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D3.js vs NVD3: What are the differences?
- Integration with D3.js library: One key difference between D3.js and NVD3 is that NVD3 is built on top of the D3.js library. NVD3 simplifies the process of creating charts and graphs by providing ready-to-use chart components, whereas D3.js is more flexible and allows for more customization but requires more coding from scratch.
- Ease of Use: NVD3 is known for its ease of use and requires less coding compared to D3.js. It provides a higher level of abstraction and simplifies the creation of complex visualizations, making it ideal for developers who want to create interactive charts quickly without delving into the complexities of D3.js.
- Chart Types: While D3.js offers a wide range of chart types and customization options, NVD3 offers a more limited selection of pre-built chart types. D3.js allows for complete control over the appearance and behavior of charts, whereas NVD3 focuses on providing a curated set of commonly used chart types such as line charts, bar charts, and pie charts.
- Community Support: D3.js has a larger and more active community compared to NVD3, which means there are more resources, tutorials, and examples available for D3.js. This can be beneficial for developers looking to troubleshoot issues, learn new techniques, or collaborate with other developers.
- Learning Curve: D3.js has a steeper learning curve compared to NVD3 due to its lower level of abstraction and greater flexibility. Developers may need to invest more time in learning D3.js and understanding its concepts in order to create custom visualizations, whereas NVD3 offers a more straightforward approach that is easier to grasp for beginners.
- Customization Options: D3.js provides more extensive customization options for creating unique and highly customized visualizations, whereas NVD3 simplifies the customization process by offering predefined styles and configurations for its chart components.
In Summary, the key differences between D3.js and NVD3 lie in their level of customization, ease of use, available chart types, community support, learning curve, and integration with the D3.js library.
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Learn MorePros of D3.js
Pros of NVD3
Pros of D3.js
- Beautiful visualizations195
- Svg103
- Data-driven92
- Large set of examples81
- Data-driven documents61
- Visualization components24
- Transitions20
- Dynamic properties18
- Plugins16
- Transformation11
- Makes data interactive7
- Open Source4
- Enter and Exit4
- Components4
- Exhaustive3
- Backed by the new york times3
- Easy and beautiful2
- Highly customizable1
- Awesome Community Support1
- Simple elegance1
- Templates, force template1
- Angular 41
Pros of NVD3
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Cons of D3.js
Cons of NVD3
Cons of D3.js
- Beginners cant understand at all11
- Complex syntax6
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What is D3.js?
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.
What is NVD3?
This project is an attempt to build re-usable charts and chart components for d3.js without taking away the power that d3.js gives you. This is a very young collection of components, with the goal of keeping these components very customizable, staying away from your standard cookie cutter solutions.
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What companies use D3.js?
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What tools integrate with D3.js?
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What are some alternatives to D3.js and NVD3?
three.js
It is a cross-browser JavaScript library and Application Programming Interface used to create and display animated 3D computer graphics in a web browser.
Plotly.js
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.
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.
Python
Python is a general purpose programming language created by Guido Van Rossum. Python is most praised for its elegant syntax and readable code, if you are just beginning your programming career python suits you best.
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.