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Streamlit for Data Science

You're reading from   Streamlit for Data Science Create interactive data apps in Python

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Product type Paperback
Published in Sep 2023
Publisher Packt
ISBN-13 9781803248226
Length 300 pages
Edition 2nd Edition
Languages
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Author (1):
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Tyler Richards Tyler Richards
Author Profile Icon Tyler Richards
Tyler Richards
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Table of Contents (15) Chapters Close

Preface 1. An Introduction to Streamlit 2. Uploading, Downloading, and Manipulating Data FREE CHAPTER 3. Data Visualization 4. Machine Learning and AI with Streamlit 5. Deploying Streamlit with Streamlit Community Cloud 6. Beautifying Streamlit Apps 7. Exploring Streamlit Components 8. Deploying Streamlit Apps with Hugging Face and Heroku 9. Connecting to Databases 10. Improving Job Applications with Streamlit 11. The Data Project – Prototyping Projects in Streamlit 12. Streamlit Power Users 13. Other Books You May Enjoy
14. Index

Creating drill-down graphs with streamlit-plotly-events

One of the most popular advanced features in any plotting library is the ability to drill down into sections or parts of graphs. The users of your apps will often have questions about your data that you have not anticipated in advance! Instead of creating new Streamlit inputs around graphs, users often will want to click on items in your graphs like points or bars, and get more information about that point. For example, in our penguins scatterplot graph, a user might want to see all the data available for a penguin, which is represented by a point being scrolled over in a DataFrame.

streamlit-plotly-events turns the unidirectional st.plotly_chart function into a bidirectional one, where we can receive events like clicks or hovers back into our Streamlit app. To test this out, we will create another app inside the pages folder, this one called plotly_events and will create a graph based on the penguins dataset.

To start...

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