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Which is more popular?
Based on our record, Matplotlib
seems to be a lot more popular than Sumatra PDF.
While we know about 114 links to Matplotlib,
we've tracked only 1 mention of Sumatra PDF.
social mentions
1 vs 114
PDF Tools popularity
100% vs 0%
alternatives listed
240+ vs 238
Base details
Website, pricing, platforms and company facts side by side.
Lightweight Sumatra PDF is known for its small footprint, making it quick to download and install. It runs efficiently on older hardware.
Speed The application is fast to open and navigate, even with large PDF files, enhancing the user experience.
Simplicity Sumatra PDF offers a minimalistic interface that is easy to navigate for users who need a straightforward PDF reader without unnecessary features.
Portable Version Sumatra PDF offers a portable version that can be run without installation, ideal for use on multiple computers or USB drives.
Free and Open Source The software is free to use and open-source, allowing users to inspect the code and contribute to its development.
Support for Multiple Formats In addition to PDFs, Sumatra PDF supports ePub, Mobi, XPS, DjVu, CHM, and comic book formats (CBZ and CBR), making it versatile.
Possible disadvantages
Limited Features Sumatra PDF lacks advanced features such as form filling, text editing, and annotations, which are available in other PDF readers.
No Document Editing The application does not support document editing, which can be a drawback for users needing to make changes to their PDFs.
Basic User Interface The simplistic design might not appeal to users who prefer a more modern or visually appealing interface.
Restricted Customization Sumatra PDF offers limited customization options, providing fewer settings and user preferences compared to other PDF readers.
No Cloud Integration The software lacks integrated support for cloud storage services, which can be inconvenient for users who manage documents online.
No Advanced Security Features Sumatra PDF does not include advanced security features such as digital signatures or encryption, which are essential for some professional users.
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
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
An editorial look at what each product does well and who it suits.
Sumatra PDFMatplotlib
Overall verdict
Sumatra PDF is a great choice for anyone looking for a reliable and efficient PDF reader. Its performance, coupled with its simplicity, makes it a top recommendation for those who need a no-frills document viewer.
Why this product is good
Sumatra PDF is considered good because it is lightweight, fast, and easy to use. Its simplicity and minimalistic design make it an excellent choice for users who need a straightforward PDF reader without any unnecessary features. It has a quick load time and supports a variety of document formats including PDF, ePub, MOBI, CHM, XPS, DjVu, CBZ, and CBR. Additionally, it is open-source and doesn't require installation, making it ideal for users who prioritize portability.
Recommended for
Sumatra PDF is especially recommended for users who need a fast and lightweight PDF reader with basic functionalities. It's ideal for those who want a simple tool for reading PDFs and other document formats without the complications of advanced features. It is also suitable for users who value open-source software.
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.
Sumatra PDF Reader is a lightweight PDF reader with the basics of PDF viewing and processing. It works with various versions of the Windows operating system, such as the previous XP, Vista, 7, 8 and the latest Windows...
A free eBook reader for Windows that can act as an all-in-one tool is Sumatra PDF Reader. Besides being free of cost, Sumatra is small and portable, which makes it a fast and lightweight tool for eBook viewing. The...
Being a simple application, the user interface itself is pretty minimal. What’s more, Sumatra does lack some advanced features. Bookmarks, highlights, and other typical features aren’t in the box. Even so, Sumatra is...
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...
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...
Recommendations tracked on public social media and blogs since March 2021.
Sumatra PDF1 mentionMatplotlib114 mentions
anyone know any good epub/pdf readers for windows 11?
You can use your browser for both, there are extensions(FireFox - PDF & EPUB/Chrome - PDF& EPUB) for that. In case, you want you use a separate software for them, I suggest SumatraPDF--it handles both PDFs and .EPUB files.
Source:
almost 4 years ago
The soul file
In February, an AI agent named MJ Rathbun submitted a pull request to matplotlib — the Python plotting library used by half the scientific computing world. Scott Shambaugh, a volunteer maintainer, rejected it. Standard code review....
- Source: dev.to
/
8 months ago
Numbers are useful, but sometimes it’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...
- Source: dev.to
/
11 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
/
12 months ago
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iLovePDF
Pandas
NumPy
Seaborn
D3.js
Plotly
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Jupyter
