diff --git a/pandas/tests/computation/test_eval.py b/pandas/tests/computation/test_eval.py
index 728ffc6f85ba4..3e16ec134db46 100644
--- a/pandas/tests/computation/test_eval.py
+++ b/pandas/tests/computation/test_eval.py
@@ -6,7 +6,6 @@
 import warnings
 
 import numpy as np
-from numpy.random import rand, randint, randn
 import pytest
 
 from pandas.compat import is_platform_windows
@@ -126,15 +125,15 @@ def _is_py3_complex_incompat(result, expected):
 @pytest.fixture(params=list(range(5)))
 def lhs(request):
 
-    nan_df1 = DataFrame(rand(10, 5))
+    nan_df1 = DataFrame(np.random.rand(10, 5))
     nan_df1[nan_df1 > 0.5] = np.nan
 
     opts = (
-        DataFrame(randn(10, 5)),
-        Series(randn(5)),
+        DataFrame(np.random.randn(10, 5)),
+        Series(np.random.randn(5)),
         Series([1, 2, np.nan, np.nan, 5]),
         nan_df1,
-        randn(),
+        np.random.randn(),
     )
     return opts[request.param]
 
@@ -455,7 +454,7 @@ def test_frame_invert(self):
         # ~ ##
         # frame
         # float always raises
-        lhs = DataFrame(randn(5, 2))
+        lhs = DataFrame(np.random.randn(5, 2))
         if self.engine == "numexpr":
             msg = "couldn't find matching opcode for 'invert_dd'"
             with pytest.raises(NotImplementedError, match=msg):
@@ -466,7 +465,7 @@ def test_frame_invert(self):
                 result = pd.eval(expr, engine=self.engine, parser=self.parser)
 
         # int raises on numexpr
-        lhs = DataFrame(randint(5, size=(5, 2)))
+        lhs = DataFrame(np.random.randint(5, size=(5, 2)))
         if self.engine == "numexpr":
             msg = "couldn't find matching opcode for 'invert"
             with pytest.raises(NotImplementedError, match=msg):
@@ -477,13 +476,13 @@ def test_frame_invert(self):
             tm.assert_frame_equal(expect, result)
 
         # bool always works
-        lhs = DataFrame(rand(5, 2) > 0.5)
+        lhs = DataFrame(np.random.rand(5, 2) > 0.5)
         expect = ~lhs
         result = pd.eval(expr, engine=self.engine, parser=self.parser)
         tm.assert_frame_equal(expect, result)
 
         # object raises
-        lhs = DataFrame({"b": ["a", 1, 2.0], "c": rand(3) > 0.5})
+        lhs = DataFrame({"b": ["a", 1, 2.0], "c": np.random.rand(3) > 0.5})
         if self.engine == "numexpr":
             with pytest.raises(ValueError, match="unknown type object"):
                 result = pd.eval(expr, engine=self.engine, parser=self.parser)
@@ -498,7 +497,7 @@ def test_series_invert(self):
 
         # series
         # float raises
-        lhs = Series(randn(5))
+        lhs = Series(np.random.randn(5))
         if self.engine == "numexpr":
             msg = "couldn't find matching opcode for 'invert_dd'"
             with pytest.raises(NotImplementedError, match=msg):
@@ -509,7 +508,7 @@ def test_series_invert(self):
                 result = pd.eval(expr, engine=self.engine, parser=self.parser)
 
         # int raises on numexpr
-        lhs = Series(randint(5, size=5))
+        lhs = Series(np.random.randint(5, size=5))
         if self.engine == "numexpr":
             msg = "couldn't find matching opcode for 'invert"
             with pytest.raises(NotImplementedError, match=msg):
@@ -520,7 +519,7 @@ def test_series_invert(self):
             tm.assert_series_equal(expect, result)
 
         # bool
-        lhs = Series(rand(5) > 0.5)
+        lhs = Series(np.random.rand(5) > 0.5)
         expect = ~lhs
         result = pd.eval(expr, engine=self.engine, parser=self.parser)
         tm.assert_series_equal(expect, result)
@@ -543,19 +542,19 @@ def test_frame_negate(self):
         expr = self.ex("-")
 
         # float
-        lhs = DataFrame(randn(5, 2))
+        lhs = DataFrame(np.random.randn(5, 2))
         expect = -lhs
         result = pd.eval(expr, engine=self.engine, parser=self.parser)
         tm.assert_frame_equal(expect, result)
 
         # int
-        lhs = DataFrame(randint(5, size=(5, 2)))
+        lhs = DataFrame(np.random.randint(5, size=(5, 2)))
         expect = -lhs
         result = pd.eval(expr, engine=self.engine, parser=self.parser)
         tm.assert_frame_equal(expect, result)
 
         # bool doesn't work with numexpr but works elsewhere
-        lhs = DataFrame(rand(5, 2) > 0.5)
+        lhs = DataFrame(np.random.rand(5, 2) > 0.5)
         if self.engine == "numexpr":
             msg = "couldn't find matching opcode for 'neg_bb'"
             with pytest.raises(NotImplementedError, match=msg):
@@ -569,19 +568,19 @@ def test_series_negate(self):
         expr = self.ex("-")
 
         # float
-        lhs = Series(randn(5))
+        lhs = Series(np.random.randn(5))
         expect = -lhs
         result = pd.eval(expr, engine=self.engine, parser=self.parser)
         tm.assert_series_equal(expect, result)
 
         # int
-        lhs = Series(randint(5, size=5))
+        lhs = Series(np.random.randint(5, size=5))
         expect = -lhs
         result = pd.eval(expr, engine=self.engine, parser=self.parser)
         tm.assert_series_equal(expect, result)
 
         # bool doesn't work with numexpr but works elsewhere
-        lhs = Series(rand(5) > 0.5)
+        lhs = Series(np.random.rand(5) > 0.5)
         if self.engine == "numexpr":
             msg = "couldn't find matching opcode for 'neg_bb'"
             with pytest.raises(NotImplementedError, match=msg):
@@ -595,11 +594,11 @@ def test_series_negate(self):
         "lhs",
         [
             # Float
-            DataFrame(randn(5, 2)),
+            DataFrame(np.random.randn(5, 2)),
             # Int
-            DataFrame(randint(5, size=(5, 2))),
+            DataFrame(np.random.randint(5, size=(5, 2))),
             # bool doesn't work with numexpr but works elsewhere
-            DataFrame(rand(5, 2) > 0.5),
+            DataFrame(np.random.rand(5, 2) > 0.5),
         ],
     )
     def test_frame_pos(self, lhs):
@@ -613,11 +612,11 @@ def test_frame_pos(self, lhs):
         "lhs",
         [
             # Float
-            Series(randn(5)),
+            Series(np.random.randn(5)),
             # Int
-            Series(randint(5, size=5)),
+            Series(np.random.randint(5, size=5)),
             # bool doesn't work with numexpr but works elsewhere
-            Series(rand(5) > 0.5),
+            Series(np.random.rand(5) > 0.5),
         ],
     )
     def test_series_pos(self, lhs):
@@ -688,7 +687,7 @@ def test_disallow_scalar_bool_ops(self):
         exprs += ("2 * x > 2 or 1 and 2",)
         exprs += ("2 * df > 3 and 1 or a",)
 
