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Streamlit for Data Science - Second Edition

You're reading from  Streamlit for Data Science - Second Edition

Product type Book
Published in Sep 2023
Publisher Packt
ISBN-13 9781803248226
Pages 300 pages
Edition 2nd Edition
Languages
Author (1):
Tyler Richards Tyler Richards
Profile icon Tyler Richards

Table of Contents (15) Chapters

Preface An Introduction to Streamlit Uploading, Downloading, and Manipulating Data Data Visualization Machine Learning and AI with Streamlit Deploying Streamlit with Streamlit Community Cloud Beautifying Streamlit Apps Exploring Streamlit Components Deploying Streamlit Apps with Hugging Face and Heroku Connecting to Databases Improving Job Applications with Streamlit The Data Project – Prototyping Projects in Streamlit Streamlit Power Users Other Books You May Enjoy
Index

Setting up the SF Trees dataset

For this chapter, we will be working with the SF Trees dataset again, the same dataset that we used in Chapter 3, Data Visualization. As we did in the previous chapters, we need to follow this list of steps for the setup:

  1. Create a new folder for the chapter.
  2. Add our data to the folder.
  3. Create a Python file for our app.

Let’s see each of these steps in detail.

In our main streamlit_apps folder, run the following code in your terminal to make a new folder cleverly called pretty_trees. You can also create a new folder manually outside the terminal:

mkdir pretty_trees

Now, we need to move our data from Chapter 3, Data Visualization, into our folder for this chapter. The following code copies the data into the correct folder:

cp trees_app/trees.csv pretty_trees

If you do not have the trees_app folder and have not yet completed Chapter 3, Data Visualization, you can also download the necessary...

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