To clarify, Plotly's charting libraries for Python and JavaScripts [sic] were not non-proprietary two years ago when this discussion happened.
To clarify, Plotly's charting libraries for Python and JavaScripts are non-proprietary and 100% open-source under MIT.
Plotly aims for parity with matplotlib or MATLAB graphics features, but with modern, interactive SVG and WebGL renderers. These renderers also make embedding and sharing on the web low-friction. We have regular release cycles every Monday for the JavaScript library and are used from university student homework assignments to production at the largest Fortune 500s.
More: Getting started with plotly in Python
Contributing: GitHub - plotly/plotly.js: Open-source JavaScript charting library behind Plotly and Dash (JavaScript layer) GitHub - plotly/plotly.py: The interactive graphing library for Python This project now includes Plotly Express! (Python client to JavaScript layer)
-Jack / Plotly CEO
On Tuesday, September 2, 2014 at 11:46:17 AM UTC-7, Josh Wasserstein wrote:
Thanks Peter. I actually wasn't aware of some of the other proprietary offerings (Spotfire, Tableou and Palantir). As a matter of fact, I didn't know that Plotly was proprietary ether. That's good to know. I also understand that comparing open-source vs proprietary source makes it difficult, since it's hard to know what assumptions and architectural decisions were made in closed-source SW.
I can't speak for others, and I know it's difficult to draw the line and single out specific alternatives in a comparison, but I think a high-level analysis, perhaps at the level of features, capabilities and requirements (e.g. having to be online, being able to build your own apps with widgets, or being able to self-host your own interactive engine, etc.) against mainstream alternatives that directly target Python support (mostly plotly, mpl3d, vispy and vincent), even if in their present form, would already be very helpful.
I think the problem my team has (and perhaps others do as well) is that the landscape of solution looks fragmented, and it's hard to understand what each solution provides and requires. It looks like Bokeh and Plotly are emerging as the main all-encompassing high-end interactive solutions available, which is why I focused on these two, but perhaps I am wrong.
~Josh
On Tue, Sep 2, 2014 at 11:31 AM, Peter Wang <[email protected]> wrote:
Hey Josh,
On Tue, Sep 2, 2014 at 10:02 AM, Josh Wasserstein <[email protected]> wrote:
This takes me to the following question: What makes Bokeh different from alternatives like Plotly and others?
With this, my questions are: Where does Bokeh excel in your opinion in particular? What are the major differences that you would highlight between Bokeh and other solutions like Plotly in terms of scope/approach/vision that will impact the way the library is used over time?
Good questions! Before I respond in depth, however, I wanted to understand the scope. Do you want me to list only open-source alternatives, or also proprietary offerings like Plotly, Spotfire, Tableau, Palantir, and others? Are you primarily interested in the area of business & statistical infovis (e.g. ggplot and trelliscope's target domains) or also the realm of scientific visualization (vtk, paraview, dislin, and matplotlib's roots)?
Thanks,
Peter
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