NVD3 vs Bokeh

Struggling to choose between NVD3 and Bokeh? Both products offer unique advantages, making it a tough decision.

NVD3 is a Development solution with tags like javascript, d3js, charts, data-visualization.

It boasts features such as Reusable chart components, Support for common chart types like line, bar, pie, scatter, etc, Animated transitions and interactions, Responsive and customizable, Built on top of D3.js and pros including Open source and free to use, Large set of features and chart types, Good documentation and examples, Active development and support, Integration with AngularJS.

On the other hand, Bokeh is a Development product tagged with python, data-visualization, interactive, graphics, web-browser.

Its standout features include Interactive data visualization, Supports streaming data, Python library, Targets modern web browsers, Elegant and concise graphics, High-performance interactivity, Can handle large datasets, and it shines with pros like Very flexible and customizable visualizations, Integrates well with other Python data tools like NumPy and Pandas, Open source and free, Good performance even with large datasets, Nice web-based interface for sharing visualizations.

To help you make an informed decision, we've compiled a comprehensive comparison of these two products, delving into their features, pros, cons, pricing, and more. Get ready to explore the nuances that set them apart and determine which one is the perfect fit for your requirements.

NVD3

NVD3

NVD3 is a JavaScript charting library for building interactive visualizations using D3.js. It provides pre-built chart components and is optimized for rapid data visualization.

Categories:
Development Data Visualization
javascript d3js charts data-visualization

NVD3 Features

  1. Reusable chart components
  2. Support for common chart types like line, bar, pie, scatter, etc
  3. Animated transitions and interactions
  4. Responsive and customizable
  5. Built on top of D3.js

Pricing

  • Open Source

Pros

Open source and free to use

Large set of features and chart types

Good documentation and examples

Active development and support

Integration with AngularJS

Cons

Steep learning curve due to dependency on D3.js

Configuring charts requires knowledge of D3

Not as feature rich as some commercial libraries

Limited customization compared to building from scratch with D3

Bokeh

Bokeh

Bokeh is an interactive data visualization library for Python that targets modern web browsers for presentation. It offers elegant, concise construction of versatile graphics, and affords high-performance interactivity over large or streaming datasets.

Categories:
Development Data Visualization
python data-visualization interactive graphics web-browser

Bokeh Features

  1. Interactive data visualization
  2. Supports streaming data
  3. Python library
  4. Targets modern web browsers
  5. Elegant and concise graphics
  6. High-performance interactivity
  7. Can handle large datasets

Pricing

  • Open Source

Pros

Very flexible and customizable visualizations

Integrates well with other Python data tools like NumPy and Pandas

Open source and free

Good performance even with large datasets

Nice web-based interface for sharing visualizations

Cons

Steeper learning curve than some visualization libraries

Visualizations can be more complex to build

Limited built-in statistical analysis features

Requires knowledge of Python and web development

Not as simple as drag-and-drop visualization builders