Build on top of Plotly.js, React, and Flask, Dash ties modern UI elements like dropdowns, sliders, and graphs directly to your analytical python code. Here’s a 43-line example of a Dash App that ties a Dropdown to a D3.js Plotly Graph. As the user selects a value in the Dropdown, the application code dynamically exports data from Google Finance into a Pandas DataFrame. This app was written in just 43 lines of code (view the source).
dash plotly data-visualization data-science gui-framework flask react finance bioinformatics technical-computing charting plotly-dash web-appColt distribution consists of several free Java libraries bundled under one single uniform umbrella. Namely the Colt library, the Jet library, the CoreJava library, and the Concurrent library. It provides support for resizable arrays, dense, sparse matrices, histogramming functionality, Random Number Generators etc.
math math-library java-collection library map utility scientific technical-computingJulia is a high-level, high-performance dynamic programming language for technical computing, with syntax that is familiar to users of other technical computing environments. It provides a sophisticated compiler, distributed parallel execution, numerical accuracy, and an extensive mathematical function library. This computation is automatically distributed across all available compute nodes, and the result, reduced by summation (+), is returned at the calling node.
language programming-language statistical-language statistics technical-computingThe Julia base package is pretty big, although at the same time, there are lots of other packages around to expand it with. The result is that on the whole, it is impossible to give a thorough overview of all that Julia can do in just a few brief exercises. Therefore, I had to adopt a little 'bias', or 'slant' if you please, in deciding what to focus on and what to ignore. Julia is a technical computing language, although it does have the capabilities of any general purpose language and you'd be hard-pressed to find tasks it's completely unsuitable for (although that does not mean it's the best or easiest choice for any of them). Julia was developed with the occasional reference to R, and with an avowed intent to improve upon R's clunkiness. R is a great language, but relatively slow, to the point that most people use it to rapid prototype, then implement the algorithm for production in Python or Java. Julia seeks to be as approachable as R but without the speed penalty.
julia learning-julia language learning learning-by-doing julia-language julialang data-science statistics technical-computing hpc scientific-computing🚧 Dash.jl is a work-in-progress. Feel free to test the waters and submit issues. Built on top of Plotly.js, React and HTTP.jl, Dash ties modern UI elements like dropdowns, sliders, and graphs directly to your analytical Julia code.
react productivity finance data-science bioinformatics dashboard julia web-app modeling plotly data-visualization dash gui-framework charting no-javascript technical-computing plotly-dash no-vbaMATLAB is a registered trademarks of The MathWorks, Inc. The latest version of the wrapper can be downloaded here.
d3 webgl data-science matlab plotly data-visualization d3js technical-computingThis is a demo of the Dash interactive Python framework developed by Plotly. Dash abstracts away all of the technologies and protocols required to build an interactive web-based application and is a simple and effective way to bind a user interface around your Python code.
dash plotly data-science data-visualization technical-computing energyThe latest version of the wrapper can be downloaded here. Once downloaded, run plotlysetup('your_username', 'your_api_key') to get started.
matlab plotly data-visualization d3js d3 webgl data-science technical-computing
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.