CLN/TST: Remove old data creation methods in _testing/__init__.py (#56144)

* Clean up sparely used index generating methods

* Remove makePeriodSeries

* Remove from all

* Remove makeIntervalIndex

* Remove makeIntervalIndex

* Cast as object

Author: mroeschke

pandas/_testing/__init__.py

@@ -43,7 +43,6 @@
     DataFrame,
     DatetimeIndex,
     Index,
-    IntervalIndex,
     MultiIndex,
     RangeIndex,
     Series,
@@ -106,8 +105,6 @@
 from pandas.core.construction import extract_array
 
 if TYPE_CHECKING:
-    from collections.abc import Iterable
-
     from pandas._typing import (
         Dtype,
         Frequency,
@@ -388,12 +385,6 @@ def makeCategoricalIndex(
     )
 
 
-def makeIntervalIndex(k: int = 10, name=None, **kwargs) -> IntervalIndex:
-    """make a length k IntervalIndex"""
-    x = np.linspace(0, 100, num=(k + 1))
-    return IntervalIndex.from_breaks(x, name=name, **kwargs)
-
-
 def makeBoolIndex(k: int = 10, name=None) -> Index:
     if k == 1:
         return Index([True], name=name)
@@ -465,45 +456,6 @@ def makePeriodIndex(k: int = 10, name=None, **kwargs) -> PeriodIndex:
     return pi
 
 
-def makeMultiIndex(k: int = 10, names=None, **kwargs):
-    N = (k // 2) + 1
-    rng = range(N)
-    mi = MultiIndex.from_product([("foo", "bar"), rng], names=names, **kwargs)
-    assert len(mi) >= k  # GH#38795
-    return mi[:k]
-
-
-def index_subclass_makers_generator():
-    make_index_funcs = [
-        makeDateIndex,
-        makePeriodIndex,
-        makeTimedeltaIndex,
-        makeRangeIndex,
-        makeIntervalIndex,
-        makeCategoricalIndex,
-        makeMultiIndex,
-    ]
-    yield from make_index_funcs
-
-
-def all_timeseries_index_generator(k: int = 10) -> Iterable[Index]:
-    """
-    Generator which can be iterated over to get instances of all the classes
-    which represent time-series.
-
-    Parameters
-    ----------
-    k: length of each of the index instances
-    """
-    make_index_funcs: list[Callable[..., Index]] = [
-        makeDateIndex,
-        makePeriodIndex,
-        makeTimedeltaIndex,
-    ]
-    for make_index_func in make_index_funcs:
-        yield make_index_func(k=k)
-
-
 # make series
 def make_rand_series(name=None, dtype=np.float64) -> Series:
     index = makeStringIndex(_N)
@@ -546,24 +498,10 @@ def makeTimeSeries(nper=None, freq: Frequency = "B", name=None) -> Series:
     )
 
 
-def makePeriodSeries(nper=None, name=None) -> Series:
-    if nper is None:
-        nper = _N
-    return Series(
-        np.random.default_rng(2).standard_normal(nper),
-        index=makePeriodIndex(nper),
-        name=name,
-    )
-
-
 def getTimeSeriesData(nper=None, freq: Frequency = "B") -> dict[str, Series]:
     return {c: makeTimeSeries(nper, freq) for c in getCols(_K)}
 
 
-def getPeriodData(nper=None) -> dict[str, Series]:
-    return {c: makePeriodSeries(nper) for c in getCols(_K)}
-
-
 # make frame
 def makeTimeDataFrame(nper=None, freq: Frequency = "B") -> DataFrame:
     data = getTimeSeriesData(nper, freq)
@@ -592,11 +530,6 @@ def makeMixedDataFrame() -> DataFrame:
     return DataFrame(getMixedTypeDict()[1])
 
 
-def makePeriodFrame(nper=None) -> DataFrame:
-    data = getPeriodData(nper)
-    return DataFrame(data)
-
-
 def makeCustomIndex(
     nentries,
     nlevels,
@@ -1080,7 +1013,6 @@ def shares_memory(left, right) -> bool:
     "ALL_INT_NUMPY_DTYPES",
     "ALL_NUMPY_DTYPES",
     "ALL_REAL_NUMPY_DTYPES",
-    "all_timeseries_index_generator",
     "assert_almost_equal",
     "assert_attr_equal",
     "assert_categorical_equal",
@@ -1129,12 +1061,10 @@ def shares_memory(left, right) -> bool:
     "get_finest_unit",
     "get_obj",
     "get_op_from_name",
-    "getPeriodData",
     "getSeriesData",
     "getTimeSeriesData",
     "iat",
     "iloc",
-    "index_subclass_makers_generator",
     "loc",
     "makeBoolIndex",
     "makeCategoricalIndex",
@@ -1144,15 +1074,11 @@ def shares_memory(left, right) -> bool:
     "makeDateIndex",
     "makeFloatIndex",
     "makeFloatSeries",
-    "makeIntervalIndex",
     "makeIntIndex",
     "makeMixedDataFrame",
-    "makeMultiIndex",
     "makeNumericIndex",
     "makeObjectSeries",
-    "makePeriodFrame",
     "makePeriodIndex",
-    "makePeriodSeries",
     "make_rand_series",
     "makeRangeIndex",
     "makeStringIndex",

