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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 FREE CHAPTER 2. Uploading, Downloading, and Manipulating Data 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

Flow control in Streamlit

As we talked about just before, there are two solutions to this data upload default situation. We can provide a default file to use until the user interacts with the application, or we can stop the app until a file is uploaded. Let’s start with the first option. The following code uses the st.file_uploader() function from within an if statement. If the user uploads a file, then the app uses that; if they do not, then we default to the file we have used before:

import altair as alt
import pandas as pd
import seaborn as sns
import streamlit as st
 
st.title("Palmer's Penguins")
st.markdown("Use this Streamlit app to make your own scatterplot about penguins!")
 
penguin_file = st.file_uploader("Select Your Local Penguins CSV (default provided)")
if penguin_file is not None:
    penguins_df = pd.read_csv(penguin_file)
else:
    penguins_df = pd.read_csv("penguins.csv")
 
selected_x_var = st.selectbox(
 ...
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