-        x, a, b, df = np.random.randn(3), 1, 2, DataFrame(randn(3, 2))  # noqa
+        x, a, b, df = np.random.randn(3), 1, 2, DataFrame(np.random.randn(3, 2))  # noqa
         for ex in exprs:
             msg = "cannot evaluate scalar only bool ops|'BoolOp' nodes are not"
             with pytest.raises(NotImplementedError, match=msg):
@@ -909,7 +908,7 @@ def test_frame_comparison(self, engine, parser, r_idx_type, c_idx_type):
         res = pd.eval("df < 2", engine=engine, parser=parser)
         tm.assert_frame_equal(res, df < 2)
 
-        df3 = DataFrame(randn(*df.shape), index=df.index, columns=df.columns)
+        df3 = DataFrame(np.random.randn(*df.shape), index=df.index, columns=df.columns)
         res = pd.eval("df < df3", engine=engine, parser=parser)
         tm.assert_frame_equal(res, df < df3)
 
@@ -1089,8 +1088,8 @@ def test_complex_series_frame_alignment(self, engine, parser, r1, c1, r2, c2):
             tm.assert_frame_equal(res, expected)
 
     def test_performance_warning_for_poor_alignment(self, engine, parser):
-        df = DataFrame(randn(1000, 10))
-        s = Series(randn(10000))
+        df = DataFrame(np.random.randn(1000, 10))
+        s = Series(np.random.randn(10000))
         if engine == "numexpr":
             seen = PerformanceWarning
         else:
@@ -1099,17 +1098,17 @@ def test_performance_warning_for_poor_alignment(self, engine, parser):
         with tm.assert_produces_warning(seen):
             pd.eval("df + s", engine=engine, parser=parser)
 
-        s = Series(randn(1000))
+        s = Series(np.random.randn(1000))
         with tm.assert_produces_warning(False):
             pd.eval("df + s", engine=engine, parser=parser)
 
-        df = DataFrame(randn(10, 10000))
-        s = Series(randn(10000))
+        df = DataFrame(np.random.randn(10, 10000))
+        s = Series(np.random.randn(10000))
         with tm.assert_produces_warning(False):
             pd.eval("df + s", engine=engine, parser=parser)
 
-        df = DataFrame(randn(10, 10))
-        s = Series(randn(10000))
+        df = DataFrame(np.random.randn(10, 10))
+        s = Series(np.random.randn(10000))
 
         is_python_engine = engine == "python"
 
@@ -1206,8 +1205,8 @@ def test_bool_ops_with_constants(self, rhs, lhs, op):
         assert res == exp
 
     def test_4d_ndarray_fails(self):
-        x = randn(3, 4, 5, 6)
-        y = Series(randn(10))
+        x = np.random.randn(3, 4, 5, 6)
+        y = Series(np.random.randn(10))
         msg = "N-dimensional objects, where N > 2, are not supported with eval"
         with pytest.raises(NotImplementedError, match=msg):
             self.eval("x + y", local_dict={"x": x, "y": y})
@@ -1217,7 +1216,7 @@ def test_constant(self):
         assert x == 1
 
     def test_single_variable(self):
-        df = DataFrame(randn(10, 2))
+        df = DataFrame(np.random.randn(10, 2))
         df2 = self.eval("df", local_dict={"df": df})
         tm.assert_frame_equal(df, df2)
 
@@ -1574,7 +1573,7 @@ def test_nested_period_index_subscript_expression(self):
         tm.assert_frame_equal(r, e)
 
     def test_date_boolean(self):
-        df = DataFrame(randn(5, 3))
+        df = DataFrame(np.random.randn(5, 3))
         df["dates1"] = date_range("1/1/2012", periods=5)
         res = self.eval(
             "df.dates1 < 20130101",
@@ -1859,7 +1858,7 @@ class TestMathNumExprPython(TestMathPythonPython):
     parser = "python"
 
 
-_var_s = randn(10)
+_var_s = np.random.randn(10)
 
 
 class TestScope:
diff --git a/pandas/tests/indexing/multiindex/test_insert.py b/pandas/tests/indexing/multiindex/test_insert.py
index 42922c3deeee4..9f5ad90d36e03 100644
--- a/pandas/tests/indexing/multiindex/test_insert.py
+++ b/pandas/tests/indexing/multiindex/test_insert.py
@@ -1,4 +1,4 @@
-from numpy.random import randn
+import numpy as np
 
 from pandas import DataFrame, MultiIndex, Series
 import pandas._testing as tm
@@ -14,7 +14,7 @@ def test_setitem_mixed_depth(self):
 
         tuples = sorted(zip(*arrays))
         index = MultiIndex.from_tuples(tuples)
-        df = DataFrame(randn(4, 6), columns=index)
+        df = DataFrame(np.random.randn(4, 6), columns=index)
 
         result = df.copy()
         expected = df.copy()
diff --git a/pandas/tests/indexing/multiindex/test_setitem.py b/pandas/tests/indexing/multiindex/test_setitem.py
index b58b81d5aa1b3..059f8543104a7 100644
--- a/pandas/tests/indexing/multiindex/test_setitem.py
+++ b/pandas/tests/indexing/multiindex/test_setitem.py
@@ -1,5 +1,4 @@
 import numpy as np
-from numpy.random import randn
 import pytest
 
 import pandas as pd
@@ -311,7 +310,9 @@ def test_frame_getitem_setitem_multislice(self):
         tm.assert_frame_equal(df, result)
 
     def test_frame_setitem_multi_column(self):
-        df = DataFrame(randn(10, 4), columns=[["a", "a", "b", "b"], [0, 1, 0, 1]])
+        df = DataFrame(
+            np.random.randn(10, 4), columns=[["a", "a", "b", "b"], [0, 1, 0, 1]]
+        )
 
         cp = df.copy()
         cp["a"] = cp["b"]
diff --git a/pandas/tests/indexing/multiindex/test_sorted.py b/pandas/tests/indexing/multiindex/test_sorted.py
index bafe5068e1418..8a013c769f2cc 100644
--- a/pandas/tests/indexing/multiindex/test_sorted.py
+++ b/pandas/tests/indexing/multiindex/test_sorted.py
@@ -1,5 +1,4 @@
 import numpy as np
-from numpy.random import randn
 import pytest
 
 from pandas import DataFrame, MultiIndex, Series
@@ -115,7 +114,7 @@ def test_series_getitem_not_sorted(self):
         ]
         tuples = zip(*arrays)
         index = MultiIndex.from_tuples(tuples)
-        s = Series(randn(8), index=index)
+        s = Series(np.random.randn(8), index=index)
 
         arrays = [np.array(x) for x in zip(*index.values)]
 
diff --git a/pandas/tests/io/test_clipboard.py b/pandas/tests/io/test_clipboard.py
index a454d3b855cdf..569bc8a04862e 100644
--- a/pandas/tests/io/test_clipboard.py
+++ b/pandas/tests/io/test_clipboard.py
@@ -1,7 +1,6 @@
 from textwrap import dedent
 
 import numpy as np
-from numpy.random import randint
 import pytest
 
 import pandas as pd
@@ -54,7 +53,7 @@ def df(request):
         return tm.makeCustomDataframe(
             max_rows + 1,
             3,
-            data_gen_f=lambda *args: randint(2),
+            data_gen_f=lambda *args: np.random.randint(2),
             c_idx_type="s",
             r_idx_type="i",
             c_idx_names=[None],
@@ -95,7 +94,7 @@ def df(request):
         return tm.makeCustomDataframe(
             5,
             3,
-            data_gen_f=lambda *args: randint(2),
+            data_gen_f=lambda *args: np.random.randint(2),
             c_idx_type="s",
             r_idx_type="i",
             c_idx_names=[None],
diff --git a/pandas/tests/io/test_html.py b/pandas/tests/io/test_html.py
index 59034e9f3d807..f929d4ac31484 100644
--- a/pandas/tests/io/test_html.py
+++ b/pandas/tests/io/test_html.py
@@ -7,7 +7,6 @@
 from urllib.error import URLError
 
