The latest articles on DEV Community by Priya (@priyakalashi). https://dev.to/priyakalashi https://media2.dev.to/dynamic/image/width=90,height=90,fit=cover,gravity=auto,format=auto/https:%2F%2Fdev-to-uploads.s3.us-east-2.amazonaws.com%2Fuploads%2Fuser%2Fprofile_image%2F4243339%2F9d915d17-328a-4319-a1ce-51caed997481.jpg https://dev.to/priyakalashi en Priya Fri, 13 Nov 2026 17:10:16 +0000 https://dev.to/priyakalashi/data-cleaning-for-messy-date-3fmi https://dev.to/priyakalashi/data-cleaning-for-messy-date-3fmi <p>import pandas as pd</p> <h1> Sample messy data </h1> <p>df = pd.DataFrame(<br> {'raw_date': ['2026-11-13', '13/11/2026', 'Nov 13, 2026', 'invalid_date', None]}<br> )</p> <h1> Convert to standard datetime objects </h1> <p>df['clean_date'] = pd.to_datetime(<br> df['raw_date'], format='mixed', dayfirst=True, errors='coerce'<br> )</p> <p>print(df)</p> datacleaningmessydates convertintostandarddate