S&P500 Trends Visualizations & Analysis with Preswald

Amrutha Gujjar•March 22, 2025•3 min read

Community Showcase: S&P 500 Data Analysis with Preswald

We're thrilled to feature Vidyuth Sridhar in this edition of the Preswald Community Showcase! 🎉 Vidyuth has built an impressive Preswald app that analyzes and visualizes S&P 500 stock market data using interactive charts and tables.

🌟 Project Overview

📊 Preswald and Analytics

This blog explores how Preswald utilizes analytics to track stock market trends, providing insights into historical performance, sector-wise growth, and market volatility through dynamic visualizations.

Project Name: S&P 500 Market Explorer
Built by: Vidyuth Sridhar
Dataset: S&P 500 dataset

Check out the project on GitHub

📊 Description

Vidyuth's project provides an interactive dashboard for exploring S&P 500 stock market trends. The app allows users to:

Filter stocks by sector, market cap, and performance metrics.
Visualize trends using Plotly charts to analyze stock price movements and volatility.
Compare companies dynamically in an interactive table.
Gain insights into historical trends and investment opportunities.

With Preswald, Vidyuth has created a seamless user experience, where users can dynamically adjust inputs and get instant updates without writing frontend code.

🚀 Code Snippets

Here’s a sneak peek at how Vidyuth's project is structured:

Loading the Data

from preswald import connect, get_df, text

connect()  # Establish connection to data

# Load S&P 500 dataset
sp500_df = get_df("sp500_data")

Creating an Interactive Market Trend Chart

from preswald import plotly
import plotly.express as px

fig = px.line(sp500_df, x='date', y='closing_price', color='company',
             title='S&P 500 Market Trends Over Time')
plotly(fig)

Displaying S&P 500 Data in a Table

from preswald import table

table(sp500_df[['company', 'sector', 'market_cap', 'closing_price']])

With just a few lines of Python, Vidyuth has built a fully interactive data app powered by Preswald! 🚀

What is Preswald?

Preswald is an open-source framework for building data apps, dashboards, and internal tools with just Python. It provides pre-built UI components like tables, charts, and forms, so you don't have to write frontend code. Users can interact with your app, changing inputs, running queries, and updating visualizations, without you needing to manage the UI manually.

Preswald tracks state and dependencies, making computations efficient by updating only when necessary. It uses a workflow DAG to manage execution order, ensuring performance and predictability. Preswald allows you to turn Python scripts into shareable, production-ready applications easily.

Key Features

Add UI components to Python scripts: user-interactive buttons, text inputs, tables, and charts.
Stateful execution with automatic state tracking and updates.
Structured computation using a DAG-based execution model.
Deploy with a single command.
Query and display live data from various sources.
Build interactive reports and dashboards.
Easy local or cloud hosting.
Shareable via a simple link.

🚀 Getting Started

Installation

First, install Preswald via pip: https://pypi.org/project/preswald/

pip install preswald

👩‍💻 Quick Start

1. Initialize a New Project

To start using Preswald, initialize a new project:

preswald init my_project
cd my_project

This creates a folder my_project with essential files:

hello.py: Your first Preswald app.
preswald.toml: Settings for your app.
secrets.toml: Secure sensitive information.
.gitignore: Keep secrets.toml safe from version control.

2. Write Your First App

Open hello.py and write:

from preswald import text, plotly, connect, get_df, table
import pandas as pd
import plotly.express as px

text("# Welcome to Preswald!")
text("This is your first app. 🎉")

# Load CSV data
connect() # loads default sample CSV
df = get_df('sample_csv')

# Create a scatter plot
fig = px.scatter(df, x='quantity', y='value', text='item',
                 title='Quantity vs. Value')
fig.update_traces(textposition='top center')
fig.update_layout(template='plotly_white')

# Show plot and data
table(df)

3. Run Your App

Launch the app with:

preswald run

4. Deploy Your App to the Cloud

Deploy your app using:

preswald deploy --target structured

Your app will be built and accessible online.

Huge Thanks to Vidyuth Sridhar!

A big thank you to Vidyuth Sridhar for sharing their work and inspiring the Preswald community! Want to see more of their work? Check them out on GitHub.

Want to Contribute?

Got a cool idea for a Preswald app? We'd love to see it! Get started here: https://github.com/StructuredLabs/preswald and get featured in our next Community Showcase.

Happy building! 🚀

#community