REF/TST: directories for CategoricalIndex, RangeIndex tests (pandas-dev#30476)

Author: jbrockmendel

pandas/tests/indexes/categorical/__init__.py

@@ -12,7 +12,7 @@
 from pandas.core.indexes.api import CategoricalIndex, Index
 import pandas.util.testing as tm
 
-from .common import Base
+from ..common import Base
 
 
 class TestCategoricalIndex(Base):
@@ -32,147 +32,6 @@ def test_can_hold_identifiers(self):
         key = idx[0]
         assert idx._can_hold_identifiers_and_holds_name(key) is True
 
-    def test_construction(self):
-
-        ci = self.create_index(categories=list("abcd"))
-        categories = ci.categories
-
-        result = Index(ci)
-        tm.assert_index_equal(result, ci, exact=True)
-        assert not result.ordered
-
-        result = Index(ci.values)
-        tm.assert_index_equal(result, ci, exact=True)
-        assert not result.ordered
-
-        # empty
-        result = CategoricalIndex(categories=categories)
-        tm.assert_index_equal(result.categories, Index(categories))
-        tm.assert_numpy_array_equal(result.codes, np.array([], dtype="int8"))
-        assert not result.ordered
-
-        # passing categories
-        result = CategoricalIndex(list("aabbca"), categories=categories)
-        tm.assert_index_equal(result.categories, Index(categories))
-        tm.assert_numpy_array_equal(
-            result.codes, np.array([0, 0, 1, 1, 2, 0], dtype="int8")
-        )
-
-        c = pd.Categorical(list("aabbca"))
-        result = CategoricalIndex(c)
-        tm.assert_index_equal(result.categories, Index(list("abc")))
-        tm.assert_numpy_array_equal(
-            result.codes, np.array([0, 0, 1, 1, 2, 0], dtype="int8")
-        )
-        assert not result.ordered
-
-        result = CategoricalIndex(c, categories=categories)
-        tm.assert_index_equal(result.categories, Index(categories))
-        tm.assert_numpy_array_equal(
-            result.codes, np.array([0, 0, 1, 1, 2, 0], dtype="int8")
-        )
-        assert not result.ordered
-
-        ci = CategoricalIndex(c, categories=list("abcd"))
-        result = CategoricalIndex(ci)
-        tm.assert_index_equal(result.categories, Index(categories))
-        tm.assert_numpy_array_equal(
-            result.codes, np.array([0, 0, 1, 1, 2, 0], dtype="int8")
-        )
-        assert not result.ordered
-
-        result = CategoricalIndex(ci, categories=list("ab"))
-        tm.assert_index_equal(result.categories, Index(list("ab")))
-        tm.assert_numpy_array_equal(
-            result.codes, np.array([0, 0, 1, 1, -1, 0], dtype="int8")
-        )
-        assert not result.ordered
-
-        result = CategoricalIndex(ci, categories=list("ab"), ordered=True)
-        tm.assert_index_equal(result.categories, Index(list("ab")))
-        tm.assert_numpy_array_equal(
-            result.codes, np.array([0, 0, 1, 1, -1, 0], dtype="int8")
-        )
-        assert result.ordered
-
-        result = pd.CategoricalIndex(ci, categories=list("ab"), ordered=True)
-        expected = pd.CategoricalIndex(
-            ci, categories=list("ab"), ordered=True, dtype="category"
-        )
