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Chart.js VS Panel

Compare Chart.js VS Panel and see what are their differences

Draxlr
Turn SQL Data into Decisions. Build professional dashboards and data visualizations without technical expertise. Easily embed analytics anywhere, receive automated alerts, and discover AI-powered insights all through a straightforward interface. featured
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  3. » Reviews
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Chart.js logo Chart.js

Easy, object oriented client side graphs for designers and developers.

Panel logo Panel

High-level app and dashboarding solution for Python
  • Chart.js Landing page
    Landing page //
    2023-03-13
  • Panel Landing page
    Landing page //
    2023-05-28

Chart.js features and specs

  • Open Source
    Chart.js is open source and free to use, which makes it accessible for both personal and commercial projects without any licensing costs.
  • Ease of Use
    Chart.js is known for its simple and easy-to-use API. Developers can quickly create charts by just including the library and writing minimal JavaScript.
  • Lightweight
    The library is relatively lightweight compared to other charting libraries, which helps in maintaining the performance of web applications.
  • Responsive Design
    Charts created with Chart.js are responsive by default, ensuring that they look good on all devices, including desktops, tablets, and mobile phones.
  • Variety of Chart Types
    Chart.js supports a variety of chart types including line, bar, radar, pie, doughnut, and polar area charts, providing flexibility for different data visualization needs.
  • Customization
    Developers can customize the appearance of charts extensively through Chart.js options such as colors, labels, and tooltips.
  • Active Community
    Chart.js has an active community and a strong support base, which means that developers can easily find help, tutorials, and plugins to enhance functionality.

Possible disadvantages of Chart.js

  • Limited Advanced Features
    While Chart.js is good for basic and intermediate charting needs, it may lack some advanced features and customizations offered by more complex charting libraries like D3.js.
  • Performance Issues with Large Datasets
    Chart.js can struggle with performance when dealing with very large datasets or complex visualizations, which can result in slower rendering times.
  • Learning Curve for Customization
    Although the basic usage is straightforward, achieving deeper customizations can involve a steeper learning curve as it requires understanding the underlying JavaScript and options.
  • Limited Interactivity
    Interactivity options with Chart.js are somewhat limited compared to other libraries that offer more advanced interactive features.
  • Dependency on Canvas
    Charts are rendered using the HTML5 canvas element, which may not be as flexible as SVG-based rendering used by some other libraries.

Panel features and specs

  • Flexibility
    Panel provides a flexible framework for creating interactive web applications, dashboards, and complex visualizations using Python, allowing developers to leverage their existing Python code without needing to switch to JavaScript or another language.
  • Integration with HoloViz Ecosystem
    Panel integrates seamlessly with other HoloViz tools like HoloViews, GeoViews, and Datashader, enhancing its capabilities for building rich, data-visualization-centric applications.
  • Support for Multiple Backends
    It supports multiple backends, including Bokeh, Plotly, and Matplotlib, giving developers the flexibility to choose their preferred plotting library for rendering their visualizations.
  • Dynamic and Reactive Features
    Panel supports dynamic and reactive UI components that update automatically as data changes, facilitating the creation of interactive and live data applications.
  • Easy Deployment
    Applications built with Panel can be easily deployed on the web using various options, including deploying on Heroku, AWS, or with simple HTTP servers, which helps in transitioning from development to production.

Possible disadvantages of Panel

  • Steep Learning Curve
    For those unfamiliar with the HoloViz ecosystem or Python-based web development, there can be a steep learning curve associated with mastering Panel and its related tools.
  • Performance Limitations
    While Panel is powerful, it may not perform as well as JavaScript-native solutions for extremely high-frequency, real-time data updates due to the overhead of Python-to-JavaScript communication.
  • Limited Community and Resources
    Although growing, the community and resources are not as extensive as some other more-established frameworks like React or Angular, which may lead to a lack of readily available support or third-party plugins.
  • Complexity with Large Applications
    As applications grow in size and complexity, managing state and ensuring efficient communication between components can become challenging.
  • Dependency on Python Environment
    Panel applications require a running Python environment, which can complicate deployment or hosting compared to purely static or client-side applications.

Analysis of Chart.js

Overall verdict

  • Chart.js is a good choice for developers looking for a straightforward solution to incorporate charts into their web projects. Its ease of use, comprehensive documentation, and active community support make it an excellent option for both beginners and experienced developers.

Why this product is good

  • Chart.js is a popular open-source library for creating charts and graphs in web applications. It is valued for its simplicity, ease of use, and ability to create responsive, interactive charts with minimal effort. The library supports a wide range of chart types, including line, bar, radar, doughnut, pie, polar area, bubble, and scatter charts. Chart.js also provides customization options, allowing developers to tailor the look and behavior of their charts to fit their specific needs.

Recommended for

  • Web developers who need to quickly implement charts in their applications.
  • Teams looking for a lightweight and performant charting library.
  • Projects where customization and responsiveness of charts are important.
  • Beginner developers who want to learn and implement basic data visualization techniques.

