Software Alternatives, Accelerators & Startups

DataSource.ai VS D3.js

Compare DataSource.ai VS D3.js and see what are their differences

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DataSource.ai logo DataSource.ai

Community-funded data science tournaments

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.
  • DataSource.ai Landing page
    Landing page //
    2023-08-26
  • 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.

DataSource.ai features and specs

  • Wide Range of Competitions
    DataSource.ai offers a variety of data science tournaments, providing opportunities for users to engage with diverse datasets and problems, thereby enhancing their learning and skill development across different domains.
  • Community Engagement
    The platform fosters a community of data enthusiasts and professionals where members can collaborate, share solutions, and learn from each other, promoting a sense of camaraderie and collective growth.
  • Skill Development
    Participants can improve their data science skills by working on real-world problems with community feedback and access to a repository of past solutions to learn from.
  • Career Opportunities
    By participating in these competitions, users can improve their visibility in the data science community, which might lead to potential job offers and networking opportunities with industry professionals.

Possible disadvantages of DataSource.ai

  • Highly Competitive Environment
    The competitive nature of data science tournaments might be intimidating for beginners, potentially discouraging them from participating or fully engaging with the challenges.
  • Limited Support for Beginners
    While the community is active, the platform might lack structured resources or mentoring programs specifically aimed at helping newcomers start and progress effectively in data science competitions.
  • Time-Consuming
    Participating in data science tournaments can be time-intensive, which might be challenging for individuals who have to balance other professional or personal commitments.
  • Quality Variance in Datasets
    Not all datasets and competitions might have the same level of quality or relevance, which can be a constraint for participants seeking specific learning outcomes or industry-aligned challenges.

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.

DataSource.ai videos

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D3.js videos

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 DataSource.ai and D3.js)
Development
100 100%
0% 0
Charting Libraries
0 0%
100% 100
Education & Reference
100 100%
0% 0
Data Visualization
0 0%
100% 100

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Reviews

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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...
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.
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...

Social recommendations and mentions

Based on our record, D3.js seems to be more popular. It has been mentiond 167 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.

DataSource.ai mentions (0)

We have not tracked any mentions of DataSource.ai yet. Tracking of DataSource.ai recommendations started around May 2021.

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 / 3 months ago
  • 2024 Nuxt3 Annual Ecosystem Summary🚀
    Document address: D3.js Official Document. - Source: dev.to / 6 months ago
  • 100+ Must-Have Web Development Resources
    D3.js: One of the most popular JavaScript visualization libraries. - Source: dev.to / 8 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 / 8 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 / 10 months ago
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What are some alternatives?

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

Colaboratory - Free Jupyter notebook environment in the cloud.

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

Crowd AnalytiX - Crowd AnalytiX is a data science community and a perfect solution for businesses that want to take advantage of AI but don’t have the in-house expertise or resources.

Plotly - Low-Code Data Apps

Kaggle - Kaggle offers innovative business results and solutions to companies.

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