Matplotlib vs Victory | What are the differences? | StackShare

Matplotlib vs Victory

Overview

Matplotlib

Stacks1.3K

Followers336

Votes11

Victory

Stacks35

Followers83

Votes0

GitHub Stars11.2K

Forks537

Matplotlib vs Victory: What are the differences?

Matplotlib: A plotting library for the Python programming language. 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; Victory: ReactJS library for building interactive data visualizations. A collection of composable React components for building interactive data visualizations.

Matplotlib and Victory can be primarily classified as "Charting Libraries" tools.

Victory is an open source tool with 7.33K GitHub stars and 311 GitHub forks. Here's a link to Victory's open source repository on GitHub.

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Detailed Comparison

Matplotlib	Victory
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.	A collection of composable React components for building interactive data visualizations.
-	Robust; Flexible; Native
Statistics
GitHub Stars -	GitHub Stars 11.2K
GitHub Forks -	GitHub Forks 537
Stacks 1.3K	Stacks 35
Followers 336	Followers 83
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

What are some alternatives to Matplotlib, Victory?

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.