🏭VAHAN 2.0

A data-driven dashboard to analyze and visualize vehicle registration trends in India using Streamlit, Pandas, and NumPy.
This project processes raw vehicle registration data, performs aggregations, and presents interactive visualizations for market insights.

RESULT

output.mp4

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📈 key Investor Insights I discovered

Segment	Insight
EV Market	EVs form only 2.5% of total registrations, showing huge growth potential but still early-stage adoption.
Two-Wheelers	74.2% of all registrations are two-wheelers, highlighting a larger and more stable market than passenger cars.

📦 Setup Instructions

Follow the steps below to run the project locally:

1️⃣ Clone the repository

git clone https://github.com/galaxyhub9/VAHAN-2.0.git

2️⃣ Navigate to the 'test' directory

cd VAHAN-2.0/test

3️⃣ Create a virtual environment

python -m venv venv

4️⃣ Activate the virtual environment

Windows

venv\Scripts\activate

Mac/Linux

source venv/bin/activate

5️⃣ Install dependencies

pip install -r requirements.txt

6️⃣ Run the Streamlit dashboard

streamlit run vahan.py

📊 Data Assumptions

• Source: Data has been downloaded from the official VAHAN Dashboard.

• Data Preparation:

  • Data is dowmloaded in excel format.
  • Added a Year column for each dataset.
  • Converted it into DataFrame using pandas.
  • Aggregated monthly and yearly data into separate files for better modularity.
  • Data of year 2020 to 2022 has been used.
  • All datasets are cleaned and structured for easier analysis in the dashboard.

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🚀 Feature Roadmap

If the project is continued, the following features will be added:

1. Predictive Market Analysis

   • Use historical trends to forecast future market share for each vehicle category.

2. Advanced Filtering Options

   • More granular filters such as fuel type, region, manufacturer, and time period.

3. Data Source Integration

   • Automated scraping or API integration to fetch the latest VAHAN data directly.

4. Export & Reporting

   • Option to export visualizations and reports as PDF/Excel.

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🛠 Tech Stack

• Python → Data processing & dashboard logic
• Pandas & NumPy → Data cleaning, transformation, and aggregation
• Streamlit → Interactive UI for visualization