pandas/conftest.py

@@ -61,6 +61,7 @@
 from pandas import (
     DataFrame,
     Interval,
+    IntervalIndex,
     Period,
     Series,
     Timedelta,
@@ -630,7 +631,7 @@ def _create_mi_with_dt64tz_level():
     "complex64": tm.makeNumericIndex(100, dtype="float64").astype("complex64"),
     "complex128": tm.makeNumericIndex(100, dtype="float64").astype("complex128"),
     "categorical": tm.makeCategoricalIndex(100),
-    "interval": tm.makeIntervalIndex(100),
+    "interval": IntervalIndex.from_breaks(np.linspace(0, 100, num=101)),
     "empty": Index([]),
     "tuples": MultiIndex.from_tuples(zip(["foo", "bar", "baz"], [1, 2, 3])),
     "mi-with-dt64tz-level": _create_mi_with_dt64tz_level(),

pandas/tests/dtypes/test_missing.py

@@ -40,6 +40,7 @@
     Series,
     TimedeltaIndex,
     date_range,
+    period_range,
 )
 import pandas._testing as tm
 
@@ -81,7 +82,7 @@ def test_notna_notnull(notna_f):
         tm.makeStringSeries(),
         tm.makeObjectSeries(),
         tm.makeTimeSeries(),
-        tm.makePeriodSeries(),
+        Series(range(5), period_range("2020-01-01", periods=5)),
     ],
 )
 def test_null_check_is_series(null_func, ser):
@@ -124,15 +125,25 @@ def test_isna_isnull(self, isna_f):
 
     @pytest.mark.parametrize("isna_f", [isna, isnull])
     @pytest.mark.parametrize(
-        "df",
+        "data",
         [
-            tm.makeTimeDataFrame(),
-            tm.makePeriodFrame(),
-            tm.makeMixedDataFrame(),
+            np.arange(4, dtype=float),
+            [0.0, 1.0, 0.0, 1.0],
+            Series(list("abcd"), dtype=object),
+            date_range("2020-01-01", periods=4),
         ],
     )
-    def test_isna_isnull_frame(self, isna_f, df):
+    @pytest.mark.parametrize(
+        "index",
+        [
+            date_range("2020-01-01", periods=4),
+            range(4),
+            period_range("2020-01-01", periods=4),
+        ],
+    )
+    def test_isna_isnull_frame(self, isna_f, data, index):
         # frame
+        df = pd.DataFrame(data, index=index)
         result = isna_f(df)
         expected = df.apply(isna_f)
         tm.assert_frame_equal(result, expected)

pandas/tests/frame/methods/test_shift.py

@@ -241,7 +241,9 @@ def test_shift_by_offset(self, datetime_frame, frame_or_series):
 
     def test_shift_with_periodindex(self, frame_or_series):
         # Shifting with PeriodIndex
-        ps = tm.makePeriodFrame()
+        ps = DataFrame(
+            np.arange(4, dtype=float), index=pd.period_range("2020-01-01", periods=4)
+        )
         ps = tm.get_obj(ps, frame_or_series)
 
         shifted = ps.shift(1)
@@ -492,7 +494,7 @@ def test_shift_axis1_multiple_blocks_with_int_fill(self):
         tm.assert_frame_equal(result, expected)
 
     def test_period_index_frame_shift_with_freq(self, frame_or_series):
-        ps = tm.makePeriodFrame()
+        ps = DataFrame(range(4), index=pd.period_range("2020-01-01", periods=4))
         ps = tm.get_obj(ps, frame_or_series)
 
         shifted = ps.shift(1, freq="infer")
@@ -529,7 +531,7 @@ def test_datetime_frame_shift_with_freq(self, datetime_frame, frame_or_series):
         tm.assert_equal(unshifted, inferred_ts)
 
     def test_period_index_frame_shift_with_freq_error(self, frame_or_series):
-        ps = tm.makePeriodFrame()
+        ps = DataFrame(range(4), index=pd.period_range("2020-01-01", periods=4))
         ps = tm.get_obj(ps, frame_or_series)
         msg = "Given freq M does not match PeriodIndex freq D"
         with pytest.raises(ValueError, match=msg):

pandas/tests/indexes/test_base.py

@@ -1,5 +1,6 @@
 from collections import defaultdict
 from datetime import datetime
+from functools import partial
 import math
 import operator
 import re
@@ -1596,11 +1597,23 @@ def test_generated_op_names(opname, index):
     assert method.__name__ == opname
 
