Pandas version checks
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[X] I have checked that this issue has not already been reported.
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[X] I have confirmed this bug exists on the latest version of pandas.
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[ ] I have confirmed this bug exists on the main branch of pandas.
Reproducible Example
import pandas as pd
s = pd.Series(['6/30/2025','1 27 2024'])
pd.to_datetime(s,errors='raise',infer_datetime_format=True)
Issue Description
I'm confused about the interaction between errors = {raise, coerce} and infer_datetime_format = {True, False}.
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From experiment 3, it tells me if I want to follow the format in first row using infer=True, the second row has a problem which causes it to be coerced to NaT.
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I also understand that in experiment 4, because infer=False, each row is free to have it's own format not necessarily following the format inferred from first row, so it doesn't have any problem being converted, thus not NaT.
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I don't understand why experiment 1 does not raise any error but converts row 2 properly? (From experiment 3 i expect row 2 to be problematic when infer=True)
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I understand experiment 2 converts with no problem because infer=False allows every row to have it's own format, similar reasoning as for experiment 4.
I tried 4 experiments on the same series of s = pd.Series(['6/30/2025','1 27 2024'])
Experiment 1. errors = 'raise', infer_datetime_format=True
Input: pd.to_datetime(s,errors='raise',infer_datetime_format=True)
Output:
0 2025-06-30
1 2024-01-27
dtype: datetime64[ns]
Experiment 2. errors = 'raise', infer_datetime_format=False
Input: pd.to_datetime(s,errors='raise',infer_datetime_format=False)
Output: Same as experiment 1
Experiment 3. errors = 'coerce', infer_datetime_format=True
Input: pd.to_datetime(s,errors='coerce',infer_datetime_format=True)
Output:
0 2025-06-30
1 NaT
dtype: datetime64[ns]
Experiment 4. errors = 'coerce', infer_datetime_format=False
Input: pd.to_datetime(s,errors='coerce',infer_datetime_format=False)
Output: Same as experiment 1
Expected Behavior
I expect the same error that caused experiment 3 to produce NaT in 2nd row with '1 27 2024', to generate some error in experiment 1 for 2nd row too.
I'm not sure what caused the NaT in experiment 3, but reasoning from the assumption that if errors='coerce' has found some problem, errors='raise' should find that problem too.
I also assume the NaT in experiment 3 is caused by infer_datetime_format by comparing experiment 3 and 4.
Installed Versions
Comment From: srotondo
take