Python Data Visualization Transcripts
Chapter: Course Conclusion
Lecture: Streamlit

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0:00 The next tool we looked at was Streamlit, which provides a small but powerful API for adding interactivity to your visualizations.
0:10 You can create your visualization with plotly or other tools and then use Streamlit
0:16 to create a standalone app to display that visualization. Streamlit is a great place for adding
0:23 interactivity to visualizations that you've already created with another tool, such as Plotly or Seaborn.
0:30 It does have a somewhat limited widget and customization capability right now,
0:34 but Streamlit was purchased by Snowflake and is getting continually updated. So I encourage you to come back and check in on it and see if it
0:43 meets your needs, if you have complex layout needs that seems like it can't meet today.

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