Streamlit’s built-in visualization options

For the rest of this chapter, we’re going to run through the rest of the Streamlit visualization options, which are Plotly, Matplotlib, Seaborn, Bokeh, Altair, and PyDeck.

Plotly

Plotly is an interactive visualization library that many data scientists use to visualize data in a Jupyter notebook, either locally in the browser or even hosted on a web platform such as Dash (the creator of Plotly). This library is very similar to Streamlit in its intent and is primarily used for internal or external dashboards (hence, the name Dash).

Streamlit allows us to call plotly graphs from within Streamlit apps using the st.plotly_chart() function, which makes it a breeze to port any Plotly or Dash dashboards. We’ll test this out by making a histogram of the height of trees in SF, essentially the same graph that we’ve made before. The following code makes our Plotly histogram:

import streamlit as st
import...