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  1. Stackups
  2. Business Tools
  3. UI Components
  4. Charting Libraries
  5. Chart.js vs D3.js vs Plotly

Chart.js vs D3.js vs Plotly

OverviewComparisonAlternatives

Overview

D3.js
D3.js
Stacks2.0K
Followers1.7K
Votes653
GitHub Stars111.7K
Forks22.9K
Plotly.js
Plotly.js
Stacks399
Followers694
Votes69
GitHub Stars17.9K
Forks1.9K
Chart.js
Chart.js
Stacks2.0K
Followers786
Votes44
GitHub Stars66.7K
Forks12.0K

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

<Write Introduction here>
  1. Data Visualization Libraries: Chart.js is a simpler and easier-to-use library compared to D3.js and Plotly. It is designed for quick and simple chart creation with limited customization options. D3.js, on the other hand, provides a high level of customization and control over the visualization process but has a steeper learning curve compared to Chart.js. Plotly combines the features of both libraries, offering a balance between ease of use and advanced customization options.

  2. Community Support and Documentation: D3.js has a robust community with extensive documentation and resources available online due to its popularity among developers for complex data visualizations. Chart.js also has a supportive community but may not have as many resources or documentation as D3.js. Plotly, being a relatively newer library, is quickly gaining popularity and has a growing community with good documentation and support available.

  3. Chart Types and Features: Chart.js provides a limited set of chart types and features compared to D3.js and Plotly. While it covers basic chart types like bar, line, and pie charts, D3.js offers a wide range of customization options and supports complex visualizations like force-directed graphs and interactive maps. Plotly, similar to D3.js, provides a rich set of chart types and interactive features for creating dynamic and engaging visuals.

  4. Ease of Integration: Chart.js is easy to integrate into web applications with minimal setup and configuration required, making it ideal for beginners and simple projects. D3.js, being more complex, may require additional effort and knowledge to integrate seamlessly into projects due to its low-level approach to data visualization. Plotly offers multiple integration options, including APIs for various programming languages, making it easy to incorporate into different platforms and applications.

  5. Animation and Interactivity: D3.js excels in providing high levels of animation and interactivity capabilities compared to Chart.js and Plotly. It allows for smooth transitions and real-time visual updates, enhancing the user experience. While Chart.js supports basic animations, Plotly offers intermediate levels of animation and interactivity features, making it suitable for creating engaging and dynamic visualizations without the complexity of D3.js.

  6. License Restrictions: Chart.js, D3.js, and Plotly have different licensing models. Chart.js is available under the MIT license, allowing for free commercial use and modification. D3.js is released under the BSD license, permitting both personal and commercial use with attribution. Plotly offers a dual licensing model, with a permissive MIT license for open-source projects and a commercial license for proprietary use, making it suitable for both open-source and commercial applications.

In Summary, Chart.js is beginner-friendly with limited chart types, while D3.js offers high customization and complexity, and Plotly provides a balance between ease of use and advanced features for data visualization on the web.

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Detailed Comparison

D3.js
D3.js
Plotly.js
Plotly.js
Chart.js
Chart.js

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.

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

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
animated;HTML5 based;Responsive;Modular;Bar;Doughnut;Radar;Line;Polar Area;Interactive
Statistics
GitHub Stars
111.7K
GitHub Stars
17.9K
GitHub Stars
66.7K
GitHub Forks
22.9K
GitHub Forks
1.9K
GitHub Forks
12.0K
Stacks
2.0K
Stacks
399
Stacks
2.0K
Followers
1.7K
Followers
694
Followers
786
Votes
653
Votes
69
Votes
44
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
  • 19
    Offers all types of charts
  • 14
    Interactive Charts
  • 10
    It's totally free
Cons
  • 12
    Slow rendering
  • 2
    Bitmap quality export
  • 1
    Low quality zoom plugin
  • 0
    It's totally free
Integrations
JavaScript
JavaScript
React Native
React Native
AngularJS
AngularJS
React
React
Bootstrap
Bootstrap
Python
Python
React
React
MATLAB
MATLAB
Jupyter
Jupyter
Julia
Julia
React
React
AngularJS
AngularJS

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

Underscore

Underscore

A JavaScript library that provides a whole mess of useful functional programming helpers without extending any built-in objects.

Deno

Deno

It is a secure runtime for JavaScript and TypeScript built with V8, Rust, and Tokio.

Highcharts

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.

Recharts

Recharts

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

ECharts

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

ZingChart

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

amCharts

amCharts

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.

CanvasJS

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

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.

Immutable.js

Immutable.js

Immutable provides Persistent Immutable List, Stack, Map, OrderedMap, Set, OrderedSet and Record. They are highly efficient on modern JavaScript VMs by using structural sharing via hash maps tries and vector tries as popularized by Clojure and Scala, minimizing the need to copy or cache data.

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