I've been using Maxima since my undergraduate (over 10 years), now with Ubuntu20.04 lts, I become a newbie of SageMath. For a small project (both symbolical and numerical), in particular, student lab activities, Maxima has been a powerful tool for analyzing and visualizing data. (The Android version is also fantastic, but the poor keyboard.)
Mathematica is always enemy/friend. (My coworkers are all Mathematica speakers.)
Based on our record, Pandas should be more popular than Maxima. It has been mentiond 199 times since March 2021. 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 think the really neat piece of software behind this is maxima (https://maxima.sourceforge.io/), a rather influential computer algebra system of ancient lineage still in use today in more place than you might think. - Source: Hacker News / 26 days ago
In the maxima computer algebra system[1] which was ancestrally based on lisp it has a single quote operator[2] which delays evaluation of something and a "double quote" (which acually two single quotes rather than an actual double quote) operator[3] which asks maxima to evaluate some expression immediately rather than leaving it in symbolic form.[4] [1] https://maxima.sourceforge.io/ [2]... - Source: Hacker News / about 2 months ago
Use wxmaxima, a free and open-source computer algebra system:. Source: 5 months ago
There are several options, here is one of them: https://maxima.sourceforge.io. Source: 12 months ago
You may use maxima cas (https://maxima.sourceforge.io/) to solve symbolic complex problems. Source: about 1 year ago
It's also possible for you to give a package an alias by using the as keyword. For instance, you could use the pandas package as pd like this:. - Source: dev.to / 1 day 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 / 19 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 / 13 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
MATLAB - A high-level language and interactive environment for numerical computation, visualization, and programming
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.
GNU Octave - GNU Octave is a programming language for scientific computing.
OpenCV - OpenCV is the world's biggest computer vision library