REF: collect to_xarray tests

pandas/tests/generic/test_frame.py

@@ -1,27 +1,15 @@
 from copy import deepcopy
-from distutils.version import LooseVersion
 from operator import methodcaller
 
 import numpy as np
 import pytest
 
-import pandas.util._test_decorators as td
-
-from pandas.core.dtypes.generic import ABCMultiIndex
-
 import pandas as pd
 from pandas import DataFrame, MultiIndex, Series, date_range
 import pandas._testing as tm
 
 from .test_generic import Generic
 
-try:
-    import xarray
-
-    _XARRAY_INSTALLED = True
-except ImportError:
-    _XARRAY_INSTALLED = False
-
 
 class TestDataFrame(Generic):
     _typ = DataFrame
@@ -238,91 +226,3 @@ def test_unexpected_keyword(self):
 
         with pytest.raises(TypeError, match=msg):
             ts.fillna(0, in_place=True)
-
-
-class TestToXArray:
-    @pytest.mark.skipif(
-        not _XARRAY_INSTALLED
-        or _XARRAY_INSTALLED
-        and LooseVersion(xarray.__version__) < LooseVersion("0.10.0"),
-        reason="xarray >= 0.10.0 required",
-    )
-    def test_to_xarray_index_types(self, indices):
-        if isinstance(indices, ABCMultiIndex):
-            pytest.skip("MultiIndex is tested separately")
-        if len(indices) == 0:
-            pytest.skip("Test doesn't make sense for empty index")
-
-        from xarray import Dataset
-
-        df = DataFrame(
-            {
-                "a": list("abc"),
-                "b": list(range(1, 4)),
-                "c": np.arange(3, 6).astype("u1"),
-                "d": np.arange(4.0, 7.0, dtype="float64"),
-                "e": [True, False, True],
-                "f": pd.Categorical(list("abc")),
-                "g": pd.date_range("20130101", periods=3),
-                "h": pd.date_range("20130101", periods=3, tz="US/Eastern"),
-            }
-        )
-
-        df.index = indices[:3]
-        df.index.name = "foo"
-        df.columns.name = "bar"
-        result = df.to_xarray()
-        assert result.dims["foo"] == 3
-        assert len(result.coords) == 1
-        assert len(result.data_vars) == 8
-        tm.assert_almost_equal(list(result.coords.keys()), ["foo"])
-        assert isinstance(result, Dataset)
-
-        # idempotency
-        # datetimes w/tz are preserved
-        # column names are lost
-        expected = df.copy()
-        expected["f"] = expected["f"].astype(object)
-        expected.columns.name = None
-        tm.assert_frame_equal(
-            result.to_dataframe(), expected,
-        )
-
-    @td.skip_if_no("xarray", min_version="0.7.0")
-    def test_to_xarray(self):
-        from xarray import Dataset
-
-        df = DataFrame(
-            {
-                "a": list("abc"),
-                "b": list(range(1, 4)),
-                "c": np.arange(3, 6).astype("u1"),
-                "d": np.arange(4.0, 7.0, dtype="float64"),
-                "e": [True, False, True],
-                "f": pd.Categorical(list("abc")),
-                "g": pd.date_range("20130101", periods=3),
-                "h": pd.date_range("20130101", periods=3, tz="US/Eastern"),
-            }
-        )
-
-        df.index.name = "foo"
-        result = df[0:0].to_xarray()
-        assert result.dims["foo"] == 0
-        assert isinstance(result, Dataset)
-
-        # available in 0.7.1
-        # MultiIndex
-        df.index = pd.MultiIndex.from_product([["a"], range(3)], names=["one", "two"])
-        result = df.to_xarray()
-        assert result.dims["one"] == 1
-        assert result.dims["two"] == 3
-        assert len(result.coords) == 2
-        assert len(result.data_vars) == 8
-        tm.assert_almost_equal(list(result.coords.keys()), ["one", "two"])
-        assert isinstance(result, Dataset)
-
-        result = result.to_dataframe()
-        expected = df.copy()
-        expected["f"] = expected["f"].astype(object)
-        expected.columns.name = None
-        tm.assert_frame_equal(result, expected, check_index_type=False)

pandas/tests/generic/test_series.py

@@ -1,25 +1,14 @@
-from distutils.version import LooseVersion
 from operator import methodcaller
 
 import numpy as np
 import pytest
 
-import pandas.util._test_decorators as td
-
 import pandas as pd
 from pandas import MultiIndex, Series, date_range
 import pandas._testing as tm
 
