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  1. Stackups
  2. Business Tools
  3. UI Components
  4. Charting Libraries
  5. Frappé Charts vs Matplotlib

Frappé Charts vs Matplotlib

OverviewComparisonAlternatives

Overview

Matplotlib
Matplotlib
Stacks1.6K
Followers336
Votes11
Frappé Charts
Frappé Charts
Stacks7
Followers16
Votes2
GitHub Stars15.1K
Forks751

Frappé Charts vs Matplotlib: What are the differences?

### Introduction
Frappé Charts and Matplotlib are both popular libraries for data visualization in Python. While Matplotlib is a versatile and powerful library, Frappé Charts offers interactive and dynamic visualizations for web applications.

1. **Ease of Use**: Frappé Charts provide a more user-friendly approach to creating interactive visualizations for web applications, making it easier for developers to implement dynamic charts without extensive customization compared to Matplotlib.
2. **Interactive Features**: Frappé Charts come with built-in interactive features such as tooltips, zooming, and panning capabilities, which allow users to explore data more effectively compared to Matplotlib, which may require additional customization for similar interactive functionalities.
3. **Web Compatibility**: Frappé Charts are specifically designed for web applications, providing seamless integration and compatibility with HTML, CSS, and JavaScript, whereas Matplotlib's primary focus is on static images and print publications, requiring more effort for web deployment.
4. **Real-time Data Updates**: Frappé Charts have the ability to handle real-time data updates and live charts out of the box, making it suitable for applications that require frequent data updates, a feature that Matplotlib may lack without additional customization.
5. **Animation Support**: Frappé Charts offer animation support for chart elements, allowing for visually appealing and dynamic data representations, whereas Matplotlib may require additional scripting for similar animation effects.
6. **Customization Options**: While both libraries offer customization options, Matplotlib provides more fine-grained control over chart aesthetics, allowing users to create highly tailored visualizations compared to Frappé Charts, where customization options may be more limited.

In Summary, Frappé Charts excel in providing user-friendly, interactive, and web-compatible visualizations, whereas Matplotlib offers extensive customization and versatile charting capabilities.

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Detailed Comparison

Matplotlib
Matplotlib
Frappé Charts
Frappé Charts

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.

📊🍩📈 Simple, responsive, modern SVG Charts with zero dependencies

Statistics
GitHub Stars
-
GitHub Stars
15.1K
GitHub Forks
-
GitHub Forks
751
Stacks
1.6K
Stacks
7
Followers
336
Followers
16
Votes
11
Votes
2
Pros & Cons
Pros
  • 11
    The standard Swiss Army Knife of plotting
Cons
  • 5
    Lots of code
Pros
  • 1
    Small bundlesize
  • 1
    SVG based

What are some alternatives to Matplotlib, Frappé Charts?

D3.js

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

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

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

Chart.js

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

Recharts

Recharts

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

ECharts

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

ZingChart

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

amCharts

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

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

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.

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