TST/CLN: Remove make_rand_series (pandas-dev#56163)

* TST/CLN: Remove make_rand_series

* Remove old usages

* Adjust test

Author: mroeschke

pandas/_testing/__init__.py

@@ -456,23 +456,6 @@ def makePeriodIndex(k: int = 10, name=None, **kwargs) -> PeriodIndex:
     return pi
 
 
-# make series
-def make_rand_series(name=None, dtype=np.float64) -> Series:
-    index = makeStringIndex(_N)
-    data = np.random.default_rng(2).standard_normal(_N)
-    with np.errstate(invalid="ignore"):
-        data = data.astype(dtype, copy=False)
-    return Series(data, index=index, name=name)
-
-
-def makeFloatSeries(name=None) -> Series:
-    return make_rand_series(name=name)
-
-
-def makeStringSeries(name=None) -> Series:
-    return make_rand_series(name=name)
-
-
 def makeObjectSeries(name=None) -> Series:
     data = makeStringIndex(_N)
     data = Index(data, dtype=object)
@@ -1073,16 +1056,13 @@ def shares_memory(left, right) -> bool:
     "makeDataFrame",
     "makeDateIndex",
     "makeFloatIndex",
-    "makeFloatSeries",
     "makeIntIndex",
     "makeMixedDataFrame",
     "makeNumericIndex",
     "makeObjectSeries",
     "makePeriodIndex",
-    "make_rand_series",
     "makeRangeIndex",
     "makeStringIndex",
-    "makeStringSeries",
     "makeTimeDataFrame",
     "makeTimedeltaIndex",
     "makeTimeSeries",

pandas/conftest.py

@@ -729,9 +729,11 @@ def string_series() -> Series:
     """
     Fixture for Series of floats with Index of unique strings
     """
-    s = tm.makeStringSeries()
-    s.name = "series"
-    return s
+    return Series(
+        np.arange(30, dtype=np.float64) * 1.1,
+        index=Index([f"i_{i}" for i in range(30)], dtype=object),
+        name="series",
+    )
 
 
 @pytest.fixture
@@ -776,7 +778,9 @@ def series_with_simple_index(index) -> Series:
 
 
 _narrow_series = {
-    f"{dtype.__name__}-series": tm.make_rand_series(name="a", dtype=dtype)
+    f"{dtype.__name__}-series": Series(
+        range(30), index=[f"i-{i}" for i in range(30)], name="a", dtype=dtype
+    )
     for dtype in tm.NARROW_NP_DTYPES
 }
 

pandas/tests/apply/test_invalid_arg.py

@@ -338,11 +338,8 @@ def test_transform_wont_agg_series(string_series, func):
     # we are trying to transform with an aggregator
     msg = "Function did not transform"
 
-    warn = RuntimeWarning if func[0] == "sqrt" else None
-    warn_msg = "invalid value encountered in sqrt"
     with pytest.raises(ValueError, match=msg):
-        with tm.assert_produces_warning(warn, match=warn_msg, check_stacklevel=False):
-            string_series.transform(func)
+        string_series.transform(func)
 
 
 @pytest.mark.parametrize(

pandas/tests/base/test_misc.py

@@ -132,7 +132,7 @@ def test_memory_usage_components_series(series_with_simple_index):
 
 @pytest.mark.parametrize("dtype", tm.NARROW_NP_DTYPES)
 def test_memory_usage_components_narrow_series(dtype):
-    series = tm.make_rand_series(name="a", dtype=dtype)
+    series = Series(range(5), dtype=dtype, index=[f"i-{i}" for i in range(5)], name="a")
     total_usage = series.memory_usage(index=True)
     non_index_usage = series.memory_usage(index=False)
     index_usage = series.index.memory_usage()

pandas/tests/dtypes/test_missing.py

@@ -78,8 +78,6 @@ def test_notna_notnull(notna_f):
 @pytest.mark.parametrize(
     "ser",
     [
-        tm.makeFloatSeries(),
-        tm.makeStringSeries(),
         tm.makeObjectSeries(),
         tm.makeTimeSeries(),
         Series(range(5), period_range("2020-01-01", periods=5)),

pandas/tests/generic/test_generic.py

@@ -316,7 +316,11 @@ class TestNDFrame:
     # tests that don't fit elsewhere
 
     @pytest.mark.parametrize(
-        "ser", [tm.makeFloatSeries(), tm.makeStringSeries(), tm.makeObjectSeries()]
+        "ser",
+        [
+            Series(range(10), dtype=np.float64),
+            Series([str(i) for i in range(10)], dtype=object),
+        ],
     )
     def test_squeeze_series_noop(self, ser):
         # noop
@@ -360,14 +364,18 @@ def test_squeeze_axis_len_3(self):
         tm.assert_frame_equal(df.squeeze(axis=0), df)
 
     def test_numpy_squeeze(self):
-        s = tm.makeFloatSeries()
+        s = Series(range(2), dtype=np.float64)
         tm.assert_series_equal(np.squeeze(s), s)
 
         df = tm.makeTimeDataFrame().reindex(columns=["A"])
         tm.assert_series_equal(np.squeeze(df), df["A"])
 
