Plotly vs Victory

Overview

Plotly.js

Stacks399

Followers694

Votes69

GitHub Stars17.9K

Forks1.9K

Victory

Stacks44

Followers83

Votes0

GitHub Stars11.2K

Forks537

Plotly vs Victory: What are the differences?

Customization Abilities: Plotly offers extensive customization options with the ability to create highly interactive and visually appealing plots. Users can easily tweak every aspect of the plot including colors, fonts, and styles using built-in tools. On the other hand, Victory provides a more streamlined customization experience with a focus on simplicity and ease of use, offering a limited set of customizable features compared to Plotly.
Chart Types: Plotly supports a wide range of chart types including scatter plots, line charts, bar charts, and more with intricate control over each element of the chart. Victory, on the other hand, has a smaller selection of chart types but excels in creating complex and dynamic data visualizations such as shared axes, grouped bars, and more intricate layouts that are not easily achievable in Plotly.
Community Support: Plotly has a large and active community of users and contributors providing extensive documentation, tutorials, and support forums to help users navigate and leverage the full potential of the library. In contrast, Victory has a smaller community base with fewer resources available for troubleshooting and assistance, making it slightly more challenging for users to find solutions to their queries.
Ease of Use: Plotly is known for its user-friendly interface and intuitive design, making it easy for beginners to create stunning visualizations without extensive programming knowledge. Victory, although user-friendly, may require a more intermediate level of understanding due to its unique approach to data visualization and some advanced concepts that might not be immediately graspable for novices.
Rendering Performance: Plotly is optimized for fast rendering speeds and can handle large datasets efficiently, making it suitable for applications requiring real-time updating and data streaming. Victory, while capable of handling moderate data sizes, may experience performance issues when dealing with extremely large datasets or complex visualizations due to its architecture and rendering mechanisms.
Integration Capabilities: Plotly seamlessly integrates with various programming languages and tools including Python, R, and JavaScript, enabling cross-platform compatibility and versatility in data visualization. On the other hand, Victory is primarily designed for React applications, limiting its integration options and versatility for users working with different frameworks or languages.

In Summary, Plotly offers extensive customization abilities, a diverse range of chart types, strong community support, ease of use, efficient rendering performance, and broad integration capabilities compared to Victory, which focuses on streamlined customization, unique and complex chart types, limited community support, intermediate level ease of use, potential rendering performance limitations, and compatibility primarily with React applications.

Share your Stack

Help developers discover the tools you use. Get visibility for your team's tech choices and contribute to the community's knowledge.

View Docs

CLI (Node.js)

Manual

Advice on Plotly.js, Victory

Steve

Lead Software Tools Engineer at Leonardo UK

Oct 30, 2020

Review

I would specifically recommend basing your application on Pandas which will handle the vast majority of the work for you. You will be amazed at what you will be able to get done with only a few lines of code.

Pandas can load the data from either Excel xslx files or csv files (and a lot of other places)

If you structure your code well you can have a cross platform command line program, a GUI desktop program, a Jupyter Notebook and a web service all with the vast majority of the code in common.

A jupyter notebook is a great place to start developing your code and may be all that you need.

Some plug-ins & resources that can help:

pandas-summary (for a rapid overview of the data): https://github.com/mouradmourafiq/pandas-summary
pandasgui (for exploring what you would like to do): https://github.com/adamerose/pandasgui
Pandas-Bokeh (plotting): https://github.com/PatrikHlobil/Pandas-Bokeh
plot.ly (plotting): https://plotly.com/python/pandas-backend/
wxPython (for a desktop GUI): https://wxpython.org/

8.81k views8.81k

Comments

Detailed Comparison

Plotly.js	Victory
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.	A collection of composable React components for building interactive data visualizations.
Feature parity with MATLAB/matplotlib graphing; Online chart editor; Fully interactive (hover, zoom, pan); SVG and WebGL backends; Publication-quality image export	Robust; Flexible; Native
Statistics
GitHub Stars 17.9K	GitHub Stars 11.2K
GitHub Forks 1.9K	GitHub Forks 537
Stacks 399	Stacks 44
Followers 694	Followers 83
Votes 69	Votes 0
Pros & Cons
Pros 16 Bindings to popular languages like Python, Node, R, etc 10 Integrated zoom and filter-out tools in charts and maps 9 Great support for complex and multiple axes 8 Powerful out-of-the-box featureset 6 Beautiful visualizations Cons 18 Terrible document	No community feedback yet
Integrations
Python React MATLAB Jupyter Julia	React

What are some alternatives to Plotly.js, 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.

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.

ApexCharts

A modern JavaScript charting library to build interactive charts and visualizations with simple API.

Related Comparisons

Plotly vs Victory: What are the differences?

Customization Abilities: Plotly offers extensive customization options with the ability to create highly interactive and visually appealing plots. Users can easily tweak every aspect of the plot including colors, fonts, and styles using built-in tools. On the other hand, Victory provides a more streamlined customization experience with a focus on simplicity and ease of use, offering a limited set of customizable features compared to Plotly.
Chart Types: Plotly supports a wide range of chart types including scatter plots, line charts, bar charts, and more with intricate control over each element of the chart. Victory, on the other hand, has a smaller selection of chart types but excels in creating complex and dynamic data visualizations such as shared axes, grouped bars, and more intricate layouts that are not easily achievable in Plotly.
Community Support: Plotly has a large and active community of users and contributors providing extensive documentation, tutorials, and support forums to help users navigate and leverage the full potential of the library. In contrast, Victory has a smaller community base with fewer resources available for troubleshooting and assistance, making it slightly more challenging for users to find solutions to their queries.
Ease of Use: Plotly is known for its user-friendly interface and intuitive design, making it easy for beginners to create stunning visualizations without extensive programming knowledge. Victory, although user-friendly, may require a more intermediate level of understanding due to its unique approach to data visualization and some advanced concepts that might not be immediately graspable for novices.
Rendering Performance: Plotly is optimized for fast rendering speeds and can handle large datasets efficiently, making it suitable for applications requiring real-time updating and data streaming. Victory, while capable of handling moderate data sizes, may experience performance issues when dealing with extremely large datasets or complex visualizations due to its architecture and rendering mechanisms.
Integration Capabilities: Plotly seamlessly integrates with various programming languages and tools including Python, R, and JavaScript, enabling cross-platform compatibility and versatility in data visualization. On the other hand, Victory is primarily designed for React applications, limiting its integration options and versatility for users working with different frameworks or languages.

Plotly vs Victory

Overview