diff --git a/pandas/core/arrays/timedeltas.py b/pandas/core/arrays/timedeltas.py
index ac4e8934570ce..1aedc3a31e3e7 100644
--- a/pandas/core/arrays/timedeltas.py
+++ b/pandas/core/arrays/timedeltas.py
@@ -316,7 +316,7 @@ def _unbox_scalar(self, value) -> np.timedelta64:
raise ValueError("'value' should be a Timedelta.")
self._check_compatible_with(value)
if value is NaT:
- return np.timedelta64(value.value, "ns")
+ return np.timedelta64(value.value, self.unit)
else:
return value.as_unit(self.unit).asm8
diff --git a/pandas/core/reshape/merge.py b/pandas/core/reshape/merge.py
index 8d009d25a66ba..7d8d7a37ff7e7 100644
--- a/pandas/core/reshape/merge.py
+++ b/pandas/core/reshape/merge.py
@@ -89,7 +89,10 @@
)
from pandas.core.arrays._mixins import NDArrayBackedExtensionArray
import pandas.core.common as com
-from pandas.core.construction import extract_array
+from pandas.core.construction import (
+ ensure_wrapped_if_datetimelike,
+ extract_array,
+)
from pandas.core.frame import _merge_doc
from pandas.core.indexes.api import default_index
from pandas.core.sorting import is_int64_overflow_possible
@@ -2109,12 +2112,24 @@ def injection(obj):
# initial type conversion as needed
if needs_i8_conversion(left_values):
- left_values = left_values.view("i8")
- right_values = right_values.view("i8")
if tolerance is not None:
tolerance = Timedelta(tolerance)
+
+ # TODO: we have no test cases with PeriodDtype here; probably
+ # need to adjust tolerance for that case.
+ if left_values.dtype.kind in ["m", "M"]:
+ # Make sure the i8 representation for tolerance
+ # matches that for left_values/right_values.
+ lvs = ensure_wrapped_if_datetimelike(left_values)
+ tolerance = tolerance.as_unit(lvs.unit)
+
tolerance = tolerance.value
+ # TODO: require left_values.dtype == right_values.dtype, or at least
+ # comparable for e.g. dt64tz
+ left_values = left_values.view("i8")
+ right_values = right_values.view("i8")
+
# a "by" parameter requires special handling
if self.left_by is not None:
# remove 'on' parameter from values if one existed
diff --git a/pandas/tests/reshape/merge/test_merge_asof.py b/pandas/tests/reshape/merge/test_merge_asof.py
index 4123f686163d4..3b522eaa075f0 100644
--- a/pandas/tests/reshape/merge/test_merge_asof.py
+++ b/pandas/tests/reshape/merge/test_merge_asof.py
@@ -16,6 +16,14 @@
from pandas.core.reshape.merge import MergeError
+@pytest.fixture(params=["s", "ms", "us", "ns"])
+def unit(request):
+ """
+ Resolution for datetimelike dtypes.
+ """
+ return request.param
+
+
class TestAsOfMerge:
def read_data(self, datapath, name, dedupe=False):
path = datapath("reshape", "merge", "data", name)
@@ -63,8 +71,13 @@ def test_examples1(self):
result = merge_asof(left, right, on="a")
tm.assert_frame_equal(result, expected)
- def test_examples2(self):
+ def test_examples2(self, unit):
"""doc-string examples"""
+ if unit == "s":
+ pytest.skip(
+ "This test is invalid for unit='s' because that would "
+ "round the trades['time']]"
+ )
trades = pd.DataFrame(
{
"time": to_datetime(
@@ -75,7 +88,7 @@ def test_examples2(self):
"20160525 13:30:00.048",
"20160525 13:30:00.048",
]
- ),
+ ).astype(f"M8[{unit}]"),
"ticker": ["MSFT", "MSFT", "GOOG", "GOOG", "AAPL"],
"price": [51.95, 51.95, 720.77, 720.92, 98.00],