 import numpy as np
-from numpy.random import rand
 import pytest
 
 from pandas.compat import is_platform_windows
@@ -110,7 +109,7 @@ def test_to_html_compat(self):
             tm.makeCustomDataframe(
                 4,
                 3,
-                data_gen_f=lambda *args: rand(),
+                data_gen_f=lambda *args: np.random.rand(),
                 c_idx_names=False,
                 r_idx_names=False,
             )
diff --git a/pandas/tests/plotting/common.py b/pandas/tests/plotting/common.py
index 2a6bd97c93b8e..c04b70f3c2953 100644
--- a/pandas/tests/plotting/common.py
+++ b/pandas/tests/plotting/common.py
@@ -2,7 +2,6 @@
 import warnings
 
 import numpy as np
-from numpy import random
 
 from pandas.util._decorators import cache_readonly
 import pandas.util._test_decorators as td
@@ -50,11 +49,11 @@ def setup_method(self, method):
                 {
                     "gender": gender,
                     "classroom": classroom,
-                    "height": random.normal(66, 4, size=n),
-                    "weight": random.normal(161, 32, size=n),
-                    "category": random.randint(4, size=n),
+                    "height": np.random.normal(66, 4, size=n),
+                    "weight": np.random.normal(161, 32, size=n),
+                    "category": np.random.randint(4, size=n),
                     "datetime": to_datetime(
-                        random.randint(
+                        np.random.randint(
                             self.start_date_to_int64,
                             self.end_date_to_int64,
                             size=n,
diff --git a/pandas/tests/plotting/test_boxplot_method.py b/pandas/tests/plotting/test_boxplot_method.py
index 0a096acc9fa6d..dc2e9e1e8d15f 100644
--- a/pandas/tests/plotting/test_boxplot_method.py
+++ b/pandas/tests/plotting/test_boxplot_method.py
@@ -2,7 +2,6 @@
 import string
 
 import numpy as np
-from numpy import random
 import pytest
 
 import pandas.util._test_decorators as td
@@ -186,7 +185,7 @@ def test_boxplot_numeric_data(self):
     )
     def test_color_kwd(self, colors_kwd, expected):
         # GH: 26214
-        df = DataFrame(random.rand(10, 2))
+        df = DataFrame(np.random.rand(10, 2))
         result = df.boxplot(color=colors_kwd, return_type="dict")
         for k, v in expected.items():
             assert result[k][0].get_color() == v
@@ -197,7 +196,7 @@ def test_color_kwd(self, colors_kwd, expected):
     )
     def test_color_kwd_errors(self, dict_colors, msg):
         # GH: 26214
-        df = DataFrame(random.rand(10, 2))
+        df = DataFrame(np.random.rand(10, 2))
         with pytest.raises(ValueError, match=msg):
             df.boxplot(color=dict_colors, return_type="dict")
 
@@ -293,7 +292,7 @@ def test_grouped_box_return_type(self):
         self._check_box_return_type(result, "dict", expected_keys=["Male", "Female"])
 
         columns2 = "X B C D A G Y N Q O".split()
-        df2 = DataFrame(random.randn(50, 10), columns=columns2)
+        df2 = DataFrame(np.random.randn(50, 10), columns=columns2)
         categories2 = "A B C D E F G H I J".split()
         df2["category"] = categories2 * 5
 
diff --git a/pandas/tests/plotting/test_frame.py b/pandas/tests/plotting/test_frame.py
index ba59fc1a3cc3f..e6a61d35365a3 100644
--- a/pandas/tests/plotting/test_frame.py
+++ b/pandas/tests/plotting/test_frame.py
@@ -6,7 +6,6 @@
 import warnings
 
 import numpy as np
-from numpy.random import rand, randn
 import pytest
 
 import pandas.util._test_decorators as td
@@ -170,7 +169,7 @@ def test_integer_array_plot(self):
 
     def test_mpl2_color_cycle_str(self):
         # GH 15516
-        df = DataFrame(randn(10, 3), columns=["a", "b", "c"])
+        df = DataFrame(np.random.randn(10, 3), columns=["a", "b", "c"])
         colors = ["C0", "C1", "C2", "C3", "C4", "C5", "C6", "C7", "C8", "C9"]
         with warnings.catch_warnings(record=True) as w:
             warnings.simplefilter("always", "MatplotlibDeprecationWarning")
@@ -198,7 +197,7 @@ def test_rgb_tuple_color(self):
         _check_plot_works(df.plot, x="x", y="y", color=(1, 0, 0, 0.5))
 
     def test_color_empty_string(self):
-        df = DataFrame(randn(10, 2))
+        df = DataFrame(np.random.randn(10, 2))
         with pytest.raises(ValueError):
             df.plot(color="")
 
@@ -243,14 +242,14 @@ def test_nonnumeric_exclude(self):
 
     @pytest.mark.slow
     def test_implicit_label(self):
-        df = DataFrame(randn(10, 3), columns=["a", "b", "c"])
+        df = DataFrame(np.random.randn(10, 3), columns=["a", "b", "c"])
         ax = df.plot(x="a", y="b")
         self._check_text_labels(ax.xaxis.get_label(), "a")
 
     @pytest.mark.slow
     def test_donot_overwrite_index_name(self):
         # GH 8494
-        df = DataFrame(randn(2, 2), columns=["a", "b"])
+        df = DataFrame(np.random.randn(2, 2), columns=["a", "b"])
         df.index.name = "NAME"
         df.plot(y="b", label="LABEL")
         assert df.index.name == "NAME"
@@ -813,7 +812,7 @@ def test_subplots_dup_columns(self):
 
     def test_negative_log(self):
         df = -DataFrame(
-            rand(6, 4),
+            np.random.rand(6, 4),
             index=list(string.ascii_letters[:6]),
             columns=["x", "y", "z", "four"],
         )
@@ -832,15 +831,20 @@ def _compare_stacked_y_cood(self, normal_lines, stacked_lines):
 
     def test_line_area_stacked(self):
         with tm.RNGContext(42):
-            df = DataFrame(rand(6, 4), columns=["w", "x", "y", "z"])
+            df = DataFrame(np.random.rand(6, 4), columns=["w", "x", "y", "z"])
             neg_df = -df
             # each column has either positive or negative value
             sep_df = DataFrame(
-                {"w": rand(6), "x": rand(6), "y": -rand(6), "z": -rand(6)}
+                {
+                    "w": np.random.rand(6),
+                    "x": np.random.rand(6),
+                    "y": -np.random.rand(6),
+                    "z": -np.random.rand(6),
+                }
             )
             # each column has positive-negative mixed value
             mixed_df = DataFrame(
-                randn(6, 4),
+                np.random.randn(6, 4),
                 index=list(string.ascii_letters[:6]),
                 columns=["w", "x", "y", "z"],
             )
@@ -908,7 +912,7 @@ def test_line_area_nan_df(self):
             tm.assert_numpy_array_equal(ax.lines[1].get_ydata(), expected2)
 
     def test_line_lim(self):
-        df = DataFrame(rand(6, 3), columns=["x", "y", "z"])
+        df = DataFrame(np.random.rand(6, 3), columns=["x", "y", "z"])
         ax = df.plot()
         xmin, xmax = ax.get_xlim()
         lines = ax.get_lines()
@@ -932,7 +936,7 @@ def test_line_lim(self):
             assert xmax >= lines[0].get_data()[0][-1]
 
     def test_area_lim(self):
-        df = DataFrame(rand(6, 4), columns=["x", "y", "z", "four"])
+        df = DataFrame(np.random.rand(6, 4), columns=["x", "y", "z", "four"])
 
         neg_df = -df
         for stacked in [True, False]:
@@ -954,7 +958,7 @@ def test_bar_colors(self):
 
         default_colors = self._unpack_cycler(plt.rcParams)
 
