TST/REF: collect indexing tests by method (pandas-dev#37507)

* TST/REF: indexing tests by method

* TST: collect indexing tests by method

Author: jbrockmendel

pandas/tests/frame/methods/test_reset_index.py

@@ -8,6 +8,8 @@
 
 import pandas as pd
 from pandas import (
+    Categorical,
+    CategoricalIndex,
     DataFrame,
     Index,
     IntervalIndex,
@@ -542,6 +544,33 @@ def test_reset_index_nat_multiindex(self, ix_data, exp_data):
         expected = DataFrame(exp_data)
         tm.assert_frame_equal(result, expected)
 
+    @pytest.mark.parametrize(
+        "codes", ([[0, 0, 1, 1], [0, 1, 0, 1]], [[0, 0, -1, 1], [0, 1, 0, 1]])
+    )
+    def test_rest_index_multiindex_categorical_with_missing_values(self, codes):
+        # GH#24206
+
+        index = MultiIndex(
+            [CategoricalIndex(["A", "B"]), CategoricalIndex(["a", "b"])], codes
+        )
+        data = {"col": range(len(index))}
+        df = DataFrame(data=data, index=index)
+
+        expected = DataFrame(
+            {
+                "level_0": Categorical.from_codes(codes[0], categories=["A", "B"]),
+                "level_1": Categorical.from_codes(codes[1], categories=["a", "b"]),
+                "col": range(4),
+            }
+        )
+
+        res = df.reset_index()
+        tm.assert_frame_equal(res, expected)
+
+        # roundtrip
+        res = expected.set_index(["level_0", "level_1"]).reset_index()
+        tm.assert_frame_equal(res, expected)
+
 
 @pytest.mark.parametrize(
     "array, dtype",

pandas/tests/frame/test_alter_axes.py

@@ -10,13 +10,10 @@
 )
 
 from pandas import (
-    Categorical,
-    CategoricalIndex,
     DataFrame,
     DatetimeIndex,
     Index,
     IntervalIndex,
-    MultiIndex,
     Series,
     Timestamp,
     cut,
@@ -192,32 +189,3 @@ def test_set_reset_index(self):
         df = df.set_index("B")
 
         df = df.reset_index()
-
-
-class TestCategoricalIndex:
-    @pytest.mark.parametrize(
-        "codes", ([[0, 0, 1, 1], [0, 1, 0, 1]], [[0, 0, -1, 1], [0, 1, 0, 1]])
-    )
-    def test_reindexing_with_missing_values(self, codes):
-        # GH 24206
-
-        index = MultiIndex(
-            [CategoricalIndex(["A", "B"]), CategoricalIndex(["a", "b"])], codes
-        )
-        data = {"col": range(len(index))}
-        df = DataFrame(data=data, index=index)
-
-        expected = DataFrame(
-            {
-                "level_0": Categorical.from_codes(codes[0], categories=["A", "B"]),
-                "level_1": Categorical.from_codes(codes[1], categories=["a", "b"]),
-                "col": range(4),
-            }
-        )
-
-        res = df.reset_index()
-        tm.assert_frame_equal(res, expected)
-
-        # roundtrip
-        res = expected.set_index(["level_0", "level_1"]).reset_index()
-        tm.assert_frame_equal(res, expected)

pandas/tests/series/indexing/test_getitem.py

@@ -9,14 +9,27 @@
 from pandas._libs.tslibs import conversion, timezones
 
 import pandas as pd
-from pandas import Index, Series, Timestamp, date_range, period_range
+from pandas import DataFrame, Index, Series, Timestamp, date_range, period_range
 import pandas._testing as tm
 from pandas.core.indexing import IndexingError
 
 from pandas.tseries.offsets import BDay
 
 
 class TestSeriesGetitemScalars:
+    def test_getitem_out_of_bounds_indexerror(self, datetime_series):
+        # don't segfault, GH#495
+        msg = r"index \d+ is out of bounds for axis 0 with size \d+"
+        with pytest.raises(IndexError, match=msg):
+            datetime_series[len(datetime_series)]
+
+    def test_getitem_out_of_bounds_empty_rangeindex_keyerror(self):
+        # GH#917
+        # With a RangeIndex, an int key gives a KeyError
+        ser = Series([], dtype=object)
+        with pytest.raises(KeyError, match="-1"):
+            ser[-1]
+
     def test_getitem_keyerror_with_int64index(self):
         ser = Series(np.random.randn(6), index=[0, 0, 1, 1, 2, 2])
 
