Software Alternatives, Accelerators & Startups

Solid Explorer VS Matplotlib

Compare Solid Explorer VS Matplotlib and see what are their differences

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Solid Explorer logo Solid Explorer

Solid Explorer is a powerful Android file manager featuring access to most popular cloud storages, root access and easy extensibility.

Matplotlib logo Matplotlib

matplotlib is a python 2D plotting library which produces publication quality figures in a variety...
  • Solid Explorer Landing page
    Landing page //
    2021-09-25
  • Matplotlib Landing page
    Landing page //
    2023-06-14

Solid Explorer features and specs

  • User Interface
    Solid Explorer has a clean and visually appealing user interface that supports both light and dark themes, making it pleasant to use.
  • Dual-pane mode
    The app supports a dual-pane mode, which allows you to manage files in two different locations simultaneously, enhancing productivity.
  • Cloud Storage Integration
    Solid Explorer supports a wide range of cloud storage services like Google Drive, Dropbox, OneDrive, and more, allowing for seamless file management across different platforms.
  • File Encryption
    The app includes features for encrypting and decrypting files, providing an extra layer of security for sensitive information.
  • Customization Options
    Solid Explorer offers extensive customization options, allowing users to change themes, icon sets, and layout to fit their preference.
  • Root Access
    It supports root access for rooted devices, enabling advanced file management tasks such as modifying system files.

Possible disadvantages of Solid Explorer

  • Payment Required
    Solid Explorer offers a 14-day trial period, after which a one-time payment is required to continue using the app, which might deter some users.
  • Occasional Bugs
    Some users have reported occasional bugs and crashes, which can disrupt the file management experience.
  • Storage Permissions
    The app requires extensive storage permissions, which some users might find concerning from a privacy standpoint.
  • Resource Intensive
    Solid Explorer can be resource-intensive, consuming more battery and memory compared to some of its competitors.
  • Limited Free Features
    While the app is feature-rich, the free version has limited functionalities, which could be a downside for users not willing to pay.

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.

Analysis of Solid Explorer

Overall verdict

  • Solid Explorer is generally considered a good file management app, appreciated for its comprehensive functionality and ease of use. It is well-regarded for providing solid performance and reliability.

Why this product is good

  • Solid Explorer is popular for its clean and intuitive user interface, robust file management features, and strong support for cloud storage integration. It offers dual-pane navigation, file encryption, and extensive customization options, making it versatile for various file management needs.

Recommended for

  • Users looking for a feature-rich file manager with cloud integration
  • Those who appreciate customizable interfaces
  • Users who need efficient file management on Android devices
  • Individuals looking for secure file encryption options

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.

Solid Explorer videos

Es File Explorer Vs Solid Explorer

More videos:

  • Review - 8 Cool Things You Can do with Solid Explorer - Best ES File Explorer Alternative
  • Review - best paid android apps 2016 - Solid explorer file manager (Review, Pros, Cons, Does It Worth It)

Matplotlib videos

Learn Matplotlib in 6 minutes | Matplotlib Python Tutorial

Category Popularity

0-100% (relative to Solid Explorer and Matplotlib)
File Manager
100 100%
0% 0
Data Science And Machine Learning
File Explorer
100 100%
0% 0
Technical Computing
0 0%
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 Solid Explorer and Matplotlib

Solid Explorer Reviews

The best third-party file managers for Android
Keep it simple with Simple File Manager Pro. Like Solid Explorer, the app is designed within the Material Design schematic, including using one floating action button to add a new file or folder. Simple File Manager Pro only works with localized files, however, and though it doesn't offer access to exterior cloud accounts, you can navigate root files, SD cards, and USB files...

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 doesnโ€™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 a lot more popular than Solid Explorer. While we know about 114 links to Matplotlib, we've tracked only 1 mention of Solid Explorer. 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.

Solid Explorer mentions (1)

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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What are some alternatives?

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

MiXplorer - MiXplorer is a mobile app that was designed to make it easy to organize and manage the files on your Android device.

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

Total Commander - A Shareware file manager for Windowsยฎ 95/98/ME/NT/2000/XP/Vista/7, and Windowsยฎ 3.1.

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

Amaze File Manager - Free and open-source Android file manager with no ads.

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