected["new"] = pd.Series(list(intervals))

frame.to_excel(self.path, "test1")
df.to_excel(self.path, "test1")
reader = ExcelFile(self.path)

recons = pd.read_excel(reader, "test1", index_col=0)
tm.assert_frame_equal(expected, recons)

def test_to_excel_timedelta(self, frame, *_):
def test_to_excel_timedelta(self, *_):
# see gh-19242, gh-9155
#
# Test writing timedelta to xls.
frame = DataFrame(np.random.randint(-10, 10, size=(20, 1)),
columns=["A"], dtype=np.int64)
expected = frame.copy()
df = DataFrame(np.random.randint(-10, 10, size=(20, 1)),
columns=["A"], dtype=np.int64)
expected = df.copy()

frame["new"] = frame["A"].apply(lambda x: timedelta(seconds=x))
df["new"] = df["A"].apply(lambda x: timedelta(seconds=x))
expected["new"] = expected["A"].apply(
lambda x: timedelta(seconds=x).total_seconds() / float(86400))

frame.to_excel(self.path, "test1")
df.to_excel(self.path, "test1")
reader = ExcelFile(self.path)

recons = pd.read_excel(reader, "test1", index_col=0)
Expand All @@ -1492,7 +1492,6 @@ def test_to_excel_periodindex(
tm.assert_frame_equal(xp, rs.to_period('M'))

def test_to_excel_multiindex(self, merge_cells, engine, ext, frame):
frame = frame
arrays = np.arange(len(frame.index) * 2).reshape(2, -1)
new_index = MultiIndex.from_arrays(arrays,
names=['first', 'second'])
Expand All @@ -1509,21 +1508,20 @@ def test_to_excel_multiindex(self, merge_cells, engine, ext, frame):

# GH13511
def test_to_excel_multiindex_nan_label(
self, merge_cells, engine, ext, frame):
frame = pd.DataFrame({'A': [None, 2, 3],
'B': [10, 20, 30],
'C': np.random.sample(3)})
frame = frame.set_index(['A', 'B'])

frame.to_excel(self.path, merge_cells=merge_cells)
df = pd.read_excel(self.path, index_col=[0, 1])
tm.assert_frame_equal(frame, df)
self, merge_cells, engine, ext, ):
df = pd.DataFrame({'A': [None, 2, 3],
'B': [10, 20, 30],
'C': np.random.sample(3)})
df = df.set_index(['A', 'B'])

df.to_excel(self.path, merge_cells=merge_cells)
df1 = pd.read_excel(self.path, index_col=[0, 1])
tm.assert_frame_equal(df, df1)

# Test for Issue 11328. If column indices are integers, make
# sure they are handled correctly for either setting of
# merge_cells
def test_to_excel_multiindex_cols(self, merge_cells, engine, ext, frame):
frame = frame
arrays = np.arange(len(frame.index) * 2).reshape(2, -1)
new_index = MultiIndex.from_arrays(arrays,
names=['first', 'second'])
Expand Down
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