针对pulse-transit的工具

dist/client/pandas/tests/generic/test_to_xarray.py

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+import numpy as np
+import pytest
+
+import pandas.util._test_decorators as td
+
+from pandas import (
+    Categorical,
+    DataFrame,
+    MultiIndex,
+    Series,
+    date_range,
+)
+import pandas._testing as tm
+
+
+@td.skip_if_no("xarray")
+class TestDataFrameToXArray:
+    @pytest.fixture
+    def df(self):
+        return 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": Categorical(list("abc")),
+                "g": date_range("20130101", periods=3),
+                "h": date_range("20130101", periods=3, tz="US/Eastern"),
+            }
+        )
+
+    def test_to_xarray_index_types(self, index_flat, df):
+        index = index_flat
+        # MultiIndex is tested in test_to_xarray_with_multiindex
+        if len(index) == 0:
+            pytest.skip("Test doesn't make sense for empty index")
+
+        from xarray import Dataset
+
+        df.index = index[: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)
+
+    def test_to_xarray_empty(self, df):
+        from xarray import Dataset
+
+        df.index.name = "foo"
+        result = df[0:0].to_xarray()
+        assert result.dims["foo"] == 0
+        assert isinstance(result, Dataset)
+
+    def test_to_xarray_with_multiindex(self, df):
+        from xarray import Dataset
+
+        # MultiIndex
+        df.index = 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)
+
+
+@td.skip_if_no("xarray")
+class TestSeriesToXArray:
+    def test_to_xarray_index_types(self, index_flat):
+        index = index_flat
+        # MultiIndex is tested in test_to_xarray_with_multiindex
+
+        from xarray import DataArray
+
+        ser = Series(range(len(index)), index=index, dtype="int64")
+        ser.index.name = "foo"
+        result = ser.to_xarray()
+        repr(result)
+        assert len(result) == len(index)
+        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(), ser)
+
+    def test_to_xarray_empty(self):
+        from xarray import DataArray
+
+        ser = Series([], dtype=object)
+        ser.index.name = "foo"
+        result = ser.to_xarray()
+        assert len(result) == 0
+        assert len(result.coords) == 1
+        tm.assert_almost_equal(list(result.coords.keys()), ["foo"])
+        assert isinstance(result, DataArray)
+
+    def test_to_xarray_with_multiindex(self):
+        from xarray import DataArray
+
+        mi = MultiIndex.from_product([["a", "b"], range(3)], names=["one", "two"])
+        ser = Series(range(6), dtype="int64", index=mi)
+        result = ser.to_xarray()
+        assert len(result) == 2
+        tm.assert_almost_equal(list(result.coords.keys()), ["one", "two"])
+        assert isinstance(result, DataArray)
+        res = result.to_series()
+        tm.assert_series_equal(res, ser)