-        tm.assert_index_equal(result, expected, exact=True)
-
-        # turn me to an Index
-        result = Index(np.array(ci))
-        assert isinstance(result, Index)
-        assert not isinstance(result, CategoricalIndex)
-
-    def test_construction_with_dtype(self):
-
-        # specify dtype
-        ci = self.create_index(categories=list("abc"))
-
-        result = Index(np.array(ci), dtype="category")
-        tm.assert_index_equal(result, ci, exact=True)
-
-        result = Index(np.array(ci).tolist(), dtype="category")
-        tm.assert_index_equal(result, ci, exact=True)
-
-        # these are generally only equal when the categories are reordered
-        ci = self.create_index()
-
-        result = Index(np.array(ci), dtype="category").reorder_categories(ci.categories)
-        tm.assert_index_equal(result, ci, exact=True)
-
-        # make sure indexes are handled
-        expected = CategoricalIndex([0, 1, 2], categories=[0, 1, 2], ordered=True)
-        idx = Index(range(3))
-        result = CategoricalIndex(idx, categories=idx, ordered=True)
-        tm.assert_index_equal(result, expected, exact=True)
-
-    def test_construction_empty_with_bool_categories(self):
-        # see gh-22702
-        cat = pd.CategoricalIndex([], categories=[True, False])
-        categories = sorted(cat.categories.tolist())
-        assert categories == [False, True]
-
-    def test_construction_with_categorical_dtype(self):
-        # construction with CategoricalDtype
-        # GH18109
-        data, cats, ordered = "a a b b".split(), "c b a".split(), True
-        dtype = CategoricalDtype(categories=cats, ordered=ordered)
-
-        result = CategoricalIndex(data, dtype=dtype)
-        expected = CategoricalIndex(data, categories=cats, ordered=ordered)
-        tm.assert_index_equal(result, expected, exact=True)
-
-        # GH 19032
-        result = Index(data, dtype=dtype)
-        tm.assert_index_equal(result, expected, exact=True)
-
-        # error when combining categories/ordered and dtype kwargs
-        msg = "Cannot specify `categories` or `ordered` together with `dtype`."
-        with pytest.raises(ValueError, match=msg):
-            CategoricalIndex(data, categories=cats, dtype=dtype)
-
-        with pytest.raises(ValueError, match=msg):
-            Index(data, categories=cats, dtype=dtype)
-
-        with pytest.raises(ValueError, match=msg):
-            CategoricalIndex(data, ordered=ordered, dtype=dtype)
-
-        with pytest.raises(ValueError, match=msg):
-            Index(data, ordered=ordered, dtype=dtype)
-
-    def test_create_categorical(self):
-        # https://github.com/pandas-dev/pandas/pull/17513
-        # The public CI constructor doesn't hit this code path with
-        # instances of CategoricalIndex, but we still want to test the code
-        ci = CategoricalIndex(["a", "b", "c"])
-        # First ci is self, second ci is data.
-        result = CategoricalIndex._create_categorical(ci, ci)
-        expected = Categorical(["a", "b", "c"])
-        tm.assert_categorical_equal(result, expected)
-
     @pytest.mark.parametrize(
         "func,op_name",
         [

