Python Data Visualization Transcripts
0:00 Let's discuss how to get your streamlit environment set up, fortunately you can install stream lit using pip as we've done in previous exercises.
0:08 You can use python -m Pip install streamlit and everything should be ready to go in your environment.
0:14 One thing I wanted to call out is that streamlit does have its own native plot types. Some basic plot types,
0:20 such as line and bar charts and geographic charts are available. I'm not going to cover that.
0:24 So for this course will focus on the libraries that we've already reviewed.
0:27 As I mentioned, streamlit is a very recently developed library and it is constantly evolving
0:33 and improving. I encourage you to take a look at some of the beta features
0:37 and evaluate those and look at the documentation to see if there are improvements to the
0:43 code that have been made that you may want to incorporate your own visualizations.
0:47 And then finally, there is a library of third party apps that provide additional specialized
0:52 functionality. You can view those at the URL on the screen.