"quantity": [75, 155, 100, 100, 100],
@@ -96,7 +109,7 @@ def test_examples2(self):
"20160525 13:30:00.072",
"20160525 13:30:00.075",
]
- ),
+ ).astype(f"M8[{unit}]"),
"ticker": [
"GOOG",
"MSFT",
@@ -127,7 +140,7 @@ def test_examples2(self):
"20160525 13:30:00.048",
"20160525 13:30:00.048",
]
- ),
+ ).astype(f"M8[{unit}]"),
"ticker": ["MSFT", "MSFT", "GOOG", "GOOG", "AAPL"],
"price": [51.95, 51.95, 720.77, 720.92, 98.00],
"quantity": [75, 155, 100, 100, 100],
@@ -639,7 +652,7 @@ def test_tolerance_nearest(self):
result = merge_asof(left, right, on="a", direction="nearest", tolerance=1)
tm.assert_frame_equal(result, expected)
- def test_tolerance_tz(self):
+ def test_tolerance_tz(self, unit):
# GH 14844
left = pd.DataFrame(
{
@@ -648,6 +661,7 @@ def test_tolerance_tz(self):
freq="D",
periods=5,
tz=pytz.timezone("UTC"),
+ unit=unit,
),
"value1": np.arange(5),
}
@@ -659,6 +673,7 @@ def test_tolerance_tz(self):
freq="D",
periods=5,
tz=pytz.timezone("UTC"),
+ unit=unit,
),
"value2": list("ABCDE"),
}
@@ -672,6 +687,7 @@ def test_tolerance_tz(self):
freq="D",
periods=5,
tz=pytz.timezone("UTC"),
+ unit=unit,
),
"value1": np.arange(5),
"value2": list("BCDEE"),
@@ -1314,22 +1330,27 @@ def test_by_mixed_tz_aware(self):
expected["value_y"] = np.array([np.nan], dtype=object)
tm.assert_frame_equal(result, expected)
- def test_timedelta_tolerance_nearest(self):
+ def test_timedelta_tolerance_nearest(self, unit):
# GH 27642
+ if unit == "s":
+ pytest.skip(
+ "This test is invalid with unit='s' because that would "
+ "round left['time']"
+ )
left = pd.DataFrame(
list(zip([0, 5, 10, 15, 20, 25], [0, 1, 2, 3, 4, 5])),
columns=["time", "left"],
)
- left["time"] = pd.to_timedelta(left["time"], "ms")
+ left["time"] = pd.to_timedelta(left["time"], "ms").astype(f"m8[{unit}]")
right = pd.DataFrame(
list(zip([0, 3, 9, 12, 15, 18], [0, 1, 2, 3, 4, 5])),
columns=["time", "right"],
)
- right["time"] = pd.to_timedelta(right["time"], "ms")
+ right["time"] = pd.to_timedelta(right["time"], "ms").astype(f"m8[{unit}]")
expected = pd.DataFrame(
list(
@@ -1342,7 +1363,7 @@ def test_timedelta_tolerance_nearest(self):
columns=["time", "left", "right"],
)
- expected["time"] = pd.to_timedelta(expected["time"], "ms")
+ expected["time"] = pd.to_timedelta(expected["time"], "ms").astype(f"m8[{unit}]")
result = merge_asof(
left, right, on="time", tolerance=Timedelta("1ms"), direction="nearest"
@@ -1400,12 +1421,17 @@ def test_merge_index_column_tz(self):
)
tm.assert_frame_equal(result, expected)
- def test_left_index_right_index_tolerance(self):
+ def test_left_index_right_index_tolerance(self, unit):
# https://github.com/pandas-dev/pandas/issues/35558
- dr1 = pd.date_range(start="1/1/2020", end="1/20/2020", freq="2D") + Timedelta(
- seconds=0.4
- )
- dr2 = pd.date_range(start="1/1/2020", end="2/1/2020")
+ if unit == "s":
+ pytest.skip(
+ "This test is invalid with unit='s' because that would round dr1"
+ )
+
+ dr1 = pd.date_range(
+ start="1/1/2020", end="1/20/2020", freq="2D", unit=unit
+ ) + Timedelta(seconds=0.4).as_unit(unit)
+ dr2 = pd.date_range(start="1/1/2020", end="2/1/2020", unit=unit)
df1 = pd.DataFrame({"val1": "foo"}, index=pd.DatetimeIndex(dr1))
df2 = pd.DataFrame({"val2": "bar"}, index=pd.DatetimeIndex(dr2))