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Camelot is a Python library and processing engine designed to extract tabular data from PDF documents. It converts unstructured tables into machine-readable formats such as CSV, JSON, and Excel. The project provides specialized toolsets for different document types, using line detection for ruled tables and whitespace analysis for borderless tables. It includes an optical character recognition system to recover structured data from image-based scanned PDFs that lack a digital text layer. The library handles complex document layouts, including encrypted files, rotated pages, and tables that s
Tabula is a PDF table extraction tool and data scraper designed to isolate tabular structures within text-based PDF files. It functions as a converter that transforms these layouts into structured CSV or spreadsheet formats for data recovery and analysis. The project provides both a visual interface for manually selecting table areas and a headless command-line interface. This dual approach allows for a choice between manual data recovery via visual-area selection and the integration of table extraction into automated data pipelines. The extraction process utilizes Java-based PDF parsing and
Sparrow is an LLM document extraction platform and vision-based inference engine designed to convert images and PDFs into validated structured data. It functions as an agentic workflow orchestrator that chains classification, extraction, and validation tasks into multi-step pipelines. The system distinguishes itself through a backend-agnostic inference layer that manages models across local GPUs, Apple Silicon, and cloud providers. It employs coordinate-based visual grounding to map extracted text to precise bounding box coordinates and utilizes hint-based model steering to guide attention an
This project is a comprehensive pandas data analysis tutorial and instructional guide designed for learning data manipulation and analysis. It serves as a tabular data processing guide and a manual for time series analysis, providing a structured approach to cleaning, merging, and transforming datasets. The repository functions as a data feature engineering course, providing tutorials on constructing and selecting dataset features to improve machine learning model performance. It also includes a vectorized data operations guide for performing element-wise mathematical computations and matrix
Camelot is a Python-based library designed to parse, extract, and clean tabular data from PDF files. It converts table elements from text-based PDF documents into programmable data structures and dataframes.
The main features of atlanhq/camelot are: Table Extraction, Stream-Based Extraction, PDF to CSV Converters, PDF Table Parsing, PDF Coordinate Extraction, PDF Lattice Detection, Data Cleaning Procedures, Table Extraction Quality Metrics.
Projects with overlapping indexed features include: camelot-dev/camelot — Camelot is a Python library and processing engine designed to extract tabular data from PDF documents. It converts… tabulapdf/tabula — Tabula is a PDF table extraction tool and data scraper designed to isolate tabular structures within text-based PDF… katanaml/sparrow — Sparrow is an LLM document extraction platform and vision-based inference engine designed to convert images and PDFs… cleanlab/cleanlab — Cleanlab is a data-centric AI library and toolkit designed to improve machine learning model performance by detecting… dathere/qsv — qsv is a high-performance command line toolkit for querying, transforming, and analyzing comma-separated value files.… datawhalechina/joyful-pandas — This project is a comprehensive pandas data analysis tutorial and instructional guide designed for learning data…