This extension allows you to seamlessly combine multiple tables—performing joins and merges—from different data sources that share common fields. Table joins are one of the most essential operations in data analysis, enabling you to consolidate scattered information, enrich datasets, and create comprehensive views of your data.

With this tool you can:

  • •Load data in multiple ways: upload multiple files in formats such as CSV, Excel, or others, use datasets already stored in your Datasketch library, or combine data from publicly shared sources with your own datasets.
  • •Automatically detect common fields: the extension intelligently identifies shared columns between your tables (such as IDs, names, codes, or dates) and suggests the best matching fields for joining your data.
  • •Choose from different join types: perform inner joins (matching records only), left joins (keep all records from main table), right joins (keep all records from secondary table), or full outer joins (keep all records from both tables).
  • •Preview results before finalizing: see exactly how your tables will be combined and which records will be matched, merged, or excluded, allowing you to verify the join logic before processing.
  • •Handle data inconsistencies automatically: the extension manages common issues like different formatting, extra spaces, or slight variations in matching fields, ensuring successful joins even with imperfect data.
  • •Create enriched datasets instantly: combine basic information with detailed attributes, merge transactional data with reference tables, or consolidate related information scattered across multiple sources.
  • •Export and save combined tables: download the unified dataset in various formats or store it in your Datasketch library for future analysis, visualization, or sharing with other users.

Perfect for combining: customer data with transaction history, geographical coordinates with regional information, product catalogs with sales data, survey responses with demographic information, financial records with account details, inventory data with supplier information, and any datasets where related information exists in separate tables.