-from ...core.dtypes.generic import ABCMultiIndex
 from .test_generic import Generic
 
-try:
-    import xarray
-
-    _XARRAY_INSTALLED = True
-except ImportError:
-    _XARRAY_INSTALLED = False
-
 
 class TestSeries(Generic):
     _typ = Series
@@ -199,56 +188,3 @@ def test_datetime_shift_always_copy(self, move_by_freq):
         # GH22397
         s = pd.Series(range(5), index=pd.date_range("2017", periods=5))
         assert s.shift(freq=move_by_freq) is not s
-
-
-class TestToXArray:
-    @pytest.mark.skipif(
-        not _XARRAY_INSTALLED
-        or _XARRAY_INSTALLED
-        and LooseVersion(xarray.__version__) < LooseVersion("0.10.0"),
-        reason="xarray >= 0.10.0 required",
-    )
-    def test_to_xarray_index_types(self, indices):
-        if isinstance(indices, ABCMultiIndex):
-            pytest.skip("MultiIndex is tested separately")
-
-        from xarray import DataArray
-
-        s = Series(range(len(indices)), index=indices, dtype="object")
-        s.index.name = "foo"
-        result = s.to_xarray()
-        repr(result)
-        assert len(result) == len(indices)
-        assert len(result.coords) == 1
-        tm.assert_almost_equal(list(result.coords.keys()), ["foo"])
-        assert isinstance(result, DataArray)
-
-        # idempotency
-        tm.assert_series_equal(result.to_series(), s, check_index_type=False)
-
-    @td.skip_if_no("xarray", min_version="0.7.0")
-    def test_to_xarray_multiindex(self):
-        from xarray import DataArray
-
-        s = Series(range(6))
-        s.index.name = "foo"
-        s.index = pd.MultiIndex.from_product(
-            [["a", "b"], range(3)], names=["one", "two"]
-        )
-        result = s.to_xarray()
-        assert len(result) == 2
-        tm.assert_almost_equal(list(result.coords.keys()), ["one", "two"])
-        assert isinstance(result, DataArray)
-        tm.assert_series_equal(result.to_series(), s)
-
-    @td.skip_if_no("xarray", min_version="0.7.0")
-    def test_to_xarray(self):
-        from xarray import DataArray
-
-        s = Series([], dtype=object)
-        s.index.name = "foo"
-        result = s.to_xarray()
-        assert len(result) == 0
-        assert len(result.coords) == 1
-        tm.assert_almost_equal(list(result.coords.keys()), ["foo"])
-        assert isinstance(result, DataArray)