-        df = DataFrame(randn(5, 5))
+        df = DataFrame(np.random.randn(5, 5))
         ax = df.plot.bar()
         self._check_colors(ax.patches[::5], facecolors=default_colors[:5])
         tm.close()
@@ -1004,7 +1008,7 @@ def test_bar_user_colors(self):
 
     @pytest.mark.slow
     def test_bar_linewidth(self):
-        df = DataFrame(randn(5, 5))
+        df = DataFrame(np.random.randn(5, 5))
 
         # regular
         ax = df.plot.bar(linewidth=2)
@@ -1025,7 +1029,7 @@ def test_bar_linewidth(self):
 
     @pytest.mark.slow
     def test_bar_barwidth(self):
-        df = DataFrame(randn(5, 5))
+        df = DataFrame(np.random.randn(5, 5))
 
         width = 0.9
 
@@ -1063,7 +1067,7 @@ def test_bar_barwidth(self):
 
     @pytest.mark.slow
     def test_bar_barwidth_position(self):
-        df = DataFrame(randn(5, 5))
+        df = DataFrame(np.random.randn(5, 5))
         self._check_bar_alignment(
             df, kind="bar", stacked=False, width=0.9, position=0.2
         )
@@ -1084,7 +1088,7 @@ def test_bar_barwidth_position(self):
     @pytest.mark.slow
     def test_bar_barwidth_position_int(self):
         # GH 12979
-        df = DataFrame(randn(5, 5))
+        df = DataFrame(np.random.randn(5, 5))
 
         for w in [1, 1.0]:
             ax = df.plot.bar(stacked=True, width=w)
@@ -1103,7 +1107,7 @@ def test_bar_barwidth_position_int(self):
 
     @pytest.mark.slow
     def test_bar_bottom_left(self):
-        df = DataFrame(rand(5, 5))
+        df = DataFrame(np.random.rand(5, 5))
         ax = df.plot.bar(stacked=False, bottom=1)
         result = [p.get_y() for p in ax.patches]
         assert result == [1] * 25
@@ -1179,7 +1183,7 @@ def test_bar_categorical(self):
     @pytest.mark.slow
     def test_plot_scatter(self):
         df = DataFrame(
-            randn(6, 4),
+            np.random.randn(6, 4),
             index=list(string.ascii_letters[:6]),
             columns=["x", "y", "z", "four"],
         )
@@ -1291,7 +1295,7 @@ def test_plot_scatter_with_categorical_data(self, x, y):
     @pytest.mark.slow
     def test_plot_scatter_with_c(self):
         df = DataFrame(
-            randn(6, 4),
+            np.random.randn(6, 4),
             index=list(string.ascii_letters[:6]),
             columns=["x", "y", "z", "four"],
         )
@@ -1394,7 +1398,7 @@ def test_scatter_colorbar_different_cmap(self):
     @pytest.mark.slow
     def test_plot_bar(self):
         df = DataFrame(
-            randn(6, 4),
+            np.random.randn(6, 4),
             index=list(string.ascii_letters[:6]),
             columns=["one", "two", "three", "four"],
         )
@@ -1407,7 +1411,9 @@ def test_plot_bar(self):
         _check_plot_works(df.plot.bar, stacked=True)
 
         df = DataFrame(
-            randn(10, 15), index=list(string.ascii_letters[:10]), columns=range(15)
+            np.random.randn(10, 15),
+            index=list(string.ascii_letters[:10]),
+            columns=range(15),
         )
         _check_plot_works(df.plot.bar)
 
@@ -1523,7 +1529,7 @@ def test_bar_subplots_center(self):
 
     @pytest.mark.slow
     def test_bar_align_single_column(self):
-        df = DataFrame(randn(5))
+        df = DataFrame(np.random.randn(5))
         self._check_bar_alignment(df, kind="bar", stacked=False)
         self._check_bar_alignment(df, kind="bar", stacked=True)
         self._check_bar_alignment(df, kind="barh", stacked=False)
@@ -1641,7 +1647,7 @@ def test_boxplot_vertical(self):
     @pytest.mark.slow
     def test_boxplot_return_type(self):
         df = DataFrame(
-            randn(6, 4),
+            np.random.randn(6, 4),
             index=list(string.ascii_letters[:6]),
             columns=["one", "two", "three", "four"],
         )
@@ -1683,7 +1689,7 @@ def test_boxplot_subplots_return_type(self):
     @pytest.mark.slow
     @td.skip_if_no_scipy
     def test_kde_df(self):
-        df = DataFrame(randn(100, 4))
+        df = DataFrame(np.random.randn(100, 4))
         ax = _check_plot_works(df.plot, kind="kde")
         expected = [pprint_thing(c) for c in df.columns]
         self._check_legend_labels(ax, labels=expected)
@@ -1710,7 +1716,7 @@ def test_kde_missing_vals(self):
     def test_hist_df(self):
         from matplotlib.patches import Rectangle
 
-        df = DataFrame(randn(100, 4))
+        df = DataFrame(np.random.randn(100, 4))
         series = df[0]
 
         ax = _check_plot_works(df.plot.hist)
@@ -1918,16 +1924,16 @@ def test_hist_df_coord(self):
 
     @pytest.mark.slow
     def test_plot_int_columns(self):
-        df = DataFrame(randn(100, 4)).cumsum()
+        df = DataFrame(np.random.randn(100, 4)).cumsum()
         _check_plot_works(df.plot, legend=True)
 
     @pytest.mark.slow
     def test_df_legend_labels(self):
         kinds = ["line", "bar", "barh", "kde", "area", "hist"]
-        df = DataFrame(rand(3, 3), columns=["a", "b", "c"])
-        df2 = DataFrame(rand(3, 3), columns=["d", "e", "f"])
-        df3 = DataFrame(rand(3, 3), columns=["g", "h", "i"])
-        df4 = DataFrame(rand(3, 3), columns=["j", "k", "l"])
+        df = DataFrame(np.random.rand(3, 3), columns=["a", "b", "c"])
+        df2 = DataFrame(np.random.rand(3, 3), columns=["d", "e", "f"])
+        df3 = DataFrame(np.random.rand(3, 3), columns=["g", "h", "i"])
+        df4 = DataFrame(np.random.rand(3, 3), columns=["j", "k", "l"])
 
         for kind in kinds:
 
@@ -1956,9 +1962,9 @@ def test_df_legend_labels(self):
 
