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import pandas as pd

rg = pd.date_range("2020-01-01", periods=100_000, freq="s")

ts_ns = pd.Timestamp("1996-01-01 00:00:00.00000000000")
ts_s = pd.Timestamp("1996-01-01")

%timeit rg < ts_s
3.68 ms ± 138 µs per loop (mean ± std. dev. of 7 runs, 100 loops each)   # <- main
139 µs ± 3.96 µs per loop (mean ± std. dev. of 7 runs, 10,000 loops each)  # <- PR

@MarcoGorelli can you confirm this closes #52080

@mroeschke mroeschke requested a review from MarcoGorelli March 22, 2023 17:42
@mroeschke mroeschke added Performance Memory or execution speed performance Non-Nano datetime64/timedelta64 with non-nanosecond resolution labels Mar 22, 2023
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Looks good to me, can confirm this resolves the issue - both paths are covered, so should be fine

@phofl any objections?

@MarcoGorelli MarcoGorelli added this to the 2.0 milestone Mar 23, 2023
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let's ship it

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thanks @jbrockmendel

@MarcoGorelli MarcoGorelli merged commit 25c1942 into pandas-dev:main Mar 24, 2023
meeseeksmachine pushed a commit to meeseeksmachine/pandas that referenced this pull request Mar 24, 2023
@jbrockmendel jbrockmendel deleted the perf-nano-cmp branch March 24, 2023 15:18
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Thx for taking care of this.

phofl pushed a commit that referenced this pull request Mar 24, 2023
…th Timestamp mismatched resos) (#52160)

Backport PR #52111: PERF: DatetimeIndex comparison with Timestamp mismatched resos

Co-authored-by: jbrockmendel <[email protected]>
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PERF: performance problem when comparing timestamp to datetimindex
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