We're thrilled to feature Vinit in this edition of the Preswald Community Showcase! 🎉 Vinit has built an impressive Preswald app that analyzes and visualizes Airbnb listings data using interactive charts and tables.
🌟 Project Overview
📊 Preswald and Analytics
This blog explores how Preswald utilizes analytics to examine Airbnb trends, providing insights into pricing patterns, occupancy rates, and location-based demand through dynamic visualizations.
Project Name: Airbnb Analytics Explorer
Built by: Vinit Shah
Dataset: Airbnb dataset
Check out the project on GitHub
📊 Description
Vinit's project provides an interactive dashboard for exploring Airbnb trends. The app allows users to:
- Filter listings by location, price range, and property type.
- Visualize trends using Plotly charts to analyze rental pricing and availability.
- Compare Airbnb properties dynamically in an interactive table.
- Gain insights into market demand and optimal pricing strategies.
With Preswald, Vinit 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 Vinit's project is structured:
Loading the Data
from preswald import connect, get_df, text
connect() # Establish connection to data
# Load Airbnb dataset
airbnb_df = get_df("airbnb_listings")
Creating an Interactive Pricing Chart
from preswald import plotly
import plotly.express as px
fig = px.scatter(airbnb_df, x='price', y='number_of_reviews', color='location',
title='Airbnb Pricing vs. Reviews')
plotly(fig)
Displaying Airbnb Listings in a Table
from preswald import table
table(airbnb_df[['name', 'location', 'price', 'room_type', 'availability_365']])
With just a few lines of Python, Vinit 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: Keepsecrets.tomlsafe 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 Vinit Shah!
A big thank you to Vinit 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! 🚀
