Common CSV Date Import Errors We Fix
Databases (PostgreSQL, BigQuery, MySQL) and BI dashboards demand unified date formatting. Here is how CleanMyCSV standardizes your file:
1. Excel Serial Number Conversion (e.g. 45292 → 2024-01-12)
When exporting from Microsoft Excel, date columns often revert to raw integer serial numbers (counting days since January 1, 1900, such as 45292). CleanMyCSV detects 5-digit Excel serial numbers in date columns and converts them back into human-readable ISO dates.
2. US vs European Day/Month Inversion (MM/DD/YYYY vs DD/MM/YYYY)
Inverting days and months causes subtle data corruption during CRM or SQL imports. Our engine uses locale-aware parsing to correctly identify whether a file originates from European (DD-MM-YYYY) or American (MM-DD-YYYY) conventions, including fallback safety checks for impossible month values.
3. Text Months & Mixed Separator Normalization
Text dates containing month abbreviations (e.g., "12 Jan 2024", "12-Fév-2024", or "2024.01.12") prevent databases from setting DATE column data types. CleanMyCSV maps multi-language textual months and unifies all slashes, dots, and spaces into hyphenated ISO format.
4. Immediate Integration for BigQuery, PostgreSQL & PowerBI
Stop writing custom SQL PARSE_DATE() or Python Pandas cleaning scripts for every dataset. CleanMyCSV converts dates, repairs encoding accents, normalizes currency decimals, and delivers a clean CSV file in seconds.