D3.js vs Plotly vs amCharts

Overview

D3.js

Stacks2.0K

Followers1.7K

Votes653

GitHub Stars111.7K

Forks22.9K

Plotly.js

Stacks399

Followers694

Votes69

GitHub Stars17.9K

Forks1.9K

amCharts

Stacks216

Followers230

Votes21

D3.js vs Plotly vs amCharts: What are the differences?

Introduction:

D3.js, Plotly, and amCharts are popular JavaScript libraries used for data visualization. Each of these libraries has unique features and differences that set them apart. Below are the key differences between D3.js, Plotly, and amCharts.

1. Customization and Flexibility: D3.js provides the most flexibility and customization options among the three libraries. Users have granular control over every aspect of the visualization, making it suitable for complex and unique data visualizations. Plotly and amCharts offer easier implementation and come with a wide range of pre-designed templates and charts, limiting the extent of customization compared to D3.js.

2. Ease of Use and Learning Curve: Plotly and amCharts are known for their user-friendly interfaces and simplified coding syntax, which make them easier to use for those with less experience in data visualization. D3.js, on the other hand, has a steeper learning curve due to its more complex API and implementation requirements.

3. Community Support and Documentation: D3.js has a robust community of users and extensive documentation, making it easier to troubleshoot issues and find resources for development. Plotly and amCharts also have active user communities, but they may not have the same level of comprehensive documentation and resources available as D3.js.

4. Interactivity and Real-time Data: Plotly provides excellent support for real-time data streaming and interactive visualizations, suitable for dynamic applications. amCharts also offers interactive features, but Plotly is known for its advanced interactivity capabilities, while D3.js requires more effort to implement real-time data visualization features.

5. Performance and Scalability: D3.js is highly optimized for performance and scalability, making it suitable for handling large datasets and complex visualizations efficiently. Plotly and amCharts are designed for ease of use and may not offer the same level of performance optimization as D3.js, particularly when dealing with extensive data processing and rendering requirements.

6. Licensing and Pricing: D3.js is open-source and free to use, making it a cost-effective option for developers. Plotly and amCharts offer both open-source and commercial versions, with additional features and support available in the paid plans. Users looking for a budget-friendly solution may opt for D3.js, while those requiring premium features and support may choose Plotly or amCharts.

In Summary, D3.js stands out for its customization and flexibility, while Plotly and amCharts offer easier implementation and user-friendly interfaces. Developers can choose the best library based on their specific requirements for data visualization projects.

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Advice on D3.js, Plotly.js, amCharts

Steve

Lead Software Tools Engineer at Leonardo UK

Oct 30, 2020

Review

I would specifically recommend basing your application on Pandas which will handle the vast majority of the work for you. You will be amazed at what you will be able to get done with only a few lines of code.

Pandas can load the data from either Excel xslx files or csv files (and a lot of other places)

If you structure your code well you can have a cross platform command line program, a GUI desktop program, a Jupyter Notebook and a web service all with the vast majority of the code in common.

A jupyter notebook is a great place to start developing your code and may be all that you need.

Some plug-ins & resources that can help:

pandas-summary (for a rapid overview of the data): https://github.com/mouradmourafiq/pandas-summary
pandasgui (for exploring what you would like to do): https://github.com/adamerose/pandasgui
Pandas-Bokeh (plotting): https://github.com/PatrikHlobil/Pandas-Bokeh
plot.ly (plotting): https://plotly.com/python/pandas-backend/
wxPython (for a desktop GUI): https://wxpython.org/

8.82k views8.82k

Comments

Ayaskant

SSE-II at Akamai

Oct 25, 2019

Needs advice

I want to get suggestions on these 2 open source js libraries (D3.js & echarts) that help in creating charts or graphs on the UI. Which one will be better for bar graphs. Which is easy to learn and start with? Which provides better features and community support?

My requirements are 1 - Plot data in X-Y axis graph where x-axis will present time till seconds level and Y-Axis will present the data corresponding to that time.

2 - Zoom-in and zoom out feature.

