Software Alternatives, Accelerators & Startups

AnyChart VS Matplotlib

Compare AnyChart VS Matplotlib and see what are their differences

AnyChart logo AnyChart

Award-winning JavaScript charting library & Qlik Sense extensions from a global leader in data visualization! Loved by thousands of happy customers, including over 75% of Fortune 500 companies & over half of the top 1000 software vendors worldwide.

Matplotlib logo Matplotlib

matplotlib is a python 2D plotting library which produces publication quality figures in a variety...
  • AnyChart Home Page of AnyChart JS Charts
    Home Page of AnyChart JS Charts //
    2025-03-10

Founded in 2003, AnyChart is one of the global leaders in interactive data visualization, offering award-winning, flexible JavaScript (HTML5) charting libraries with numerous chart types and features, great API & documentation, and enterprise-grade support.

Cross-browser JS charts and graphs, maps, stock charts, and Gantt charts powered by AnyChart have helped thousands of companies including industry leaders โ€” from startups to corporate giants such as AT&T, Bosch, BP, Citi, ExxonMobil, Lockheed Martin, Merck, Novartis, Oracle, Reuters, Samsung, Tencent, UBS, Volkswagen, Yahoo, 3M & many others โ€” gain better insight, make right decisions, and improve their enterprise performance based on robust, insightful data visualization.

Whether you need to enhance your website with better reporting, embed dashboards into your on-premises and SaaS systems, or build an entirely new product, AnyChart covers all your data visualization needs. The company's products include massive out-of-the-box capabilities, combined with flexibility & simplicity.

Loved by thousands of happy customers, including more than 75% of Fortune 500 companies across all industries and over half of the top 1,000 software vendors worldwide.

In 2019, AnyChart launched a technology alliance partnership with Qlik, adding three new product extensions for Qlik Sense. The partnership enables the Qlik community to be provided with more than 30 new chart types and many valuable features natively in the Qlik environment.

  • Matplotlib Landing page
    Landing page //
    2023-06-14

AnyChart

$ Details
freemium $49.0 / One-off (Next Unicorn license for startups)
Platforms
JavaScript Web Qlik Windows Mac OSX Linux Android iOS TypeScript PHP Google Chrome Safari Opera Firefox Java iPhone Mobile Laravel ReactJS React Native Angular Python Node JS Cross Platform
Release Date
2003 May
Startup details
Country
United States
State
Florida
Founder(s)
Anton Baranchuk
Employees
10 - 19

AnyChart features and specs

  • Chart types
    70+ (bar, line, Gantt, candlestick, waterfall, sunburst...)
  • Data formats
    Multiple (JavaScript API, XML, JSON, CSV, HTML table, Google Sheets...)
  • Integrations
    Seamlessly runs with any language, framework, and database (multiple integration templates are available)
  • Docs
    The documentation and API reference are very detailed and everything is explained in detail in a simple and clear way, with numerous readymade chart samples
  • Browser support
    Supports all browsers, including IE6+ along with mobile browsers
  • Dependencies
    None
  • Product history
    AnyChart has been operating from 2003 and the team is very experienced with a long history of releasing high-quality products.
  • Open source
    The open source code is hosted on GitHub under different licenses depending on the library
  • Flexibility
    Extremely flexible and customizable Any part of a chart can be changed and customized.
  • Interactivity
    Events can be distributed to chart elements which respond to user actions. Event listeners are simple JavaScript functions which are very easy to use and understand

Matplotlib features and specs

  • Versatility
    Matplotlib can generate a wide variety of plots, ranging from simple line plots to complex 3D plots. This versatility makes it a go-to library for many scientific and technical visualizations.
  • Customization
    It offers extensive customization options for virtually every element of a plot, including colors, labels, line styles, and more, allowing users to tailor plots to meet specific needs.
  • Integrations
    Matplotlib integrates well with other Python libraries such as NumPy, Pandas, and SciPy, making it easier to plot data directly from these sources.
  • Community and Documentation
    It has a large, active community and comprehensive documentation that includes tutorials, examples, and detailed references, which can help users solve problems and improve their plot-making skills.
  • Interactivity
    Matplotlib supports interactive plots, which can be embedded in Jupyter notebooks and GUIs, allowing for dynamic data exploration and presentation.
  • Publication-Quality
    The library is capable of producing high-quality, publication-ready graphics that meet the stringent requirements of academic journals and professional presentations.

