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  1. Stackups
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  4. Charting Libraries
  5. D3.js vs Highcharts vs Plotly

D3.js vs Highcharts vs Plotly

OverviewDecisionsComparisonAlternatives

Overview

Highcharts
Highcharts
Stacks1.5K
Followers1.1K
Votes92
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

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

Introduction

D3.js, Highcharts, and Plotly are all popular JavaScript libraries used for creating interactive and dynamic data visualizations on websites. While they share some similarities, there are key differences between them that make each library unique and suitable for specific use cases. In this Markdown code, we will provide a concise description of the key differences between D3.js, Highcharts, and Plotly.

  1. Data Binding and DOM Manipulation: D3.js, being a low-level library, gives developers complete control over data binding and DOM manipulation. It allows for fine-grained control over how data is mapped to visual elements and enables the creation of custom visualizations with ease. On the other hand, Highcharts and Plotly provide a higher-level API that abstracts away the details of data binding and DOM manipulation, making it easier to create standard chart types quickly.

  2. Chart Types and Customizability: Highcharts offers a wide range of pre-built chart types out-of-the-box, including bar charts, line charts, pie charts, etc. It provides extensive customization options, allowing developers to tweak various aspects of the chart's appearance and behavior. Plotly also offers a good selection of chart types and customizability options, but it goes a step further by providing interactive charts that support zooming, panning, and hover interactions. In contrast, D3.js does not come with built-in chart types but instead provides a powerful set of tools for creating custom visualizations from scratch, giving developers the most flexibility and control over every aspect of the chart.

  3. Learning Curve and Ease of Use: D3.js has a steeper learning curve compared to Highcharts and Plotly due to its lower-level nature. It requires a deeper understanding of JavaScript and SVG (Scalable Vector Graphics), but it offers the most flexibility and customization options. Highcharts and Plotly, on the other hand, have a more intuitive and beginner-friendly API, making them easier to learn and use out-of-the-box, especially for developers who are not well-versed in JavaScript or data visualization concepts.

  4. Interactivity and User Interaction: Plotly shines in terms of interactivity and user interaction. It offers fully interactive charts that support zooming, panning, hovering, and tooltips by default. Highcharts also provides interactive features but not to the same extent as Plotly. D3.js, being a low-level library, requires developers to manually implement interactivity features, although it provides the necessary tools and flexibility to achieve any desired interactive behavior.

  5. Community and Support: D3.js has a thriving community and a vast ecosystem of plugins and resources available. It has been around for a longer time and is widely adopted, making it easier to find help and examples online. Highcharts also has a large and active community but not as extensive as D3.js. Plotly, although relatively newer than the other two, has gained popularity in recent years and has an active community as well.

  6. Licensing: D3.js is an open-source library released under the BSD 3-Clause License, allowing developers to use it freely and modify its source code. Highcharts, on the other hand, is available for free for non-commercial use but requires a commercial license for commercial projects. Plotly offers both open-source and commercial licenses, giving developers the flexibility to choose based on their requirements.

In summary, D3.js provides complete control and customization options, suitable for creating highly custom visualizations, but with a steeper learning curve. Highcharts offers a wide range of pre-built chart types and customization options, making it easier to create standard charts quickly. Plotly excels in interactivity and provides fully interactive charts with zooming, panning, and hover features, offering an intuitive experience for users. The choice between these libraries depends on the project requirements and the developer's comfort level with customization and interactivity.

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Advice on Highcharts, D3.js, Plotly.js

Steve
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/
8.84k views8.84k
Comments
Shaik
Shaik

Feb 18, 2020

Needs advice

I have used highcharts and it is pretty awesome for my previous project. now as I am about to start my new project I want to use other charting libraries such as recharts, chart js, Nivo, d3 js.... my upcoming project might use react js as front end and laravel as a backend technology. the project would be of hotel management type. please suggest me the best charts to use

247k views247k
Comments
Ayaskant
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.

56.1k views56.1k
Comments

Detailed Comparison

Highcharts
Highcharts
D3.js
D3.js
Plotly.js
Plotly.js

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.

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.

It works in all modern mobile and desktop browsers including the iPhone/iPad and Internet Explorer from version 6;Free for non-commercial;One of the key features of Highcharts is that under any of the licenses, free or not, you are allowed to download the source code and make your own edits;Pure Javascript - Highcharts is solely based on native browser technologies and doesn't require client side plugins like Flash or Java.
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
Statistics
GitHub Stars
-
GitHub Stars
111.7K
GitHub Stars
17.9K
GitHub Forks
-
GitHub Forks
22.9K
GitHub Forks
1.9K
Stacks
1.5K
Stacks
2.0K
Stacks
399
Followers
1.1K
Followers
1.7K
Followers
694
Votes
92
Votes
653
Votes
69
Pros & Cons
Pros
  • 34
    Low learning curve and powerful
  • 17
    Multiple chart types such as pie, bar, line and others
  • 13
    Responsive charts
  • 9
    Handles everything you throw at it
  • 8
    Extremely easy-to-parse documentation
Cons
  • 9
    Expensive
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
Integrations
No integrations available
JavaScript
JavaScript
React Native
React Native
AngularJS
AngularJS
React
React
Bootstrap
Bootstrap
Python
Python
React
React
MATLAB
MATLAB
Jupyter
Jupyter
Julia
Julia

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

Chart.js

Chart.js

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

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.

ApexCharts

ApexCharts

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

Bokeh

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

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.

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