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PyGWalker VS D3.js

Compare PyGWalker VS D3.js and see what are their differences

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PyGWalker logo PyGWalker

PyGWalker: Turn your pandas dataframe into a Tableau-style User Interface for visual analysis - GitHub - Kanaries/pygwalker: PyGWalker: Turn your pandas dataframe into a Tableau-style User Interfac...

D3.js logo 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.
  • PyGWalker Landing page
    Landing page //
    2023-09-01
  • D3.js Landing page
    Landing page //
    2023-07-11

D3 allows you to bind arbitrary data to a Document Object Model (DOM), and then apply data-driven transformations to the document. For example, you can use D3 to generate an HTML table from an array of numbers. Or, use the same data to create an interactive SVG bar chart with smooth transitions and interaction.

D3 is not a monolithic framework that seeks to provide every conceivable feature. Instead, D3 solves the crux of the problem: efficient manipulation of documents based on data. This avoids proprietary representation and affords extraordinary flexibility, exposing the full capabilities of web standards such as HTML, SVG, and CSS. With minimal overhead, D3 is extremely fast, supporting large datasets and dynamic behaviors for interaction and animation. D3’s functional style allows code reuse through a diverse collection of official and community-developed modules.

PyGWalker features and specs

No features have been listed yet.

D3.js features and specs

  • Powerful Visualization
    D3.js allows for the creation of highly customized and interactive data visualizations, harnessing the full power of web standards like SVG, Canvas, and HTML.
  • Data Binding
    It offers robust support for data-driven transformations and binding, enabling intuitive connections between data sets and DOM elements.
  • Community and Ecosystem
    A large and active community contributes to tutorials, plugins, and tools, which can significantly simplify the development process.
  • Flexibility
    D3.js is highly flexible, providing low-level manipulation capabilities without being tied to any specific chart types or patterns.
  • Performance
    It is highly optimized for performance, allowing for efficient rendering of complex visualizations even with large data sets.

Possible disadvantages of D3.js

  • Steep Learning Curve
    D3.js has a steep learning curve due to its low-level nature and requires a solid understanding of JavaScript, DOM manipulation, and data concepts.
  • Complexity
    Creating complex visualizations can be time-consuming and require a significant amount of custom code, making it less approachable for quick, simple tasks.
  • Browser Compatibility
    Although widely supported, some D3.js features may have inconsistent behavior across different browsers, requiring additional testing and debugging.
  • Documentation
    While extensive, D3.js documentation can be challenging for beginners to navigate and understand, causing misunderstandings and slower development times.
  • Dependency Management
    The library itself is modular, but managing dependencies and integrating D3.js with other JavaScript frameworks or libraries can sometimes be problematic.

Analysis of D3.js

Overall verdict

  • Yes, D3.js is a highly regarded library for data visualization in the web development community.

Why this product is good

  • Flexibility: D3.js provides incredible flexibility in creating complex and interactive visualizations with web standards (SVG, HTML, and CSS).
  • Customization: It allows for high levels of customization, which lets developers create unique and detailed visualizations tailored to their specific needs.
  • Community and Ecosystem: D3.js has a large, active community and a rich ecosystem of plugins and extensions conducive to learning and integration.
  • Data Binding: Offers powerful ways to manipulate documents based on data; the data-driven approach simplifies dynamic interaction creation.
  • Performance: Efficiently manipulates DOM elements and performs well with large datasets if used correctly.

Recommended for

  • Data Scientists and Analysts looking to create custom, interactive visualizations.
  • Web Developers who need to incorporate complex data visualizations into applications.
  • Educators and Researchers presenting data in an engaging way.
  • Anyone needing to build bespoke visualizations that are not possible with off-the-shelf solutions.

