Software Alternatives, Accelerators & Startups

Pie Chart Maker VS Matplotlib

Compare Pie Chart Maker VS Matplotlib and see what are their differences

Pie Chart Maker logo Pie Chart Maker

Craft stunning, customizable pie charts in a snap! - PieChartMaker

Matplotlib logo Matplotlib

matplotlib is a python 2D plotting library which produces publication quality figures in a variety...
  • Pie Chart Maker Home Screen
    Home Screen //
    2025-03-16
  • Pie Chart Maker Donut Pie Chart Maker
    Donut Pie Chart Maker //
    2025-03-16
  • Pie Chart Maker Polar Area Chart Maker
    Polar Area Chart Maker //
    2025-03-16
  • Pie Chart Maker Ring Chart Maker
    Ring Chart Maker //
    2025-03-16

๐ŸŽฏ What Sets PieChartMaker.com Apart? ๐ŸŽจ๐Ÿฅง

๐Ÿš€ Diverse Chart Selection: From classic pies to donuts, rings, and polar areas! ๐Ÿฅฏ๐ŸŽฏ โšก Real-Time Previews: See changes instantly as you tweak your data. ๐Ÿ–Œ๏ธ๐Ÿ‘€ ๐Ÿ“‚ CSV Uploads: Effortlessly import large datasets. ๐Ÿ“Š๐Ÿ“ ๐ŸŽจ Advanced Customization: Adjust colors, fonts, and themes with ease. ๐ŸŒˆโœ๏ธ ๐Ÿ“ค High-Quality Exports: Download in PNG, JPG, or SVG formats. ๐Ÿ–ผ๏ธโฌ‡๏ธ ๐ŸŒ Cross-Device Accessibility: Works seamlessly on desktop, tablet, and mobile. ๐Ÿ“ฑ๐Ÿ’ป

๐ŸŒŸ Your data, your style, your perfect pie chart! ๐Ÿฅงโœจ

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

Pie Chart Maker

$ Details
free
Release Date
2024 December
Startup details
Country
India
State
Maharashtra
City
Pune
Employees
1 - 9

Pie Chart Maker features and specs

  • Variety of Chart Types
    Beyond standard pie charts, it offers options like double, triple, quadruple, multi-series, semi-circular, half, circle, donut, doughnut, polar area, and ring charts, catering to diverse visualization needs.
  • Real-Time Previews
    As you input or modify data, the platform provides instant visual feedback, allowing for efficient adjustments.
  • CSV Data Uploads
    Users can upload CSV files directly, streamlining the process of importing large datasets.
  • Advanced Customization
    The tool allows customization of titles, labels, legends, colors, and fonts. Additionally, it offers theme options that adjust slice colors based on data values, such as gradient shifts or value-based color variations.
  • High-Quality Exports
    Completed charts can be downloaded in high-resolution PNG, JPG, or SVG formats, suitable for various applications.
  • Accessibility
    Being web-based, it operates seamlessly across devices like desktops, tablets, and smartphones, without the need for additional software installations.

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.

Pie Chart Maker videos

Pie Chart Maker by Grafi App Review

Matplotlib videos

Learn Matplotlib in 6 minutes | Matplotlib Python Tutorial

Category Popularity

0-100% (relative to Pie Chart Maker and Matplotlib)
Design Tools
100 100%
0% 0
Data Science And Machine Learning
Charts
100 100%
0% 0
Technical Computing
0 0%
100% 100

Questions & Answers

As answered by people managing Pie Chart Maker and Matplotlib.

What makes your product unique?

Pie Chart Maker's answer

Completely FREE! Support for THEMES so that you can create the Pie Chart that matches your existing Content. Apart from JPG, PNG and SVG you can download in multiple aspect rations and sizes.

Why should a person choose your product over its competitors?

Pie Chart Maker's answer

ONE CLICK change from One Pie Chart type to another (Pie, Half Pie, Donut, Ring, Polar Area, etc.). Multiple Pie Chart Sub-Types to chose from. Ability to embedd LIVE interactive charts into your Websites. No longer you need to put in Static Images.

How would you describe the primary audience of your product?

Pie Chart Maker's answer

Students to Enthusiasts to Professionals across domains! Ideal tool for everyone.

Which are the primary technologies used for building your product?

Pie Chart Maker's answer

Microsoft Stack - C#, ASP.NET, CSS, JavaScript

User comments

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Reviews

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

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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.

Pie Chart Maker mentions (0)

We have not tracked any mentions of Pie Chart Maker yet. Tracking of Pie Chart Maker recommendations started around Mar 2025.

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 / 4 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 / 7 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 / 8 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 / 9 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 / 10 months ago
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What are some alternatives?

When comparing Pie Chart Maker and Matplotlib, you can also consider the following products

PieChartMaker.me - Pie Chart Maker Free. Create a Pie Chart for free with easy to use tool and download the Pie Chart as jpg or png or svg file. Customize according to your choice.

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

PieChartGenerator.co - Create beautiful pie charts instantly with PieChartGenerator - free online pie chart maker. Customize colors, labels, legends, download as PNG/JPEG/SVG.

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

AECharts - Animated Chart Maker for Presentations and Videos. Export Charts as mp4 Videos in Seconds.

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