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Matplotlib VS CuPy

Compare Matplotlib VS CuPy and see what are their differences

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Matplotlib logo Matplotlib

matplotlib is a python 2D plotting library which produces publication quality figures in a variety...

CuPy logo CuPy

CuPy is an open-source array library for GPU-accelerated computing with Python. CuPy utilizes CUDA Toolkit libraries including cuBLAS, cuRAND, cuSOLVER, cuSPARSE, cuFFT, cuDNN and NCCL to make full use of the GPU architecture.
  • Matplotlib Landing page
    Landing page //
    2023-06-14
Not present

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.

CuPy features and specs

No features have been listed yet.

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.

Matplotlib videos

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Learn Matplotlib in 6 minutes | Matplotlib Python Tutorial

CuPy videos

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Category Popularity

0-100% (relative to Matplotlib and CuPy)

Matplotlib

CuPy

Technical Computing
97 97%
Technical Computing
3% 3
Numerical Computation
91 91%
Numerical Computation
9% 9
Data Science And Machine Learning
100 100%
Data Science And Machine Learning
0% 0
Data Visualization
100 100%
Data Visualization
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 Matplotlib and CuPy

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.
Source: www.technotification.com
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.
Source: searchbusinessanalytics.techtarget.com
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.
Source: www.analyticsvidhya.com
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...
Source: www.geeksforgeeks.org

CuPy Reviews

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Social recommendations and mentions

Based on our record, Matplotlib seems to be more popular. It has been mentiond 110 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.

Matplotlib mentions (110)

  • 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, A…. - Source: dev.to / 14 days ago
  • Streamlit Chart Libraries Comparison: A Frontend Developer's Guide
    Matplotlib is Python's visualization standard:. - Source: dev.to / 3 months ago
  • Why Use Matplotlib for Data Visualization?
    Matplotlib is a foundational and incredibly versatile plotting library in Python, making it a go-to choice for many data scientists and analysts. While many data visualization libraries exist, Matplotlib offers some significant advantages that make it indispensable. - Source: dev.to / 4 months ago
  • 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 / 6 months 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 / 10 months ago
View more

CuPy mentions (0)

We have not tracked any mentions of CuPy yet. Tracking of CuPy recommendations started around May 2025.

What are some alternatives?

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

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

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

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

SciPy - SciPy is a Python-based ecosystem of open-source software for mathematics, science, and engineering. 

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

Julia - Julia is a sophisticated programming language designed especially for numerical computing with specializations in analysis and computational science. It is also efficient for web use, general programming, and can be used as a specification language.

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