Getting Started with Streamlit: Build Your First Data App

📘 Introduction

Data scientists and analysts often struggle to share their work interactively. Whether it's model results or beautiful visualizations, the gap between code and a usable interface can be frustrating. That's where Streamlit comes in.

Streamlit is a powerful Python framework that turns your data scripts into shareable web apps with minimal effort. No front-end skills? No problem. In this tutorial, you'll learn how to install Streamlit, write your first app, and run it locally.

✅ Prerequisites

Before we start, make sure you have the following ready:

☑️ Python installed (3.8 or later)

✍️1️⃣ Install Streamlit

Let’s begin by installing Streamlit. Open your terminal and run:

pip install streamlit

To test if everything’s working, run:

streamlit hello

This opens a demo app in your browser and confirms Streamlit is installed correctly. ✅

💻2️⃣ Write Your First Streamlit Code

In your working directory, create a new file named app.py. This file will contain the code for your Streamlit app. Open it in your editor and paste the following code:

import streamlit as st
import pandas as pd
import numpy as np

st.title("My First Streamlit App 🎉")

st.write("Welcome to your first interactive data app!")

# Add a slider
points = st.slider("Select number of points", 10, 100)

# Generate random data
data = pd.DataFrame({
    'x': np.arange(points),
    'y': np.random.randn(points).cumsum()
})

# Show a line chart
st.line_chart(data.set_index('x'))