plotly.py, colloquially referred to as Plotly, is an interactive, open-source, and browser-based graphing library. It offers Python-based charting, powered by plotly.js. The library ships with over 30 chart types, including scientific charts, 3D graphs, statistical charts, SVG maps, financial charts, and more. Plotly Inc. the company responsible for the development and maintenance of the library was founded by Alex Johnson, Jack Parmer, Chris Parmer, and Matthew Sundquist. Plotly Inc. was featured in "startup row" at PyCon 2013,[4] and sponsored the SciPy 2018 conference. The company now is headquartered in Montreal, Quebec.
Dash is another open-source Python framework from Plotly Inc., which is manly used for building ML and data science web apps. It is built on top of plotly.py, and ties modern UI elements such as dropdowns, sliders, and graphs directly to your analytical Python code. The enterprise version of Dash provides several other features including scalable hosting and deployment.
All three of these are very popular data visualization packages. While Matplotlib is one of the earliest and most robust visualization tools in Python, Plotly and Bokeh provide much more interactive and appealing visualizations to the user.
Plotly | Matplotlib | Bokeh |
Ease of Use | ||
Convenient in most situations | Can be tedious | Very simple |
Number of Charts Supported | ||
30+ | 50+ | 80+ |
Interactive | ||
Yes | Yes | No |
Dashboards | ||
Dash server | Bokeh server | No dashboard |
Supports 3D Graphs | ||
Yes | No | Yes |
Supported Programming Languages | ||
Javascript, Python, R, Julia | Python, R, Scala | Python |
Domino comes with built-in support for Dash and enables users to leverage the powerful features of this framework for the purposes of data visualization and ML models interaction. Publishing a Dash web application is a fairly straightforward process, which involves the following steps:.
You can find the detailed steps here.