@@ -292,11 +305,23 @@ def test_getitem_multilevel_scalar_slice_not_implemented(
         ser[2000, 3:4]
 
 
+def test_getitem_dataframe_raises():
+    rng = list(range(10))
+    ser = Series(10, index=rng)
+    df = DataFrame(rng, index=rng)
+    msg = (
+        "Indexing a Series with DataFrame is not supported, "
+        "use the appropriate DataFrame column"
+    )
+    with pytest.raises(TypeError, match=msg):
+        ser[df > 5]
+
+
 def test_getitem_assignment_series_aligment():
     # https://github.com/pandas-dev/pandas/issues/37427
     # with getitem, when assigning with a Series, it is not first aligned
-    s = Series(range(10))
+    ser = Series(range(10))
     idx = np.array([2, 4, 9])
-    s[idx] = Series([10, 11, 12])
+    ser[idx] = Series([10, 11, 12])
     expected = Series([0, 1, 10, 3, 11, 5, 6, 7, 8, 12])
-    tm.assert_series_equal(s, expected)
+    tm.assert_series_equal(ser, expected)

pandas/tests/series/indexing/test_indexing.py

@@ -163,19 +163,6 @@ def test_getitem_with_duplicates_indices(result_1, duplicate_item, expected_1):
     assert result[2] == result_1[2]
 
 
-def test_getitem_out_of_bounds(datetime_series):
-    # don't segfault, GH #495
-    msg = r"index \d+ is out of bounds for axis 0 with size \d+"
-    with pytest.raises(IndexError, match=msg):
-        datetime_series[len(datetime_series)]
-
-    # GH #917
-    # With a RangeIndex, an int key gives a KeyError
-    s = Series([], dtype=object)
-    with pytest.raises(KeyError, match="-1"):
-        s[-1]
-
-
 def test_getitem_setitem_integers():
     # caused bug without test
     s = Series([1, 2, 3], ["a", "b", "c"])
@@ -260,18 +247,6 @@ def test_setitem_ambiguous_keyerror():
     tm.assert_series_equal(s2, expected)
 
 
-def test_getitem_dataframe():
-    rng = list(range(10))
-    s = Series(10, index=rng)
-    df = DataFrame(rng, index=rng)
-    msg = (
-        "Indexing a Series with DataFrame is not supported, "
-        "use the appropriate DataFrame column"
-    )
-    with pytest.raises(TypeError, match=msg):
-        s[df > 5]
-
-
 def test_setitem(datetime_series, string_series):
     datetime_series[datetime_series.index[5]] = np.NaN
     datetime_series[[1, 2, 17]] = np.NaN
@@ -296,22 +271,6 @@ def test_setitem(datetime_series, string_series):
     tm.assert_series_equal(s, expected)
 
 
-def test_setitem_empty_series():
-    # Test for issue #10193
-    key = pd.Timestamp("2012-01-01")
-    series = Series(dtype=object)
-    series[key] = 47
-    expected = Series(47, [key])
-    tm.assert_series_equal(series, expected)
-
-    # GH#33573 our index should retain its freq
-    series = Series([], pd.DatetimeIndex([], freq="D"), dtype=object)
-    series[key] = 47
-    expected = Series(47, pd.DatetimeIndex([key], freq="D"))
-    tm.assert_series_equal(series, expected)
-    assert series.index.freq == expected.index.freq
-
-
 def test_setitem_dtypes():
     # change dtypes
     # GH 4463
@@ -338,32 +297,13 @@ def test_setitem_dtypes():
     tm.assert_series_equal(s, Series([np.nan, 1.0]))
 
 
-def test_set_value(datetime_series, string_series):
-    idx = datetime_series.index[10]
-    res = datetime_series._set_value(idx, 0)
-    assert res is None
-    assert datetime_series[idx] == 0
-
-    # equiv
-    s = string_series.copy()
-    res = s._set_value("foobar", 0)
-    assert res is None
-    assert s.index[-1] == "foobar"
-    assert s["foobar"] == 0
-
-    s = string_series.copy()
-    s.loc["foobar"] = 0
-    assert s.index[-1] == "foobar"
-    assert s["foobar"] == 0
-
-
 def test_setslice(datetime_series):
     sl = datetime_series[5:20]
     assert len(sl) == len(sl.index)
     assert sl.index.is_unique is True
 
