Python Data Visualization Transcripts
Chapter: Streamlit
Lecture: Background

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0:00 Now let's go through a little bit of background about Streamlit. It was launched in october 2019,
0:06 so it's definitely one of the most recent libraries that we've talked about so far.
0:11 Streamlit is designed to allow you to make interactive visualizations with very little additional python
0:18 code. There's not a large API and then you can use the visualization tools like plotly, altair, mat
0:24 plotlib and others that we've already talked through to add interactivity to it.
0:29 You can build your dashboards using pandas data frames and the multiple visualization back ends.
0:34 There is a very small amount of code needed to create this visualization. Streamlit,
0:39 it is open source and it's full feature and actively maintained. The company behind
0:45 It does have commercial offerings that could be useful for you in the future.
0:50 As you decide, you need to deploy it on a larger scale. For your own analysis the open source framework is sufficient.

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