Hey Enoch, thanks for pointing that out. I can't comment too much on Mathematica as I have never used it for my work. From what I can tell, it does seem to have a lot of out-of-the-box features for data viz, modeling, and optimization. The main point of difference is that Python is free and open source, so it is more accessible and has vast community support.
I also see Python as being more flexible given the extensive packages and integrations with other tools, e.g., web scraping, API connections, large language models. Deploying dashboards and web apps is also simple (and free) with Python via Streamlit or Quarto. I'm also someone who likes to have a high degree of control with data viz and Python plotting packages allow for that.
Python probably has a steeper learning curve in terms of setup and package management, but AI coding support has significantly reduced this barrier. I don't see any reason why one couldn't use both Mathematica and Python for auxiliary tasks.
Just a quick question for you. I can do all this with mathematica. Right?
Hey Enoch, thanks for pointing that out. I can't comment too much on Mathematica as I have never used it for my work. From what I can tell, it does seem to have a lot of out-of-the-box features for data viz, modeling, and optimization. The main point of difference is that Python is free and open source, so it is more accessible and has vast community support.
I also see Python as being more flexible given the extensive packages and integrations with other tools, e.g., web scraping, API connections, large language models. Deploying dashboards and web apps is also simple (and free) with Python via Streamlit or Quarto. I'm also someone who likes to have a high degree of control with data viz and Python plotting packages allow for that.
Python probably has a steeper learning curve in terms of setup and package management, but AI coding support has significantly reduced this barrier. I don't see any reason why one couldn't use both Mathematica and Python for auxiliary tasks.