done

lib/python3.11/site-packages/pandas/tests/extension/base/missing.py

@@ -0,0 +1,190 @@
+import numpy as np
+import pytest
+
+import pandas as pd
+import pandas._testing as tm
+
+
+class BaseMissingTests:
+    def test_isna(self, data_missing):
+        expected = np.array([True, False])
+
+        result = pd.isna(data_missing)
+        tm.assert_numpy_array_equal(result, expected)
+
+        result = pd.Series(data_missing).isna()
+        expected = pd.Series(expected)
+        tm.assert_series_equal(result, expected)
+
+        # GH 21189
+        result = pd.Series(data_missing).drop([0, 1]).isna()
+        expected = pd.Series([], dtype=bool)
+        tm.assert_series_equal(result, expected)
+
+    @pytest.mark.parametrize("na_func", ["isna", "notna"])
+    def test_isna_returns_copy(self, data_missing, na_func):
+        result = pd.Series(data_missing)
+        expected = result.copy()
+        mask = getattr(result, na_func)()
+        if isinstance(mask.dtype, pd.SparseDtype):
+            # TODO: GH 57739
+            mask = np.array(mask)
+            mask.flags.writeable = True
+
+        mask[:] = True
+        tm.assert_series_equal(result, expected)
+
+    def test_dropna_array(self, data_missing):
+        result = data_missing.dropna()
+        expected = data_missing[[1]]
+        tm.assert_extension_array_equal(result, expected)
+
+    def test_dropna_series(self, data_missing):
+        ser = pd.Series(data_missing)
+        result = ser.dropna()
+        expected = ser.iloc[[1]]
+        tm.assert_series_equal(result, expected)
+
+    def test_dropna_frame(self, data_missing):
+        df = pd.DataFrame({"A": data_missing}, columns=pd.Index(["A"], dtype=object))
+
+        # defaults
+        result = df.dropna()
+        expected = df.iloc[[1]]
+        tm.assert_frame_equal(result, expected)
+
+        # axis = 1
+        result = df.dropna(axis="columns")
+        expected = pd.DataFrame(index=pd.RangeIndex(2), columns=pd.Index([]))
+        tm.assert_frame_equal(result, expected)
+
+        # multiple
+        df = pd.DataFrame({"A": data_missing, "B": [1, np.nan]})
+        result = df.dropna()
+        expected = df.iloc[:0]
+        tm.assert_frame_equal(result, expected)
+
+    def test_fillna_scalar(self, data_missing):
+        valid = data_missing[1]
+        result = data_missing.fillna(valid)
+        expected = data_missing.fillna(valid)
+        tm.assert_extension_array_equal(result, expected)
+
+    @pytest.mark.filterwarnings(
+        "ignore:Series.fillna with 'method' is deprecated:FutureWarning"
+    )
+    def test_fillna_limit_pad(self, data_missing):
+        arr = data_missing.take([1, 0, 0, 0, 1])
+        result = pd.Series(arr).ffill(limit=2)
+        expected = pd.Series(data_missing.take([1, 1, 1, 0, 1]))
+        tm.assert_series_equal(result, expected)
+
+    @pytest.mark.parametrize(
+        "limit_area, input_ilocs, expected_ilocs",
+        [
+            ("outside", [1, 0, 0, 0, 1], [1, 0, 0, 0, 1]),
+            ("outside", [1, 0, 1, 0, 1], [1, 0, 1, 0, 1]),
+            ("outside", [0, 1, 1, 1, 0], [0, 1, 1, 1, 1]),
+            ("outside", [0, 1, 0, 1, 0], [0, 1, 0, 1, 1]),
+            ("inside", [1, 0, 0, 0, 1], [1, 1, 1, 1, 1]),
+            ("inside", [1, 0, 1, 0, 1], [1, 1, 1, 1, 1]),
+            ("inside", [0, 1, 1, 1, 0], [0, 1, 1, 1, 0]),
+            ("inside", [0, 1, 0, 1, 0], [0, 1, 1, 1, 0]),
+        ],
+    )
+    def test_ffill_limit_area(
+        self, data_missing, limit_area, input_ilocs, expected_ilocs
+    ):
+        # GH#56616
+        arr = data_missing.take(input_ilocs)
+        result = pd.Series(arr).ffill(limit_area=limit_area)
+        expected = pd.Series(data_missing.take(expected_ilocs))
+        tm.assert_series_equal(result, expected)
+
+    @pytest.mark.filterwarnings(
+        "ignore:Series.fillna with 'method' is deprecated:FutureWarning"
+    )
+    def test_fillna_limit_backfill(self, data_missing):
+        arr = data_missing.take([1, 0, 0, 0, 1])
+        result = pd.Series(arr).fillna(method="backfill", limit=2)
+        expected = pd.Series(data_missing.take([1, 0, 1, 1, 1]))
+        tm.assert_series_equal(result, expected)
+
+    def test_fillna_no_op_returns_copy(self, data):
+        data = data[~data.isna()]
+
+        valid = data[0]
+        result = data.fillna(valid)
+        assert result is not data
+        tm.assert_extension_array_equal(result, data)
+
+        result = data._pad_or_backfill(method="backfill")
+        assert result is not data
+        tm.assert_extension_array_equal(result, data)
+
+    def test_fillna_series(self, data_missing):
+        fill_value = data_missing[1]
+        ser = pd.Series(data_missing)
+
+        result = ser.fillna(fill_value)
+        expected = pd.Series(
+            data_missing._from_sequence(
+                [fill_value, fill_value], dtype=data_missing.dtype
+            )
+        )
+        tm.assert_series_equal(result, expected)
+
+        # Fill with a series
+        result = ser.fillna(expected)
+        tm.assert_series_equal(result, expected)
+
+        # Fill with a series not affecting the missing values
+        result = ser.fillna(ser)
+        tm.assert_series_equal(result, ser)
+
+    def test_fillna_series_method(self, data_missing, fillna_method):
+        fill_value = data_missing[1]
+
+        if fillna_method == "ffill":
+            data_missing = data_missing[::-1]
+
+        result = getattr(pd.Series(data_missing), fillna_method)()
+        expected = pd.Series(
+            data_missing._from_sequence(
+                [fill_value, fill_value], dtype=data_missing.dtype
+            )
+        )
+
+        tm.assert_series_equal(result, expected)
+
+    def test_fillna_frame(self, data_missing):
+        fill_value = data_missing[1]
+
+        result = pd.DataFrame({"A": data_missing, "B": [1, 2]}).fillna(fill_value)
+
+        expected = pd.DataFrame(
+            {
+                "A": data_missing._from_sequence(
+                    [fill_value, fill_value], dtype=data_missing.dtype
+                ),
+                "B": [1, 2],
+            }
+        )
+
+        tm.assert_frame_equal(result, expected)
+
+    def test_fillna_fill_other(self, data):
+        result = pd.DataFrame({"A": data, "B": [np.nan] * len(data)}).fillna({"B": 0.0})
+
+        expected = pd.DataFrame({"A": data, "B": [0.0] * len(result)})
+
+        tm.assert_frame_equal(result, expected)
+
+    def test_use_inf_as_na_no_effect(self, data_missing):
+        ser = pd.Series(data_missing)
+        expected = ser.isna()
+        msg = "use_inf_as_na option is deprecated"
+        with tm.assert_produces_warning(FutureWarning, match=msg):
+            with pd.option_context("mode.use_inf_as_na", True):
+                result = ser.isna()
+        tm.assert_series_equal(result, expected)