56k views56k

Comments

Detailed Comparison

D3.js	Plotly.js	amCharts
It is a JavaScript library for manipulating documents based on data. Emphasises on web standards gives you the full capabilities of modern browsers without tying yourself to a proprietary framework.	It is a standalone Javascript data visualization library, and it also powers the Python and R modules named plotly in those respective ecosystems (referred to as Plotly.py and Plotly.R). It can be used to produce dozens of chart types and visualizations, including statistical charts, 3D graphs, scientific charts, SVG and tile maps, financial charts and more.	amCharts is an advanced charting library that will suit any data visualization need. Our charting solution include Column, Bar, Line, Area, Step, Step without risers, Smoothed line, Candlestick, OHLC, Pie/Donut, Radar/ Polar, XY/Scatter/Bubble, Bullet, Funnel/Pyramid charts as well as Gauges.
Declarative Approach for Individual Nodes Manipulation; Functions Factory; Web Standards; Built-in ELement Inspector to Debug; Uses SVG, Canvas, and HTML; Data-driven approach to DOM Manipulation; Voronoi Diagrams; Maps and topo.	Feature parity with MATLAB/matplotlib graphing; Online chart editor; Fully interactive (hover, zoom, pan); SVG and WebGL backends; Publication-quality image export	Free or Commercial; All chart and map types you might need; Works on all modern browsers and also old IE; Can use SVG filters; Can be styled with CSS; Online editor available; Zoomable, Scrollable; Date-based charts
Statistics
GitHub Stars 111.7K	GitHub Stars 17.9K	GitHub Stars -
GitHub Forks 22.9K	GitHub Forks 1.9K	GitHub Forks -
Stacks 2.0K	Stacks 399	Stacks 216
Followers 1.7K	Followers 694	Followers 230
Votes 653	Votes 69	Votes 21
Pros & Cons
Pros 195 Beautiful visualizations 103 Svg 92 Data-driven 81 Large set of examples 61 Data-driven documents Cons 11 Beginners cant understand at all 6 Complex syntax	Pros 16 Bindings to popular languages like Python, Node, R, etc 10 Integrated zoom and filter-out tools in charts and maps 9 Great support for complex and multiple axes 8 Powerful out-of-the-box featureset 6 Beautiful visualizations Cons 18 Terrible document	Pros 18 Mock-up tools 3 Each element can be Customized Cons 1 Amcharts upgrade often need to rewrite all code
Integrations
JavaScript React Native AngularJS React Bootstrap	Python React MATLAB Jupyter Julia	Vue.js React TypeScript AngularJS

What are some alternatives to D3.js, Plotly.js, amCharts?

Highcharts

Highcharts currently supports line, spline, area, areaspline, column, bar, pie, scatter, angular gauges, arearange, areasplinerange, columnrange, bubble, box plot, error bars, funnel, waterfall and polar chart types.

Chart.js

Visualize your data in 6 different ways. Each of them animated, with a load of customisation options and interactivity extensions.

Recharts

Quickly build your charts with decoupled, reusable React components. Built on top of SVG elements with a lightweight dependency on D3 submodules.

ECharts

It is an open source visualization library implemented in JavaScript, runs smoothly on PCs and mobile devices, and is compatible with most current browsers.

ZingChart

The most feature-rich, fully customizable JavaScript charting library available used by start-ups and the Fortune 100 alike.

CanvasJS

Lightweight, Beautiful & Responsive Charts that make your dashboards fly even with millions of data points! Self-Hosted, Secure & Scalable charts that render across devices.

AnyChart

AnyChart is a flexible JavaScript (HTML5) based solution that allows you to create interactive and great looking charts. It is a cross-browser and cross-platform charting solution intended for everybody who deals with creation of dashboard, reporting, analytics, statistical, financial or any other data visualization solutions.

ApexCharts

A modern JavaScript charting library to build interactive charts and visualizations with simple API.

Bokeh

Bokeh is an interactive visualization library for modern web browsers. It provides elegant, concise construction of versatile graphics, and affords high-performance interactivity over large or streaming datasets.

Matplotlib

It is a Python 2D plotting library which produces publication quality figures in a variety of hardcopy formats and interactive environments across platforms. It can be used in Python scripts, the Python and IPython shells, the Jupyter notebook, web application servers, and four graphical user interface toolkits.

Related Comparisons

D3.js vs Plotly vs amCharts: What are the differences?

Introduction:

D3.js vs Plotly vs amCharts

Overview