Calculate in a notebook and share — from everyday math to engineering.
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Which is more popular?
Based on our record, Matplotlib
seems to be a lot more popular than Sage Math.
While we know about 114 links to Matplotlib,
we've tracked only 4 mentions of Sage Math.
social mentions
4 vs 114
Numerical Computation popularity
100% vs 0%
alternatives listed
106 vs 238
Base details
Website, pricing, platforms and company facts side by side.
Open Source SageMath is free and open-source software, which allows users to access, modify, and distribute the software without cost. It fosters collaboration and transparency within the community.
Comprehensive Toolset It integrates many mathematics software packages into a common interface, providing tools for algebra, calculus, combinatorics, numerical mathematics, number theory, and more.
Python-Based SageMath uses Python as its primary language, which is widely known for its readability and ease of use. Python's popularity and extensive libraries enhance SageMath's functionality.
Active Community SageMath has a vibrant and active community contributing to its development, offering extensive support, tutorials, and documentation.
Web Interface SageMath provides a Jupyter Notebook interface, which allows for interactive computations, visualization, and sharing of results in a web browser.
Possible disadvantages
Resource Intensive SageMath can be resource-intensive, requiring significant computing power and memory, which can be a limitation for users with less powerful hardware.
Steep Learning Curve For users unfamiliar with Python or advanced mathematical software, SageMath can have a steep learning curve. It may require substantial effort to become proficient.
Software Dependencies SageMath relies on numerous other software packages. If one of these dependencies has issues or is incompatible with a user's system, it can be challenging to troubleshoot and resolve.
User Interface While functional, the user interface of SageMath may not be as polished or intuitive as some commercial competitors, which can affect user experience.
Limited Commercial Support There is limited commercial support available for SageMath compared to proprietary software, which might be a drawback for enterprise or commercial use requiring guaranteed support services.
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.
Sage MathMatplotlib
Overall verdict
SageMath is a robust and versatile mathematics software that is highly regarded for educational and research purposes. It is particularly valuable for anyone needing a cohesive environment for using multiple mathematical tools.
Why this product is good
SageMath is good because it is a comprehensive open-source mathematics software system that integrates a wide range of mathematics software packages into a common interface. It covers many aspects of mathematics, including algebra, calculus, matrix operations, numerical computations, and more. Its use of Python as the primary language makes it highly accessible and extensible for users familiar with programming. Additionally, being open-source allows for transparency and community-driven improvements.
Recommended for
students
educators
researchers
mathematicians
engineers
scientists
anyone interested in computational mathematics
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.
Sage Math is another software system that provides an alternative to MatLab. It is Used to analyze large data sets and help in scientific researches. Built on top of Python-based scientific library. Python is clear...
I started SageMath in 2004 to provide a FOSS alternative to expensive commercial mathematics software. Sage is Python-based and has had around 600 volunteer contributors. The project has also received millions of...
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.
Sage Math4 mentionsMatplotlib114 mentions
Did studying proof based math topics e.g. analysis make you a better programmer?
I received a Ph.D. In pure math (number theory) from Berkeley, and then worked as an academic mathematician for 20 years, so wrote a few dozen research papers and some books. My ability to write software for doing mathematics was...
- Source: Hacker News
/
over 3 years ago
How do I get this calculator to give me the derivative?
You could also try sagemath (sagemath.org), available for window, mac & linux for free.
Source:
over 3 years ago
Are there any good free numeric computing environments?
SageMath gets my vote. I use it to compute simplicial objects that turn out to be infinitely categories. https://sagemath.org SageMath includes most of the python libraries already mentioned, and much more.
Source:
almost 4 years ago
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
/
11 months ago
Mathematica has characterized the cutting edge in specialized processing—and gave the chief calculation environment to a large number of pioneers, instructors, understudies, and others around the globe.
Compare Wolfram Mathematica to Sage Math or Matplotlib:
MATLAB
GNU Octave
Wolfram Mathematica
Scilab
Maxima
Maple
Julia
Pandas
NumPy
Seaborn
D3.js
Plotly
GnuPlot
Jupyter
