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    Add or Remove Prefix or Suffix

    Bulk add or remove text at the start (prefix) or end (suffix) of each line. Perfect for CSV formatting, list numbering, and code generation.

    0 characters · 1 lines

    0 characters · 1 lines

    Why Use a Prefix & Suffix Tool?

    Our free prefix and suffix tool adds or removes text from the beginning (prefix) or end (suffix) of every line in bulk, eliminating the tedious manual editing of hundreds or thousands of lines. Developers use this to quickly format code arrays, add quotation marks to strings, or prepend comments to multiple lines. Data analysts rely on it to clean scraped data, add delimiters for CSV imports, or remove unwanted characters from database exports. Content creators use it to format lists, add bullet points, or clean up copied text with consistent formatting.

    The add mode appends text to every line—perfect for creating numbered lists, formatting code snippets, or preparing data for imports. The remove mode strips specified characters from line beginnings or endings, ideal for cleaning markdown formatting, removing line numbers from code, or stripping quotation marks from CSV exports. All processing happens line-by-line instantly in your browser, handling thousands of lines in milliseconds without server uploads, ensuring complete privacy for sensitive data like customer lists or proprietary code.

    Common Use Cases

    💻 Code Formatting & Arrays

    Developers frequently need to convert plain text lists into code arrays or add quotation marks to strings. Adding prefix and suffix quotation marks transforms a list of words into a proper string array: "apple", "banana", "cherry". Adding prefixes like "const " or suffixes like ";" helps format multiple variable declarations simultaneously. This saves hours when converting data imports, API responses, or configuration files into properly formatted code.

    After formatting code, use Sort Lines to alphabetize imports or declarations, then Remove Empty Lines to clean up spacing for linter compliance.

    📊 CSV & Data Preparation

    When preparing data for CSV imports or Excel, each field often needs specific formatting. Adding comma suffixes converts line-separated values into comma-separated format. Wrapping fields in quotation marks ensures proper CSV escaping for values containing special characters. Removing unwanted prefixes or suffixes cleans data exported from other systems that add metadata or formatting you need to strip before re-import.

    After adding delimiters, use CSV Safe to escape special characters, then Remove Duplicates to ensure data uniqueness before importing.

    📝 List & Document Formatting

    Content creators use prefix/suffix tools to quickly format lists for documents, presentations, or blog posts. Adding "- " creates markdown-style bullet points, while "1. ", "2. ", "3. " creates numbered lists (though you'd need to handle numbering separately). Removing prefixes cleans up copied text that includes unwanted formatting, line numbers, or markers from source documents, making content ready for publishing or further editing.

    After formatting lists, use Case Converter for consistent capitalization, then Trim Lines to remove extra whitespace that may have been introduced.

    🧹 Data Cleaning & Web Scraping

    Web scraping often yields data with unwanted prefixes or suffixes—timestamp markers, HTML tags, or formatting characters. The remove mode strips these characters in bulk: remove "Posted on: " from scraped dates, strip quotation marks from fields, or clean line numbers from code examples. This is especially useful when processing large datasets from multiple sources that each add different formatting you need to normalize before analysis.

    For comprehensive cleaning, combine with Remove HTML to strip tags, then Find & Replace for advanced pattern matching and cleanup operations.

    How Prefix & Suffix Works

    Our tool processes your text line by line, adding or removing text based on your selections. Add mode prepends your specified prefix text to the beginning of each line and/or appends suffix text to the end of each line. You can add just a prefix (like "- " for bullet points), just a suffix (like "," for comma-separated values), or both simultaneously (like wrapping each line in quotation marks with '"' prefix and '"' suffix).

    Remove mode searches each line's beginning for your specified prefix text and/or each line's end for your suffix text, deleting exact matches. The removal is case-sensitive and character-exact—removing prefix "- " won't affect lines starting with "-" (no space). This precision ensures you only remove intended formatting without accidentally corrupting data. Both prefix and suffix can be removed in a single operation, useful for cleaning text that has unwanted markers at both ends.

    The tool preserves line order and empty lines (though you can use Remove Empty Lines afterward if needed). All processing happens instantly in your browser using JavaScript—no server upload, ensuring complete privacy for customer data, code, or proprietary information. The tool handles large files efficiently, processing thousands of lines in milliseconds, making it suitable for bulk data operations from database exports or API responses.

    Tips for Best Results

    • 1.For code arrays, add both prefix and suffix to wrap strings: prefix = '"' and suffix = '",' creates properly formatted JavaScript array entries. After formatting, use Remove Line Breaks to create single-line arrays if needed.
    • 2.When removing formatting, be precise with spacing. Removing "- " (with space) is different from "-" (without space). Check your source text carefully to match exact characters. Use Character Counter to verify whitespace characters.
    • 3.For CSV preparation, add comma suffixes to create delimiter-separated values, then use CSV Safe to properly escape any commas or quotes within your data that could break CSV parsing.
    • 4.After bulk formatting, use Trim Lines to clean any accidental whitespace introduced, then Text Statistics to verify line counts and overall data integrity.

    Frequently Asked Questions

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