         # Time Series
         ind = date_range("1/1/2014", periods=3)
-        df = DataFrame(randn(3, 3), columns=["a", "b", "c"], index=ind)
-        df2 = DataFrame(randn(3, 3), columns=["d", "e", "f"], index=ind)
-        df3 = DataFrame(randn(3, 3), columns=["g", "h", "i"], index=ind)
+        df = DataFrame(np.random.randn(3, 3), columns=["a", "b", "c"], index=ind)
+        df2 = DataFrame(np.random.randn(3, 3), columns=["d", "e", "f"], index=ind)
+        df3 = DataFrame(np.random.randn(3, 3), columns=["g", "h", "i"], index=ind)
         ax = df.plot(legend=True, secondary_y="b")
         self._check_legend_labels(ax, labels=["a", "b (right)", "c"])
         ax = df2.plot(legend=False, ax=ax)
@@ -2012,7 +2018,7 @@ def test_missing_marker_multi_plots_on_same_ax(self):
 
     def test_legend_name(self):
         multi = DataFrame(
-            randn(4, 4),
+            np.random.randn(4, 4),
             columns=[np.array(["a", "a", "b", "b"]), np.array(["x", "y", "x", "y"])],
         )
         multi.columns.names = ["group", "individual"]
@@ -2021,7 +2027,7 @@ def test_legend_name(self):
         leg_title = ax.legend_.get_title()
         self._check_text_labels(leg_title, "group,individual")
 
-        df = DataFrame(randn(5, 5))
+        df = DataFrame(np.random.randn(5, 5))
         ax = df.plot(legend=True, ax=ax)
         leg_title = ax.legend_.get_title()
         self._check_text_labels(leg_title, "group,individual")
@@ -2038,7 +2044,7 @@ def test_legend_name(self):
     @pytest.mark.slow
     def test_no_legend(self):
         kinds = ["line", "bar", "barh", "kde", "area", "hist"]
-        df = DataFrame(rand(3, 3), columns=["a", "b", "c"])
+        df = DataFrame(np.random.rand(3, 3), columns=["a", "b", "c"])
 
         for kind in kinds:
 
@@ -2051,7 +2057,7 @@ def test_style_by_column(self):
 
         fig = plt.gcf()
 
-        df = DataFrame(randn(100, 3))
+        df = DataFrame(np.random.randn(100, 3))
         for markers in [
             {0: "^", 1: "+", 2: "o"},
             {0: "^", 1: "+"},
@@ -2078,7 +2084,7 @@ def test_line_colors(self):
         from matplotlib import cm
 
         custom_colors = "rgcby"
-        df = DataFrame(randn(5, 5))
+        df = DataFrame(np.random.randn(5, 5))
 
         ax = df.plot(color=custom_colors)
         self._check_colors(ax.get_lines(), linecolors=custom_colors)
@@ -2131,7 +2137,7 @@ def test_line_colors_and_styles_subplots(self):
 
         default_colors = self._unpack_cycler(self.plt.rcParams)
 
-        df = DataFrame(randn(5, 5))
+        df = DataFrame(np.random.randn(5, 5))
 
         axes = df.plot(subplots=True)
         for ax, c in zip(axes, list(default_colors)):
@@ -2200,7 +2206,7 @@ def test_area_colors(self):
         from matplotlib.collections import PolyCollection
 
         custom_colors = "rgcby"
-        df = DataFrame(rand(5, 5))
+        df = DataFrame(np.random.rand(5, 5))
 
         ax = df.plot.area(color=custom_colors)
         self._check_colors(ax.get_lines(), linecolors=custom_colors)
@@ -2243,7 +2249,7 @@ def test_area_colors(self):
     def test_hist_colors(self):
         default_colors = self._unpack_cycler(self.plt.rcParams)
 
-        df = DataFrame(randn(5, 5))
+        df = DataFrame(np.random.randn(5, 5))
         ax = df.plot.hist()
         self._check_colors(ax.patches[::10], facecolors=default_colors[:5])
         tm.close()
@@ -2280,7 +2286,7 @@ def test_kde_colors(self):
         from matplotlib import cm
 
         custom_colors = "rgcby"
-        df = DataFrame(rand(5, 5))
+        df = DataFrame(np.random.rand(5, 5))
 
         ax = df.plot.kde(color=custom_colors)
         self._check_colors(ax.get_lines(), linecolors=custom_colors)
@@ -2302,7 +2308,7 @@ def test_kde_colors_and_styles_subplots(self):
 
         default_colors = self._unpack_cycler(self.plt.rcParams)
 
-        df = DataFrame(randn(5, 5))
+        df = DataFrame(np.random.randn(5, 5))
 
         axes = df.plot(kind="kde", subplots=True)
         for ax, c in zip(axes, list(default_colors)):
@@ -2370,7 +2376,7 @@ def _check_colors(bp, box_c, whiskers_c, medians_c, caps_c="k", fliers_c=None):
 
         default_colors = self._unpack_cycler(self.plt.rcParams)
 
-        df = DataFrame(randn(5, 5))
+        df = DataFrame(np.random.randn(5, 5))
         bp = df.plot.box(return_type="dict")
         _check_colors(bp, default_colors[0], default_colors[0], default_colors[2])
         tm.close()
@@ -2444,7 +2450,7 @@ def test_default_color_cycle(self):
         colors = list("rgbk")
         plt.rcParams["axes.prop_cycle"] = cycler.cycler("color", colors)
 
-        df = DataFrame(randn(5, 3))
+        df = DataFrame(np.random.randn(5, 3))
         ax = df.plot()
 
         expected = self._unpack_cycler(plt.rcParams)[:3]
@@ -2484,7 +2490,7 @@ def test_all_invalid_plot_data(self):
     @pytest.mark.slow
     def test_partially_invalid_plot_data(self):
         with tm.RNGContext(42):
-            df = DataFrame(randn(10, 2), dtype=object)
+            df = DataFrame(np.random.randn(10, 2), dtype=object)
             df[np.random.rand(df.shape[0]) > 0.5] = "a"
             for kind in plotting.PlotAccessor._common_kinds:
 
@@ -2495,14 +2501,14 @@ def test_partially_invalid_plot_data(self):
         with tm.RNGContext(42):
             # area plot doesn't support positive/negative mixed data
             kinds = ["area"]
-            df = DataFrame(rand(10, 2), dtype=object)
+            df = DataFrame(np.random.rand(10, 2), dtype=object)
             df[np.random.rand(df.shape[0]) > 0.5] = "a"
             for kind in kinds:
                 with pytest.raises(TypeError):
                     df.plot(kind=kind)
 
     def test_invalid_kind(self):
-        df = DataFrame(randn(10, 2))
+        df = DataFrame(np.random.randn(10, 2))
         with pytest.raises(ValueError):
             df.plot(kind="aasdf")
 
@@ -3208,7 +3214,7 @@ def test_df_grid_settings(self):
         )
 
     def test_invalid_colormap(self):
-        df = DataFrame(randn(3, 2), columns=["A", "B"])
+        df = DataFrame(np.random.randn(3, 2), columns=["A", "B"])
 
         with pytest.raises(ValueError):
             df.plot(colormap="invalid_colormap")
@@ -3219,11 +3225,11 @@ def test_plain_axes(self):
         # a plain Axes object (GH11556)
         fig, ax = self.plt.subplots()
         fig.add_axes([0.2, 0.2, 0.2, 0.2])
-        Series(rand(10)).plot(ax=ax)
+        Series(np.random.rand(10)).plot(ax=ax)
 