pandas/tests/generic/test_to_xarray.py

@@ -0,0 +1,154 @@
+from distutils.version import LooseVersion
+
+import numpy as np
+import pytest
+
+import pandas.util._test_decorators as td
+
+import pandas as pd
+from pandas import DataFrame, Series
+import pandas._testing as tm
+
+try:
+    import xarray
+
+    _XARRAY_INSTALLED = True
+except ImportError:
+    _XARRAY_INSTALLED = False
+
+
+class TestDataFrameToXArray:
+    @pytest.mark.skipif(
+        not _XARRAY_INSTALLED
+        or _XARRAY_INSTALLED
+        and LooseVersion(xarray.__version__) < LooseVersion("0.10.0"),
+        reason="xarray >= 0.10.0 required",
+    )
+    def test_to_xarray_index_types(self, indices):
+        if isinstance(indices, pd.MultiIndex):
+            pytest.skip("MultiIndex is tested separately")
+        if len(indices) == 0:
+            pytest.skip("Test doesn't make sense for empty index")
+
+        from xarray import Dataset
+
+        df = DataFrame(
+            {
+                "a": list("abc"),
+                "b": list(range(1, 4)),
+                "c": np.arange(3, 6).astype("u1"),
+                "d": np.arange(4.0, 7.0, dtype="float64"),
+                "e": [True, False, True],
+                "f": pd.Categorical(list("abc")),
+                "g": pd.date_range("20130101", periods=3),
+                "h": pd.date_range("20130101", periods=3, tz="US/Eastern"),
+            }
+        )
+
+        df.index = indices[:3]
+        df.index.name = "foo"
+        df.columns.name = "bar"
+        result = df.to_xarray()
+        assert result.dims["foo"] == 3
+        assert len(result.coords) == 1
+        assert len(result.data_vars) == 8
+        tm.assert_almost_equal(list(result.coords.keys()), ["foo"])
+        assert isinstance(result, Dataset)
+
+        # idempotency
+        # datetimes w/tz are preserved
+        # column names are lost
+        expected = df.copy()
+        expected["f"] = expected["f"].astype(object)
+        expected.columns.name = None
+        tm.assert_frame_equal(
+            result.to_dataframe(), expected,
+        )
+
+    @td.skip_if_no("xarray", min_version="0.7.0")
+    def test_to_xarray(self):
+        from xarray import Dataset
+
+        df = DataFrame(
+            {
+                "a": list("abc"),
+                "b": list(range(1, 4)),
+                "c": np.arange(3, 6).astype("u1"),
+                "d": np.arange(4.0, 7.0, dtype="float64"),
+                "e": [True, False, True],
+                "f": pd.Categorical(list("abc")),
+                "g": pd.date_range("20130101", periods=3),
+                "h": pd.date_range("20130101", periods=3, tz="US/Eastern"),
+            }
+        )
+
+        df.index.name = "foo"
+        result = df[0:0].to_xarray()
+        assert result.dims["foo"] == 0
+        assert isinstance(result, Dataset)
+
+        # available in 0.7.1
+        # MultiIndex
+        df.index = pd.MultiIndex.from_product([["a"], range(3)], names=["one", "two"])
+        result = df.to_xarray()
+        assert result.dims["one"] == 1
+        assert result.dims["two"] == 3
+        assert len(result.coords) == 2
+        assert len(result.data_vars) == 8
+        tm.assert_almost_equal(list(result.coords.keys()), ["one", "two"])
+        assert isinstance(result, Dataset)
+
+        result = result.to_dataframe()
+        expected = df.copy()
+        expected["f"] = expected["f"].astype(object)
+        expected.columns.name = None
+        tm.assert_frame_equal(result, expected, check_index_type=False)
+
+
+class TestSeriesToXArray:
+    @pytest.mark.skipif(
+        not _XARRAY_INSTALLED
+        or _XARRAY_INSTALLED
+        and LooseVersion(xarray.__version__) < LooseVersion("0.10.0"),
+        reason="xarray >= 0.10.0 required",
+    )
+    def test_to_xarray_index_types(self, indices):
+        if isinstance(indices, pd.MultiIndex):
+            pytest.skip("MultiIndex is tested separately")
+
+        from xarray import DataArray
+
+        s = Series(range(len(indices)), index=indices)
+        s.index.name = "foo"
+        result = s.to_xarray()
+        repr(result)
+        assert len(result) == len(indices)
+        assert len(result.coords) == 1
+        tm.assert_almost_equal(list(result.coords.keys()), ["foo"])
+        assert isinstance(result, DataArray)
+
+        # idempotency
+        tm.assert_series_equal(result.to_series(), s, check_index_type=False)
+
+    @td.skip_if_no("xarray", min_version="0.7.0")
+    def test_to_xarray(self):
+        from xarray import DataArray
+
+        s = Series([], dtype=object)
+        s.index.name = "foo"
+        result = s.to_xarray()
+        assert len(result) == 0
+        assert len(result.coords) == 1
+        tm.assert_almost_equal(list(result.coords.keys()), ["foo"])
+        assert isinstance(result, DataArray)
+
+        s = Series(range(6))
+        s.index.name = "foo"
+        s.index = pd.MultiIndex.from_product(
+            [["a", "b"], range(3)], names=["one", "two"]
+        )
+        result = s.to_xarray()
+        assert len(result) == 2
+        tm.assert_almost_equal(list(result.coords.keys()), ["one", "two"])
+        assert isinstance(result, DataArray)
+        tm.assert_series_equal(result.to_series(), s)