How to catch DateParseError in pandas?

Question

I am running a script that uses pd.to_datetime() on inputs that are sometime not able to be parsed.

For example if I try to run pd.to_datetime('yesterday') it results to an error

DateParseError: Unknown datetime string format, unable to parse: yesterday, at position 0

I 'd like to catch this exception and process it further in my code.

I have tried:

try:
    pd.to_datetime('yesterday')
except pd.errors.ParserError:
    print('exception caught')

but the exception is not caught. Does anyone know where DateParseError is defined and how I can catch it? Searching in pandas documentation doesn't yield any results

Side note, it's a shame that 'yesterday' is not understood as a valid timestamp (since 'today' is valid). — mozway
– mozway, Commented Jan 29, 2024 at 12:44

mozway · Accepted Answer · 2024-01-29 10:39:14Z

7

You can import it from pandas._libs.tslibs.parsing:

from pandas._libs.tslibs.parsing import DateParseError

try:
    pd.to_datetime('yesterday')
except DateParseError:
    print('exception caught')

answered Jan 29, 2024 at 10:39

mozway

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2 Comments

jottbe Oct 9 at 8:39

I think it is generally not a good idea to import something from the intestines of a library that is not intended to be part of the (stable) interface. If a library contains names starting with _ they are usually not meant to be imported and this might not work anymore after updating the pandas version. So I guess what would be safer for the poster is @mhh's suggestion below.

mozway Oct 10 at 6:44

@jottbe That's true and I agree that using libraries internals is generally not recommended. That said, I answered the "Does anyone know where DateParseError is defined?" part. Catching ValueError is indeed a good approach, however this inheritance is also not officially defined in the API and nothing suggests that it is a stable behavior.

mhh · Accepted Answer · 2025-09-19 07:19:08Z

2

You may want to except ValueError instead.

DateParseError inherits ValueErrorand for some cases, pd.to_datetimethrows ValueError and not DateParseError. For example pd.to_datetime("123")

answered Sep 19 at 7:19

mhh

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