         # supplied ax itself is a plain Axes, but because the cmap keyword
         # a new ax is created for the colorbar -> also multiples axes (GH11520)
-        df = DataFrame({"a": randn(8), "b": randn(8)})
+        df = DataFrame({"a": np.random.randn(8), "b": np.random.randn(8)})
         fig = self.plt.figure()
         ax = fig.add_axes((0, 0, 1, 1))
         df.plot(kind="scatter", ax=ax, x="a", y="b", c="a", cmap="hsv")
@@ -3234,15 +3240,15 @@ def test_plain_axes(self):
 
         divider = make_axes_locatable(ax)
         cax = divider.append_axes("right", size="5%", pad=0.05)
-        Series(rand(10)).plot(ax=ax)
-        Series(rand(10)).plot(ax=cax)
+        Series(np.random.rand(10)).plot(ax=ax)
+        Series(np.random.rand(10)).plot(ax=cax)
 
         fig, ax = self.plt.subplots()
         from mpl_toolkits.axes_grid1.inset_locator import inset_axes
 
         iax = inset_axes(ax, width="30%", height=1.0, loc=3)
-        Series(rand(10)).plot(ax=ax)
-        Series(rand(10)).plot(ax=iax)
+        Series(np.random.rand(10)).plot(ax=ax)
+        Series(np.random.rand(10)).plot(ax=iax)
 
     def test_passed_bar_colors(self):
         import matplotlib as mpl
diff --git a/pandas/tests/plotting/test_hist_method.py b/pandas/tests/plotting/test_hist_method.py
index d9a58e808661b..9775218e0dbf6 100644
--- a/pandas/tests/plotting/test_hist_method.py
+++ b/pandas/tests/plotting/test_hist_method.py
@@ -1,7 +1,6 @@
 """ Test cases for .hist method """
 
 import numpy as np
-from numpy.random import randn
 import pytest
 
 import pandas.util._test_decorators as td
@@ -103,8 +102,8 @@ def test_hist_layout_with_by(self):
     def test_hist_no_overlap(self):
         from matplotlib.pyplot import gcf, subplot
 
-        x = Series(randn(2))
-        y = Series(randn(2))
+        x = Series(np.random.randn(2))
+        y = Series(np.random.randn(2))
         subplot(121)
         x.hist()
         subplot(122)
@@ -163,7 +162,7 @@ def test_hist_df_legacy(self):
             _check_plot_works(self.hist_df.hist)
 
         # make sure layout is handled
-        df = DataFrame(randn(100, 2))
+        df = DataFrame(np.random.randn(100, 2))
         df[2] = to_datetime(
             np.random.randint(
                 self.start_date_to_int64,
@@ -178,11 +177,11 @@ def test_hist_df_legacy(self):
         assert not axes[1, 1].get_visible()
 
         _check_plot_works(df[[2]].hist)
-        df = DataFrame(randn(100, 1))
+        df = DataFrame(np.random.randn(100, 1))
         _check_plot_works(df.hist)
 
         # make sure layout is handled
-        df = DataFrame(randn(100, 5))
+        df = DataFrame(np.random.randn(100, 5))
         df[5] = to_datetime(
             np.random.randint(
                 self.start_date_to_int64,
@@ -269,7 +268,7 @@ def test_hist_non_numerical_or_datetime_raises(self):
 
     @pytest.mark.slow
     def test_hist_layout(self):
-        df = DataFrame(randn(100, 2))
+        df = DataFrame(np.random.randn(100, 2))
         df[2] = to_datetime(
             np.random.randint(
                 self.start_date_to_int64,
@@ -404,7 +403,7 @@ def test_grouped_hist_legacy(self):
 
         from pandas.plotting._matplotlib.hist import _grouped_hist
 
-        df = DataFrame(randn(500, 1), columns=["A"])
+        df = DataFrame(np.random.randn(500, 1), columns=["A"])
         df["B"] = to_datetime(
             np.random.randint(
                 self.start_date_to_int64,
diff --git a/pandas/tests/plotting/test_misc.py b/pandas/tests/plotting/test_misc.py
index 2838bef2a10b0..f37d83cd0783e 100644
--- a/pandas/tests/plotting/test_misc.py
+++ b/pandas/tests/plotting/test_misc.py
@@ -1,8 +1,6 @@
 """ Test cases for misc plot functions """
 
 import numpy as np
-from numpy import random
-from numpy.random import randn
 import pytest
 
 import pandas.util._test_decorators as td
@@ -101,7 +99,7 @@ def test_scatter_matrix_axis(self):
         scatter_matrix = plotting.scatter_matrix
 
         with tm.RNGContext(42):
-            df = DataFrame(randn(100, 3))
+            df = DataFrame(np.random.randn(100, 3))
 
         # we are plotting multiples on a sub-plot
         with tm.assert_produces_warning(
@@ -166,9 +164,9 @@ def test_andrews_curves(self, iris):
         length = 10
         df = DataFrame(
             {
-                "A": random.rand(length),
-                "B": random.rand(length),
-                "C": random.rand(length),
+                "A": np.random.rand(length),
+                "B": np.random.rand(length),
+                "C": np.random.rand(length),
                 "Name": ["A"] * length,
             }
         )
@@ -353,11 +351,11 @@ def test_get_standard_colors_random_seed(self):
         # GH17525
         df = DataFrame(np.zeros((10, 10)))
 
-        # Make sure that the random seed isn't reset by get_standard_colors
+        # Make sure that the np.random.seed isn't reset by get_standard_colors
         plotting.parallel_coordinates(df, 0)
-        rand1 = random.random()
+        rand1 = np.random.random()
         plotting.parallel_coordinates(df, 0)
-        rand2 = random.random()
+        rand2 = np.random.random()
         assert rand1 != rand2
 
         # Make sure it produces the same colors every time it's called
diff --git a/pandas/tests/plotting/test_series.py b/pandas/tests/plotting/test_series.py
index 271cf65433afe..777bc914069a6 100644
--- a/pandas/tests/plotting/test_series.py
+++ b/pandas/tests/plotting/test_series.py
@@ -5,7 +5,6 @@
 from itertools import chain
 
 import numpy as np
-from numpy.random import randn
 import pytest
 
 import pandas.util._test_decorators as td
@@ -59,7 +58,7 @@ def test_plot(self):
             _check_plot_works(self.series[:5].plot, kind=kind)
 
         _check_plot_works(self.series[:10].plot.barh)
-        ax = _check_plot_works(Series(randn(10)).plot.bar, color="black")
+        ax = _check_plot_works(Series(np.random.randn(10)).plot.bar, color="black")
         self._check_colors([ax.patches[0]], facecolors=["black"])
 
         # GH 6951
@@ -267,7 +266,7 @@ def test_bar_user_colors(self):
         assert result == expected
 
     def test_rotation(self):
-        df = DataFrame(randn(5, 5))
+        df = DataFrame(np.random.randn(5, 5))
         # Default rot 0
         _, ax = self.plt.subplots()
         axes = df.plot(ax=ax)
@@ -282,7 +281,7 @@ def test_irregular_datetime(self):
 
         rng = date_range("1/1/2000", "3/1/2000")
         rng = rng[[0, 1, 2, 3, 5, 9, 10, 11, 12]]
-        ser = Series(randn(len(rng)), rng)
+        ser = Series(np.random.randn(len(rng)), rng)
         _, ax = self.plt.subplots()
         ax = ser.plot(ax=ax)
         xp = DatetimeConverter.convert(datetime(1999, 1, 1), "", ax)
@@ -459,8 +458,8 @@ def test_hist_layout_with_by(self):
     def test_hist_no_overlap(self):
         from matplotlib.pyplot import gcf, subplot
 
-        x = Series(randn(2))
-        y = Series(randn(2))
+        x = Series(np.random.randn(2))
+        y = Series(np.random.randn(2))
         subplot(121)
         x.hist()
         subplot(122)
@@ -590,7 +589,7 @@ def test_secondary_logy(self, input_logy, expected_scale):
 
