Matplotlib
Pandas
GnuPlot
Plotly
NumPy
SciDaVis
Seaborn
GeoGebra
D3.js
Chart.js
Plotly
Highcharts
Google Charts
AnyChart
Pixi.js
RAWGraphs
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 161 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.
Python (with Matplotlib): A powerful library for creating detailed histograms. - Source: dev.to / 4 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
Data Visualization Software is designed to help users create visual representations of their data. These tools are often used to create charts, graphs, and other visualizations that can help users understand their data better. Some popular Data Visualization Software includes Tableau, Power BI, and D3.js. Tableau and Power BI are both powerful data visualization tools, while D3.js is a JavaScript library for... - Source: dev.to / 10 days ago
Interactive User Interface: Developing an interactive UI for visualizing the graph and its communities could make the summarization process more intuitive. Tools like D3.js or Cytoscape.js can be used to create dynamic visualizations. - Source: dev.to / 29 days 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 / about 2 months ago
d3 - very power visualization library enabling dynamic visualizations. docs. - Source: dev.to / 3 months 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 / 4 months ago
Pandas - Pandas is an open source library providing high-performance, easy-to-use data structures and data analysis tools for the Python.
Chart.js - Easy, object oriented client side graphs for designers and developers.
GnuPlot - Gnuplot is a portable command-line driven interactive data and function plotting utility.
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
NumPy - NumPy is the fundamental package for scientific computing with Python