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[BACKPORT] Support inclusive argument for pd.date_range (#2718) (#2721)
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@wjsi
wjsi authored Feb 17, 2022
1 parent efa37c6 commit e27b12c
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Showing 12 changed files with 185 additions and 141 deletions.
44 changes: 33 additions & 11 deletions mars/dataframe/arithmetic/tests/test_arithmetic.py
View file
Original file line number Diff line number Diff line change
Expand Up @@ -176,7 +176,9 @@ def test_without_shuffle(func_name, func_opts):
assert df3.columns_value.should_be_monotonic is True
assert isinstance(df3.index_value.value, IndexValue.Int64Index)
assert df3.index_value.should_be_monotonic is True
pd.testing.assert_index_equal(df3.index_value.to_pandas(), pd.Int64Index([]))
pd.testing.assert_index_equal(
df3.index_value.to_pandas(), pd.Index([], dtype=np.int64)
)
assert df3.index_value.key != df1.index_value.key
assert df3.index_value.key != df2.index_value.key
assert df3.shape[1] == 11 # columns is recorded, so we can get it
Expand All @@ -190,7 +192,9 @@ def test_without_shuffle(func_name, func_opts):
assert df3.columns_value.should_be_monotonic is True
assert isinstance(df3.index_value.value, IndexValue.Int64Index)
assert df3.index_value.should_be_monotonic is True
pd.testing.assert_index_equal(df3.index_value.to_pandas(), pd.Int64Index([]))
pd.testing.assert_index_equal(
df3.index_value.to_pandas(), pd.Index([], dtype=np.int64)
)
assert df3.index_value.key != df1.index_value.key
assert df3.index_value.key != df2.index_value.key
assert df3.shape[1] == 11 # columns is recorded, so we can get it
Expand Down Expand Up @@ -408,7 +412,9 @@ def test_dataframe_and_series_with_shuffle(func_name, func_opts):
# test df2's index and columns
assert df2.shape == (df1.shape[0], np.nan)
assert df2.index_value.key == df1.index_value.key
pd.testing.assert_index_equal(df2.columns_value.to_pandas(), pd.Int64Index([]))
pd.testing.assert_index_equal(
df2.columns_value.to_pandas(), pd.Index([], dtype=np.int64)
)
assert df2.columns_value.key != df1.columns_value.key
assert df2.columns_value.should_be_monotonic is True

Expand Down Expand Up @@ -602,7 +608,9 @@ def test_series_and_series_with_shuffle(func_name, func_opts):
assert s3.shape == (np.nan,)
assert s3.index_value.key != s1.index_value.key
assert s3.index_value.key != s2.index_value.key
pd.testing.assert_index_equal(s3.index_value.to_pandas(), pd.Int64Index([]))
pd.testing.assert_index_equal(
s3.index_value.to_pandas(), pd.Index([], dtype=np.int64)
)
assert s3.index_value.should_be_monotonic is True

