- February 14, 2024
- Posted by: Alfred Romario
- Categories: Analytics, Data Visualization, Streamlit
INTRODUCTION TO STREAMLIT
Streamlit is a free and open-source framework to rapidly build and share beautiful machine learning and data science web apps. It is a Python-based library specifically designed for machine learning engineers.
Why Streamlit?
Data scientists and machine learning engineers, distinct from web developers, might not be able to spend weeks mastering complex frameworks for web app development. Instead, they seek user-friendly tools that efficiently display data and collect necessary parameters for modeling. Streamlit offers a solution by allowing the creation of visually appealing applications with just a few lines of code, meeting their requirements effectively.
Prerequisites:
- Any python module (Anaconda, Jupyter, VSCode etc)
- Streamlit library (latest version recommended)
- Github account
Streamlit Libraries:
Installation
Importing libraries in Python
Streamlit app using Python:
The streamlit app was developed using python (VScode) using streamlit libraries and other basic python libraries. The data was imported and cleaned in python, which helped to arrive to a meaningful and clean dataset.
- Basic feature engineering
Creating new features from already existing variables to provide more insightful visualization.
- Build KPIs and Charts
Deploy app:
After developing a streamlit app,
Step 1: Set up an account on Community Cloud
Step 2: Connect your account to GitHub.
Step 3: Create a GitHub repo of your app.
Step 4: Deploy the app from streamlit community cloud via github.
About the Dashboard:
This dashboard is based on a sample dataset from Kaggle. The data consists of an automobile company’s product sales, along with the customer details and order dates. The dashboard consists of KPIs, Tables and Charts to give a clear understanding of the company’s sales. The dashboard is created using python and streamlit.
The dashboard can be sliced and filtered based on Automobile Product and Years with the help of filters.
App link : https://bhanwec6z9ut7yduhvlaqz.streamlit.app/
Git link : https://github.com/gitalf96/Sales
Please feel free to get in touch with us regarding your Streamlit solution needs. Our Streamlit solutions encompass a range of services and tools designed to streamline your data visualization, quick prototyping and dashboard development processes.