streamlit example

[gyliu513]

PR Type

enhancement

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Description

• Added a new Streamlit application example.
• Displayed a title and introductory text using st.title and st.write.
• Created a DataFrame with sample data and displayed it using st.write.
• Generated a random DataFrame and displayed it as a line chart using st.line_chart.

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Changes walkthrough 📝

	Relevant files
Enhancement	streamlit-example.py Add a simple Streamlit application example                              streamlit-test/streamlit-example.py Added a new Streamlit application example. Displayed a title and introductory text. Created a DataFrame and displayed it. Generated and displayed a random line chart. +19/-0

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Summary by CodeRabbit

• New Features
  • Introduced a Streamlit application that showcases basic functionalities, including displaying a title, introductory text, and a DataFrame.
  • Added a random chart visualization to enhance user interaction with data.

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Walkthrough

This update introduces a new Streamlit application, showcasing its core functionalities. The app features a title and introductory text, displays a DataFrame with two columns, and visualizes random data through a line chart. This implementation highlights Streamlit's capabilities for interactive data presentation and analysis.

Changes

Files	Change Summary
streamlit-test/streamlit-example.py	Introduced a simple Streamlit app with title, text, DataFrame display, and line chart visualization.

Poem

🐰 In a garden of code where the data blooms,
A Streamlit app dances, dispelling the glooms.
With charts that wiggle and DataFrames neat,
Jump in, dear user, and feel the sweet beat!
Let numbers and colors together play,
In this wondrous world, come join the display! 🌼

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[github-actions]

PR Reviewer Guide 🔍

⏱️ Estimated effort to review: 2 🔵🔵⚪⚪⚪

🧪 No relevant tests

🔒 No security concerns identified

⚡ No key issues to review

[github-actions]

PR Code Suggestions ✨

Category	Suggestion	Score
Enhancement	Use np.random.normal to explicitly set the distribution parameters Replace the use of np.random.randn with np.random.normal to specify mean and standard deviation explicitly for clarity and control. streamlit-test/streamlit-example.py [15] -np.random.randn(20, 3), +np.random.normal(loc=0, scale=1, size=(20, 3)), Suggestion importance[1-10]: 8 Why: This suggestion provides better clarity and control over the random data generation by explicitly setting the mean and standard deviation, which is a meaningful enhancement.	8
Maintainability	Refactor hardcoded DataFrame into a function for better modularity Replace the hardcoded DataFrame with a function that generates the DataFrame. This will make the code more modular and easier to update or reuse. streamlit-test/streamlit-example.py [8-11] -st.write(pd.DataFrame({ - 'Column A': [1, 2, 3, 4], - 'Column B': [10, 20, 30, 40] -})) +def create_dataframe(): + return pd.DataFrame({ + 'Column A': [1, 2, 3, 4], + 'Column B': [10, 20, 30, 40] + }) +st.write(create_dataframe()) Suggestion importance[1-10]: 7 Why: This suggestion improves code modularity and reusability by refactoring the hardcoded DataFrame into a function. However, it is not crucial for the functionality of the code.	7
Readability	Store DataFrame in a variable before using it to improve readability Use a variable to store the DataFrame before passing it to st.write to enhance readability and debugging. streamlit-test/streamlit-example.py [8-11] -st.write(pd.DataFrame({ +data = pd.DataFrame({ 'Column A': [1, 2, 3, 4], 'Column B': [10, 20, 30, 40] -})) +}) +st.write(data) Suggestion importance[1-10]: 6 Why: Storing the DataFrame in a variable enhances readability and makes debugging easier, but it is a minor improvement and not essential for the code's functionality.	6