pandas/tests/indexes/test_category.py renamed to pandas/tests/indexes/categorical/test_category.py

@@ -0,0 +1,147 @@
+import numpy as np
+import pytest
+
+from pandas import Categorical, CategoricalDtype, CategoricalIndex, Index
+import pandas.util.testing as tm
+
+
+class TestCategoricalIndexConstructors:
+    def test_construction(self):
+
+        ci = CategoricalIndex(list("aabbca"), categories=list("abcd"), ordered=False)
+        categories = ci.categories
+
+        result = Index(ci)
+        tm.assert_index_equal(result, ci, exact=True)
+        assert not result.ordered
+
+        result = Index(ci.values)
+        tm.assert_index_equal(result, ci, exact=True)
+        assert not result.ordered
+
+        # empty
+        result = CategoricalIndex(categories=categories)
+        tm.assert_index_equal(result.categories, Index(categories))
+        tm.assert_numpy_array_equal(result.codes, np.array([], dtype="int8"))
+        assert not result.ordered
+
+        # passing categories
+        result = CategoricalIndex(list("aabbca"), categories=categories)
+        tm.assert_index_equal(result.categories, Index(categories))
+        tm.assert_numpy_array_equal(
+            result.codes, np.array([0, 0, 1, 1, 2, 0], dtype="int8")
+        )
+
+        c = Categorical(list("aabbca"))
+        result = CategoricalIndex(c)
+        tm.assert_index_equal(result.categories, Index(list("abc")))
+        tm.assert_numpy_array_equal(
+            result.codes, np.array([0, 0, 1, 1, 2, 0], dtype="int8")
+        )
+        assert not result.ordered
+
+        result = CategoricalIndex(c, categories=categories)
+        tm.assert_index_equal(result.categories, Index(categories))
+        tm.assert_numpy_array_equal(
+            result.codes, np.array([0, 0, 1, 1, 2, 0], dtype="int8")
+        )
+        assert not result.ordered
+
+        ci = CategoricalIndex(c, categories=list("abcd"))
+        result = CategoricalIndex(ci)
+        tm.assert_index_equal(result.categories, Index(categories))
+        tm.assert_numpy_array_equal(
+            result.codes, np.array([0, 0, 1, 1, 2, 0], dtype="int8")
+        )
+        assert not result.ordered
+
+        result = CategoricalIndex(ci, categories=list("ab"))
+        tm.assert_index_equal(result.categories, Index(list("ab")))
+        tm.assert_numpy_array_equal(
+            result.codes, np.array([0, 0, 1, 1, -1, 0], dtype="int8")
+        )
+        assert not result.ordered
+
+        result = CategoricalIndex(ci, categories=list("ab"), ordered=True)
+        tm.assert_index_equal(result.categories, Index(list("ab")))
+        tm.assert_numpy_array_equal(
+            result.codes, np.array([0, 0, 1, 1, -1, 0], dtype="int8")
+        )
+        assert result.ordered
+
+        result = CategoricalIndex(ci, categories=list("ab"), ordered=True)
+        expected = CategoricalIndex(
+            ci, categories=list("ab"), ordered=True, dtype="category"
+        )
+        tm.assert_index_equal(result, expected, exact=True)
+
+        # turn me to an Index
+        result = Index(np.array(ci))
+        assert isinstance(result, Index)
+        assert not isinstance(result, CategoricalIndex)
+
+    def test_construction_with_dtype(self):
+
+        # specify dtype
+        ci = CategoricalIndex(list("aabbca"), categories=list("abc"), ordered=False)
+
+        result = Index(np.array(ci), dtype="category")
+        tm.assert_index_equal(result, ci, exact=True)
+
+        result = Index(np.array(ci).tolist(), dtype="category")
+        tm.assert_index_equal(result, ci, exact=True)
+
+        # these are generally only equal when the categories are reordered
+        ci = CategoricalIndex(list("aabbca"), categories=list("cab"), ordered=False)
+
+        result = Index(np.array(ci), dtype="category").reorder_categories(ci.categories)
+        tm.assert_index_equal(result, ci, exact=True)
+
+        # make sure indexes are handled
+        expected = CategoricalIndex([0, 1, 2], categories=[0, 1, 2], ordered=True)
+        idx = Index(range(3))
+        result = CategoricalIndex(idx, categories=idx, ordered=True)
+        tm.assert_index_equal(result, expected, exact=True)
+
+    def test_construction_empty_with_bool_categories(self):
+        # see GH#22702
+        cat = CategoricalIndex([], categories=[True, False])
+        categories = sorted(cat.categories.tolist())
+        assert categories == [False, True]
+
+    def test_construction_with_categorical_dtype(self):
+        # construction with CategoricalDtype
+        # GH#18109
+        data, cats, ordered = "a a b b".split(), "c b a".split(), True
+        dtype = CategoricalDtype(categories=cats, ordered=ordered)
+
+        result = CategoricalIndex(data, dtype=dtype)
+        expected = CategoricalIndex(data, categories=cats, ordered=ordered)
+        tm.assert_index_equal(result, expected, exact=True)
+
+        # GH#19032
+        result = Index(data, dtype=dtype)
+        tm.assert_index_equal(result, expected, exact=True)
+
+        # error when combining categories/ordered and dtype kwargs
+        msg = "Cannot specify `categories` or `ordered` together with `dtype`."
+        with pytest.raises(ValueError, match=msg):
+            CategoricalIndex(data, categories=cats, dtype=dtype)
+
+        with pytest.raises(ValueError, match=msg):
+            Index(data, categories=cats, dtype=dtype)
+
+        with pytest.raises(ValueError, match=msg):
+            CategoricalIndex(data, ordered=ordered, dtype=dtype)
+
+        with pytest.raises(ValueError, match=msg):
+            Index(data, ordered=ordered, dtype=dtype)
+
+    def test_create_categorical(self):
+        # GH#17513 The public CI constructor doesn't hit this code path with
+        # instances of CategoricalIndex, but we still want to test the code
+        ci = CategoricalIndex(["a", "b", "c"])
+        # First ci is self, second ci is data.
+        result = CategoricalIndex._create_categorical(ci, ci)
+        expected = Categorical(["a", "b", "c"])
+        tm.assert_categorical_equal(result, expected)