Camelot: An Automated Python Library for Extracting Table Data from PDF Documents

Camelot is a powerful Python library for extracting table data from PDFs. It’s easy to use, flexible, and supports multiple output formats like CSV, JSON, and Excel.

Camelot is a powerful Python library designed for extracting table data from PDF documents. It helps you quickly and efficiently convert table data from PDFs into usable formats, making it easier to perform further analysis.

Advantages of Camelot

Camelot has several advantages that make it an ideal choice for extracting table data from PDFs:

• Easy to use: Camelot’s API is simple and intuitive, allowing even users without a Python background to easily get started.

• Flexible configuration: Camelot offers multiple configuration options, enabling you to adjust the extraction process according to the situation for optimal results.

• High accuracy: Camelot uses advanced algorithms to identify and extract table data from PDFs and provides accuracy metrics to help you assess the reliability of the results.

• Multiple output formats: Camelot supports various output formats, including CSV, JSON, Excel, HTML, Markdown, and SQLite, making it easy to import extracted data into other applications or databases for analysis.

• Integration with pandas: Each table is extracted as a pandas DataFrame, making it easy to integrate Camelot into your existing data analysis workflows.