     @pytest.mark.slow
     def test_plot_fails_with_dupe_color_and_style(self):
-        x = Series(randn(2))
+        x = Series(np.random.randn(2))
         with pytest.raises(ValueError):
             _, ax = self.plt.subplots()
             x.plot(style="k--", color="k", ax=ax)
@@ -734,7 +733,7 @@ def test_dup_datetime_index_plot(self):
         dr1 = date_range("1/1/2009", periods=4)
         dr2 = date_range("1/2/2009", periods=4)
         index = dr1.append(dr2)
-        values = randn(index.size)
+        values = np.random.randn(index.size)
         s = Series(values, index=index)
         _check_plot_works(s.plot)
 
@@ -763,7 +762,7 @@ def test_errorbar_plot(self):
 
         s = Series(np.arange(10), name="x")
         s_err = np.random.randn(10)
-        d_err = DataFrame(randn(10, 2), index=s.index, columns=["x", "y"])
+        d_err = DataFrame(np.random.randn(10, 2), index=s.index, columns=["x", "y"])
         # test line and bar plots
         kinds = ["line", "bar"]
         for kind in kinds:
@@ -785,7 +784,7 @@ def test_errorbar_plot(self):
         ix = date_range("1/1/2000", "1/1/2001", freq="M")
         ts = Series(np.arange(12), index=ix, name="x")
         ts_err = Series(np.random.randn(12), index=ix)
-        td_err = DataFrame(randn(12, 2), index=ix, columns=["x", "y"])
+        td_err = DataFrame(np.random.randn(12, 2), index=ix, columns=["x", "y"])
 
         ax = _check_plot_works(ts.plot, yerr=ts_err)
         self._check_has_errorbars(ax, xerr=0, yerr=1)
diff --git a/pandas/tests/reshape/concat/test_series.py b/pandas/tests/reshape/concat/test_series.py
index aea2840bb897f..20838a418cfea 100644
--- a/pandas/tests/reshape/concat/test_series.py
+++ b/pandas/tests/reshape/concat/test_series.py
@@ -1,5 +1,4 @@
 import numpy as np
-from numpy.random import randn
 import pytest
 
 import pandas as pd
@@ -66,8 +65,8 @@ def test_concat_series_axis1(self, sort=sort):
         tm.assert_frame_equal(result, expected)
 
         # preserve series names, #2489
-        s = Series(randn(5), name="A")
-        s2 = Series(randn(5), name="B")
+        s = Series(np.random.randn(5), name="A")
+        s2 = Series(np.random.randn(5), name="B")
 
         result = concat([s, s2], axis=1)
         expected = DataFrame({"A": s, "B": s2})
@@ -78,8 +77,8 @@ def test_concat_series_axis1(self, sort=sort):
         tm.assert_index_equal(result.columns, Index(["A", 0], dtype="object"))
 
         # must reindex, #2603
-        s = Series(randn(3), index=["c", "a", "b"], name="A")
-        s2 = Series(randn(4), index=["d", "a", "b", "c"], name="B")
+        s = Series(np.random.randn(3), index=["c", "a", "b"], name="A")
+        s2 = Series(np.random.randn(4), index=["d", "a", "b", "c"], name="B")
         result = concat([s, s2], axis=1, sort=sort)
         expected = DataFrame({"A": s, "B": s2})
         tm.assert_frame_equal(result, expected)
@@ -103,8 +102,8 @@ def test_concat_series_axis1_names_applied(self):
 
     def test_concat_series_axis1_same_names_ignore_index(self):
         dates = date_range("01-Jan-2013", "01-Jan-2014", freq="MS")[0:-1]
-        s1 = Series(randn(len(dates)), index=dates, name="value")
-        s2 = Series(randn(len(dates)), index=dates, name="value")
+        s1 = Series(np.random.randn(len(dates)), index=dates, name="value")
+        s2 = Series(np.random.randn(len(dates)), index=dates, name="value")
 
         result = concat([s1, s2], axis=1, ignore_index=True)
         expected = Index([0, 1])
diff --git a/pandas/tests/reshape/merge/test_join.py b/pandas/tests/reshape/merge/test_join.py
index c1efbb8536d68..5968fd1834f8c 100644
--- a/pandas/tests/reshape/merge/test_join.py
+++ b/pandas/tests/reshape/merge/test_join.py
@@ -1,5 +1,4 @@
 import numpy as np
-from numpy.random import randn
 import pytest
 
 import pandas as pd
@@ -290,10 +289,10 @@ def test_join_empty_bug(self):
 
     def test_join_unconsolidated(self):
         # GH #331
-        a = DataFrame(randn(30, 2), columns=["a", "b"])
-        c = Series(randn(30))
+        a = DataFrame(np.random.randn(30, 2), columns=["a", "b"])
+        c = Series(np.random.randn(30))
         a["c"] = c
-        d = DataFrame(randn(30, 1), columns=["q"])
+        d = DataFrame(np.random.randn(30, 1), columns=["q"])
 
         # it works!
         a.join(d)
@@ -412,8 +411,8 @@ def test_join_hierarchical_mixed(self):
 
     def test_join_float64_float32(self):
 
-        a = DataFrame(randn(10, 2), columns=["a", "b"], dtype=np.float64)
-        b = DataFrame(randn(10, 1), columns=["c"], dtype=np.float32)
+        a = DataFrame(np.random.randn(10, 2), columns=["a", "b"], dtype=np.float64)
+        b = DataFrame(np.random.randn(10, 1), columns=["c"], dtype=np.float32)
         joined = a.join(b)
         assert joined.dtypes["a"] == "float64"
         assert joined.dtypes["b"] == "float64"
diff --git a/pandas/tests/reshape/merge/test_multi.py b/pandas/tests/reshape/merge/test_multi.py
index 68096192c51ea..65673bdde4257 100644
--- a/pandas/tests/reshape/merge/test_multi.py
+++ b/pandas/tests/reshape/merge/test_multi.py
@@ -1,5 +1,4 @@
 import numpy as np
-from numpy.random import randn
 import pytest
 
 import pandas as pd
@@ -406,10 +405,10 @@ def test_left_merge_na_buglet(self):
         left = DataFrame(
             {
                 "id": list("abcde"),
-                "v1": randn(5),
-                "v2": randn(5),
+                "v1": np.random.randn(5),
+                "v2": np.random.randn(5),
                 "dummy": list("abcde"),
-                "v3": randn(5),
+                "v3": np.random.randn(5),
             },
             columns=["id", "v1", "v2", "dummy", "v3"],
         )
diff --git a/pandas/tests/test_expressions.py b/pandas/tests/test_expressions.py
index 6d4c1594146de..2d862fda013d5 100644
--- a/pandas/tests/test_expressions.py
+++ b/pandas/tests/test_expressions.py
@@ -2,15 +2,14 @@
 import re
 
 import numpy as np
-from numpy.random import randn
 import pytest
 
 import pandas._testing as tm
 from pandas.core.api import DataFrame, Index, Series
 from pandas.core.computation import expressions as expr
 