PyGWalker videos

+ Add

PyGWalker for Exploratory Data Analysis In Jupyter Notebooks

More videos:

  • Tutorial - A Tableau Alternative in Python for Data Analysis (in Streamlit & Jupyter) | PyGWalker Tutorial
  • Review - Kanaries/pygwalker - Gource visualisation

D3.js videos

+ Add

Data Visualization with D3.js - Full Tutorial Course

More videos:

  • Review - Let's learn D3.js - D3 for data visualization (full course)

Category Popularity

0-100% (relative to PyGWalker and D3.js)

PyGWalker

D3.js

Data Visualization
5 5%
Data Visualization
95% 95
Business Intelligence
100 100%
Business Intelligence
0% 0
Charting Libraries
0 0%
Charting Libraries
100% 100
Data Dashboard
5 5%
Data Dashboard
95% 95

User comments

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Reviews

These are some of the external sources and on-site user reviews we've used to compare PyGWalker and D3.js

PyGWalker Reviews

We have no reviews of PyGWalker yet.
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D3.js Reviews

6 JavaScript Charting Libraries for Powerful Data Visualizations in 2023
Depending on your requirements, the best JavaScript library is D3.js, as it’s by far the most customizable. However, it’s also really complex and difficult to master. Plus, it’s not as compatible with TypeScript as it is with JavaScript, which can be off-putting for some developers. If you’d prefer a less complex library that you can use with TypeScript, ECharts, and...
Source: embeddable.com
15 JavaScript Libraries for Creating Beautiful Charts
When we think of charting today, D3.js is the first name that comes up. Being an open source project, D3.js definitely brings many powerful features that were missing in most of the existing libraries. Features like dynamic properties, Enter and Exit, powerful transitions, and syntax familiarity with jQuery make it one the best JavaScript libraries for charting. Charts in...
Source: www.sitepoint.com
Top 20 Javascript Libraries
D3 stands for Data-Driven Documents. With D3, you can apply data-driven transformations to DOM objects. The keyword with D3 is ‘data-driven,’ which means documents are manipulated depending on the data received. Data can be received in any format and bound with DOM objects. D3 is very fast and supports dynamic behavior for animation and interactions. There are plenty of...
Source: hackr.io
20+ JavaScript libraries to draw your own diagrams (2022 edition)
D3.js is a JavaScript library for manipulating documents based on data. Right now, I would say is the most popular library of its kind.
Source: modeling-languages.com
15 data science tools to consider using in 2021
Another open source tool, D3.js is a JavaScript library for creating custom data visualizations in a web browser. Commonly known as D3, which stands for Data-Driven Documents, it uses web standards, such as HTML, Scalable Vector Graphics and CSS, instead of its own graphical vocabulary. D3's developers describe it as a dynamic and flexible tool that requires a minimum amount...
Source: searchbusinessanalytics.techtarget.com

Social recommendations and mentions

Based on our record, D3.js seems to be a lot more popular than PyGWalker. While we know about 167 links to D3.js, we've tracked only 1 mention of PyGWalker. 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.

PyGWalker mentions (1)

  • Top 10 growing data visualization libraries in Python in 2023
    In 2023, Python's data visualization landscape is rich and varied, with PyGWalker leading the charge towards intuitive, interactive exploration tools. While traditional powerhouses like Matplotlib remain relevant, there's a notable shift towards web-ready and interactive visualizations, as seen with Plotly and Bokeh. The diversity in this top 10 list indicates that the ideal library hinges on project specifics and... - Source: dev.to / almost 2 years ago

D3.js mentions (167)

  • IO Devices and Latency
    Do you mean something for data visualization, or tricks condensing large data sets with cursors? https://d3js.org/ Best of luck =3. - Source: Hacker News / 7 months ago
  • 2024 Nuxt3 Annual Ecosystem Summary🚀
    Document address: D3.js Official Document. - Source: dev.to / 9 months ago
  • 100+ Must-Have Web Development Resources
    D3.js: One of the most popular JavaScript visualization libraries. - Source: dev.to / 12 months ago
  • What are npm Peer Dependencies and how to use them?
    A Dependency is an npm package that our code depends on in order to be able to run. Some popular packages that can be added as dependencies are lodash, D3, and chartjs. - Source: dev.to / 12 months ago
  • Introducing RacingBars 📊
    RacingBars is an open-source, light-weight (~45kb gzipped), easy-to-use, and feature-rich javascript library for bar chart race, based on D3.js. - Source: dev.to / about 1 year ago
View more

What are some alternatives?

When comparing PyGWalker and D3.js, you can also consider the following products

Microsoft Power BI - BI visualization and reporting for desktop, web or mobile

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

Tableau - Tableau can help anyone see and understand their data. Connect to almost any database, drag and drop to create visualizations, and share with a click.

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

Superset - Superset is a platform that enables colleges to automate campus placements end-to-end, helps employers hire young talent from across colleges in the country, and empowers students to access opportunities democratically.

Plotly - Low-Code Data Apps

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