TST: split/parametrize

pandas/_testing/asserters.py

@@ -1385,7 +1385,8 @@ def assert_equal(left, right, **kwargs):
         assert kwargs == {}
         assert left == right
     else:
-        raise NotImplementedError(type(left))
+        assert kwargs == {}
+        assert_almost_equal(left, right)
 
 
 def assert_sp_array_equal(left, right):

pandas/tests/frame/methods/test_convert.py

@@ -45,6 +45,8 @@ def test_convert_objects(self, float_string_frame):
         with pytest.raises(ValueError, match="invalid literal"):
             converted["H"].astype("int32")
 
+    def test_convert_mixed_single_column(self):
+        # GH#4119, not converting a mixed type (e.g.floats and object)
         # mixed in a single column
         df = DataFrame({"s": Series([1, "na", 3, 4])})
         result = df._convert(datetime=True, numeric=True)

pandas/tests/series/accessors/test_cat_accessor.py

@@ -14,11 +14,6 @@
     timedelta_range,
 )
 import pandas._testing as tm
-from pandas.core.arrays import (
-    DatetimeArray,
-    PeriodArray,
-    TimedeltaArray,
-)
 from pandas.core.arrays.categorical import CategoricalAccessor
 from pandas.core.indexes.accessors import Properties
 
@@ -163,86 +158,84 @@ def test_categorical_delegations(self):
         )
         tm.assert_series_equal(result, expected)
 
-    def test_dt_accessor_api_for_categorical(self):
+    @pytest.mark.parametrize(
+        "idx",
+        [
+            date_range("1/1/2015", periods=5),
+            date_range("1/1/2015", periods=5, tz="MET"),
+            period_range("1/1/2015", freq="D", periods=5),
+            timedelta_range("1 days", "10 days"),
+        ],
+    )
+    def test_dt_accessor_api_for_categorical(self, idx):
         # https://github.com/pandas-dev/pandas/issues/10661
 
-        s_dr = Series(date_range("1/1/2015", periods=5, tz="MET"))
-        c_dr = s_dr.astype("category")
-
-        s_pr = Series(period_range("1/1/2015", freq="D", periods=5))
-        c_pr = s_pr.astype("category")
-
-        s_tdr = Series(timedelta_range("1 days", "10 days"))
-        c_tdr = s_tdr.astype("category")
+        ser = Series(idx)
+        cat = ser.astype("category")
 
         # only testing field (like .day)
         # and bool (is_month_start)
-        get_ops = lambda x: x._datetimelike_ops
-
-        test_data = [
-            ("Datetime", get_ops(DatetimeArray), s_dr, c_dr),
-            ("Period", get_ops(PeriodArray), s_pr, c_pr),
-            ("Timedelta", get_ops(TimedeltaArray), s_tdr, c_tdr),
-        ]
+        attr_names = type(ser._values)._datetimelike_ops
 
-        assert isinstance(c_dr.dt, Properties)
+        assert isinstance(cat.dt, Properties)
 
         special_func_defs = [
             ("strftime", ("%Y-%m-%d",), {}),
-            ("tz_convert", ("EST",), {}),
             ("round", ("D",), {}),
             ("floor", ("D",), {}),
             ("ceil", ("D",), {}),
             ("asfreq", ("D",), {}),
-            # FIXME: don't leave commented-out
-            # ('tz_localize', ("UTC",), {}),
         ]
+        if idx.dtype == "M8[ns]":
+            # exclude dt64tz since that is already localized and would raise
+            tup = ("tz_localize", ("UTC",), {})
+            special_func_defs.append(tup)
+        elif idx.dtype.kind == "M":
+            # exclude dt64 since that is not localized so would raise
+            tup = ("tz_convert", ("EST",), {})
+            special_func_defs.append(tup)
+
         _special_func_names = [f[0] for f in special_func_defs]
 
