Tablib este o bibliotecă Python concepută pentru importul, exportul și manipularea seturilor de date tabelare. Funcționează ca un convertor și manager de date multi-format, permițând utilizatorilor să mute informații între diferite standarde de fișiere.
Principalele funcționalități ale jazzband/tablib sunt: Data Format Converters, Tabular Format Bridges, Python Tabular Data Libraries, Tabular Data Exporters, Tabular Data Import, Tabular Data Managers, Tabular Data Manipulations, Tabular Format Parsing.
Alternativele open-source pentru jazzband/tablib includ: wireservice/csvkit — csvkit is a composable Unix-style command-line toolkit for converting, filtering, and analyzing CSV files directly… xlwings/xlwings — xlwings - Make Excel fly with Python! javascriptdata/danfojs — Danfo.js is a data analysis and preprocessing library for JavaScript that provides high-performance labeled data… mbloch/mapshaper — Mapshaper is a tool for processing, simplifying, and converting geographic vector data, available as a command-line… pymupdf/pymupdf — PyMuPDF is a comprehensive PDF manipulation library and document analysis tool. It serves as a text extraction tool,… kozea/weasyprint — WeasyPrint is a Python-based library and layout engine that converts HTML and CSS into printable PDF documents. It…
csvkit is a composable Unix-style command-line toolkit for converting, filtering, and analyzing CSV files directly from the terminal. It provides a suite of focused single-purpose commands that can be combined via pipes to build complex data processing workflows, with a modular architecture that includes a column-type inference engine for automatically detecting data types and a streaming-pipeline design for efficient handling of tabular data. The toolkit distinguishes itself through its SQL-engine abstraction layer, which allows users to run SQL queries directly against CSV files without req
xlwings - Make Excel fly with Python!
Danfo.js is a data analysis and preprocessing library for JavaScript that provides high-performance labeled data structures. It implements data frames and series to enable complex data analysis, statistical computing, and the manipulation of structured tabular data. The project serves as a machine learning preprocessing library, offering utilities for categorical label encoding, one-hot encoding, and numeric feature scaling and standardization. It specifically facilitates the conversion of labeled data structures into tensors for model training and evaluation. The library covers a broad set
Mapshaper is a tool for processing, simplifying, and converting geographic vector data, available as a command-line interface, a web browser tool, and a Node.js library. It functions as a coordinate projector, vector data converter, and web map asset optimizer designed to transform spatial datasets between different coordinate reference systems and file formats. The project is distinguished by its topology-preserving geometry simplification, which reduces vertex counts while maintaining shared boundaries to prevent gaps and overlaps. It further optimizes assets for the web through coordinate