CSV

CSV (Comma-Separated Values) is a simple, plain-text file format used to store tabular data in a structured way where each line represents a row and values within each row are separated by commas (or other delimiters like semicolons, tabs, or pipes). This straightforward format makes CSV one of the most universally supported data exchange formats, readable by spreadsheet applications like Microsoft Excel, Google Sheets, and LibreOffice Calc, as well as databases, data analysis tools, and virtually every programming language. CSV files are human-readable when opened in a text editor, showing data in a grid-like structure that closely mirrors how it would appear in a spreadsheet. The format’s simplicity—requiring no special markup, tags, or complex syntax—makes it ideal for representing datasets, lists, reports, and any tabular information where relationships between columns and rows need to be preserved.

Despite its simplicity, CSV has become essential for data import/export operations, data migration between systems, bulk data loading into databases, and sharing datasets for data analysis and machine learning. The format is particularly valuable in business contexts for handling customer lists, financial records, inventory data, sales reports, and scientific datasets. CSV files are compact and efficient, requiring minimal storage space compared to more verbose formats like XML or JSON, which makes them ideal for transferring large datasets over networks or storing historical data archives. However, CSV has limitations: it lacks standardized support for data types (everything is typically treated as text unless parsed), has no built-in schema definition, struggles with representing hierarchical or nested data, and can encounter issues with special characters, line breaks within fields, or commas in data values (typically addressed by enclosing fields in quotes). Despite these constraints, CSV remains the go-to format for flat, rectangular data exchange due to its universal compatibility, ease of use, and the fact that it can be created and edited with the most basic tools, from text editors to sophisticated data processing frameworks.

Tags: Data Format

Properties: Text-Based, Plain Text Format, Tabular Data, Row-Based Structure, Column-Based Structure, Delimiter-Separated, Comma Delimiter, Alternative Delimiters, Tab-Separated Values, Pipe-Separated, Semicolon-Separated, Human-Readable, Machine-Parsable, Flat File Format, Simple Syntax, Minimal Markup, No Tags, No Attributes, Lightweight, Compact, Small File Size, Efficient Storage, Fast Parsing, Universal Support, Cross-Platform, Language-Agnostic, Spreadsheet Compatible, Excel Compatible, Google Sheets Compatible, LibreOffice Compatible, Database Import/Export, SQL Bulk Loading, Data Exchange Format, Data Migration, Line-Based Records, Newline Row Separator, Field Delimiter, Quote Encapsulation, Double-Quote Escaping, Escape Characters, Header Row Support, Column Names, Schema-Less, No Data Types, Text-Only Values, No Type Enforcement, No Metadata, No Validation, No Comments, No Processing Instructions, RFC 4180, MIME Type text/csv, File Extension .csv, UTF-8 Encoding, ASCII Compatible, Character Encoding Support, Special Character Handling, Embedded Commas, Embedded Quotes, Embedded Newlines, Field Quoting, Optional Quoting, Whitespace Handling, Trailing Spaces, Leading Spaces, Empty Fields, Null Values, Missing Data Support, Sparse Data, Dense Data, Rectangular Grid, Fixed Columns, Variable Rows, No Nesting, No Hierarchy, No Relationships, Flat Structure, Single Table, No Joins, No Foreign Keys, Streaming Compatible, Incremental Processing, Line-by-Line Reading, Memory Efficient, Large File Support, Append-Only, Chronological Data, Time Series Data, Log Files, Sequential Access, Random Access, Indexing Support, Sorting Compatible, Filtering Compatible, Aggregation Compatible, Data Analysis, Statistical Analysis, Machine Learning Datasets, Training Data, Feature Vectors, Pandas Compatible, R Compatible, Python CSV Module, Java CSV Libraries, .NET CSV Support, Excel Formula Support, Cell Formatting Loss, No Styling, No Colors, No Fonts, No Borders, No Images, No Charts, Data-Only Format, Export Format, Import Format, Batch Processing, ETL Operations, Data Warehousing, Business Intelligence, Reporting Format, Audit Trails, Transaction Logs, Customer Lists, Contact Lists, Inventory Data, Sales Data, Financial Records, Scientific Data, Sensor Data, Measurement Data, Survey Results, Poll Data, Census Data, Demographic Data, Geographic Data, Coordinate Data, Latitude Longitude, Address Lists, Email Lists, Product Catalogs, Price Lists, Stock Data, Market Data, Historical Data, Archive Format, Backup Format, Version Control Friendly, Diff-Friendly, Merge-Friendly, Git Compatible, Text Editor Compatible, Command Line Tools, Awk Processing, Sed Processing, Grep Searching, Cut Command, Unix Tools, Shell Scripting, Automation Friendly, Cron Job Compatible, Scheduled Exports, API Responses, Web Scraping Output, Data Dumps, Bulk Downloads, FTP Transfer, Email Attachments, Cloud Storage, S3 Compatible, Azure Blob Storage, Google Cloud Storage, Database Export, MySQL Export, PostgreSQL Export, SQLite Export, Oracle Export, SQL Server Export, MongoDB Export, NoSQL Export, Data Conversion, Format Transformation, JSON to CSV, XML to CSV, Excel to CSV, CSV to JSON, Interoperability, Legacy System Support, Backwards Compatible, Universal Standard, Industry Standard, De Facto Standard, Widely Adopted, Mature Format, Production Ready, Battle Tested, Simple Implementation, Easy Generation, Easy Parsing, Minimal Dependencies, No External Libraries Required, Low Overhead, High Performance, Scalable, Concatenation Support, Split Support, Chunking Support, Partitioning Support, Compression Compatible, Gzip Compatible, Zip Compatible, Tar Compatible

Wikipedia: https://en.wikipedia.org/wiki/Comma-separated_values