-_frame = DataFrame(randn(10000, 4), columns=list("ABCD"), dtype="float64")
-_frame2 = DataFrame(randn(100, 4), columns=list("ABCD"), dtype="float64")
+_frame = DataFrame(np.random.randn(10000, 4), columns=list("ABCD"), dtype="float64")
+_frame2 = DataFrame(np.random.randn(100, 4), columns=list("ABCD"), dtype="float64")
 _mixed = DataFrame(
     {
         "A": _frame["A"].copy(),
diff --git a/pandas/tests/test_strings.py b/pandas/tests/test_strings.py
index 9be5abb9dda65..f52d0d0fccab8 100644
--- a/pandas/tests/test_strings.py
+++ b/pandas/tests/test_strings.py
@@ -2,7 +2,6 @@
 import re
 
 import numpy as np
-from numpy.random import randint
 import pytest
 
 from pandas._libs import lib
@@ -367,7 +366,12 @@ def test_iter_single_element(self):
         tm.assert_series_equal(ds, s)
 
     def test_iter_object_try_string(self):
-        ds = Series([slice(None, randint(10), randint(10, 20)) for _ in range(4)])
+        ds = Series(
+            [
+                slice(None, np.random.randint(10), np.random.randint(10, 20))
+                for _ in range(4)
+            ]
+        )
 
         i, s = 100, "h"
 
diff --git a/pandas/tests/window/conftest.py b/pandas/tests/window/conftest.py
index e5c5579d35a5c..1780925202593 100644
--- a/pandas/tests/window/conftest.py
+++ b/pandas/tests/window/conftest.py
@@ -1,7 +1,6 @@
 from datetime import datetime, timedelta
 
 import numpy as np
-from numpy.random import randn
 import pytest
 
 import pandas.util._test_decorators as td
@@ -254,7 +253,7 @@ def consistency_data(request):
 
 def _create_arr():
     """Internal function to mock an array."""
-    arr = randn(100)
+    arr = np.random.randn(100)
     locs = np.arange(20, 40)
     arr[locs] = np.NaN
     return arr
@@ -276,7 +275,7 @@ def _create_series():
 def _create_frame():
     """Internal function to mock DataFrame."""
     rng = _create_rng()
-    return DataFrame(randn(100, 10), index=rng, columns=np.arange(10))
+    return DataFrame(np.random.randn(100, 10), index=rng, columns=np.arange(10))
 
 
 @pytest.fixture
diff --git a/pandas/tests/window/moments/conftest.py b/pandas/tests/window/moments/conftest.py
index 39e6ae71162a9..2fab7f5c91c09 100644
--- a/pandas/tests/window/moments/conftest.py
+++ b/pandas/tests/window/moments/conftest.py
@@ -1,5 +1,4 @@
 import numpy as np
-from numpy.random import randn
 import pytest
 
 from pandas import Series
@@ -7,8 +6,8 @@
 
 @pytest.fixture
 def binary_ew_data():
-    A = Series(randn(50), index=np.arange(50))
-    B = A[2:] + randn(48)
+    A = Series(np.random.randn(50), index=np.arange(50))
+    B = A[2:] + np.random.randn(48)
 
     A[:10] = np.NaN
     B[-10:] = np.NaN
diff --git a/pandas/tests/window/moments/test_moments_consistency_ewm.py b/pandas/tests/window/moments/test_moments_consistency_ewm.py
index 089ec697b5b1c..2718bdabee96a 100644
--- a/pandas/tests/window/moments/test_moments_consistency_ewm.py
+++ b/pandas/tests/window/moments/test_moments_consistency_ewm.py
@@ -1,5 +1,4 @@
 import numpy as np
-from numpy.random import randn
 import pytest
 
 from pandas import DataFrame, Series, concat
@@ -63,7 +62,7 @@ def test_different_input_array_raise_exception(name, binary_ew_data):
     msg = "Input arrays must be of the same type!"
     # exception raised is Exception
     with pytest.raises(Exception, match=msg):
-        getattr(A.ewm(com=20, min_periods=5), name)(randn(50))
+        getattr(A.ewm(com=20, min_periods=5), name)(np.random.randn(50))
 
 
 @pytest.mark.slow
diff --git a/pandas/tests/window/moments/test_moments_consistency_expanding.py b/pandas/tests/window/moments/test_moments_consistency_expanding.py
index 3ec91dcb60610..eb348fda5782b 100644
--- a/pandas/tests/window/moments/test_moments_consistency_expanding.py
+++ b/pandas/tests/window/moments/test_moments_consistency_expanding.py
@@ -1,7 +1,6 @@
 import warnings
 
 import numpy as np
-from numpy.random import randn
 import pytest
 
 from pandas import DataFrame, Index, MultiIndex, Series, isna, notna
@@ -34,7 +33,7 @@ def _check_expanding(
 
 
 def _check_expanding_has_min_periods(func, static_comp, has_min_periods):
-    ser = Series(randn(50))
+    ser = Series(np.random.randn(50))
 
     if has_min_periods:
         result = func(ser, min_periods=30)
@@ -46,7 +45,7 @@ def _check_expanding_has_min_periods(func, static_comp, has_min_periods):
         assert isna(result.iloc[13])
         assert notna(result.iloc[14])
 
-        ser2 = Series(randn(20))
+        ser2 = Series(np.random.randn(20))
         result = func(ser2, min_periods=5)
         assert isna(result[3])
         assert notna(result[4])
@@ -62,7 +61,7 @@ def _check_expanding_has_min_periods(func, static_comp, has_min_periods):
 
 def test_expanding_corr(series):
     A = series.dropna()
-    B = (A + randn(len(A)))[:-5]
+    B = (A + np.random.randn(len(A)))[:-5]
 
     result = A.expanding().corr(B)
 
@@ -88,7 +87,7 @@ def test_expanding_quantile(series):
 
 def test_expanding_cov(series):
     A = series
-    B = (A + randn(len(A)))[:-5]
+    B = (A + np.random.randn(len(A)))[:-5]
 
     result = A.expanding().cov(B)
 
diff --git a/pandas/tests/window/moments/test_moments_consistency_rolling.py b/pandas/tests/window/moments/test_moments_consistency_rolling.py
index 6ab53c8e2ec0d..b7b05c1a6e30d 100644
--- a/pandas/tests/window/moments/test_moments_consistency_rolling.py
+++ b/pandas/tests/window/moments/test_moments_consistency_rolling.py
@@ -2,7 +2,6 @@
 import warnings
 
 import numpy as np
-from numpy.random import randn
 import pytest
 
 import pandas.util._test_decorators as td
@@ -34,7 +33,7 @@ def _rolling_consistency_cases():
 # binary moments
 def test_rolling_cov(series):
     A = series
-    B = A + randn(len(A))
+    B = A + np.random.randn(len(A))
 
     result = A.rolling(window=50, min_periods=25).cov(B)
     tm.assert_almost_equal(result[-1], np.cov(A[-50:], B[-50:])[0, 1])
@@ -42,7 +41,7 @@ def test_rolling_cov(series):
 
 def test_rolling_corr(series):
     A = series
-    B = A + randn(len(A))
+    B = A + np.random.randn(len(A))
 
     result = A.rolling(window=50, min_periods=25).corr(B)
     tm.assert_almost_equal(result[-1], np.corrcoef(A[-50:], B[-50:])[0, 1])
diff --git a/pandas/tests/window/moments/test_moments_ewm.py b/pandas/tests/window/moments/test_moments_ewm.py
index 605b85344ba76..def6d7289fec2 100644
--- a/pandas/tests/window/moments/test_moments_ewm.py
+++ b/pandas/tests/window/moments/test_moments_ewm.py
@@ -1,5 +1,4 @@
 import numpy as np
-from numpy.random import randn
 import pytest
 
 from pandas import DataFrame, Series
@@ -305,7 +304,7 @@ def test_ew_empty_series(method):
 @pytest.mark.parametrize("name", ["mean", "var", "vol"])
 def test_ew_min_periods(min_periods, name):
     # excluding NaNs correctly
-    arr = randn(50)
+    arr = np.random.randn(50)
     arr[:10] = np.NaN
     arr[-10:] = np.NaN
     s = Series(arr)