jupyterlab_voyager - JupyterLab extension visualize data with Voyager

  •        24

A JupyterLab MIME renderer extension to view CSV and JSON data in Voyager 2. Then right click on any csv, tsv or json file click "Open with...", then "Voyager".



@jupyterlab/application : ^0.18.4
@jupyterlab/apputils : ^0.18.4
@jupyterlab/cells : ^0.18.4
@jupyterlab/console : ^0.18.4
@jupyterlab/coreutils : ^2.1.4
@jupyterlab/docmanager : ^0.18.4
@jupyterlab/docregistry : ^0.18.4
@jupyterlab/filebrowser : ^0.18.6
@jupyterlab/mainmenu : ^0.7.4
@jupyterlab/notebook : 0.18.4
@jupyterlab/rendermime : ^0.18.4
@jupyterlab/rendermime-interfaces : ^1.1.2
@phosphor/widgets : ^1.6.0
datavoyager : 2.0.0-alpha.23
node-sass : ^4.9.0
react : ^16.3.2
react-dom : ^16.3.2
vega : 4.0.0-rc.1
webpack : ^4.8.3



Related Projects

jupyterlab-nvdashboard - A JupyterLab extension for displaying dashboards of GPU usage.

  •    Python

This extension is composed of a Python package named jupyterlab_nvdashboard for the server extension and a NPM package named jupyterlab-nvdashboard for the frontend extension. Note: You will need NodeJS to build the extension package.

jupyterlab - JupyterLab computational environment.

  •    Javascript

An extensible environment for interactive and reproducible computing, based on the Jupyter Notebook and Architecture. Currently ready for users. JupyterLab is the next-generation user interface for Project Jupyter. It offers all the familiar building blocks of the classic Jupyter Notebook (notebook, terminal, text editor, file browser, rich outputs, etc.) in a flexible and powerful user interface. Eventually, JupyterLab will replace the classic Jupyter Notebook.

jupyter-matplotlib - Matplotlib Jupyter Extension

  •    Javascript

Leveraging the Jupyter interactive widgets framework, jupyter-matplotlib enables the interactive features of matplotlib in the Jupyter notebook and in Jupyterlab. Besides, the figure canvas element is a proper Jupyter interactive widget which can be positioned in interactive widget layouts.

awesome-jupyter - A curated list of awesome Jupyter projects, libraries and resources


A curated list of awesome Jupyter projects, libraries and resources. Jupyter is an open-source web application that allows you to create and share documents that contain live code, equations, visualizations and narrative text. Your contributions are always welcome! Please take a look at the contribution guidelines first.

ipygany - 3-D Scientific Visualization in the Jupyter Notebook

  •    Python

ipygany is an early developer preview. Features and implementation are subject to change. Most of those features are very fast, because they are computed entirely on the GPU.

nbdime - Tools for diffing and merging of Jupyter notebooks.

  •    Python

nbdime provides tools for diffing and merging of Jupyter Notebooks. See the installation docs for more installation details and development installation instructions.

ipyleaflet - A Jupyter - Leaflet.js bridge

  •    Javascript

A Jupyter / Leaflet bridge enabling interactive maps in the Jupyter notebook.

ipywidgets - Interactive Widgets for the Jupyter Notebook

  •    TypeScript

ipywidgets are interactive HTML widgets for Jupyter notebooks and the IPython kernel. Notebooks come alive when interactive widgets are used. Users gain control of their data and can visualize changes in the data.

scriptedforms - Quickly create live-update GUIs for Python packages using Markdown and simple HTML elements

  •    TypeScript

Making GUIs easy for everyone on your team. The primary benefit is that front ends for Python code become easily accessible to everyone on your team. Easy to use, easy to update, easy to extend, and easy to understand.

vincent - A Python to Vega translator

  •    Python

If you are interested in this library, I would direct you to the Altair project: https://github.com/altair-viz/altair It supports the latest version of vega, is fully-featured, has a great development team, and has been developed with the support of the Vega team at UW. There will be no more updates, closed issues, or PR merges for the Vincent project. Thanks so much to everyone who tried it or used it along the way.

altair - Declarative statistical visualization library for Python

  •    Python

Altair is a declarative statistical visualization library for Python. With Altair, you can spend more time understanding your data and its meaning. Altair's API is simple, friendly and consistent and built on top of the powerful Vega-Lite JSON specification. This elegant simplicity produces beautiful and effective visualizations with a minimal amount of code. Altair is developed by Jake Vanderplas and Brian Granger in close collaboration with the UW Interactive Data Lab. See Altair's Documentation Site, as well as Altair's Tutorial Notebooks.

voyager - Recommendation-Powered Visualization Tool for Data Exploration

  •    TypeScript

Voyager 2 is a data exploration tool that blends manual and automated chart specification. Voyager 2 combines PoleStar, a traditional chart specification tool inspired by Tableau and Polaris (research project that led to the birth of Tableau), with two partial chart specification interfaces: (1) wildcards let users specify multiple charts in parallel,(2) related views suggest visualizations relevant to the currently specified chart. With Voyager 2, we aim to help analysts engage in both breadth-oriented exploration and depth-oriented question answering. For a quick overview of Voyager, see our preview video, or a 4-minute demo in our Vega-Lite talk at OpenVisConf, or watch our research talk at CHI 2017. For more information about our design, please read our CHI paper and other related papers (1, 2, 3).

Altair - The only GraphQL client editor you will need - Postman for GraphQL

  •    Typescript

Altair is a beautiful feature-rich GraphQL Client IDE for all platforms. It enables you interact with any GraphQL server you are authorized to access from any platform you are on. Much like Postman for GraphQL, you can easily test and optimize your GraphQL implementations.

pdvega - Interactive plotting for Pandas using Vega-Lite

  •    Python

pdvega is a library that allows you to quickly create interactive Vega-Lite plots from Pandas dataframes, using an API that is nearly identical to Pandas' built-in visualization tools, and designed for easy use within the Jupyter notebook. The above image is a static screenshot of the interactive output; please see the Documentation for a full set of live usage examples.

Vega Lite - A concise grammar of interactive graphics, built on Vega

  •    TypeScript

Vega-Lite is a high-level grammar of interactive graphics. It provides a concise JSON syntax for rapidly generating visualizations to support analysis. Vega-Lite specifications can be compiled to Vega specifications.

vue-vega - Vega Lite and Vega bridge to Vue.js ecosystem

  •    Javascript

vue-vega is a set of components and utilises dedicated to help developer access vega-lite and vega functionality through convenient API for Vue.js ecosystem.

dashboards - Jupyter Dashboards Layout Extension

  •    Jupyter

The dashboards layout extension is an add-on for Jupyter Notebook. It lets you arrange your notebook outputs (text, plots, widgets, ...) in grid- or report-like layouts. It saves information about your layouts in your notebook document. Other people with the extension can open your notebook and view your layouts. For a sample of what's possible with the dashboard layout extension, have a look at the demo dashboard-notebooks in this repository.

vega - A visualization grammar.

  •    Javascript

Vega is a visualization grammar, a declarative format for creating, saving, and sharing interactive visualization designs. With Vega you can describe data visualizations in a JSON format, and generate interactive views using either HTML5 Canvas or SVG. For documentation, tutorials, and examples, see the Vega website. For a description of changes between Vega 2 and later versions, please refer to the Vega Porting Guide.

We have large collection of open source products. Follow the tags from Tag Cloud >>

Open source products are scattered around the web. Please provide information about the open source projects you own / you use. Add Projects.