diff --git a/pyproject.toml b/pyproject.toml
index a7aaf932a..e1fc29648 100644
--- a/pyproject.toml
+++ b/pyproject.toml
@@ -34,7 +34,7 @@ python = ">=3.8,<3.11"
 types-pytz = ">= 2022.1.1"
 
 [tool.poetry.dev-dependencies]
-mypy = "==0.990"
+mypy = "0.990"
 pyarrow = ">=9.0.0"
 pytest = ">=7.1.2"
 pyright = ">=1.1.278"
@@ -42,7 +42,7 @@ poethepoet = "0.16.0"
 loguru = ">=0.6.0"
 pandas = "1.5.1"
 typing-extensions = ">=4.2.0"
-matplotlib = "~=3.5.0"
+matplotlib = ">=3.5.1"
 pre-commit = ">=2.19.0"
 black = ">=22.8.0"
 isort = ">=5.10.1"
diff --git a/tests/test_resampler.py b/tests/test_resampler.py
index 3d9dc3538..c4287d1a9 100644
--- a/tests/test_resampler.py
+++ b/tests/test_resampler.py
@@ -16,12 +16,14 @@
 )
 from pandas.core.groupby.generic import SeriesGroupBy
 from pandas.core.resample import Resampler
-import pytest
 from typing_extensions import assert_type
 
 from pandas._typing import Scalar
 
-from tests import check
+from tests import (
+    check,
+    pytest_warns_bounded,
+)
 
 DR = date_range("1999-1-1", periods=365, freq="D")
 DF_ = DataFrame(np.random.standard_normal((365, 1)), index=DR)
@@ -298,7 +300,9 @@ def s2scalar(val: Series) -> float:
 
     check(S.resample("m").aggregate(np.sum), Series)
     check(S.resample("m").aggregate("sum"), Series)
-    with pytest.warns(FutureWarning, match="Not prepending group keys"):
+    with pytest_warns_bounded(
+        FutureWarning, match="Not prepending group keys", upper="1.5.99"
+    ):
         check(S.resample("m").aggregate(s2series), Series)
     check(S.resample("m").aggregate(s2scalar), Series)
     check(S.resample("m").aggregate([np.mean]), DataFrame)
@@ -319,7 +323,9 @@ def df2scalar(val: DataFrame) -> float:
 
     check(DF.resample("m").aggregate(np.sum), DataFrame)
     check(DF.resample("m").aggregate("sum"), DataFrame)
-    with pytest.warns(FutureWarning, match="Not prepending group keys"):
+    with pytest_warns_bounded(
+        FutureWarning, match="Not prepending group keys", upper="1.5.99"
+    ):
         check(DF.resample("m").aggregate(df2frame), DataFrame)
     check(DF.resample("m").aggregate(df2series), DataFrame)
     check(DF.resample("m").aggregate(df2scalar), DataFrame)