Chart.js videos

+ Add

1.3: Graphing with Chart.js - Working With Data & APIs in JavaScript

More videos:

  • Tutorial - How to Build Ionic 4 Apps with Chart.js

Panel videos

+ Add

Ready To Love S7 E8 PANEL REVIEW WITH SPECIAL GUEST #readytolove

More videos:

  • Review - Solar Panel Shenanigans Bluetti Review
  • Review - BLUETTI PV420 420w Water Resistant Portable Solar Panel Review

Category Popularity

0-100% (relative to Chart.js and Panel)

Chart.js

Panel

Charting Libraries
100 100%
Charting Libraries
0% 0
Developer Tools
0 0%
Developer Tools
100% 100
Data Visualization
100 100%
Data Visualization
0% 0
Web App
0 0%
Web App
100% 100

User comments

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Reviews

These are some of the external sources and on-site user reviews we've used to compare Chart.js and Panel

Chart.js Reviews

6 JavaScript Charting Libraries for Powerful Data Visualizations in 2023
Of the free libraries on this list, ECharts has the widest range of chart types available, second only to D3. Unlike D3, ECharts also ranks highly on the user-friendliness scale, although some users find ApexCharts and Chart.js even easier to use. You can check out some examples of basic charts on ECharts.
Source: embeddable.com
5 top picks for JavaScript chart libraries
Chart.js is a chart library that is available as a client-side JavaScript package. There are also derivatives for other frontend frameworks, like React, Vue, and Angular. It displays the chart on an HTML canvas element.
Source: blog.logrocket.com
Top 10 JavaScript Charting Libraries for Every Data Visualization Need
Chart.js is a simple yet quite flexible JavaScript library for data viz, popular among web designers and developers. It’s a great basic solution for those who don’t need lots of chart types and customization features but want their charts to look neat, clear and informative at a glance.
Source: hackernoon.com
A Complete Overview of the Best Data Visualization Tools
Chart.js uses HTML5 Canvas for output, so it renders charts well across all modern browsers. Charts created are also responsive, so it’s great for creating visualizations that are mobile-friendly.
Source: www.toptal.com
The Best Data Visualization Tools - Top 30 BI Software
Chart.js is better for smaller chart projects. It’s open source and small in size, supporting six different types of charts: bar, line, pie, radar, doughnut, and polar. You can also add or remove any of these 6 types to reduce your footprint. Chart.js uses HTML5 Canvas and ships with polyfills for IE6/7 support. Chart.js offers the ability to create simple charts quickly.
Source: improvado.io

Panel Reviews

We have no reviews of Panel yet.
Be the first one to post

Social recommendations and mentions

Based on our record, Panel should be more popular than Chart.js. It has been mentiond 10 times since March 2021. We are tracking product recommendations and mentions on various public social media platforms and blogs. They can help you identify which product is more popular and what people think of it.

Chart.js mentions (1)

  • Chart library for Svelte?
    Https://chartjs.org works well, but you have to call the update function yourself if you want to do some reactive updates. Source: about 4 years ago

Panel mentions (10)

  • Show HN: Manganite – Quickly turn Jupyter notebooks into web apps
    Manganite allows easy conversion of Jupyter notebooks into dashboards. Simply annotate existing notebooks with Jupyter magics and serve them as interactive web apps. Manganite has been created to empower master and doctoral students in econ and management to turn research notebooks into interactive dashboards. The students use Python for data analysis, math programming, and basic machine learning. Instead of... - Source: Hacker News / over 1 year ago
  • What python library you are using for interactive visualisation?(other than plotly)
    Https://panel.holoviz.org/ It's a web app framework for Python similar to what Dash does for plotly. It plays nicely with bokeh visuals and I think the front-end is built using bokeh css elements. Source: about 2 years ago
  • How to approach GIS and which language to use
    If you want to build Python dashboards, look at the solara (react-style lib, https://solara.dev/) and panel (https://panel.holoviz.org/). Source: about 2 years ago
  • Ask HN: Fastest way to turn a Jupyter notebook into a website these days?
    My suggestion is https://panel.holoviz.org/ Fully open sourced, makes it easy to make reactive apps with small changes, can even configured as a graphical REPL. - Source: Hacker News / about 2 years ago
  • Updating a page with MQTT
    I am doing something like this in a [panel](https://panel.holoviz.org/) dashboard, which I am currently converting to nicegui. Maybe I can provide an example in some days. Source: about 2 years ago
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What are some alternatives?

When comparing Chart.js and Panel, you can also consider the following products

D3.js - D3.js is a JavaScript library for manipulating documents based on data. D3 helps you bring data to life using HTML, SVG, and CSS.

Streamlit - Turn python scripts into beautiful ML tools

Highcharts - A charting library written in pure JavaScript, offering an easy way of adding interactive charts to your web site or web application

Dash by Plotly - Dash is a Python framework for building analytical web applications. No JavaScript required.

Plotly - Low-Code Data Apps

Turtle - New kind of anonymous messaging app

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