👀 Views: 288 💬 Answers: 1 📅 Created: 2025-06-03

pandas datetime valueerror Python

I'm migrating some code and Quick question that's been bugging me - I've searched everywhere and can't find a clear answer. I'm working with an scenario while converting a column of dates in a DataFrame to a DateTimeIndex. The dates are in a non-standard format, like '02/15/2022 14:30:00', and when I try to convert this column using `pd.to_datetime()`, I encounter a `ValueError`. Here's the code I'm using: ```python import pandas as pd data = { 'date_column': ['02/15/2022 14:30:00', '03/16/2022 10:00:00', 'not_a_date'] } df = pd.DataFrame(data) # Attempting to convert to DateTimeIndex try: df['date_column'] = pd.to_datetime(df['date_column'], format='%m/%d/%Y %H:%M:%S') except ValueError as e: print(f'ValueError: {e}') ``` The behavior message I receive is `ValueError: time data 'not_a_date' does not match format '%m/%d/%Y %H:%M:%S' (match)`. I've also tried adding the `errors='coerce'` parameter, but then I end up with `NaT` for invalid entries. I want to keep the valid dates and handle the invalid ones gracefully, possibly by filling them with a default date or dropping them altogether. How can I achieve this while still converting the valid dates correctly and creating a DateTimeIndex? I'm using Pandas version 1.4.2 and Python 3.9. Any help would be greatly appreciated! Thanks in advance! My development environment is macOS. My development environment is Windows 10.