JSON Schema is a declarative language for annotating and validating JSON documents' structure, constraints, and data types. It enables JSON data consistency, validity, and interoperability, and has a tooling ecosystem of validators, generators, and linters. Documentation covers schema design, guides, and keyword reference.
Apache Zeppelin is a web-based notebook for data-driven, interactive data analytics and collaborative documents with SQL, Scala, Python, R and more. It uses interpreters to plug in language and data-processing backends, including built-in Apache Spark integration, and includes basic charts, pivot charts, dynamic forms and paragraph publishing to embed results in websites.
A podcast on data visualization hosted by Enrico Bertini and Moritz Stefaner. The site lists episode archives, news items and classics, and notes that transcriptions of 170 episodes were produced with Miska Knapek.
Data Engineering Podcast is a show that covers the tools, techniques, and challenges of the data engineering discipline. Its episodes address topics including databases, workflows, automation, and data manipulation, and it is available for listening on a range of podcast platforms.
Shiny is an R and Python package for creating interactive web apps, letting users interact with data and analysis without web development skills. Apps can be written from R or Python. Questions are answered through Posit Community and Stack Overflow, with subscription support for hosting services.
Matplotlib is a comprehensive Python library for creating static, animated, and interactive visualizations. It supports publication quality plots, interactive figures that zoom, pan and update, customizable visual styles and layouts, and exporting to many file formats. It can be embedded in JupyterLab and graphical user interfaces, and third-party packages extend and build on its functionality.
The mat package from Gonum provides implementations of float64 and complex128 matrix structures and linear algebra operations on them in Go. It offers interfaces for matrix classes, concrete implementations such as Dense and SymDense, methods for using matrix data, and types for matrix factorizations such as QR and LU.
Community notes
Be the first to share how this project worked for you.
Sign in with a verified account to leave a review or join the discussion.
Sign in to reviewKeep exploring
Apache Zeppelin is a web-based notebook for data-driven, interactive data analytics and collaborative documents with SQL, Scala, Python, R and more. It uses interpreters to plug in language and data-processing backends, including built-in Apache Spark integration, and includes basic charts, pivot charts, dynamic forms and paragraph publishing to embed results in websites.
A podcast on data visualization hosted by Enrico Bertini and Moritz Stefaner. The site lists episode archives, news items and classics, and notes that transcriptions of 170 episodes were produced with Miska Knapek.
Data Engineering Podcast is a show that covers the tools, techniques, and challenges of the data engineering discipline. Its episodes address topics including databases, workflows, automation, and data manipulation, and it is available for listening on a range of podcast platforms.
Shiny is an R and Python package for creating interactive web apps, letting users interact with data and analysis without web development skills. Apps can be written from R or Python. Questions are answered through Posit Community and Stack Overflow, with subscription support for hosting services.
Matplotlib is a comprehensive Python library for creating static, animated, and interactive visualizations. It supports publication quality plots, interactive figures that zoom, pan and update, customizable visual styles and layouts, and exporting to many file formats. It can be embedded in JupyterLab and graphical user interfaces, and third-party packages extend and build on its functionality.
The mat package from Gonum provides implementations of float64 and complex128 matrix structures and linear algebra operations on them in Go. It offers interfaces for matrix classes, concrete implementations such as Dense and SymDense, methods for using matrix data, and types for matrix factorizations such as QR and LU.
