merge_asof() tolerance cannot be datetime.timedelta · Issue #28098 · pandas-dev/pandas (original) (raw)

import pandas as pd
import numpy as np
from datetime import timedelta

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")

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")

expected = pd.DataFrame(
    list(
        zip(
            [0, 5, 10, 15, 20, 25],
            [0, 1, 2, 3, 4, 5],
            [0, np.nan, 2, 4, np.nan, np.nan],
        )
    ),
    columns=["time", "left", "right"],
)
expected["time"] = pd.to_timedelta(expected["time"], "ms")
print(expected)

# this throws MergeError: incompatible tolerance <class 'datetime.timedelta'>, must be compat with type dtype('<m8[ns]')
result = pd.merge_asof(left, right, on="time", tolerance=timedelta(microseconds=1000), direction="nearest")

# this works!
# result = pd.merge_asof(left, right, on="time", tolerance=pd.Timedelta("1ms"), direction="nearest")

print(result)

I can use pd.Timedelta as tolerance, but not datetime.timedelta.