🗂️CSV

NEW

Also known as: Comma Separated Values

A simple delimited text format where fields are separated by commas to represent tabular data.

DESCRIPTION

CSV stores rows of fields separated by commas, optionally quoted to handle embedded commas or newlines. It is human-readable, widely supported, and lacks an explicit schema. Variations in delimiter, quoting, encoding, and header presence can cause interoperability issues. While convenient, CSV is inefficient for large-scale analytics compared to columnar formats like Parquet. RFC 4180 describes a common, though not universal, CSV convention.

ALTERNATIVE DEFINITIONS

Wikipedia

Comma-separated values (CSV) is a delimited text file that uses a comma to separate values.

Highlights file nature and delimiter choice.

Source

IETF RFC 4180

This memo describes the format that is commonly used for the exchange of Comma-Separated Values (CSV) files and proposes a new MIME type, “text/csv”, for CSV files.

Defines common format and registers MIME type text/csv.

Source

Python Documentation

The csv module implements classes to read and write tabular data in CSV format.

Emphasizes practical reading/writing of CSV data.

Source

RELATED TERMS

TSV Delimited Text RFC 4180 Escaping Data Schema Encoding Excel Data Ingestion

COMPETING TERMS

JSON Parquet

RELATIONS

• Conforms to: RFC 4180

KNOWLEDGE AREAS

Data Integration & Interoperability Data Storage & Operations Data Engineering

TARGET AUDIENCE

Data Engineer Data Analyst BI Specialist Software Developer

EXTERNAL SOURCES

• Wikipedia - Comma-separated values
• Apache Arrow - Efficient CSV reading/writing APIs
• pandas - Dataframe loader for CSV files
• Apache Spark - Distributed CSV data source guide

TOP QUESTIONS

When should I use CSV?

Use CSV for simple tabular data exchange and interoperability, especially when human readability and tool compatibility are priorities.

Category: Guidance

What are CSV’s limitations?

No schema, ambiguous types, encoding issues, and inefficiency for large analytics workloads are common limitations.

Category: Limitations

How do I handle commas inside fields?

Quote fields with embedded commas and escape embedded quotes by doubling them, per RFC 4180 conventions.

Category: HowTo

Is CSV standardized?

CSV has common conventions, with RFC 4180 widely referenced, but implementations vary across tools and locales.

Category: Understanding

How does CSV compare to Parquet?

CSV is row-oriented and text-based; Parquet is columnar and efficient for analytics with compression and schema.

Category: Comparison

What encoding should I use for CSV?

UTF-8 is safest for interoperability, though some tools default to locale-specific encodings.

Category: BestPractice

Can CSV store nested data?

Not naturally. Flatten or serialize nested structures (e.g., JSON strings) at the cost of complexity.

Category: Limitations

How to validate CSV files?

Use schema-on-read tools, header checks, delimiter consistency, and row length validation.

Category: Testing

What delimiter alternatives exist?

TSV (tab-separated) and semicolon-separated formats are common locale-specific alternatives.

Category: Alternatives