Possible disadvantages of Matplotlib

  • Complexity
    While Matplotlib offers extensive customization, it can be complex and sometimes unintuitive for beginners, requiring a steep learning curve to master all its functionality.
  • Performance
    Rendering a large number of plots or handling very large datasets can be slow, making Matplotlib less suitable for real-time data visualization.
  • Modern Aesthetics
    Out-of-the-box plots from Matplotlib can look somewhat dated compared to those from newer plotting libraries like Seaborn or Plotly, requiring additional customization to achieve a modern look.
  • 3D Plots
    Although Matplotlib supports 3D plotting, its capabilities are relatively limited and less sophisticated compared to specialized 3D plotting libraries.
  • Size and Structure
    The package is relatively large and can be slow to import. Its extensive structure can make finding specific functions and understanding the overall architecture challenging.

Analysis of Matplotlib

Overall verdict

  • Yes, Matplotlib is a good library for data visualization, particularly for users who require a versatile and powerful plotting solution in Python.

Why this product is good

  • Matplotlib is highly regarded due to its extensive customization options, versatility in creating a wide range of static, animated, and interactive plots, and its large user community and support. It integrates well with other scientific libraries in Python, making it a staple for data visualization. The library is also open-source and frequently updated, ensuring it remains a reliable choice for users.

Recommended for

  • Data scientists and analysts needing to create detailed, customized visual representations of their data.
  • Researchers and engineers looking for a comprehensive plotting library that supports scientific and engineering formats.
  • Python developers who require integration with other scientific computing libraries like NumPy and Pandas.

AnyChart videos

Heatmap Chart using AnyChart with Python

More videos:

  • Tutorial - Creating Interactive Charts with AnyChart library for Your Android App
  • Tutorial - How to Create a Gantt Chart in Qlik Sense using AnyGantt Extension by AnyChart

Matplotlib videos

Learn Matplotlib in 6 minutes | Matplotlib Python Tutorial

Category Popularity

0-100% (relative to AnyChart and Matplotlib)
Data Dashboard
72 72%
28% 28
Data Science And Machine Learning
Charting Libraries
100 100%
0% 0
Technical Computing
0 0%
100% 100

User comments

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Reviews

These are some of the external sources and on-site user reviews we've used to compare AnyChart and Matplotlib

AnyChart Reviews

  1. alairedeforest
    Fast, effective charts

    Probably the best JS chart library on the market right now.

    ๐Ÿ Competitors: CanvasJS
    ๐Ÿ‘ Pros:    Extremely simple|Fast|Affordable
    ๐Ÿ‘Ž Cons:    Not free

15 JavaScript Libraries for Creating Beautiful Charts
AnyChart is a lightweight and robust JavaScript charting library with charts designed to be embedded and integrated. AnyChart allows you to display 68 charts out-of-the-box and provides features to create your own chart types. You can save a chart as an image in PDF, PNG, JPG or SVG format.
Top 10 Visual Analytics Provider For 2021
AnyChart provides products for those who are slightly well-versed with HTML and JavaScript. Their products provide robust JavaScript charting libraries with APIs, documentation, and enterprise-grade support. Developers can integrate a variety of charts into their mobile, desktops, or web products. Their component is compatible with any database and runs on any platform....
Top 10 JavaScript Charting Libraries for Every Data Visualization Need
AnyChart is a robust, lightweight and feature-rich JS chart library with rendering in SVG/VML. It actually gives web developers a great opportunity to create any different charts that will help to make decisions based on what is seen.
Source: hackernoon.com