     @pytest.mark.parametrize(
-        "ser", [tm.makeFloatSeries(), tm.makeStringSeries(), tm.makeObjectSeries()]
+        "ser",
+        [
+            Series(range(10), dtype=np.float64),
+            Series([str(i) for i in range(10)], dtype=object),
+        ],
     )
     def test_transpose_series(self, ser):
         # calls implementation in pandas/core/base.py
@@ -393,7 +401,11 @@ def test_numpy_transpose(self, frame_or_series):
             np.transpose(obj, axes=1)
 
     @pytest.mark.parametrize(
-        "ser", [tm.makeFloatSeries(), tm.makeStringSeries(), tm.makeObjectSeries()]
+        "ser",
+        [
+            Series(range(10), dtype=np.float64),
+            Series([str(i) for i in range(10)], dtype=object),
+        ],
     )
     def test_take_series(self, ser):
         indices = [1, 5, -2, 6, 3, -1]

pandas/tests/io/pytables/test_append.py

@@ -99,7 +99,7 @@ def test_append(setup_path):
 def test_append_series(setup_path):
     with ensure_clean_store(setup_path) as store:
         # basic
-        ss = tm.makeStringSeries()
+        ss = Series(range(20), dtype=np.float64, index=[f"i_{i}" for i in range(20)])
         ts = tm.makeTimeSeries()
         ns = Series(np.arange(100))
 

pandas/tests/io/pytables/test_keys.py

@@ -3,6 +3,7 @@
 from pandas import (
     DataFrame,
     HDFStore,
+    Series,
     _testing as tm,
 )
 from pandas.tests.io.pytables.common import (
@@ -16,7 +17,9 @@
 def test_keys(setup_path):
     with ensure_clean_store(setup_path) as store:
         store["a"] = tm.makeTimeSeries()
-        store["b"] = tm.makeStringSeries()
+        store["b"] = Series(
+            range(10), dtype="float64", index=[f"i_{i}" for i in range(10)]
+        )
         store["c"] = tm.makeDataFrame()
 
         assert len(store) == 3

pandas/tests/io/pytables/test_read.py

@@ -356,7 +356,7 @@ def test_read_hdf_series_mode_r(tmp_path, format, setup_path):
     # GH 16583
     # Tests that reading a Series saved to an HDF file
     # still works if a mode='r' argument is supplied
-    series = tm.makeFloatSeries()
+    series = Series(range(10), dtype=np.float64)
     path = tmp_path / setup_path
     series.to_hdf(path, key="data", format=format)
     result = read_hdf(path, key="data", mode="r")

pandas/tests/io/pytables/test_round_trip.py

@@ -36,7 +36,7 @@ def roundtrip(key, obj, **kwargs):
         o = tm.makeTimeSeries()
         tm.assert_series_equal(o, roundtrip("series", o))
 
-        o = tm.makeStringSeries()
+        o = Series(range(10), dtype="float64", index=[f"i_{i}" for i in range(10)])
         tm.assert_series_equal(o, roundtrip("string_series", o))
 
         o = tm.makeDataFrame()
@@ -249,7 +249,7 @@ def test_table_values_dtypes_roundtrip(setup_path):
 
 @pytest.mark.filterwarnings("ignore::pandas.errors.PerformanceWarning")
 def test_series(setup_path):
-    s = tm.makeStringSeries()
+    s = Series(range(10), dtype="float64", index=[f"i_{i}" for i in range(10)])
     _check_roundtrip(s, tm.assert_series_equal, path=setup_path)
 
     ts = tm.makeTimeSeries()

pandas/tests/io/pytables/test_store.py

@@ -103,7 +103,9 @@ def test_repr(setup_path):
         repr(store)
         store.info()
         store["a"] = tm.makeTimeSeries()
-        store["b"] = tm.makeStringSeries()
+        store["b"] = Series(
+            range(10), dtype="float64", index=[f"i_{i}" for i in range(10)]
+        )
         store["c"] = tm.makeDataFrame()
 
         df = tm.makeDataFrame()

pandas/tests/plotting/test_series.py

@@ -43,7 +43,9 @@ def ts():
 
 @pytest.fixture
 def series():
-    return tm.makeStringSeries(name="series")
+    return Series(
+        range(20), dtype=np.float64, name="series", index=[f"i_{i}" for i in range(20)]
+    )
 
 
 class TestSeriesPlots:

pandas/tests/reductions/test_reductions.py

@@ -868,7 +868,7 @@ def test_idxmin_dt64index(self, unit):
     def test_idxmin(self):
         # test idxmin
         # _check_stat_op approach can not be used here because of isna check.
-        string_series = tm.makeStringSeries().rename("series")
+        string_series = Series(range(20), dtype=np.float64, name="series")
 
