Car Data Analysis using Streamlit

This repository contains a data analysis project on car sales data with a user-friendly interface created using Streamlit. The data was obtained from Kaggle.

The project is done using Python and its popular data analysis libraries such as Pandas, Matplotlib, Seaborn, and Streamlit.

Contents

• car_data.csv - raw data file.
• car_data_analysis.py - Python script for the Streamlit app.
• README.md - this file.

Installation

1. Clone the repository to your local machine.
2. Install the required libraries by running pip install -r requirements.txt in your terminal.

Usage

Run the following command in your terminal to start the Streamlit app:

streamlit run car_data_analysis.py

Open your web browser and go to the URL provided in the terminal to use the app.

Results

The analysis explores the car sales data to answer the following questions:

1. What are the top 10 car brands sold in the US?
2. Which brand has the maximum average price of cars?
3. Which body type of cars sold the most?
4. Which state has the most number of car sales?
5. What is the correlation between the car price and car mileage?
6. How does the price distribution vary with respect to body type?

The analysis is presented with descriptive statistics, visualizations, and insights in a user-friendly interface created using Streamlit.

This is My Web Application link: https://share.streamlit.io/athesh007/car_data_analysis/main/autoindus-analysis.py