Backport PR #53213 on branch 2.0.x (FIX preserve dtype with datetime …

…columns of different resolution when merging) (#53228)

FIX preserve dtype with datetime columns of different resolution when merging (#53213)

(cherry picked from commit 935244a)

Co-authored-by: Guillaume Lemaitre <g.lemaitre58@gmail.com>

doc/source/whatsnew/v2.0.2.rst

@@ -28,6 +28,7 @@ Bug fixes
 - Bug in :func:`api.interchange.from_dataframe` was raising ``IndexError`` on empty categorical data (:issue:`53077`)
 - Bug in :func:`api.interchange.from_dataframe` was returning :class:`DataFrame`'s of incorrect sizes when called on slices (:issue:`52824`)
 - Bug in :func:`api.interchange.from_dataframe` was unnecessarily raising on bitmasks (:issue:`49888`)
+- Bug in :func:`merge` when merging on datetime columns on different resolutions (:issue:`53200`)
 - Bug in :meth:`DataFrame.convert_dtypes` ignores ``convert_*`` keywords when set to False ``dtype_backend="pyarrow"`` (:issue:`52872`)
 - Bug in :meth:`Series.describe` treating pyarrow-backed timestamps and timedeltas as categorical data (:issue:`53001`)
 - Bug in :meth:`Series.rename` not making a lazy copy when Copy-on-Write is enabled when a scalar is passed to it (:issue:`52450`)

pandas/core/reshape/merge.py

@@ -1401,6 +1401,12 @@ def _maybe_coerce_merge_keys(self) -> None:
                 rk.dtype, DatetimeTZDtype
             ):
                 raise ValueError(msg)
+            elif (
+                isinstance(lk.dtype, DatetimeTZDtype)
+                and isinstance(rk.dtype, DatetimeTZDtype)
+            ) or (lk.dtype.kind == "M" and rk.dtype.kind == "M"):
+                # allows datetime with different resolutions
+                continue
 
             elif lk_is_object and rk_is_object:
                 continue
@@ -2355,7 +2361,7 @@ def _factorize_keys(
     if isinstance(lk.dtype, DatetimeTZDtype) and isinstance(rk.dtype, DatetimeTZDtype):
         # Extract the ndarray (UTC-localized) values
         # Note: we dont need the dtypes to match, as these can still be compared
-        # TODO(non-nano): need to make sure resolutions match
+        lk, rk = cast("DatetimeArray", lk)._ensure_matching_resos(rk)
         lk = cast("DatetimeArray", lk)._ndarray
         rk = cast("DatetimeArray", rk)._ndarray
 

pandas/tests/reshape/merge/test_merge.py

@@ -7,6 +7,7 @@
 
 import numpy as np
 import pytest
+import pytz
 
 from pandas.core.dtypes.common import (
     is_categorical_dtype,
@@ -2750,3 +2751,26 @@ def test_merge_arrow_and_numpy_dtypes(dtype):
     result = df2.merge(df)
     expected = df2.copy()
     tm.assert_frame_equal(result, expected)
+
+
+@pytest.mark.parametrize("tzinfo", [None, pytz.timezone("America/Chicago")])
+def test_merge_datetime_different_resolution(tzinfo):
+    # https://github.com/pandas-dev/pandas/issues/53200
+    df1 = DataFrame(
+        {
+            "t": [pd.Timestamp(2023, 5, 12, tzinfo=tzinfo, unit="ns")],
+            "a": [1],
+        }
+    )
+    df2 = df1.copy()
+    df2["t"] = df2["t"].dt.as_unit("s")
+
+    expected = DataFrame(
+        {
+            "t": [pd.Timestamp(2023, 5, 12, tzinfo=tzinfo)],
+            "a_x": [1],
+            "a_y": [1],
+        }
+    )
+    result = df1.merge(df2, on="t")
+    tm.assert_frame_equal(result, expected)