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CSV format specification

CSV (Comma-Separated Values) is defined by RFC 4180. The basic rules:

Each record is on its own line (CRLF line breaks in strict RFC 4180)
Fields are separated by commas (or another delimiter)
Fields containing commas, double quotes, or newlines must be enclosed in double quotes
A literal double quote is escaped by doubling it: "He said ""hello"""

Common CSV variants

TSV: tab-separated values. Avoids comma-in-data issues. Common in bioinformatics.
PSV: pipe-separated values (|). Less common but unambiguous.
CSV with semicolons: default in European Excel due to comma being the decimal separator in many locales.

How to open a large CSV

This tool runs entirely in your browser and has no hard row/column limits, but browser memory constraints apply. Files under 50 MB typically load fine. For files over 100 MB or with millions of rows, consider:

Python pandas: pd.read_csv("file.csv") can handle multi-GB files efficiently with chunking.
DuckDB: an in-process SQL database that can query CSV files directly without loading them into memory: SELECT * FROM 'file.csv' WHERE ...
csvkit: command-line suite (csvstat, csvcut, csvsql) for quick inspection and manipulation.

Sorting and filtering

Click any column header to sort ascending/descending. Use the search box to filter rows by keyword (searches all columns). For advanced filtering (e.g., "show rows where column A > 100"), export to JSON and use a tool like jq, or load into a SQL database.

Data validation tips

Duplicate headers: Two columns with the same name cause key collisions in JSON conversion. Rename one.
Empty rows: Trailing commas or blank lines at the end of the file create empty records. Remove them before processing.
Mismatched column counts: If a row has more or fewer values than the header, the parser may skip it or fill with nulls. Check row counts in the summary.
Encoding issues: If non-ASCII characters appear garbled, the file may be in ISO-8859-1 or Windows-1252 instead of UTF-8. Re-save as UTF-8 in a text editor.