Matplotlib vs React D3 Library

Overview

Matplotlib

Stacks1.6K

Followers336

Votes11

React D3 Library

Stacks28

Followers115

Votes0

GitHub Stars1.5K

Forks82

Matplotlib vs React D3 Library: What are the differences?

Matplotlib and React D3 Library are both tools used for data visualization, but they have some key differences in terms of their functionality and usage.

Ease of Use: Matplotlib is a Python library that provides a MATLAB-like interface, making it easier to create basic visualizations quickly. React D3 Library, on the other hand, is a JavaScript library that requires knowledge of both React and D3.js, making it more complex to set up and use.
Interactivity: Matplotlib allows for basic interactivity by providing tools like zooming and panning, but it lacks full interactivity for complex visualizations. React D3 Library, on the other hand, provides extensive interactive features through the use of D3.js, such as tooltips, brushing, and zooming, allowing for more dynamic and engaging visualizations.
Performance: Matplotlib is a server-side library that generates static images, which can limit its performance when dealing with large datasets or real-time updates. React D3 Library, being client-side, leverages the power of modern web browsers and can handle large datasets and real-time updates more efficiently.
Customizability: Matplotlib provides a wide range of customization options through its extensive API, allowing users to fine-tune every aspect of their visualizations. React D3 Library, being built on top of D3.js, provides even more flexibility and customization options, as D3.js is a powerful and versatile library for creating data-driven visualizations.
Integration with other libraries: Matplotlib is widely used in the Python data science ecosystem and integrates seamlessly with other libraries like Pandas and NumPy. React D3 Library, being a JavaScript library, can be easily integrated with other JavaScript libraries and frameworks like React and Redux.
Browser Compatibility: Matplotlib generates images using the backend specified in the Python environment, which may limit the compatibility with different web browsers. React D3 Library, being based on JavaScript and leveraging web standards, ensures compatibility across different browsers.

In Summary, Matplotlib provides an easy-to-use interface for basic visualizations in Python, while React D3 Library offers more flexibility and interactivity, making it suitable for complex and dynamic visualizations in web applications.

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CLI (Node.js)

Manual

Detailed Comparison

Matplotlib	React D3 Library
It is a Python 2D plotting library which produces publication quality figures in a variety of hardcopy formats and interactive environments across platforms. It can be used in Python scripts, the Python and IPython shells, the Jupyter notebook, web application servers, and four graphical user interface toolkits.	An open source library that will allow developers the ability to reroute D3 output to React’s virtual DOM. Just use your existing D3 code, and with a few simples lines, you can now harness the power of React with the flexibility of D3!
Statistics
GitHub Stars -	GitHub Stars 1.5K
GitHub Forks -	GitHub Forks 82
Stacks 1.6K	Stacks 28
Followers 336	Followers 115
Votes 11	Votes 0
Pros & Cons
Pros 11 The standard Swiss Army Knife of plotting Cons 5 Lots of code	No community feedback yet
Integrations
No integrations available	React D3.js

What are some alternatives to Matplotlib, React D3 Library?

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.

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.

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.

Chart.js

Visualize your data in 6 different ways. Each of them animated, with a load of customisation options and interactivity extensions.

Recharts

Quickly build your charts with decoupled, reusable React components. Built on top of SVG elements with a lightweight dependency on D3 submodules.

ECharts

It is an open source visualization library implemented in JavaScript, runs smoothly on PCs and mobile devices, and is compatible with most current browsers.

ZingChart

The most feature-rich, fully customizable JavaScript charting library available used by start-ups and the Fortune 100 alike.

amCharts

amCharts is an advanced charting library that will suit any data visualization need. Our charting solution include Column, Bar, Line, Area, Step, Step without risers, Smoothed line, Candlestick, OHLC, Pie/Donut, Radar/ Polar, XY/Scatter/Bubble, Bullet, Funnel/Pyramid charts as well as Gauges.

CanvasJS

Lightweight, Beautiful & Responsive Charts that make your dashboards fly even with millions of data points! Self-Hosted, Secure & Scalable charts that render across devices.

AnyChart

AnyChart is a flexible JavaScript (HTML5) based solution that allows you to create interactive and great looking charts. It is a cross-browser and cross-platform charting solution intended for everybody who deals with creation of dashboard, reporting, analytics, statistical, financial or any other data visualization solutions.

Related Comparisons

Matplotlib vs React D3 Library: What are the differences?

Matplotlib and React D3 Library are both tools used for data visualization, but they have some key differences in terms of their functionality and usage.

Ease of Use: Matplotlib is a Python library that provides a MATLAB-like interface, making it easier to create basic visualizations quickly. React D3 Library, on the other hand, is a JavaScript library that requires knowledge of both React and D3.js, making it more complex to set up and use.
Interactivity: Matplotlib allows for basic interactivity by providing tools like zooming and panning, but it lacks full interactivity for complex visualizations. React D3 Library, on the other hand, provides extensive interactive features through the use of D3.js, such as tooltips, brushing, and zooming, allowing for more dynamic and engaging visualizations.
Performance: Matplotlib is a server-side library that generates static images, which can limit its performance when dealing with large datasets or real-time updates. React D3 Library, being client-side, leverages the power of modern web browsers and can handle large datasets and real-time updates more efficiently.
Customizability: Matplotlib provides a wide range of customization options through its extensive API, allowing users to fine-tune every aspect of their visualizations. React D3 Library, being built on top of D3.js, provides even more flexibility and customization options, as D3.js is a powerful and versatile library for creating data-driven visualizations.
Integration with other libraries: Matplotlib is widely used in the Python data science ecosystem and integrates seamlessly with other libraries like Pandas and NumPy. React D3 Library, being a JavaScript library, can be easily integrated with other JavaScript libraries and frameworks like React and Redux.
Browser Compatibility: Matplotlib generates images using the backend specified in the Python environment, which may limit the compatibility with different web browsers. React D3 Library, being based on JavaScript and leveraging web standards, ensures compatibility across different browsers.

Matplotlib vs React D3 Library

Overview