         # add some NaNs
         string_series[5:15] = np.nan
@@ -901,7 +901,7 @@ def test_idxmin(self):
     def test_idxmax(self):
         # test idxmax
         # _check_stat_op approach can not be used here because of isna check.
-        string_series = tm.makeStringSeries().rename("series")
+        string_series = Series(range(20), dtype=np.float64, name="series")
 
         # add some NaNs
         string_series[5:15] = np.nan

pandas/tests/reductions/test_stat_reductions.py

@@ -154,35 +154,35 @@ def _check_stat_op(
                 f(string_series_, numeric_only=True)
 
     def test_sum(self):
-        string_series = tm.makeStringSeries().rename("series")
+        string_series = Series(range(20), dtype=np.float64, name="series")
         self._check_stat_op("sum", np.sum, string_series, check_allna=False)
 
     def test_mean(self):
-        string_series = tm.makeStringSeries().rename("series")
+        string_series = Series(range(20), dtype=np.float64, name="series")
         self._check_stat_op("mean", np.mean, string_series)
 
     def test_median(self):
-        string_series = tm.makeStringSeries().rename("series")
+        string_series = Series(range(20), dtype=np.float64, name="series")
         self._check_stat_op("median", np.median, string_series)
 
         # test with integers, test failure
         int_ts = Series(np.ones(10, dtype=int), index=range(10))
         tm.assert_almost_equal(np.median(int_ts), int_ts.median())
 
     def test_prod(self):
-        string_series = tm.makeStringSeries().rename("series")
+        string_series = Series(range(20), dtype=np.float64, name="series")
         self._check_stat_op("prod", np.prod, string_series)
 
     def test_min(self):
-        string_series = tm.makeStringSeries().rename("series")
+        string_series = Series(range(20), dtype=np.float64, name="series")
         self._check_stat_op("min", np.min, string_series, check_objects=True)
 
     def test_max(self):
-        string_series = tm.makeStringSeries().rename("series")
+        string_series = Series(range(20), dtype=np.float64, name="series")
         self._check_stat_op("max", np.max, string_series, check_objects=True)
 
     def test_var_std(self):
-        string_series = tm.makeStringSeries().rename("series")
+        string_series = Series(range(20), dtype=np.float64, name="series")
         datetime_series = tm.makeTimeSeries().rename("ts")
 
         alt = lambda x: np.std(x, ddof=1)
@@ -208,7 +208,7 @@ def test_var_std(self):
         assert pd.isna(result)
 
     def test_sem(self):
-        string_series = tm.makeStringSeries().rename("series")
+        string_series = Series(range(20), dtype=np.float64, name="series")
         datetime_series = tm.makeTimeSeries().rename("ts")
 
         alt = lambda x: np.std(x, ddof=1) / np.sqrt(len(x))
@@ -228,7 +228,7 @@ def test_sem(self):
     def test_skew(self):
         sp_stats = pytest.importorskip("scipy.stats")
 
-        string_series = tm.makeStringSeries().rename("series")
+        string_series = Series(range(20), dtype=np.float64, name="series")
 
         alt = lambda x: sp_stats.skew(x, bias=False)
         self._check_stat_op("skew", alt, string_series)
@@ -250,7 +250,7 @@ def test_skew(self):
     def test_kurt(self):
         sp_stats = pytest.importorskip("scipy.stats")
 
-        string_series = tm.makeStringSeries().rename("series")
+        string_series = Series(range(20), dtype=np.float64, name="series")
 
         alt = lambda x: sp_stats.kurtosis(x, bias=False)
         self._check_stat_op("kurt", alt, string_series)

pandas/tests/series/test_arithmetic.py

@@ -47,7 +47,11 @@ class TestSeriesFlexArithmetic:
             (lambda x: x, lambda x: x * 2, False),
             (lambda x: x, lambda x: x[::2], False),
             (lambda x: x, lambda x: 5, True),
-            (lambda x: tm.makeFloatSeries(), lambda x: tm.makeFloatSeries(), True),
+            (
+                lambda x: Series(range(10), dtype=np.float64),
+                lambda x: Series(range(10), dtype=np.float64),
+                True,
+            ),
         ],
     )
     @pytest.mark.parametrize(

pandas/tests/series/test_unary.py

@@ -8,13 +8,11 @@ class TestSeriesUnaryOps:
     # __neg__, __pos__, __invert__
 
     def test_neg(self):
-        ser = tm.makeStringSeries()
-        ser.name = "series"
+        ser = Series(range(5), dtype="float64", name="series")
         tm.assert_series_equal(-ser, -1 * ser)
 
     def test_invert(self):
-        ser = tm.makeStringSeries()
-        ser.name = "series"
+        ser = Series(range(5), dtype="float64", name="series")
         tm.assert_series_equal(-(ser < 0), ~(ser < 0))
 
     @pytest.mark.parametrize(