Removes references to pandas older than 1.5.0

Author: chalmerlowe

db_dtypes/__init__.py

@@ -46,15 +46,7 @@
 # nanosecond precision when boxing scalars.
 _NP_BOX_DTYPE = "datetime64[us]"
 
-
-# To use JSONArray and JSONDtype, you'll need Pandas 1.5.0 or later. With the removal
-# of Python 3.7 compatibility, the minimum Pandas version will be updated to 1.5.0.
-if packaging.version.Version(pandas.__version__) >= packaging.version.Version("1.5.0"):
-    from db_dtypes.json import JSONArray, JSONArrowType, JSONDtype
-else:
-    JSONArray = None
-    JSONDtype = None
-
+from db_dtypes.json import JSONArray, JSONArrowType, JSONDtype
 
 @pandas.api.extensions.register_extension_dtype
 class TimeDtype(core.BaseDatetimeDtype):

db_dtypes/core.py

@@ -186,8 +186,6 @@ def median(
         keepdims: bool = False,
         skipna: bool = True,
     ):
-        if not hasattr(pandas_backports, "numpy_validate_median"):
-            raise NotImplementedError("Need pandas 1.3 or later to calculate median.")
 
         pandas_backports.numpy_validate_median(
             (),

tests/compliance/time/test_time_compliance_1_5.py

@@ -24,7 +24,7 @@
 import pytest
 
 # NDArrayBacked2DTests suite added in https://github.com/pandas-dev/pandas/pull/44974
-pytest.importorskip("pandas", minversion="1.5.0dev")
+pytest.importorskip("pandas")
 
 
 class Test2DCompat(base.NDArrayBacked2DTests):

tests/unit/test_dtypes.py

@@ -20,8 +20,6 @@
 pd = pytest.importorskip("pandas")
 np = pytest.importorskip("numpy")
 
-pandas_release = packaging.version.parse(pd.__version__).release
-
 SAMPLE_RAW_VALUES = dict(
     dbdate=(datetime.date(2021, 2, 2), "2021-2-3", pd.NaT),
     dbtime=(datetime.time(1, 2, 2), "1:2:3.5", pd.NaT),
@@ -538,39 +536,37 @@ def test_min_max_median(dtype):
         a = cls(data)
         assert a.min() == sample_values[0]
         assert a.max() == sample_values[-1]
-        if pandas_release >= (1, 3):
-            assert (
-                a.median() == datetime.time(1, 2, 4)
-                if dtype == "dbtime"
-                else datetime.date(2021, 2, 3)
-            )
+        
+        assert (
+            a.median() == datetime.time(1, 2, 4)
+            if dtype == "dbtime"
+            else datetime.date(2021, 2, 3)
+        )
 
     empty = cls([])
     assert empty.min() is pd.NaT
     assert empty.max() is pd.NaT
-    if pandas_release >= (1, 3):
-        assert empty.median() is pd.NaT
+    assert empty.median() is pd.NaT
     empty = cls([None])
     assert empty.min() is pd.NaT
     assert empty.max() is pd.NaT
     assert empty.min(skipna=False) is pd.NaT
     assert empty.max(skipna=False) is pd.NaT
-    if pandas_release >= (1, 3):
-        with pytest.warns(RuntimeWarning, match="empty slice"):
-            # It's weird that we get the warning here, and not
-            # below. :/
-            assert empty.median() is pd.NaT
-        assert empty.median(skipna=False) is pd.NaT
+
+    with pytest.warns(RuntimeWarning, match="empty slice"):
+        # It's weird that we get the warning here, and not
+        # below. :/
+        assert empty.median() is pd.NaT
+    assert empty.median(skipna=False) is pd.NaT
 
     a = _make_one(dtype)
     assert a.min() == sample_values[0]
     assert a.max() == sample_values[1]
-    if pandas_release >= (1, 3):
-        assert (
-            a.median() == datetime.time(1, 2, 2, 750000)
-            if dtype == "dbtime"
-            else datetime.date(2021, 2, 2)
-        )
+    assert (
+        a.median() == datetime.time(1, 2, 2, 750000)
+        if dtype == "dbtime"
+        else datetime.date(2021, 2, 2)
+    )
 
 
 def test_date_add():