Pandas VS SymPy

panda’s

> The big thing pandas has going for it is that it's already been through this field testing. All the bugs have been ironed out by the hundreds of thousands of users.

At this very moment pandas github repo has 1563 open issues labeled with a bug tag [0]. So much for "all the bugs have been ironed out".

[0] https://github.com/pandas-dev/pandas/issues?q=is%3Aopen+is%3...

Python is the main programming language I use nowadays. In particular numpy and pandas are of course extremely useful. I also use biopython package - a collection of software tools for biological computation written in Python by an international group of researchers and developers.

Below is the python Task that transforms the tweets list into a Pandas dataframe, then dumps it in our MinIO Object Storage as a CSV file:

It was rewarding to dig into SQLite a bit while solving this puzzle, so I figured this would be a good opportunity to learn a bit more about pandas too! So how would I adapt this working SQL solution to pandas?

All the data has been extracted from the official Tor Metrics website, and using Python with the Pandas library I've cleaned the data. Finally, the visualizations have been made with Tableau.

If you did that you could use a built-in library like csv to read and parse the file or you could use a 3rd party library like Pandas. Alternatively, you could store your file as json:

With less than 100 lines of code, I made a web app with just under 100 lines of code using Streamlit - used to build a nice and interactive frontend, Plotly - a library to visualize data, and Pandas, an open-source data analysis and manipulation tool built on top of the Python programming language.

Are you taking a math class? Having a useful reason to use python will help you solve problems like math. Ditch your old calculator and check out sympy.org It will help to use something like jupyter.org so you can create notebooks for each chapter of your class. It also displays your formulas so you can read them just like your text book. I like to keep formulas I make in my Jupyter notebook and notes on how to use the formulas in my lessons. I am no expert and still learning but I do know the documentation is amazing.

Wait. Wait a minute. Just wait one little minute here...

Your company has issued a DMCA takedown notice for "plagiarized code snippets" against the library-in-questions own documentation? (The take down was issued against docs.sympy.org; linked directly within sympy's GIT repo README.md: https://github.com/sympy/sympy)

And this is an "initiative" your organization has undertaken? Have you thought this through?

Where should engineers who want to learn about sympy go to attain that knowledge?

Where did your team learn about and generate the assessment questions?

Where do you stop with this initiative? Would you issue takedown notices to MDN? Stack Overflow? What about VSCode Copilot?

+ SymPy links from the wiki https://github.com/sympy/sympy/wiki/External-SymPy-Media%2C-...

[ Reference of equations from advanced physics in a very condensed manner ]

Now compare that to SymPy: https://github.com/sympy/sympy/blob/9e8f62e059d83178c1d8a1e19acac5473bdbf1c1/sympy/ntheory/primetest.py#L472-L634

The trouble with SymPy is it's, well, buggy. I tried it years ago and as soon as I got serious I quite quickly ran into problems that I reported, some of which I see they apparently still haven't gotten around to addressing. [1] [2]

Symbolic math is hard; they have my sympathies. I don't think I could do better. But as long as bugs like these exist, it's going to be hard to convince people to switch away from better tools like Mathematica.

[1] https://github.com/sympy/sympy/issues/12561

[2] https://github.com/sympy/sympy/issues/12562