From Python Script to Personal App: Building Your Own Car Sales Dashboard with Streamlit

Tableau is excellent for data visualization, but sometimes I wanted to explore building custom analytics tools from scratch. And, Streamlit opens up new possibilities — allowing me to build a personalized analytics application that offers functionalities beyond traditional BI tools. Now I can have my own dashboard running locally with features tailored exactly to our business needs.

Today, I’ll walk you through how I built a professional car sales dashboard using Python and Streamlit. Let’s break down the key components that make this dashboard both functional and user-friendly.

1. Setting Up and Build Interactive Interface on Python

The foundation of my dashboard is efficient data loading and caching. I use Streamlit’s @st.cache_data decorator to prevent unnecessary reloading of data.

One of the dashboard’s strengths is its flexible viewing options, either Yearly or Monthly&Yearly. I implement this using Streamlit’s sidebar controls:

st.sidebar.header("🔍 Data View Options")
view_mode = st.sidebar.radio("Select View Mode:", ["Yearly", "Monthly & Yearly"])

if view_mode == "Yearly":
    selected_year = st.selectbox("📅 Select Year:"…