New to Python in 2020

Hey all,

New to python and trying to set a 2020 goal of becoming more fluent with the language. My interest mainly lie with data science and I came across this tool/library yesterday. A couple of questions for the community:

  1. Is this the right place to ask advice about this type of topic?
  2. If so, is anyone familar with this library and would they recommend it to someone just starting out in the python and data science world?

Thanks for the help and apologies if this isn’t the right place for this type of question.

Edit: GitHub repository if helpful.

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In the github repository, there is a link to their user’s forum: That is the place where you should ask questions about streamlit.

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Welcome to Python!

I hope you will discover each day how great Python can be, especially in data science. I’m not familiar with Streamlit. Traditionally, I would recommend installing Anaconda and starting with standard scipy libraries (Pandas, Numpy, Matplotlib, etc.). Streamlit likely wraps these tools and seems to focus on ease and visualization.

It’s a bit too new to give a solid recommendation (< 1 year old). If you did start there, you would likely become the expert, and we would ask you about it. :slightly_smiling_face:

It looks fascinating enough to try. Let us know how it works out.


Thanks @pylang for the feedback :relaxed:. It’s been working well so far, there are a lot of user articles/how-to guides written so learning about it has been relatively easy. Found a short YouTube series from one of the creators of Streamlit that’s pretty cool.

Also, I’ve started looking more into Anaconda as well as the scipy libraries! I’ll keep you updated if I find out anything else.

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That’s great to hear!

Yes one of the wonderful things about Python in this era is that there are a lot of materials online on nearly any topic. See also, which gathers a number of talks and deeper tutorials, especially on the scipy stack.

Anaconda can be your best friend through this process, particularly on:

  • Installing versions of Python
  • Installing bulky packages (numpy, scipy, etc.) via > conda install
  • Installing packages via pip install
  • Managing virtual environments

Keep us posted.