Based on our record, Matplotlib seems to be a lot more popular than Plotly.js. While we know about 100 links to Matplotlib, we've tracked only 3 mentions of Plotly.js. We are tracking product recommendations and mentions on various public social media platforms and blogs. They can help you identify which product is more popular and what people think of it.
Well, MathML[1] support is (nearly) everywhere now, and as the docs say: MathML Core is a subset with increased implementation details based on rules from LaTeX and the Open Font Format. It is tailored for browsers and designed specifically to work well with other web standards including HTML, CSS, DOM, JavaScript. I don't have a lot of experience working with this stuff (yet) but if you can script your... - Source: Hacker News / 11 months ago
Plotly offers multiple options (python, R, javascript). The weby stuff is done with plotly.js and uses d3.js underneath - https://github.com/plotly/plotly.js. - Source: Hacker News / over 1 year ago
So you didn't use Django DRF as the backend? I'm just curious how Dash communicated with Django - did it communicate via plain HTTP calls? I guess you ran non-React Plotly.js (https://github.com/plotly/plotly.js)? Source: almost 3 years ago
Python (with Matplotlib): A powerful library for creating detailed histograms. - Source: dev.to / 3 days ago
Below is an example of a code cell. We'll visualize some simple data using two popular packages in Python. We'll use NumPy to create some random data, and Matplotlib to visualize it. - Source: dev.to / 9 months ago
Matplotlib: for displaying our image result. - Source: dev.to / 2 months ago
Matplotlib: Acomprehensive library for creating static, animated, and interactive visualizations in Python. - Source: dev.to / 4 months ago
Data visualization: utilizing Python's Matplotlib for visualizing order book information. - Source: dev.to / 7 months ago
D3.js - D3.js is a JavaScript library for manipulating documents based on data. D3 helps you bring data to life using HTML, SVG, and CSS.
Pandas - Pandas is an open source library providing high-performance, easy-to-use data structures and data analysis tools for the Python.
Highcharts - A charting library written in pure JavaScript, offering an easy way of adding interactive charts to your web site or web application
GnuPlot - Gnuplot is a portable command-line driven interactive data and function plotting utility.
Chart.js - Easy, object oriented client side graphs for designers and developers.
Google Charts - Interactive charts for browsers and mobile devices.