A CSV WHERE clause filter lets you query and filter rows in your spreadsheet data using SQL-like syntax. Instead of manually searching through hundreds of rows, you can write conditions like age > 30 or city = 'London' to instantly isolate the data you need. This tool parses your CSV file, understands the column structure, and applies your filter logic — just like a database query but entirely in your browser with no server required.

This tool supports a comprehensive set of operators: Comparison (=, !=, <>, >, <, >=, <=), Pattern matching (LIKE with % and _ wildcards), List checks (IN ('a','b','c')), Range checks (BETWEEN x AND y), Null checks (IS NULL, IS NOT NULL), and Logical operators (AND, OR, NOT) with parentheses for grouping complex conditions.

If your CSV column names contain spaces or special characters, wrap them in backticks (`column name`) or double quotes ("column name") in your WHERE clause. For example: `annual salary` > 50000 or "first name" LIKE 'J%'. The column tags above the input area are clickable — they'll automatically insert the properly quoted column name for you.

Absolutely secure. All CSV parsing, filtering, and processing happens entirely within your browser using client-side JavaScript. Your data never leaves your computer — there is no upload to any server, no cloud processing, and no third-party involvement. You can use this tool offline once the page is loaded. This makes it ideal for sensitive business data, personal information, or confidential datasets.

Yes, this tool handles CSV files with tens of thousands of rows efficiently. The filtering engine is optimized for client-side performance. For very large files (50,000+ rows), you may notice a slight delay during filtering, but most operations complete in under a second. There's no hard row limit — the only constraint is your browser's available memory. For optimal performance with massive datasets, consider splitting your file into smaller chunks.

The LIKE operator supports two wildcard characters: % matches any sequence of characters (including empty), and _ matches exactly one character. Examples: name LIKE 'J%' matches names starting with "J"; email LIKE '%@gmail.com' matches Gmail addresses; code LIKE 'AB_' matches "AB" followed by one character. For literal % or _ in your search pattern, use the NOT LIKE alternative or escape them with careful quoting.

The tool follows the RFC 4180 CSV standard. It supports: comma-separated values, fields wrapped in double quotes, embedded commas and line breaks within quoted fields, and escaped double quotes (two consecutive double quotes). UTF-8 encoding is fully supported. The tool auto-detects whether the first row contains column headers (toggle this with the switch). Common CSV exports from Excel, Google Sheets, and database tools work out of the box.

Yes! After applying a filter, click the Export CSV button to download the filtered rows as a new CSV file. The exported file preserves the original column structure and headers, containing only the rows that matched your WHERE clause. This is perfect for creating targeted subsets of your data for reports, further analysis, or sharing with colleagues.