Software Alternatives, Accelerators & Startups

Maple VS Matplotlib

Compare Maple VS Matplotlib and see what are their differences

Maple logo Maple

Considered the leading mathematical software, Maple intertwines the world’s most advanced math engine with a user-friendly interface.

Matplotlib logo Matplotlib

matplotlib is a python 2D plotting library which produces publication quality figures in a variety...
  • Maple Landing page
    Landing page //
    2021-12-16
  • Matplotlib Landing page
    Landing page //
    2023-06-14

Maple features and specs

  • Powerful Symbolic Computation
    Maple excels at symbolic mathematics, providing robust tools for algebra, calculus, and more through its comprehensive symbolic computation engine.
  • Extensive Mathematical Library
    The software includes a vast library of built-in mathematical functions and toolkits, making it versatile for various complex mathematical problems.
  • Interactive Visualizations
    Maple offers a range of interactive plotting and visualization tools, aiding in better understanding and presentations of the mathematical data.
  • Programmatically Accessible
    Users can write scripts and create custom functions using Maple's powerful programming language, enabling automation and extended functionality.
  • Integration with Other Tools
    Maple integrates with other software such as MATLAB, further extending its utility in various domains and collaborative projects.

Possible disadvantages of Maple

  • Steep Learning Curve
    Due to its extensive features and programming capabilities, new users might find it challenging to learn and navigate effectively.
  • High Cost
    Maple is a commercially licensed software, which can be expensive, especially for individual users and small businesses.
  • Resource Intensive
    Running complex calculations and visualizations in Maple can be demanding on system resources, potentially requiring high-end hardware configurations.
  • Limited Numerical Computation Performance
    While exceptional at symbolic computation, Maple's numerical computation performance may lag behind specialized numerical software like MATLAB.
  • User Interface Complexity
    The interface, while powerful, can be quite complex and may require significant time to master and utilize efficiently.

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.

Maple videos

Tim Reviews the MAPLE AIRSOFT SUPPLY M4 AEG!

More videos:

  • Review - Whisky Review/Tasting: Crown Royal Maple
  • Review - Pearl Masters Maple Gum Review

Matplotlib videos

Learn Matplotlib in 6 minutes | Matplotlib Python Tutorial

Category Popularity

0-100% (relative to Maple and Matplotlib)
Technical Computing
40 40%
60% 60
Numerical Computation
100 100%
0% 0
Data Science And Machine Learning
Math Solver
100 100%
0% 0

User comments

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Reviews

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

Maple Reviews

10 Best MATLAB Alternatives [For Beginners and Professionals]
Next that comes in our list is Maple from Maplesoft. It’s an essential mathematical tool for education, engineering, and research.
6 MATLAB Alternatives You Could Use
Having a powerful Math engine, Maple is a pretty feature heavy MATLAB alternative. It lets you enter problems in traditional mathematical notation, and allows creation of custom interfaces. Maple includes a dynamically typed, imperative-style programming language, identical to Pascal. And of course, it can interface with other languages (e.g. C, Java) as well. It has over...
Source: beebom.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 doesn’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 107 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.

Maple mentions (0)

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

Matplotlib mentions (107)

  • Python for Data Visualization: Best Tools and Practices
    Matplotlib is the backbone of Python data visualization. It’s a flexible, reliable library for creating static plots. Whether you're making simple bar charts or complex graphs, Matplotlib allows extensive customization. You can adjust nearly every aspect of a plot to suit your needs. - Source: dev.to / about 1 month ago
  • Build a Competitive Intelligence Tool Powered by AI
    Add data visualization to make it actionable for your business using pandas.pydata.org and matplotlib.org. - Source: dev.to / 5 months ago
  • Data Visualisation Basics
    Matplotlib: a versatile library for visualizations, but it can take some code effort to put together common visualizations. - Source: dev.to / 9 months ago
  • Creating a CSV to Graph Generator App Using ToolJet and Python Libraries
    In this tutorial, we'll create a CSV to Graph Generator app using ToolJet and Python code. This app enables users to upload a CSV file and generate various types of graphs, including line, scatter, bar, histogram, and box plots. Since ToolJet supports Python (and JavaScript) code out of the box, we'll incorporate Python code and the matplotlib library to handle the graph generation. Additionally, we'll use... - Source: dev.to / 10 months ago
  • Something is strange with CrowdStrike timeline
    It looks like matplotlib to me: https://matplotlib.org/. - Source: Hacker News / 10 months ago
View more

What are some alternatives?

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

MATLAB - A high-level language and interactive environment for numerical computation, visualization, and programming

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

Wolfram Mathematica - Mathematica has characterized the cutting edge in specialized processing—and gave the chief calculation environment to a large number of pioneers, instructors, understudies, and others around the globe.

GnuPlot - Gnuplot is a portable command-line driven interactive data and function plotting utility.

GNU Octave - GNU Octave is a programming language for scientific computing.

Plotly - Low-Code Data Apps