D3.js vs Dash

Overview

D3.js

Stacks2.0K

Followers1.7K

Votes653

GitHub Stars111.7K

Forks22.9K

Dash

Stacks314

Followers408

Votes63

D3.js vs Dash: What are the differences?

Scalability: One key difference between D3.js and Dash is the scalability of the tools. D3.js, which stands for Data-Driven Documents, is a JavaScript library that provides powerful data visualization capabilities. It allows users to create highly customized and interactive visualizations using web standards such as HTML, CSS, and SVG. On the other hand, Dash is a Python framework for building analytical web applications. It is built on top of Flask and Plotly.js, and allows for easy integration of data visualization components. While D3.js is more suitable for creating complex and highly customized visualizations, Dash provides a more scalable solution for building analytical dashboards and applications.
Learning Curve: Another difference between D3.js and Dash is the learning curve associated with each tool. D3.js is a low-level library that requires a good understanding of JavaScript, HTML, CSS, and SVG in order to create visualizations. It provides a wide range of functionality but requires more coding and customization. On the other hand, Dash is a higher-level framework that is built on top of Python, which is a popular and widely-used programming language. It provides a more intuitive and user-friendly interface for creating web applications, making it easier for users with a background in Python to get started.
Interactivity: D3.js is known for its powerful interactivity features. It allows users to create highly interactive visualizations that respond to user interactions such as mouse clicks, hovers, and brush selections. Users can add tooltips, animations, and other interactive elements to enhance the overall user experience. Dash, on the other hand, also supports interactivity but to a lesser extent. It provides basic interactivity features such as dropdown menus, sliders, and buttons, but does not offer the same level of customization and flexibility as D3.js.
Community and Support: D3.js has a large and active community of developers and enthusiasts who contribute to its development and share their work. There are numerous online resources, tutorials, and examples available for learning and using D3.js. Dash, although relatively newer compared to D3.js, also has a growing community and support network. However, the resources and documentation available for Dash may not be as extensive as those available for D3.js.
Integration with Backend: D3.js is a client-side library, which means that all the code runs on the client's browser. It can be easily integrated with any backend technology such as Node.js or Flask to fetch data from APIs or databases. In contrast, Dash is a server-side framework that requires a backend to handle data processing and storage. Dash applications are built using Python and run on a server, which allows for more complex data processing and integration with other Python libraries such as Pandas or NumPy.

In Summary, D3.js is a powerful JavaScript library for creating highly customized and interactive visualizations, while Dash is a Python framework that provides a more scalable solution for building analytical web applications. D3.js requires more coding and customization but offers greater flexibility and interactivity, while Dash is easier to learn and provides a higher-level interface for creating web applications.

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Advice on D3.js, Dash

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	Dash
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.	Dash is an API Documentation Browser and Code Snippet Manager. Dash stores snippets of code and instantly searches offline documentation sets for 150+ APIs. You can even generate your own docsets or request docsets to be included.
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.	150+ offline docsets;Instant, fuzzy search;Great integration with other apps;Easily download docsets;Easily generate docsets:;Supports AppleDoc docsets;Supports Doxygen docsets;Supports CocoaDocs docsets;Supports Python / Sphinx docsets;Supports Ruby / RDoc docsets;Supports Javadoc docsets;Supports Scaladoc docsets;Supports Any HTML docsets;Easily switch between docsets:;Smart search profiles;Docset keywords;Documentation bookmarks;Convenient, filterable table of contents;Highlighted in-page search
Statistics
GitHub Stars 111.7K	GitHub Stars -
GitHub Forks 22.9K	GitHub Forks -
Stacks 2.0K	Stacks 314
Followers 1.7K	Followers 408
Votes 653	Votes 63
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 17 Dozens of API docs and Cheat-Sheets 12 Great for offline use 8 Excellent documentation 8 Works with Alfred 8 Quick API search
Integrations
JavaScript React Native AngularJS React Bootstrap	No integrations available

What are some alternatives to D3.js, Dash?

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.

Plotly.js

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.

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.

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

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.

Related Comparisons

D3.js vs Dash: What are the differences?

Scalability: One key difference between D3.js and Dash is the scalability of the tools. D3.js, which stands for Data-Driven Documents, is a JavaScript library that provides powerful data visualization capabilities. It allows users to create highly customized and interactive visualizations using web standards such as HTML, CSS, and SVG. On the other hand, Dash is a Python framework for building analytical web applications. It is built on top of Flask and Plotly.js, and allows for easy integration of data visualization components. While D3.js is more suitable for creating complex and highly customized visualizations, Dash provides a more scalable solution for building analytical dashboards and applications.
Learning Curve: Another difference between D3.js and Dash is the learning curve associated with each tool. D3.js is a low-level library that requires a good understanding of JavaScript, HTML, CSS, and SVG in order to create visualizations. It provides a wide range of functionality but requires more coding and customization. On the other hand, Dash is a higher-level framework that is built on top of Python, which is a popular and widely-used programming language. It provides a more intuitive and user-friendly interface for creating web applications, making it easier for users with a background in Python to get started.
Interactivity: D3.js is known for its powerful interactivity features. It allows users to create highly interactive visualizations that respond to user interactions such as mouse clicks, hovers, and brush selections. Users can add tooltips, animations, and other interactive elements to enhance the overall user experience. Dash, on the other hand, also supports interactivity but to a lesser extent. It provides basic interactivity features such as dropdown menus, sliders, and buttons, but does not offer the same level of customization and flexibility as D3.js.
Community and Support: D3.js has a large and active community of developers and enthusiasts who contribute to its development and share their work. There are numerous online resources, tutorials, and examples available for learning and using D3.js. Dash, although relatively newer compared to D3.js, also has a growing community and support network. However, the resources and documentation available for Dash may not be as extensive as those available for D3.js.
Integration with Backend: D3.js is a client-side library, which means that all the code runs on the client's browser. It can be easily integrated with any backend technology such as Node.js or Flask to fetch data from APIs or databases. In contrast, Dash is a server-side framework that requires a backend to handle data processing and storage. Dash applications are built using Python and run on a server, which allows for more complex data processing and integration with other Python libraries such as Pandas or NumPy.

D3.js vs Dash

Overview