 
-def test_2d_to_1d_assignment_raises():
+def test_loc_setitem_2d_to_1d_raises():
     x = np.random.randn(2, 2)
     y = Series(range(2))
 
@@ -611,25 +551,6 @@ def test_loc_setitem(string_series):
     assert string_series[d2] == 6
 
 
-def test_setitem_na():
-    # these induce dtype changes
-    expected = Series([np.nan, 3, np.nan, 5, np.nan, 7, np.nan, 9, np.nan])
-    s = Series([2, 3, 4, 5, 6, 7, 8, 9, 10])
-    s[::2] = np.nan
-    tm.assert_series_equal(s, expected)
-
-    # gets coerced to float, right?
-    expected = Series([np.nan, 1, np.nan, 0])
-    s = Series([True, True, False, False])
-    s[::2] = np.nan
-    tm.assert_series_equal(s, expected)
-
-    expected = Series([np.nan, np.nan, np.nan, np.nan, np.nan, 5, 6, 7, 8, 9])
-    s = Series(np.arange(10))
-    s[:5] = np.nan
-    tm.assert_series_equal(s, expected)
-
-
 def test_timedelta_assignment():
     # GH 8209
     s = Series([], dtype=object)
@@ -829,52 +750,11 @@ def test_multilevel_preserve_name():
     assert result2.name == s.name
 
 
-def test_setitem_scalar_into_readonly_backing_data():
-    # GH14359: test that you cannot mutate a read only buffer
-
-    array = np.zeros(5)
-    array.flags.writeable = False  # make the array immutable
-    series = Series(array)
-
-    for n in range(len(series)):
-        msg = "assignment destination is read-only"
-        with pytest.raises(ValueError, match=msg):
-            series[n] = 1
-
-        assert array[n] == 0
-
-
-def test_setitem_slice_into_readonly_backing_data():
-    # GH14359: test that you cannot mutate a read only buffer
-
-    array = np.zeros(5)
-    array.flags.writeable = False  # make the array immutable
-    series = Series(array)
-
-    msg = "assignment destination is read-only"
-    with pytest.raises(ValueError, match=msg):
-        series[1:3] = 1
-
-    assert not array.any()
-
-
 """
 miscellaneous methods
 """
 
 
-def test_pop():
-    # GH 6600
-    df = DataFrame({"A": 0, "B": np.arange(5, dtype="int64"), "C": 0})
-    k = df.iloc[4]
-
-    result = k.pop("B")
-    assert result == 4
-
-    expected = Series([0, 0], index=["A", "C"], name=4)
-    tm.assert_series_equal(k, expected)
-
-
 def test_uint_drop(any_int_dtype):
     # see GH18311
     # assigning series.loc[0] = 4 changed series.dtype to int

pandas/tests/series/indexing/test_pop.py

@@ -0,0 +1,13 @@
+from pandas import Series
+import pandas._testing as tm
+
+
+def test_pop():
+    # GH#6600
+    ser = Series([0, 4, 0], index=["A", "B", "C"], name=4)
+
+    result = ser.pop("B")
+    assert result == 4
+
+    expected = Series([0, 0], index=["A", "C"], name=4)
+    tm.assert_series_equal(ser, expected)

pandas/tests/series/indexing/test_set_value.py

@@ -19,3 +19,24 @@ def test_series_set_value():
     expected = Series([1.0, np.nan], index=index)
 
     tm.assert_series_equal(s, expected)
+
+
+def test_set_value_dt64(datetime_series):
+    idx = datetime_series.index[10]
+    res = datetime_series._set_value(idx, 0)
+    assert res is None
+    assert datetime_series[idx] == 0
+
+
+def test_set_value_str_index(string_series):
+    # equiv
+    ser = string_series.copy()
+    res = ser._set_value("foobar", 0)
+    assert res is None
+    assert ser.index[-1] == "foobar"
+    assert ser["foobar"] == 0
+
+    ser2 = string_series.copy()
+    ser2.loc["foobar"] = 0
+    assert ser2.index[-1] == "foobar"
+    assert ser2["foobar"] == 0