01. Getting Started with Streamlit (Setup)

Beginner20 minutes

1. What is Streamlit?

Streamlit is an open-source app framework for data analysts. You can create data dashboards with pure Python code without complex web frontend knowledge (HTML, CSS, JS).

Features

Python Only: You just need to know Python syntax.
Interactive: Easily add buttons, sliders, input fields, etc.
Fast: The web page refreshes instantly when you save your code.

2. Installation and Environment Setup

First, you need to install the Streamlit library.

❓ Problem 1: Install Streamlit

Q. Open the Terminal and use pip to install streamlit.

Terminal


pip install streamlit

To verify the installation was successful, run the following command:


streamlit hello

3. Hello World!

Let’s create your first app.

❓ Problem 2: Run First App

Q. Create a file called app.py and display a large title saying “Hello, Analyst!” on the screen.

Step 1: Create Python File

Create an app.py file in your working directory.

Step 2: Write Code

Copy and paste the following code into app.py.


import streamlit as st
import pandas as pd
 
# Write title
st.title("My First Dashboard 📊")
 
# Write text
st.write("Hello, Analyst! Welcome to the world of data analysis.")

Step 3: Run App

Run the following command in the terminal.


streamlit run app.py

A browser will automatically open and show you the results.

4. Displaying DataFrames

Displaying the DataFrame - the output of your analysis - beautifully is key.

❓ Problem 3: DataFrame Visualization

Q. Add code to app.py to read a CSV file or create a sample DataFrame and display it on the screen.

Python (Streamlit)

💡

Hint: Using st.dataframe() creates a table with sorting and filtering capabilities.


# (Continue writing in app.py)
 
st.header("1. Data Overview")
 
# Create sample data
data = {
    'Product': ['Shirt', 'Pants', 'Hat'],
    'Price': [25, 40, 15],
    'Stock': [100, 50, 200]
}
df = pd.DataFrame(data)
 
# Display DataFrame
st.dataframe(df)
 
# Tip: st.table() might look cleaner for small tables.
st.subheader("Static Table")
st.table(df)

💡 Summary

pip install streamlit: Installation only takes once.
streamlit run app.py: Command to run the app.
st.title(), st.write(), st.dataframe(): The three most commonly used functions.

In the next chapter, we’ll use Sidebar and Columns to create a layout that looks like a real dashboard.