-        # the series is already localized
-        _ignore_names = ["tz_localize", "components"]
-
-        for name, attr_names, s, c in test_data:
-            func_names = [
-                f
-                for f in dir(s.dt)
-                if not (
-                    f.startswith("_")
-                    or f in attr_names
-                    or f in _special_func_names
-                    or f in _ignore_names
-                )
-            ]
-
-            func_defs = [(f, (), {}) for f in func_names]
-            for f_def in special_func_defs:
-                if f_def[0] in dir(s.dt):
-                    func_defs.append(f_def)
-
-            for func, args, kwargs in func_defs:
-                with warnings.catch_warnings():
-                    if func == "to_period":
-                        # dropping TZ
-                        warnings.simplefilter("ignore", UserWarning)
-                    res = getattr(c.dt, func)(*args, **kwargs)
-                    exp = getattr(s.dt, func)(*args, **kwargs)
-
-                tm.assert_equal(res, exp)
-
-            for attr in attr_names:
-                if attr in ["week", "weekofyear"]:
-                    # GH#33595 Deprecate week and weekofyear
-                    continue
-                res = getattr(c.dt, attr)
-                exp = getattr(s.dt, attr)
-
-            if isinstance(res, DataFrame):
-                tm.assert_frame_equal(res, exp)
-            elif isinstance(res, Series):
-                tm.assert_series_equal(res, exp)
-            else:
-                tm.assert_almost_equal(res, exp)
+        _ignore_names = ["components", "tz_localize", "tz_convert"]
+
+        func_names = [
+            fname
+            for fname in dir(ser.dt)
+            if not (
+                fname.startswith("_")
+                or fname in attr_names
+                or fname in _special_func_names
+                or fname in _ignore_names
+            )
+        ]
+
+        func_defs = [(fname, (), {}) for fname in func_names]
+
+        for f_def in special_func_defs:
+            if f_def[0] in dir(ser.dt):
+                func_defs.append(f_def)
+
+        for func, args, kwargs in func_defs:
+            with warnings.catch_warnings():
+                if func == "to_period":
+                    # dropping TZ
+                    warnings.simplefilter("ignore", UserWarning)
+                res = getattr(cat.dt, func)(*args, **kwargs)
+                exp = getattr(ser.dt, func)(*args, **kwargs)
+
+            tm.assert_equal(res, exp)
+
+        for attr in attr_names:
+            if attr in ["week", "weekofyear"]:
+                # GH#33595 Deprecate week and weekofyear
+                continue
+            res = getattr(cat.dt, attr)
+            exp = getattr(ser.dt, attr)
+
+            tm.assert_equal(res, exp)
 
+    def test_dt_accessor_api_for_categorical_invalid(self):
         invalid = Series([1, 2, 3]).astype("category")
         msg = "Can only use .dt accessor with datetimelike"
 

pandas/tests/series/methods/test_convert.py

@@ -32,6 +32,7 @@ def test_convert(self):
         results = ser._convert(timedelta=True)
         tm.assert_series_equal(results, ser)
 
+    def test_convert_numeric_strings_with_other_true_args(self):
         # test pass-through and non-conversion when other types selected
         ser = Series(["1.0", "2.0", "3.0"])
         results = ser._convert(datetime=True, numeric=True, timedelta=True)
@@ -40,6 +41,7 @@ def test_convert(self):
         results = ser._convert(True, False, True)
         tm.assert_series_equal(results, ser)
 
+    def test_convert_datetime_objects(self):
         ser = Series(
             [datetime(2001, 1, 1, 0, 0), datetime(2001, 1, 1, 0, 0)], dtype="O"
         )
@@ -49,6 +51,27 @@ def test_convert(self):
         results = ser._convert(datetime=False, numeric=True, timedelta=True)
         tm.assert_series_equal(results, ser)
 
+    def test_convert_datetime64(self):
+        # no-op if already dt64 dtype
+        ser = Series(
+            [
+                datetime(2001, 1, 1, 0, 0),
+                datetime(2001, 1, 2, 0, 0),
+                datetime(2001, 1, 3, 0, 0),
+            ]
+        )
+
+        result = ser._convert(datetime=True)
+        expected = Series(
+            [Timestamp("20010101"), Timestamp("20010102"), Timestamp("20010103")],
+            dtype="M8[ns]",
+        )
+        tm.assert_series_equal(result, expected)
+
+        result = ser._convert(datetime=True)
+        tm.assert_series_equal(result, expected)
+
+    def test_convert_timedeltas(self):
         td = datetime(2001, 1, 1, 0, 0) - datetime(2000, 1, 1, 0, 0)
         ser = Series([td, td], dtype="O")
         results = ser._convert(datetime=True, numeric=True, timedelta=True)
@@ -57,6 +80,7 @@ def test_convert(self):
         results = ser._convert(True, True, False)
         tm.assert_series_equal(results, ser)
 
+    def test_convert_numeric_strings(self):
         ser = Series([1.0, 2, 3], index=["a", "b", "c"])
         result = ser._convert(numeric=True)
         tm.assert_series_equal(result, ser)
@@ -79,6 +103,7 @@ def test_convert(self):
         expected["a"] = np.nan
         tm.assert_series_equal(result, expected)
 
+    def test_convert_mixed_type_noop(self):
         # GH 4119, not converting a mixed type (e.g.floats and object)
         ser = Series([1, "na", 3, 4])
         result = ser._convert(datetime=True, numeric=True)
@@ -89,25 +114,7 @@ def test_convert(self):
         result = ser._convert(datetime=True, numeric=True)
         tm.assert_series_equal(result, expected)
 
-        # dates
-        ser = Series(
-            [
-                datetime(2001, 1, 1, 0, 0),
-                datetime(2001, 1, 2, 0, 0),
-                datetime(2001, 1, 3, 0, 0),
-            ]
-        )
-
-        result = ser._convert(datetime=True)
-        expected = Series(
-            [Timestamp("20010101"), Timestamp("20010102"), Timestamp("20010103")],
-            dtype="M8[ns]",
-        )
-        tm.assert_series_equal(result, expected)
-
-        result = ser._convert(datetime=True)
-        tm.assert_series_equal(result, expected)
-
+    def test_convert_preserve_non_object(self):
         # preserve if non-object
         ser = Series([1], dtype="float32")
         result = ser._convert(datetime=True)