DEPS: Bump NumPy and tzdata

ci/deps/actions-310-minimum_versions.yaml

@@ -22,7 +22,7 @@ dependencies:
 
   # required dependencies
   - python-dateutil=2.8.2
-  - numpy=1.23.5
+  - numpy=1.26.0
 
   # optional dependencies
   - beautifulsoup4=4.12.3
@@ -62,4 +62,4 @@ dependencies:
   - pip:
     - adbc-driver-postgresql==0.10.0
     - adbc-driver-sqlite==0.8.0
-    - tzdata==2022.7
+    - tzdata==2023.3

ci/deps/actions-310.yaml

@@ -60,4 +60,4 @@ dependencies:
   - pip:
     - adbc-driver-postgresql>=0.10.0
     - adbc-driver-sqlite>=0.8.0
-    - tzdata>=2022.7
+    - tzdata>=2023.3

ci/deps/actions-311-downstream_compat.yaml

@@ -73,4 +73,4 @@ dependencies:
   - pip:
     - adbc-driver-postgresql>=0.10.0
     - adbc-driver-sqlite>=0.8.0
-    - tzdata>=2022.7
+    - tzdata>=2023.3

ci/deps/actions-311-numpydev.yaml

@@ -24,4 +24,4 @@ dependencies:
     - "--extra-index-url https://pypi.anaconda.org/scientific-python-nightly-wheels/simple"
     - "--pre"
     - "numpy"
-    - "tzdata>=2022.7"
+    - "tzdata>=2023.3"

ci/deps/actions-311-pyarrownightly.yaml

@@ -22,7 +22,7 @@ dependencies:
   - pip
 
   - pip:
-    - "tzdata>=2022.7"
+    - "tzdata>=2023.3"
     - "--extra-index-url https://pypi.anaconda.org/scientific-python-nightly-wheels/simple"
     - "--prefer-binary"
     - "--pre"

ci/deps/actions-312.yaml

@@ -60,4 +60,4 @@ dependencies:
   - pip:
     - adbc-driver-postgresql>=0.10.0
     - adbc-driver-sqlite>=0.8.0
-    - tzdata>=2022.7
+    - tzdata>=2023.3

ci/deps/actions-313-freethreading.yaml

@@ -25,5 +25,5 @@ dependencies:
   - pip:
     # No free-threaded coveragepy (with the C-extension) on conda-forge yet
     - pytest-cov
-    - "tzdata>=2022.7"
+    - tzdata>=2023.3
     - "--extra-index-url https://pypi.anaconda.org/scientific-python-nightly-wheels/simple"

ci/deps/actions-313.yaml

@@ -60,4 +60,4 @@ dependencies:
   - pip:
     - adbc-driver-postgresql>=0.10.0
     - adbc-driver-sqlite>=0.8.0
-    - tzdata>=2022.7
+    - tzdata>=2023.3

ci/deps/actions-pypy-39.yaml

@@ -23,4 +23,4 @@ dependencies:
   - numpy
   - python-dateutil
   - pip:
-    - tzdata>=2022.7
+    - tzdata>=2023.3

ci/meta.yaml

@@ -37,7 +37,7 @@ requirements:
     - numpy >=1.21.6  # [py<311]
     - numpy >=1.23.2  # [py>=311]
     - python-dateutil >=2.8.2
-    - python-tzdata >=2022.7
+    - python-tzdata >=2023.3
 
 test:
   imports:

doc/source/getting_started/install.rst

@@ -148,9 +148,9 @@ pandas requires the following dependencies.
 ================================================================ ==========================
 Package                                                          Minimum supported version
 ================================================================ ==========================
-`NumPy <https://numpy.org>`__                                    1.23.5
+`NumPy <https://numpy.org>`__                                    1.26.0
 `python-dateutil <https://dateutil.readthedocs.io/en/stable/>`__ 2.8.2
-`tzdata <https://pypi.org/project/tzdata/>`__                    2022.7
+`tzdata <https://pypi.org/project/tzdata/>`__                    2023.3
 ================================================================ ==========================
 
 .. _install.optional_dependencies:

doc/source/whatsnew/v3.0.0.rst

@@ -306,13 +306,15 @@ pandas 3.0.0 supports Python 3.10 and higher.
 Increased minimum versions for dependencies
 ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
 Some minimum supported versions of dependencies were updated.
-If installed, we now require:
-
-+-----------------+-----------------+----------+---------+
-| Package         | Minimum Version | Required | Changed |
-+=================+=================+==========+=========+
-| numpy           | 1.23.5          |    X     |    X    |
-+-----------------+-----------------+----------+---------+
+The following required dependencies were updated:
+
++-----------------+----------------------+
+| Package         | New Minimum Version  |
++=================+======================+
+| numpy           | 1.26.0               |
++-----------------+----------------------+
+| tzdata          | 2023.3               |
++-----------------+----------------------+
 
 For `optional libraries <https://pandas.pydata.org/docs/getting_started/install.html>`_ the general recommendation is to use the latest version.
 The following table lists the lowest version per library that is currently being tested throughout the development of pandas.

environment.yml

@@ -123,4 +123,4 @@ dependencies:
       - adbc-driver-postgresql>=0.10.0
       - adbc-driver-sqlite>=0.8.0
       - typing_extensions; python_version<"3.11"
-      - tzdata>=2022.7
+      - tzdata>=2023.3

pandas/compat/_optional.py

@@ -54,7 +54,6 @@
     "xlrd": "2.0.1",
     "xlsxwriter": "3.2.0",
     "zstandard": "0.22.0",
-    "tzdata": "2022.7",
     "qtpy": "2.3.0",
     "pyqt5": "5.15.9",
 }

pandas/compat/numpy/__init__.py

@@ -9,19 +9,15 @@
 # numpy versioning
 _np_version = np.__version__
 _nlv = Version(_np_version)
-np_version_gte1p24 = _nlv >= Version("1.24")
-np_version_gte1p24p3 = _nlv >= Version("1.24.3")
-np_version_gte1p25 = _nlv >= Version("1.25")
 np_version_gt2 = _nlv >= Version("2.0.0")
 is_numpy_dev = _nlv.dev is not None
-_min_numpy_ver = "1.23.5"
+_min_numpy_ver = "1.26.0"
 
 
 if _nlv < Version(_min_numpy_ver):
     raise ImportError(
-        f"this version of pandas is incompatible with numpy < {_min_numpy_ver}\n"
-        f"your numpy version is {_np_version}.\n"
-        f"Please upgrade numpy to >= {_min_numpy_ver} to use this pandas version"
+        f"Please upgrade numpy to >= {_min_numpy_ver} to use this pandas version.\n"
+        f"Your numpy version is {_np_version}."
     )
 
 
@@ -49,5 +45,4 @@
 __all__ = [
     "_np_version",
     "is_numpy_dev",
-    "np",
 ]

pandas/core/common.py

@@ -29,12 +29,10 @@
     cast,
     overload,
 )
-import warnings
 
 import numpy as np
 
 from pandas._libs import lib
-from pandas.compat.numpy import np_version_gte1p24
 
 from pandas.core.dtypes.cast import construct_1d_object_array_from_listlike
 from pandas.core.dtypes.common import (
@@ -243,12 +241,7 @@ def asarray_tuplesafe(values: Iterable, dtype: NpDtype | None = None) -> ArrayLi
         return construct_1d_object_array_from_listlike(values)
 
     try:
-        with warnings.catch_warnings():
-            # Can remove warning filter once NumPy 1.24 is min version
-            if not np_version_gte1p24:
-                # np.VisibleDeprecationWarning only in np.exceptions in 2.0
-                warnings.simplefilter("ignore", np.VisibleDeprecationWarning)  # type: ignore[attr-defined]
-            result = np.asarray(values, dtype=dtype)
+        result = np.asarray(values, dtype=dtype)
     except ValueError:
         # Using try/except since it's more performant than checking is_list_like
         # over each element

pandas/tests/apply/test_frame_apply_relabeling.py

@@ -1,7 +1,4 @@
 import numpy as np
-import pytest
-
-from pandas.compat.numpy import np_version_gte1p25
 
 import pandas as pd
 import pandas._testing as tm
@@ -45,7 +42,6 @@ def test_agg_relabel_multi_columns_multi_methods():
     tm.assert_frame_equal(result, expected)
 
 
-@pytest.mark.xfail(np_version_gte1p25, reason="name of min now equals name of np.min")
 def test_agg_relabel_partial_functions():
     # GH 26513, test on partial, functools or more complex cases
     df = pd.DataFrame({"A": [1, 2, 1, 2], "B": [1, 2, 3, 4], "C": [3, 4, 5, 6]})
@@ -57,16 +53,16 @@ def test_agg_relabel_partial_functions():
 
     result = df.agg(
         foo=("A", min),
-        bar=("A", np.min),
+        bar=("B", np.min),
         cat=("B", max),
         dat=("C", "min"),
         f=("B", np.sum),
         kk=("B", lambda x: min(x)),
     )
     expected = pd.DataFrame(
         {
-            "A": [1.0, 1.0, np.nan, np.nan, np.nan, np.nan],
-            "B": [np.nan, np.nan, 4.0, np.nan, 10.0, 1.0],
+            "A": [1.0, np.nan, np.nan, np.nan, np.nan, np.nan],
+            "B": [np.nan, 1.0, 4.0, np.nan, 10.0, 1.0],
             "C": [np.nan, np.nan, np.nan, 3.0, np.nan, np.nan],
         },
         index=pd.Index(["foo", "bar", "cat", "dat", "f", "kk"]),

pandas/tests/extension/test_period.py

@@ -26,7 +26,6 @@
     iNaT,
 )
 from pandas.compat import is_platform_windows
-from pandas.compat.numpy import np_version_gte1p24
 
 from pandas.core.dtypes.dtypes import PeriodDtype
 
@@ -104,7 +103,7 @@ def check_reduce(self, ser: pd.Series, op_name: str, skipna: bool):
 
     @pytest.mark.parametrize("periods", [1, -2])
     def test_diff(self, data, periods):
-        if is_platform_windows() and np_version_gte1p24:
+        if is_platform_windows():
             with tm.assert_produces_warning(RuntimeWarning, check_stacklevel=False):
                 super().test_diff(data, periods)
         else:

pandas/tests/frame/methods/test_compare.py

@@ -1,8 +1,6 @@
 import numpy as np
 import pytest
 
-from pandas.compat.numpy import np_version_gte1p25
-
 import pandas as pd
 import pandas._testing as tm
 
@@ -270,7 +268,7 @@ def test_compare_ea_and_np_dtype(val1, val2):
         # GH#18463 TODO: is this really the desired behavior?
         expected.loc[1, ("a", "self")] = np.nan
 
-    if val1 is pd.NA and np_version_gte1p25:
+    if val1 is pd.NA:
         # can't compare with numpy array if it contains pd.NA
         with pytest.raises(TypeError, match="boolean value of NA is ambiguous"):
             result = df1.compare(df2, keep_shape=True)

pandas/tests/frame/test_unary.py

@@ -3,8 +3,6 @@
 import numpy as np
 import pytest
 
-from pandas.compat.numpy import np_version_gte1p25
-
 import pandas as pd
 import pandas._testing as tm
 
@@ -123,13 +121,10 @@ def test_pos_object(self, df_data):
     def test_pos_object_raises(self):
         # GH#21380
         df = pd.DataFrame({"a": ["a", "b"]})
-        if np_version_gte1p25:
-            with pytest.raises(
-                TypeError, match=r"^bad operand type for unary \+: \'str\'$"
-            ):
-                tm.assert_frame_equal(+df, df)
-        else:
-            tm.assert_series_equal(+df["a"], df["a"])
+        with pytest.raises(
+            TypeError, match=r"^bad operand type for unary \+: \'str\'$"
+        ):
+            tm.assert_frame_equal(+df, df)
 
     def test_pos_raises(self):
         df = pd.DataFrame({"a": pd.to_datetime(["2017-01-22", "1970-01-01"])})

pandas/tests/indexes/test_common.py

@@ -14,7 +14,6 @@
 import pytest
 
 from pandas.compat import IS64
-from pandas.compat.numpy import np_version_gte1p25
 
 from pandas.core.dtypes.common import (
     is_integer_dtype,
@@ -381,13 +380,11 @@ def test_astype_preserves_name(self, index, dtype):
         else:
             index.name = "idx"
 
-        warn = None
-        if index.dtype.kind == "c" and dtype in ["float64", "int64", "uint64"]:
-            # imaginary components discarded
-            if np_version_gte1p25:
-                warn = np.exceptions.ComplexWarning
-            else:
-                warn = np.ComplexWarning
+        warn = (
+            np.exceptions.ComplexWarning
+            if index.dtype.kind == "c" and dtype in ["float64", "int64", "uint64"]
+            else None
+        )
 
         is_pyarrow_str = str(index.dtype) == "string[pyarrow]" and dtype == "category"
         try:

pandas/tests/io/parser/test_c_parser_only.py

@@ -19,7 +19,6 @@
 import pytest
 
 from pandas.compat import WASM
-from pandas.compat.numpy import np_version_gte1p24
 from pandas.errors import (
     ParserError,
     ParserWarning,
@@ -90,10 +89,9 @@ def test_dtype_and_names_error(c_parser_only):
 3.0 3
 """
     # fallback casting, but not castable
-    warning = RuntimeWarning if np_version_gte1p24 else None
     if not WASM:  # no fp exception support in wasm
         with pytest.raises(ValueError, match="cannot safely convert"):
-            with tm.assert_produces_warning(warning, check_stacklevel=False):
+            with tm.assert_produces_warning(RuntimeWarning, check_stacklevel=False):
                 parser.read_csv(
                     StringIO(data),
                     sep=r"\s+",

pandas/tests/io/pytables/test_complex.py

@@ -82,6 +82,9 @@ def test_complex_mixed_fixed(tmp_path, setup_path):
     tm.assert_frame_equal(df, reread)
 
 
+@pytest.mark.filterwarnings(
+    "ignore:`alltrue` is deprecated as of NumPy 1.25.0:DeprecationWarning"
+)
 def test_complex_mixed_table(tmp_path, setup_path):
     complex64 = np.array(
         [1.0 + 1.0j, 1.0 + 1.0j, 1.0 + 1.0j, 1.0 + 1.0j], dtype=np.complex64

pandas/tests/io/pytables/test_timezones.py

@@ -42,6 +42,9 @@ def _compare_with_tz(a, b):
 gettz_pytz = lambda x: x
 
 
+@pytest.mark.filterwarnings(
+    "ignore:`alltrue` is deprecated as of NumPy 1.25.0:DeprecationWarning"
+)
 @pytest.mark.parametrize("gettz", [gettz_dateutil, gettz_pytz])
 def test_append_with_timezones(setup_path, gettz):
     # as columns
@@ -332,6 +335,9 @@ def test_dst_transitions(setup_path):
             tm.assert_frame_equal(result, df)
 
 
+@pytest.mark.filterwarnings(
+    "ignore:`alltrue` is deprecated as of NumPy 1.25.0:DeprecationWarning"
+)
 def test_read_with_where_tz_aware_index(tmp_path, setup_path):
     # GH 11926
     periods = 10

pandas/tests/plotting/frame/test_frame_subplots.py

@@ -6,7 +6,6 @@
 import pytest
 
 from pandas.compat import is_platform_linux
-from pandas.compat.numpy import np_version_gte1p24
 
 import pandas as pd
 from pandas import (
@@ -423,7 +422,7 @@ def test_subplots_dup_columns_secondary_y_no_subplot(self):
         assert len(ax.right_ax.lines) == 5
 
     @pytest.mark.xfail(
-        np_version_gte1p24 and is_platform_linux(),
+        is_platform_linux(),
         reason="Weird rounding problems",
         strict=False,
     )
@@ -438,7 +437,7 @@ def test_bar_log_no_subplots(self):
         tm.assert_numpy_array_equal(ax.yaxis.get_ticklocs(), expected)
 
     @pytest.mark.xfail(
-        np_version_gte1p24 and is_platform_linux(),
+        is_platform_linux(),
         reason="Weird rounding problems",
         strict=False,
     )