[BUG] Loosen random_state input restriction

doc/source/whatsnew/v1.1.0.rst

@@ -69,6 +69,7 @@ Other enhancements
 - `OptionError` is now exposed in `pandas.errors` (:issue:`27553`)
 - :func:`timedelta_range` will now infer a frequency when passed ``start``, ``stop``, and ``periods`` (:issue:`32377`)
 - Positional slicing on a :class:`IntervalIndex` now supports slices with ``step > 1`` (:issue:`31658`)
+- :meth:`DataFrame.sample` will now also allow array-like and BitGenerator objects to be passed to ``random_state`` as seeds (:issue:`32503`)
 -
 
 .. ---------------------------------------------------------------------------

pandas/core/common.py

@@ -15,6 +15,7 @@
 
 from pandas._libs import lib, tslibs
 from pandas._typing import T
+from pandas.compat.numpy import _np_version_under1p17
 
 from pandas.core.dtypes.cast import construct_1d_object_array_from_listlike
 from pandas.core.dtypes.common import (
@@ -395,8 +396,9 @@ def random_state(state=None):
 
     Parameters
     ----------
-    state : int, np.random.RandomState, None.
-        If receives an int, passes to np.random.RandomState() as seed.
+    state : int, array-like, BitGenerator (NumPy>=1.17), np.random.RandomState, None.
+        If receives an int, array-like, or BitGenerator, passes to
+        np.random.RandomState() as seed.
         If receives an np.random.RandomState object, just returns object.
         If receives `None`, returns np.random.
         If receives anything else, raises an informative ValueError.
@@ -405,16 +407,27 @@ def random_state(state=None):
     Returns
     -------
     np.random.RandomState
+
+    ..versionchanged:: 1.1.0
+        array-like and BitGenerator (for NumPy>=1.17) object now passed to
+        np.random.RandomState() as seed
     """
-    if is_integer(state):
+    if (
+        is_integer(state)
+        or is_array_like(state)
+        or (not _np_version_under1p17 and isinstance(state, np.random.BitGenerator))
+    ):
         return np.random.RandomState(state)
     elif isinstance(state, np.random.RandomState):
         return state
     elif state is None:
         return np.random
     else:
         raise ValueError(
-            "random_state must be an integer, a numpy RandomState, or None"
+            (
+                "random_state must be an integer, array-like, a BitGenerator, "
+                "a numpy RandomState, or None"
+            )
         )
 
 

pandas/core/generic.py

@@ -4794,9 +4794,10 @@ def sample(
             If weights do not sum to 1, they will be normalized to sum to 1.
             Missing values in the weights column will be treated as zero.
             Infinite values not allowed.
-        random_state : int or numpy.random.RandomState, optional
-            Seed for the random number generator (if int), or numpy RandomState
-            object.
+        random_state : int, array-like, BitGenerator, np.random.RandomState, optional
+            If int, array-like, or BitGenerator (NumPy>=1.17), seed for
+            random number generator
+            If np.random.RandomState, use as numpy RandomState object.
         axis : {0 or ‘index’, 1 or ‘columns’, None}, default None
             Axis to sample. Accepts axis number or name. Default is stat axis
             for given data type (0 for Series and DataFrames).

pandas/tests/generic/test_generic.py

@@ -3,11 +3,14 @@
 import numpy as np
 import pytest
 
+from pandas.compat.numpy import _np_version_under1p17
+
 from pandas.core.dtypes.common import is_scalar
 
 import pandas as pd
 from pandas import DataFrame, MultiIndex, Series, date_range
 import pandas._testing as tm
+import pandas.core.common as com
 
 # ----------------------------------------------------------------------
 # Generic types test cases
@@ -641,6 +644,30 @@ def test_sample(sel):
         with pytest.raises(ValueError):
             df.sample(1, weights=s4)
 
+    @pytest.mark.parametrize(
+        "func_str,arg",
+        [
+            ("np.array", [2, 3, 1, 0]),
+            pytest.param(
+                "np.random.MT19937",
+                3,
+                marks=pytest.mark.skipif(_np_version_under1p17, reason="NumPy<1.17"),
+            ),
+            pytest.param(
+                "np.random.PCG64",
+                11,
+                marks=pytest.mark.skipif(_np_version_under1p17, reason="NumPy<1.17"),
+            ),
+        ],
+    )
+    def test_sample_random_state(self, func_str, arg):
+        # GH32503
+        df = pd.DataFrame({"col1": range(10, 20), "col2": range(20, 30)})
+        tm.assert_frame_equal(
+            df.sample(n=3, random_state=com.random_state(eval(func_str)(arg))),
+            df.sample(n=3, random_state=eval(func_str)(arg)),
+        )
+
     def test_squeeze(self):
         # noop
         for s in [tm.makeFloatSeries(), tm.makeStringSeries(), tm.makeObjectSeries()]:

pandas/tests/test_common.py

@@ -6,6 +6,8 @@
 import numpy as np
 import pytest
 
+from pandas.compat.numpy import _np_version_under1p17
+
 import pandas as pd
 from pandas import Series, Timestamp
 from pandas.core import ops
@@ -59,8 +61,29 @@ def test_random_state():
     # check with no arg random state
     assert com.random_state() is np.random
 
+    # check array-like
+    state_arr_like = npr.randint(0, 2 ** 31, size=624, dtype="uint32")
+    assert (
+        com.random_state(state_arr_like).uniform()
+        == npr.RandomState(state_arr_like).uniform()
+    )
+
+    # Check BitGenerators
+    if not _np_version_under1p17:
+        assert (
+            com.random_state(npr.MT19937(3)).uniform()
+            == npr.RandomState(npr.MT19937(3)).uniform()
+        )
+        assert (
+            com.random_state(npr.PCG64(11)).uniform()
+            == npr.RandomState(npr.PCG64(11)).uniform()
+        )
+
     # Error for floats or strings
-    msg = "random_state must be an integer, a numpy RandomState, or None"
+    msg = (
+        "random_state must be an integer, array-like, a BitGenerator, "
+        "a numpy RandomState, or None"
+    )
     with pytest.raises(ValueError, match=msg):
         com.random_state("test")