s1, s2, s3 = tile(s1, s2, s3)
Expand Down Expand Up @@ -726,7 +734,9 @@ def test_with_one_shuffle(func_name, func_opts):
assert df3.columns_value.should_be_monotonic is True
assert isinstance(df3.index_value.value, IndexValue.Int64Index)
assert df3.index_value.should_be_monotonic is True
pd.testing.assert_index_equal(df3.index_value.to_pandas(), pd.Int64Index([]))
pd.testing.assert_index_equal(
df3.index_value.to_pandas(), pd.Index([], dtype=np.int64)
)
assert df3.index_value.key != df1.index_value.key
assert df3.index_value.key != df2.index_value.key
assert df3.shape[1] == 12 # columns is recorded, so we can get it
Expand Down Expand Up @@ -858,7 +868,9 @@ def test_with_all_shuffle(func_name, func_opts):
assert df3.columns_value.should_be_monotonic is True
assert isinstance(df3.index_value.value, IndexValue.Int64Index)
assert df3.index_value.should_be_monotonic is True
pd.testing.assert_index_equal(df3.index_value.to_pandas(), pd.Int64Index([]))
pd.testing.assert_index_equal(
df3.index_value.to_pandas(), pd.Index([], dtype=np.int64)
)
assert df3.index_value.key != df1.index_value.key
assert df3.index_value.key != df2.index_value.key
assert df3.shape[1] == 12 # columns is recorded, so we can get it
Expand Down Expand Up @@ -958,7 +970,9 @@ def test_with_all_shuffle(func_name, func_opts):
assert df6.columns_value.should_be_monotonic is True
assert isinstance(df6.index_value.value, IndexValue.Int64Index)
assert df6.index_value.should_be_monotonic is True
pd.testing.assert_index_equal(df6.index_value.to_pandas(), pd.Int64Index([]))
pd.testing.assert_index_equal(
df6.index_value.to_pandas(), pd.Index([], dtype=np.int64)
)
assert df6.index_value.key != df4.index_value.key
assert df6.index_value.key != df5.index_value.key
assert df6.shape[1] == 20 # columns is recorded, so we can get it
Expand Down Expand Up @@ -1063,7 +1077,9 @@ def test_without_shuffle_and_with_one_chunk(func_name, func_opts):
assert df3.columns_value.should_be_monotonic is True
assert isinstance(df3.index_value.value, IndexValue.Int64Index)
assert df3.index_value.should_be_monotonic is True
pd.testing.assert_index_equal(df3.index_value.to_pandas(), pd.Int64Index([]))
pd.testing.assert_index_equal(
df3.index_value.to_pandas(), pd.Index([], dtype=np.int64)
)
assert df3.index_value.key != df1.index_value.key
assert df3.index_value.key != df2.index_value.key
assert df3.shape[1] == 12 # columns is recorded, so we can get it
Expand Down Expand Up @@ -1175,7 +1191,9 @@ def test_both_one_chunk(func_name, func_opts):
assert df3.columns_value.should_be_monotonic is True
assert isinstance(df3.index_value.value, IndexValue.Int64Index)
assert df3.index_value.should_be_monotonic is True
pd.testing.assert_index_equal(df3.index_value.to_pandas(), pd.Int64Index([]))
pd.testing.assert_index_equal(
df3.index_value.to_pandas(), pd.Index([], dtype=np.int64)
)
assert df3.index_value.key != df1.index_value.key
assert df3.index_value.key != df2.index_value.key
assert df3.shape[1] == 12 # columns is recorded, so we can get it
Expand Down Expand Up @@ -1219,7 +1237,9 @@ def test_with_shuffle_and_one_chunk(func_name, func_opts):
assert df3.columns_value.should_be_monotonic is True
assert isinstance(df3.index_value.value, IndexValue.Int64Index)
assert df3.index_value.should_be_monotonic is True
pd.testing.assert_index_equal(df3.index_value.to_pandas(), pd.Int64Index([]))
pd.testing.assert_index_equal(
df3.index_value.to_pandas(), pd.Index([], dtype=np.int64)
)
assert df3.index_value.key != df1.index_value.key
assert df3.index_value.key != df2.index_value.key
assert df3.shape[1] == 12 # columns is recorded, so we can get it
Expand Down Expand Up @@ -1312,7 +1332,9 @@ def test_on_same_dataframe(func_name, func_opts):
assert df2.columns_value.should_be_monotonic is False
assert isinstance(df2.index_value.value, IndexValue.Int64Index)
assert df2.index_value.should_be_monotonic is False
pd.testing.assert_index_equal(df2.index_value.to_pandas(), pd.Int64Index([]))
pd.testing.assert_index_equal(
df2.index_value.to_pandas(), pd.Index([], dtype=np.int64)
)
assert df2.index_value.key == df.index_value.key
assert df2.columns_value.key == df.columns_value.key
assert df2.shape[1] == 10
Expand Down
12 changes: 11 additions & 1 deletion mars/dataframe/core.py
View file
Original file line number Diff line number Diff line change
Expand Up @@ -136,7 +136,11 @@ def to_pandas(self):
kw = {k: v for k, v in kw.items() if v is not None}
if kw.get("data") is None:
kw["data"] = []
return getattr(pd, type(self).__name__)(**kw)

pd_initializer = getattr(self, "_pd_initializer", None)
if pd_initializer is None:
pd_initializer = getattr(pd, type(self).__name__)
return pd_initializer(**kw)

class Index(IndexBase):
_name = AnyField("name")
Expand Down Expand Up @@ -238,6 +242,8 @@ def inferred_type(self):
return "period"

class Int64Index(IndexBase):
_pd_initializer = pd.Index

_name = AnyField("name")
_data = NDArrayField("data")
_dtype = DataTypeField("dtype")
Expand All @@ -247,6 +253,8 @@ def inferred_type(self):
return "integer"

class UInt64Index(IndexBase):
_pd_initializer = pd.Index

_name = AnyField("name")
_data = NDArrayField("data")
_dtype = DataTypeField("dtype")
Expand All @@ -256,6 +264,8 @@ def inferred_type(self):
return "integer"

class Float64Index(IndexBase):
_pd_initializer = pd.Index

_name = AnyField("name")
_data = NDArrayField("data")
_dtype = DataTypeField("dtype")
Expand Down
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