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  1. Stackups
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  3. UI Components
  4. Charting Libraries
  5. D3.js vs Plotly

D3.js vs Plotly

OverviewDecisionsComparisonAlternatives

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

D3.js vs Plotly: What are the differences?

D3.js and Plotly are both powerful data visualization libraries used for creating interactive and dynamic visualizations in web applications. Here are the key differences between D3.js and Plotly:

  1. Approach: D3.js (Data-Driven Documents) is a low-level JavaScript library for manipulating and binding data to the Document Object Model (DOM). It gives developers complete control over every aspect of the visualization process, allowing for highly customized and unique visualizations. Plotly, on the other hand, is a higher-level library that provides a declarative syntax for creating visualizations. It abstracts away many of the low-level details and provides a more streamlined approach for quickly creating interactive charts and graphs.

  2. Chart Types and Features: D3.js provides a wide range of chart types and visualizations, including bar charts, line charts, scatter plots, maps, and more. It offers extensive customization options to create complex and custom visualizations. Plotly also supports a variety of chart types and offers interactive features like zooming, panning, and tooltips. Additionally, Plotly provides built-in support for 3D visualizations and animations, making it well-suited for creating dynamic and engaging visualizations.

  3. Learning Curve: D3.js has a steeper learning curve compared to Plotly due to its low-level nature and the need to have a good understanding of JavaScript and web technologies. It requires more coding and a deeper understanding of data visualization concepts. Plotly, on the other hand, has a more user-friendly interface and a simpler syntax, making it easier to get started with and create visualizations quickly, especially for developers with limited coding experience.

  4. Community and Support: D3.js has a mature ecosystem with extensive examples and tutorials. Plotly also has a growing community and provides comprehensive documentation and support. It offers additional features like online sharing of visualizations and collaborative editing.

In summary, D3.js provides unparalleled flexibility and customization options, making it suitable for developers who require fine-grained control over their visualizations and have a good understanding of JavaScript. Plotly, on the other hand, offers a more streamlined and user-friendly approach, with a focus on creating interactive visualizations quickly and easily.

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Advice on 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/
8.81k views8.81k
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.

56k views56k
Comments

Detailed Comparison

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

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
111.7K
GitHub Stars
17.9K
GitHub Forks
22.9K
GitHub Forks
1.9K
Stacks
2.0K
Stacks
399
Followers
1.7K
Followers
694
Votes
653
Votes
69
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
Integrations
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 D3.js, Plotly.js?

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.

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.

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