18 tools

CSV Tools and Converters

CSV is the format every spreadsheet, database and analytics tool can read, which is why data keeps arriving in it. It is a row per line and fields separated by commas, until a field contains a comma, a quote or a newline, at which point the quoting rules of RFC 4180 apply and naive parsing breaks.

Those cases are not rare. Address fields contain commas, description fields contain newlines, and any field with an apostrophe eventually meets a tool that escapes quotes differently. Splitting on commas works on sample data and corrupts real exports.

CSV has no intrinsic value types or schema. Turning fields into JSON numbers or booleans requires inference, so identifiers and leading zeros need care. RFC 4180 describes an optional header row, not a mandatory one: choose whether the first row contains column names before converting. Producer-specific delimiters, encodings and quoting conventions still need to be checked.

Working with CSV

Practical guides for the tools above, including the checks to make before relying on the result.

  • How to convert CSV to JSON

    Convert CSV to JSON reliably: trimmed headers, type inference, empty cells, quoted fields, ragged rows and why dotted column names stay flat.

  • How to convert JSON to CSV

    Convert JSON to CSV correctly: flattening nested objects, handling arrays and missing keys, choosing a delimiter, and the cases where CSV cannot represent the data.

  • How to review CSV to SQL INSERT statements

    Generate and review CSV-to-SQL INSERT statements: headers, inference, NULL, booleans, dialect-specific identifier quoting, and MySQL escaping limits.