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Matplotlib VS Sourcery

Compare Matplotlib VS Sourcery and see what are their differences

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Contents:
  1. ยป Base Details
  2. ยป Videos
  3. ยป Reviews
  4. ยป Alternatives

Matplotlib logo Matplotlib

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

Sourcery logo Sourcery

Sourcery reviews your code everywhere you work and automatically suggests improvements
  • Matplotlib Landing page
    Landing page //
    2023-06-14
  • Sourcery Landing page
    Landing page //
    2024-08-19

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.

Sourcery features and specs

  • Code Improvement
    Sourcery provides automated suggestions to improve code quality by identifying and fixing issues such as code smells, redundancy, and complexity.
  • Increased Efficiency
    By automating repetitive tasks and code refactoring, Sourcery allows developers to focus on more complex and creative aspects of programming, thus increasing overall productivity.
  • Integration
    It integrates seamlessly with major code editors like VSCode and PyCharm, making it convenient for developers to incorporate it into their existing workflows without learning new software.
  • Real-time Feedback
    Sourcery provides real-time analysis and suggestions as you write your code, allowing immediate improvements without the need for additional manual reviews.

Possible disadvantages of Sourcery

  • Language Limitation
    Sourcery primarily supports Python, making it less useful for projects involving other programming languages.
  • False Positives
    Like many automated tools, it might sometimes suggest changes that are not ideal or that developers may not agree with, possibly leading to wasted time reviewing and rejecting certain recommendations.
  • Dependency on Tool
    Relying heavily on Sourcery might reduce a developer's ability to manually identify and fix code issues, potentially impacting skill development and problem-solving capability.
  • Cost
    While Sourcery offers a free tier, more extensive features are part of a paid plan, which may not be feasible for individual developers or small teams with limited budgets.

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

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Category Popularity

0-100% (relative to Matplotlib and Sourcery)

Matplotlib

Sourcery

Data Science And Machine Learning
100 100%
Data Science And Machine Learning
0% 0
Developer Tools
0 0%
Developer Tools
100% 100
Technical Computing
100 100%
Technical Computing
0% 0
AI
0 0%
AI
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 Sourcery

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 doesnโ€™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

Sourcery Reviews

11 Best AI Coding Assistants: Top Tools Every Developer Needs in 2025ย 
Early detection of subtle issues: Even experienced developers miss things under tight deadlines and multi-repo chaos. Assistants like DeepCode or Sourcery flag edge cases and logic issues early, so you catch bugs before they escalate. For database teams, SQL-aware tools highlight slow joins, ambiguous filters, or schema mismatches during developmentโ€”not after deployment.
Source: blog.devart.com

Social recommendations and mentions

Based on our record, Matplotlib seems to be a lot more popular than Sourcery. While we know about 114 links to Matplotlib, we've tracked only 8 mentions of Sourcery. 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 (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
View more

Sourcery mentions (8)

  • Sourcery GitHub Integration: PR Review Setup
    Go to sourcery.ai and click "Sign In" or "Get Started". - Source: dev.to / 4 months ago
  • I Program with Agents
    Totally agree - weโ€™re working on this at https://sourcery.ai. - Source: Hacker News / about 1 year ago
  • # AI Tools for Developers: A Practical Guide to Boost Your Productivity in 2025
    Cost: Free for open source, paid plans for commercial use Website: https://sourcery.ai. - Source: dev.to / about 1 year ago
  • Ask HN: How do you get an open-source product noticed by developers?
    In my experience, the developer tools that really catch on do so via word of mouth. For example, our whole team recently adopted https://sourcery.ai/ (not an ad) because one developer tried it and hyped it up to everyone else who also liked it. - Source: Hacker News / over 3 years ago
  • Google Python Style Guide
    To those that wish to automate a subset of these conventions, there is a tool called Sourcery[1] that I, personally, am a huge fan of! Not only does it have a large set of default rules[2], but it can also allow you to write your own rules that may be specific to your team or organization, and as mentioned it can enable you to follow Google's Python style guide as well[3]. There are some refactorings that Sourcery... - Source: Hacker News / over 3 years ago
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What are some alternatives?

When comparing Matplotlib and Sourcery, 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.

Graphite - Graphite is a highly scalable real-time graphing system.

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

Ellipsis - Ellipsis is an AI developer tool that can review code, fix bugs, and more.

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

Cursor - The AI-first Code Editor. Build software faster in an editor designed for pair-programming with AI.

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