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Matplotlib VS Python Package Index

Compare Matplotlib VS Python Package Index 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...

Python Package Index logo Python Package Index

A repository of software for the Python programming language
  • Matplotlib Landing page
    Landing page //
    2023-06-14
  • Python Package Index Landing page
    Landing page //
    2023-05-01

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.

Python Package Index features and specs

  • Extensive Library Collection
    PyPI hosts a comprehensive collection of Python libraries and packages, enabling developers to find tools and modules for almost any task, from data analysis to web development.
  • Ease of Use
    The PyPI interface is user-friendly, and installation of packages can be quickly done using pip, Python's package installer. This makes it easy for both beginners and advanced users to manage dependencies.
  • Community Support
    Many PyPI packages are well-documented and supported by a large community of developers, which provides reassurance and assistance through forums, tutorials, and user contributions.
  • Regular Updates
    Packages on PyPI are frequently updated by maintainers to include new features, improvements, and security patches, ensuring that developers have access to the latest and most secure versions.
  • Open Source
    PyPI primarily hosts open-source packages, promoting transparency, collaboration, and the ability to modify packages to better suit individual needs.

Possible disadvantages of Python Package Index

  • Quality Assurance
    Not all packages on PyPI are of high quality or well-maintained. Some may have bugs, lack proper documentation, or not adhere to best practices, requiring users to vet packages carefully.
  • Security Risks
    There is a risk of downloading malicious packages since PyPI allows anyone to upload packages. Users need to be cautious and verify the credibility of the package authors and sources.
  • Dependency Management
    Managing dependencies can become complex, especially for large projects, as conflicts between package versions can arise, leading to potential runtime issues.
  • Overhead
    For smaller projects or those with specific needs, the sheer number of available packages can be overwhelming, making it difficult to find the most suitable one without investing a significant amount of time.
  • Legacy Packages
    Some packages on PyPI may no longer be maintained or updated, which can represent a risk if they become incompatible with newer versions of Python or other dependencies.

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.

Analysis of Python Package Index

Overall verdict

  • Yes, Python Package Index (PyPI) is considered a good resource for Python developers due to its extensive collection of packages, ease of use, and strong community support.

Why this product is good

  • Integration
    Seamlessly integrates with tools like pip to simplify package management.
  • Comprehensive
    It hosts a vast array of packages, covering almost every possible need a developer may have.
  • User friendly
    PyPI provides an easy-to-navigate interface for both uploading and downloading Python packages.
  • Community support
    Many packages come with active community support and continuous updates.

Recommended for

  • Python developers seeking packages to extend their applications.
  • Open-source contributors looking to publish and distribute Python packages.
  • Beginners in Python who need easy access to libraries and tools.

Matplotlib videos

+ Add

Learn Matplotlib in 6 minutes | Matplotlib Python Tutorial

Python Package Index videos

+ Add

Python Django - Create and deploy packages to PyPI - Python Package Index

More videos:

  • Review - PIP and the Python Package Index - Open Source Language, Package Installer, Programming Python

Category Popularity

0-100% (relative to Matplotlib and Python Package Index)

Matplotlib

Python Package Index

Technical Computing
100 100%
Technical Computing
0% 0
Front End Package Manager
0 0%
Front End Package Manager
100% 100
Data Science And Machine Learning
100 100%
Data Science And Machine Learning
0% 0
Translation Service
0 0%
Translation Service
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 Matplotlib and Python Package Index

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

Python Package Index Reviews

We have no reviews of Python Package Index yet.
Be the first one to post

Social recommendations and mentions

Matplotlib might be a bit more popular than Python Package Index. We know about 110 links to it since March 2021 and only 91 links to Python Package Index. 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

Python Package Index mentions (91)

  • Don’t Let Cyber Risk Kill Your GenAI Vibe: A Developer’s Guide
    This GenAI novel cyber risk is a variant of what's called typo squatting. With typo squatting, a malicious actor published its malware on some public repository (like the Node Package Manager (NPM) for Node JavaScript, the Python Package Index (PyPI) for python, or the Comprehensive R Archive Network (CRAN) for R) using a package name that is so similar to a popular package that a typo in the package name during... - Source: dev.to / 4 days ago
  • Some thoughts on personal Git hosting
    > But we still don't have a solution to search projects on potentially thousands of servers, including self-hosted ones. We do. https://mvnrepository.com/repos/central https://npmjs.com https://packagist.org/ https://pypi.org/ https://www.debian.org/distrib/packages#search_packages https://pkg.go.dev/ https://elpa.gnu.org/packages/ And many others. And we still have forums like this one and Reddit where... - Source: Hacker News / 27 days ago
  • Configuring CSP: A Test For Django 6.0
    There has been existing tooling to test and enforce CSP in Django. The most recognizable of those has been the django-csp package developed by a team at Mozilla. It is available on PyPI and does an excellent job. You might still be wondering how this answers the question: "Why Django 6.0?" In May 2024, a conversation began to explore the possibility of adding CSP support to Django. The idea was to create... - Source: dev.to / about 2 months ago
  • PyPI Users Email Phishing Attack
    Ah, I was beaten to it... The Python Package Index (PyPI), a central repository of third-party Python packages, is now seeing what appears to be a fairly wide-scale phishing attack. The attackers are squatting on "pypj.org" — a plausible typo, but more likely chosen to visually resemble "pypi.org" in a browser address bar. This was first reported by Python core developer Ethan Furman (@stoneleaf), who was... - Source: Hacker News / 2 months ago
  • Contributing to PyPI
    If you visit PyPI and scroll to the bottom you can see that it is available in a number of languages including Hebrew, which indicates it should also support RTL (Right-to-left) rendering. Those translations need maintenance and more translations could be added. - Source: dev.to / 3 months ago
View more

What are some alternatives?

When comparing Matplotlib and Python Package Index, 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.

Python Poetry - Python packaging and dependency manager.

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

pip - The PyPA recommended tool for installing Python packages.

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

Conda - Binary package manager with support for environments.

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