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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, Pandas seems to be a lot more popular than Sage Math. While we know about 198 links to Pandas, 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 / 11 months ago
You could also try sagemath (sagemath.org), available for window, mac & linux for free. Source: about 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
Python is a natural fit for serverless development. It boasts a vast array of libraries, including Powertools for AWS and robust libraries for data engineers. Its versatility and excellent developer experience make it a top choice for serverless projects, offering a seamless and enjoyable development experience. - Source: dev.to / 15 days ago
In data analysis, managing the structure and layout of data before analyzing them is crucial. Python offers versatile tools to manipulate data, including the often-used Pandas reset_index() method. - Source: dev.to / 8 days ago
Dash is a Python framework that enables you to build interactive frontend applications without writing a single line of Javascript. Internally and in projects we like to use it in order to build a quick proof of concept for data driven applications because of the nice integration with Plotly and pandas. For this post, I'm going to assume that you're already familiar with Dash and won't explain that part in detail.... - Source: dev.to / 2 months ago
Last year I worked through the challenges using VisiData, Datasette, and Pandas. I walked through my thought process and solutions in a series of posts. - Source: dev.to / 5 months ago
Data analysis involves scrutinizing datasets for class imbalances or protected features and understanding their correlations and representations. A classical tool like pandas would be my obvious choice for most of the analysis, and I would use OpenCV or Scikit-Image for image-related tasks. - Source: dev.to / 5 months ago
GNU Octave - GNU Octave is a programming language for scientific computing.
NumPy - NumPy is the fundamental package for scientific computing with Python
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.
Scikit-learn - scikit-learn (formerly scikits.learn) is an open source machine learning library for the Python programming language.
MATLAB - A high-level language and interactive environment for numerical computation, visualization, and programming
OpenCV - OpenCV is the world's biggest computer vision library