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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 dollars in support from grants around the world, and has a very active developer community.
This site is about Software as a Service, and there are at least two easy ways to use Sage online as a service:
Based on our record, Matplotlib seems to be a lot more popular than Sage Math. While we know about 101 links to Matplotlib, we've tracked only 4 mentions of Sage Math. 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.
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 obviously better as a result of studying mathematics, e.g., I started SageMath (https://sagemath.org) and wrote a big chunk of it. Now I mostly do full stack web development (I... - Source: Hacker News / about 1 year ago
You could also try sagemath (sagemath.org), available for window, mac & linux for free. Source: over 1 year ago
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: over 1 year ago
I am a fan of this site (and of this site's tutorial in particular). I would also recommend this site. The SageMath site has some good tutorials too. Source: over 1 year ago
How to Accomplish: Utilize visualization libraries like Matplotlib, Seaborn, or Plotly in Python to create histograms, scatter plots, and bar charts. For image data, use tools that visualize images alongside their labels to check for labeling accuracy. For structured data, correlation matrices and pair plots can be highly informative. - Source: dev.to / 13 days ago
Python (with Matplotlib): A powerful library for creating detailed histograms. - Source: dev.to / 16 days ago
Below is an example of a code cell. We'll visualize some simple data using two popular packages in Python. We'll use NumPy to create some random data, and Matplotlib to visualize it. - Source: dev.to / 10 months ago
Matplotlib: for displaying our image result. - Source: dev.to / 3 months ago
Matplotlib: Acomprehensive library for creating static, animated, and interactive visualizations in Python. - Source: dev.to / 4 months ago
Wolfram Mathematica - 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.
Pandas - Pandas is an open source library providing high-performance, easy-to-use data structures and data analysis tools for the Python.
GNU Octave - GNU Octave is a programming language for scientific computing.
GnuPlot - Gnuplot is a portable command-line driven interactive data and function plotting utility.
MATLAB - A high-level language and interactive environment for numerical computation, visualization, and programming
D3.js - D3.js is a JavaScript library for manipulating documents based on data. D3 helps you bring data to life using HTML, SVG, and CSS.