Matplotlib Reviews

25 Python Frameworks to Master
Matplotlib is a widely used tool for data visualization in Python. It provides an object-oriented API for embedding plots into applications.
Source: kinsta.com
5 Best Python Libraries For Data Visualization in 2023
You can use this library for multiple purposes such as generating plots, bar charts, histograms, power spectra, stemplots, pie charts, and more. The best thing about Matplotlib is you just have to write a few lines of code and it handles the rest by itself. Metaplotilib focuses on static images for publication along with interactive figures using toolkits like Qt and GTK.
15 data science tools to consider using in 2021
Matplotlib is an open source Python plotting library that's used to read, import and visualize data in analytics applications. Data scientists and other users can create static, animated and interactive data visualizations with Matplotlib, using it in Python scripts, the Python and IPython shells, Jupyter Notebook, web application servers and various GUI toolkits.
Top Python Libraries For Image Processing In 2021
Matplotlib is primarily used for 2D visualizations such as scatter plots, bar graphs, histograms, and many more, but we can also use it for image processing. It is effective to get information out of an image. It doesnโ€™t support all file formats.
Top 8 Python Libraries for Data Visualization
Matplotlib is a data visualization library and 2-D plotting library of Python It was initially released in 2003 and it is the most popular and widely-used plotting library in the Python community. It comes with an interactive environment across multiple platforms. Matplotlib can be used in Python scripts, the Python and IPython shells, the Jupyter notebook, web application...

Social recommendations and mentions

Based on our record, Matplotlib seems to be more popular. It has been mentiond 114 times since March 2021. We are tracking product recommendations and mentions on various public social media platforms and blogs. They can help you identify which product is more popular and what people think of it.

AnyChart mentions (0)

We have not tracked any mentions of AnyChart yet. Tracking of AnyChart recommendations started around Mar 2021.

Matplotlib mentions (114)

  • The soul file
    In February, an AI agent named MJ Rathbun submitted a pull request to matplotlib โ€” the Python plotting library used by half the scientific computing world. Scott Shambaugh, a volunteer maintainer, rejected it. Standard code review. Nothing unusual. - Source: dev.to / 5 months ago
  • How to Analyze CSV Files with Python and Pandas
    Numbers are useful, but sometimes itโ€™s easier to spot patterns when you can actually see your data. Pandas works seamlessly with Matplotlib, a popular Python library for creating visualizations. Together, they make it easy to turn raw numbers into clear charts. - Source: dev.to / 8 months ago
  • libmalloc, jemalloc, tcmalloc, mimalloc - Exploring Different Memory Allocators
    We are storing the results in JSON files, which we combine, analyze and visualize using matplotlib in Python. Here's the structure of a benchmark result file:. - Source: dev.to / 9 months ago
  • Building an AI Scoring Agent: Step-By-Step
    NetworkX and Matplotlib were used to visualize the graph structure of the agent. - Source: dev.to / 10 months ago
  • Top 5 GitHub Repositories for Data Science in 2026
    The book introduces the core libraries essential for working with data in Python: particularly IPython, NumPy, Pandas, Matplotlib, Scikit-Learn, and related packages Familiarity with Python as a language is assumed; if you need a quick introduction to the language itself, see the free companion project, Aโ€ฆ. - Source: dev.to / 11 months ago
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What are some alternatives?

When comparing AnyChart and Matplotlib, you can also consider the following products

Chart.js - Easy, object oriented client side graphs for designers and developers.

Pandas - Pandas is an open source library providing high-performance, easy-to-use data structures and data analysis tools for the Python.

Highcharts - A charting library written in pure JavaScript, offering an easy way of adding interactive charts to your web site or web application

NumPy - NumPy is the fundamental package for scientific computing with Python

D3.js - D3.js is a JavaScript library for manipulating documents based on data. D3 helps you bring data to life using HTML, SVG, and CSS.

Seaborn - Seaborn is a Python data visualization library that uses Matplotlib to make statistical graphics.