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Matplotlib VS File Roller

Compare Matplotlib VS File Roller 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...

File Roller logo File Roller

File Roller is an archive manager for the GNOME desktop environment.
  • Matplotlib Landing page
    Landing page //
    2023-06-14
  • File Roller Landing page
    Landing page //
    2021-09-25

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.

File Roller features and specs

  • Integration with GNOME Desktop
    File Roller integrates seamlessly with GNOME Desktop Environment, allowing easy access and extraction of archive files directly from the file manager.
  • Supports Various Formats
    It supports a wide range of archive formats including tar, zip, 7z, rar, iso, and many others, ensuring compatibility with most archive files.
  • User-Friendly Interface
    File Roller provides a simple and intuitive graphical user interface that makes it easy for users to create, modify, and extract archives.
  • Customizable Compression Levels
    Users can customize compression levels for different archive formats, allowing for flexible space and performance management.

Possible disadvantages of File Roller

  • Dependence on GNOME
    File Roller is tailored for the GNOME desktop environment, which can make it less appealing or efficient for users of other desktop environments.
  • Limited Advanced Features
    Compared to some specialized archiving tools, File Roller lacks advanced features like automation scripts, archive repair, and specialized encryption options.
  • Performance
    While File Roller is adequate for general use, it may not perform as quickly or efficiently as command-line tools or other specialized software for handling large archives.
  • GUI-Dependent
    File Roller relies on a graphical user interface, which means it cannot be used in environments where a GUI is not available or practical, such as servers or remote systems accessed via SSH.

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 File Roller

Overall verdict

  • File Roller is a reliable and efficient tool for managing archives on Linux systems. Its straightforward interface, coupled with compatibility with numerous archive formats, makes it a good choice for users who need a no-fuss archive manager.

Why this product is good

  • File Roller is a simple, user-friendly archive manager for the GNOME desktop environment. It's capable of creating, modifying, and extracting files from various archive formats, including ZIP, TAR, RAR, and others. Its integration with the GNOME desktop allows for seamless access and file management through the file manager. It supports drag and drop functionality, making it easy to manage archives with minimal effort.

Recommended for

    File Roller is recommended for GNOME desktop users who need a simple and efficient archive manager. It's also suitable for anyone who prefers GUI tools over command-line options for managing compressed files on Linux.

Matplotlib videos

+ Add

Learn Matplotlib in 6 minutes | Matplotlib Python Tutorial

File Roller videos

+ Add

show files file roller

Category Popularity

0-100% (relative to Matplotlib and File Roller)

Matplotlib

File Roller

Data Science And Machine Learning
100 100%
Data Science And Machine Learning
0% 0
Archiver
0 0%
Archiver
100% 100
Technical Computing
100 100%
Technical Computing
0% 0
Archive Manager
0 0%
Archive Manager
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 File Roller

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

File Roller Reviews

We have no reviews of File Roller yet.
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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.

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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File Roller mentions (0)

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

What are some alternatives?

When comparing Matplotlib and File Roller, 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.

Bandizip - Bandizip : All-In-One Free Zip Archiver. Bandizip is a lightweight, fast and free All-In-One Zip Archiver.

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

The Unarchiver - Get the top application for archives on Mac. It's a RAR extractor, it allows you to unzip files, and works with dozens of other formats.

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

NanaZip - NanaZip is an open source file archiver intended for the modern Windows experience

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