DartLab Data: Structured Company Disclosures from 2,700 Korean and 970 U.S. Firms

DartLab Data provides structured company information extracted from mandatory disclosure filings in South Korea's DART and the U.S. SEC's EDGAR systems. The dataset covers approximately 2,700 Korean and 970 U.S. companies, pre-collected into Parquet files. It was created by author 'eddmpython' and was last updated on the platform in May 2026.

Use Cases

• Cross-border financial ratio analysis based on structured company data from two major regulatory systems.
• Training models for automated disclosure classification based on the standardized company map.
• Benchmarking corporate governance practices based on the collection of mandatory filings.
• Developing predictive models for market events based on historical disclosure patterns.

Strengths

• Covers a specific, disclosed scale of 2,700 Korean and 970 U.S. companies.
• Data is structured from raw filings, which may improve usability for analysis.
• Integrates disclosures from two major regulatory jurisdictions, enabling comparative study.

Limitations

• Column-level documentation is absent; field semantics must be inferred after download.
• Row count and total data size are unknown, which may limit suitability assessment.
• Freshness should be verified as the last platform update is dated 2026-05-01.

Provenance

Source

South Korea's DART (Data Analysis, Retrieval and Transfer System) and the U.S. SEC's EDGAR (Electronic Data Gathering, Analysis, and Retrieval) database.

Collection Method

Pre-collected via the DartLab Python library, which processes raw disclosure filings into a structured company map.

Time Range

null

Freshness

Last updated 2026-05-01 03:59:28; freshness should be verified.

Geography

South Korea and the United States.