Matplotlib
GnuPlot
Pandas
Plotly
Seaborn
NumPy
SciDaVis
Chart.js
D3.js
Chart.js
Plotly
Highcharts
Google Charts
AnyChart
Pixi.js
ZingChart
D3 allows you to bind arbitrary data to a Document Object Model (DOM), and then apply data-driven transformations to the document. For example, you can use D3 to generate an HTML table from an array of numbers. Or, use the same data to create an interactive SVG bar chart with smooth transitions and interaction.
D3 is not a monolithic framework that seeks to provide every conceivable feature. Instead, D3 solves the crux of the problem: efficient manipulation of documents based on data. This avoids proprietary representation and affords extraordinary flexibility, exposing the full capabilities of web standards such as HTML, SVG, and CSS. With minimal overhead, D3 is extremely fast, supporting large datasets and dynamic behaviors for interaction and animation. D3’s functional style allows code reuse through a diverse collection of official and community-developed modules.
MatplotlibBased on our record, D3.js should be more popular than Matplotlib. It has been mentiond 159 times since March 2021. 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.
Matplotlib: for displaying our image result. - Source: dev.to / 20 days ago
Matplotlib: Acomprehensive library for creating static, animated, and interactive visualizations in Python. - Source: dev.to / 2 months ago
Data visualization: utilizing Python's Matplotlib for visualizing order book information. - Source: dev.to / 5 months ago
For random, quick and dirty, ad-hoc plotting tasks my default is GNUPlot[1]. Otherwise I tend to use either Python with matplotlib, or R with ggplot2. I keep saying I'm going to invest the time to properly learn D3[4] or something similar for doing web-based plotting, but somehow never quite seem to find time to do it. sigh [1]: http://www.gnuplot.info/ [2]: https://matplotlib.org/ [3]:... - Source: Hacker News / 9 months ago
Python's pandas, NumPy, and SciPy libraries offer powerful functionality for data manipulation, while matplotlib, seaborn, and plotly provide versatile tools for creating visualizations. Similarly, in R, you can use dplyr, tidyverse, and data.table for data manipulation, and ggplot2, lattice, and shiny for visualization. These packages enable you to create insightful visualizations and perform statistical analyses... Source: 12 months ago
Yes this was done with a combination of GSAP Scrolltrigger https://gsap.com/docs/v3/Plugins/ScrollTrigger/ and https://d3js.org/. - Source: Hacker News / 9 days ago
d3 - very power visualization library enabling dynamic visualizations. docs. - Source: dev.to / about 1 month ago
Yep, Evidence is doing good work. We were most directly inspired by VitePress; we spent months rewriting both D3’s docs (https://d3js.org) and Observable Plot’s docs (https://observablehq.com/plot) in VitePress, and absolutely loved the experience. But we wanted a tool focused on data apps, dashboards, reports — observability and business intelligence use cases rather than documentation. Compared to Evidence, I’d... - Source: Hacker News / 2 months ago
They are images so it could be any number of things, datawrapper, charts.js, d3.js to name a few options. Source: 5 months ago
I made this interactive visualization that attempts to show the real-time frequency and location of births around the world. A country’s annual births (i.e. The country’s population times its birthrate) were distributed across all of the populated locations in each country, weighted by the population distribution (i.e. More populated areas got a greater fraction of the births). Data Sources and... Source: 5 months ago
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.
Pandas - Pandas is an open source library providing high-performance, easy-to-use data structures and data analysis tools for the Python.
Plotly - Low-Code Data Apps
Highcharts - A charting library written in pure JavaScript, offering an easy way of adding interactive charts to your web site or web application
Seaborn - Seaborn is a Python data visualization library that uses Matplotlib to make statistical graphics.
