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  1. Stackups
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  4. Charting Libraries
  5. D3.js vs Epoch by Fastly vs Plotly

D3.js vs Epoch by Fastly vs Plotly

OverviewDecisionsComparisonAlternatives

Overview

Epoch by Fastly
Epoch by Fastly
Stacks9
Followers16
Votes0
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 Epoch by Fastly vs Plotly: What are the differences?

# Introduction

D3.js, Epoch by Fastly, and Plotly are popular data visualization libraries used for creating interactive graphics on the web. Each of these libraries has its unique features and functionalities that set them apart from one another.

1. **Rendering Approach**: D3.js is a low-level library that gives users full control over the rendering process, allowing for customization and flexibility in creating complex visualizations. On the other hand, Epoch by Fastly provides a simpler and more streamlined approach to data visualization, offering a ready-to-use set of charts and interfaces for quick deployment. Plotly falls somewhere in between, offering a balance between customization and ease of use with its interactive plotting capabilities.

2. **Community Support**: D3.js has a robust and active community with a vast collection of resources, tutorials, and plugins available for users. This extensive community support makes it easier for developers to troubleshoot issues and find solutions to common problems. Epoch by Fastly and Plotly also have growing communities, but they may not be as extensive or well-established as D3.js.

3. **Chart Types**: D3.js has a wide range of chart types available, from basic bar and line charts to more complex visualizations like network graphs and geographical maps. Epoch by Fastly focuses primarily on time series data and provides a limited set of specialized chart types tailored for this purpose. Plotly offers a diverse array of chart types, including 3D plots, geospatial plots, and statistical charts, making it suitable for a wide range of data visualization needs.

4. **Interactivity**: D3.js provides extensive support for interactivity, allowing users to create dynamic and engaging visualizations with animations, tooltips, zooming, and panning functionalities. Epoch by Fastly also offers interactivity features but may not be as extensive as D3.js. Plotly, on the other hand, excels in interactivity with features like hover effects, linked views, and cross-filtering capabilities.

5. **Deployment Options**: While D3.js requires users to host the library on their server or include it in their web page, Epoch by Fastly and Plotly offer cloud-based solutions for data visualization. Epoch by Fastly provides the option to host charts on Fastly's CDN, while Plotly offers an online platform for creating, sharing, and collaborating on interactive visualizations.

6. **Learning Curve**: D3.js has a steep learning curve due to its low-level nature and complex API, requiring users to have a strong understanding of web technologies like HTML, CSS, and SVG. Epoch by Fastly and Plotly, on the other hand, have more user-friendly APIs and documentation, making it easier for beginners to get started with data visualization.

In Summary, D3.js, Epoch by Fastly, and Plotly each offer unique features and functionalities in data visualization, with differences in rendering approach, community support, chart types, interactivity, deployment options, and learning curve. 

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Advice on Epoch by Fastly, 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/
8.82k views8.82k
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

Epoch by Fastly
Epoch by Fastly
D3.js
D3.js
Plotly.js
Plotly.js

Epoch is a general purpose charting library for application developers and visualization designers. It focuses on two different aspects of visualization programming: basic charts for creating historical reports, and real-time charts for displaying frequently updating timeseries data.

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.

Built for Developers - open source;Real-time Charting;Unified Styling
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
9
Stacks
2.0K
Stacks
399
Followers
16
Followers
1.7K
Followers
694
Votes
0
Votes
653
Votes
69
Pros & Cons
No community feedback yet
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 Epoch by Fastly, 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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