 
-@pytest.mark.parametrize("index_maker", tm.index_subclass_makers_generator())
-def test_index_subclass_constructor_wrong_kwargs(index_maker):
+@pytest.mark.parametrize(
+    "klass",
+    [
+        partial(CategoricalIndex, data=[1]),
+        partial(DatetimeIndex, data=["2020-01-01"]),
+        partial(PeriodIndex, data=["2020-01-01"]),
+        partial(TimedeltaIndex, data=["1 day"]),
+        partial(RangeIndex, data=range(1)),
+        partial(IntervalIndex, data=[pd.Interval(0, 1)]),
+        partial(Index, data=["a"], dtype=object),
+        partial(MultiIndex, levels=[1], codes=[0]),
+    ],
+)
+def test_index_subclass_constructor_wrong_kwargs(klass):
     # GH #19348
     with pytest.raises(TypeError, match="unexpected keyword argument"):
-        index_maker(foo="bar")
+        klass(foo="bar")
 
 
 def test_deprecated_fastpath():

pandas/tests/plotting/test_datetimelike.py

@@ -347,7 +347,7 @@ def test_irregular_datetime64_repr_bug(self):
             assert rs == xp
 
     def test_business_freq(self):
-        bts = tm.makePeriodSeries()
+        bts = Series(range(5), period_range("2020-01-01", periods=5))
         msg = r"PeriodDtype\[B\] is deprecated"
         dt = bts.index[0].to_timestamp()
         with tm.assert_produces_warning(FutureWarning, match=msg):

pandas/tests/plotting/test_series.py

@@ -14,6 +14,7 @@
     DataFrame,
     Series,
     date_range,
+    period_range,
     plotting,
 )
 import pandas._testing as tm
@@ -45,11 +46,6 @@ def series():
     return tm.makeStringSeries(name="series")
 
 
-@pytest.fixture
-def iseries():
-    return tm.makePeriodSeries(name="iseries")
-
-
 class TestSeriesPlots:
     @pytest.mark.slow
     @pytest.mark.parametrize("kwargs", [{"label": "foo"}, {"use_index": False}])
@@ -82,8 +78,9 @@ def test_plot_ts_bar(self, ts):
     def test_plot_ts_area_stacked(self, ts):
         _check_plot_works(ts.plot.area, stacked=False)
 
-    def test_plot_iseries(self, iseries):
-        _check_plot_works(iseries.plot)
+    def test_plot_iseries(self):
+        ser = Series(range(5), period_range("2020-01-01", periods=5))
+        _check_plot_works(ser.plot)
 
     @pytest.mark.parametrize(
         "kind",

pandas/tests/resample/test_base.py

@@ -5,6 +5,7 @@
 
 from pandas import (
     DataFrame,
+    DatetimeIndex,
     Index,
     MultiIndex,
     NaT,
@@ -288,16 +289,19 @@ def test_resample_size_empty_dataframe(freq, empty_frame_dti):
     tm.assert_series_equal(result, expected)
 
 
-@pytest.mark.filterwarnings(r"ignore:PeriodDtype\[B\] is deprecated:FutureWarning")
-@pytest.mark.parametrize("index", tm.all_timeseries_index_generator(0))
+@pytest.mark.parametrize(
+    "index",
+    [
+        PeriodIndex([], freq="M", name="a"),
+        DatetimeIndex([], name="a"),
+        TimedeltaIndex([], name="a"),
+    ],
+)
 @pytest.mark.parametrize("dtype", [float, int, object, "datetime64[ns]"])
 def test_resample_empty_dtypes(index, dtype, resample_method):
     # Empty series were sometimes causing a segfault (for the functions
     # with Cython bounds-checking disabled) or an IndexError.  We just run
     # them to ensure they no longer do.  (GH #10228)
-    if isinstance(index, PeriodIndex):
-        # GH#53511
-        index = PeriodIndex([], freq="B", name=index.name)
     empty_series_dti = Series([], index, dtype)
     rs = empty_series_dti.resample("d", group_keys=False)
     try: