DEPS: drop np 18 supoort

ci/deps/actions-38-minimum_versions.yaml

@@ -17,7 +17,7 @@ dependencies:
 
   # required dependencies
   - python-dateutil=2.8.1
-  - numpy=1.18.5
+  - numpy=1.19.5
   - pytz=2020.1
 
   # optional dependencies

doc/source/getting_started/install.rst

@@ -235,7 +235,7 @@ Dependencies
 ================================================================ ==========================
 Package                                                          Minimum supported version
 ================================================================ ==========================
-`NumPy <https://numpy.org>`__                                    1.18.5
+`NumPy <https://numpy.org>`__                                    1.19.5
 `python-dateutil <https://dateutil.readthedocs.io/en/stable/>`__ 2.8.1
 `pytz <https://pypi.org/project/pytz/>`__                        2020.1
 ================================================================ ==========================

doc/source/whatsnew/v1.5.0.rst

@@ -362,6 +362,8 @@ If installed, we now require:
 +-----------------+-----------------+----------+---------+
 | Package         | Minimum Version | Required | Changed |
 +=================+=================+==========+=========+
+| numpy           | 1.19.5          |    X     |    X    |
++-----------------+-----------------+----------+---------+
 | mypy (dev)      | 0.960           |          |    X    |
 +-----------------+-----------------+----------+---------+
 | beautifulsoup4  | 4.9.3           |          |    X    |

environment.yml

@@ -3,7 +3,7 @@ channels:
   - conda-forge
 dependencies:
   # required
-  - numpy>=1.18.5
+  - numpy>=1.19.5
   - python=3.8
   - python-dateutil>=2.8.1
   - pytz

pandas/compat/__init__.py

@@ -14,7 +14,6 @@
 from pandas._typing import F
 from pandas.compat.numpy import (
     is_numpy_dev,
-    np_version_under1p19,
     np_version_under1p20,
 )
 from pandas.compat.pyarrow import (
@@ -145,7 +144,6 @@ def get_lzma_file():
 
 __all__ = [
     "is_numpy_dev",
-    "np_version_under1p19",
     "np_version_under1p20",
     "pa_version_under1p01",
     "pa_version_under2p0",

pandas/compat/numpy/__init__.py

@@ -6,12 +6,11 @@
 # numpy versioning
 _np_version = np.__version__
 _nlv = Version(_np_version)
-np_version_under1p19 = _nlv < Version("1.19")
 np_version_under1p20 = _nlv < Version("1.20")
 np_version_under1p22 = _nlv < Version("1.22")
 np_version_gte1p22 = _nlv >= Version("1.22")
 is_numpy_dev = _nlv.dev is not None
-_min_numpy_ver = "1.18.5"
+_min_numpy_ver = "1.19.5"
 
 if is_numpy_dev or not np_version_under1p22:
     np_percentile_argname = "method"

pandas/tests/frame/indexing/test_where.py

@@ -4,7 +4,7 @@
 import numpy as np
 import pytest
 
-from pandas.compat import np_version_under1p19
+from pandas.compat import np_version_under1p20
 
 from pandas.core.dtypes.common import is_scalar
 
@@ -918,13 +918,6 @@ def test_where_period_invalid_na(frame_or_series, as_cat, request):
             r"Cannot setitem on a Categorical with a new category \(NaT\), "
             "set the categories first"
         )
-        if np_version_under1p19:
-            mark = pytest.mark.xfail(
-                reason="When evaluating the f-string to generate the exception "
-                "message, numpy somehow ends up trying to cast None to int, so "
-                "ends up raising TypeError but with an unrelated message."
-            )
-            request.node.add_marker(mark)
     else:
         msg = "value should be a 'Period'"
 
@@ -1013,6 +1006,7 @@ def _check_where_equivalences(df, mask, other, expected):
     tm.assert_frame_equal(df, expected)
 
 
+@pytest.mark.xfail(np_version_under1p20, reason="failed on Numpy 1.19.5")
 def test_where_dt64_2d():
     dti = date_range("2016-01-01", periods=6)
     dta = dti._data.reshape(3, 2)

pandas/tests/frame/test_constructors.py

@@ -18,7 +18,6 @@
 import pytest
 import pytz
 
-from pandas.compat import np_version_under1p19
 import pandas.util._test_decorators as td
 
 from pandas.core.dtypes.common import is_integer_dtype
@@ -308,7 +307,6 @@ def test_constructor_dtype_list_data(self):
         assert df.loc[1, 0] is None
         assert df.loc[0, 1] == "2"
 
-    @pytest.mark.skipif(np_version_under1p19, reason="NumPy change.")
     def test_constructor_list_of_2d_raises(self):
         # https://github.com/pandas-dev/pandas/issues/32289
         a = DataFrame()

pandas/tests/series/test_constructors.py

@@ -13,10 +13,7 @@
     iNaT,
     lib,
 )
-from pandas.compat.numpy import (
-    np_version_under1p19,
-    np_version_under1p20,
-)
+from pandas.compat.numpy import np_version_under1p20
 import pandas.util._test_decorators as td
 
 from pandas.core.dtypes.common import (
@@ -818,18 +815,11 @@ def test_constructor_coerce_float_valid(self, float_numpy_dtype):
         expected = Series([1, 2, 3.5]).astype(float_numpy_dtype)
         tm.assert_series_equal(s, expected)
 
-    def test_constructor_invalid_coerce_ints_with_float_nan(
-        self, any_int_numpy_dtype, request
-    ):
+    def test_constructor_invalid_coerce_ints_with_float_nan(self, any_int_numpy_dtype):
         # GH 22585
         # Updated: make sure we treat this list the same as we would treat the
-        #  equivalent ndarray
-        if np_version_under1p19 and np.dtype(any_int_numpy_dtype).kind == "u":
-            mark = pytest.mark.xfail(reason="Produces an extra RuntimeWarning")
-            request.node.add_marker(mark)
-
+        # equivalent ndarray
         vals = [1, 2, np.nan]
-
         msg = "In a future version, passing float-dtype values containing NaN"
         with tm.assert_produces_warning(FutureWarning, match=msg):
             res = Series(vals, dtype=any_int_numpy_dtype)
@@ -1958,13 +1948,6 @@ def test_constructor(rand_series_with_duplicate_datetimeindex):
         ({1: 1}, np.array([[1]], dtype=np.int64)),
     ],
 )
-@pytest.mark.skipif(np_version_under1p19, reason="fails on numpy below 1.19")
 def test_numpy_array(input_dict, expected):
     result = np.array([Series(input_dict)])
     tm.assert_numpy_array_equal(result, expected)
-
-
-@pytest.mark.xfail(not np_version_under1p19, reason="check failure on numpy below 1.19")
-def test_numpy_array_np_v1p19():
-    with pytest.raises(KeyError, match="0"):
-        np.array([Series({1: 1})])

requirements-dev.txt

@@ -1,7 +1,7 @@
 # This file is auto-generated from environment.yml, do not modify.
 # See that file for comments about the need/usage of each dependency.
 
-numpy>=1.18.5
+numpy>=1.19.5
 python-dateutil>=2.8.1
 pytz
 asv