Project Title: Data-Driven Automobile Marketing Analysis Dashboard

This project intends to be an interactive, data-based automobile marketing analysis dashboard. Using Python, the Dash library, and Plotly, this data visualization tool provides visually presented information on automotive sales trends, advertising expenditure, and their relation to economic factors such as recession or unemployment rates.

Key Features

• Interactive Data Visualisation: The dashboard provides a user interface where users can select data visualization based on different metric views like 'Yearly Statistics' or 'Recession Statistics'.

• Dash Web Interface: The application uses the Dash framework in Python to create an interactive web-based platform.

• Data Exploration: Using Python's data analysis tools (such as pandas and Plotly), the application examines a dataset that spans several years and car types to provide insights into factors affecting automobile sales and their economic importance.

• Customizable Visualizations: Users can select different statistics types from a drop-down, and depending upon the selection, another input for the year is enabled or disabled to explore the visualized data further.

• Various Chart Types: The application uses line graphs, bar charts, and pie charts to represent data from different perspectives.

• Reactive Environment: Built-in with reactive programming, the graphs on the dashboard respond to inputs provided by the user.

Dependencies

This project requires Python 3 and the following Python libraries installed:

• Dash
• Pandas
• Plotly

Getting Started

1. Clone or download the repository.

git clone https://github.com/jimmyMsh/PythonStatsVisualPractice.git

2. Navigate to the downloaded directory and install the required Python packages.

cd PythonStatsVisualPractice
pip install -r requirements.txt

3. Run the Dash app.

python PythonStatsVisualPractice.py

This will start a local server. Navigate to the provided URL to interact with the application.

Purpose

The primary aim of developing this application was to gain proficiency in data manipulation and visualization using Python libraries like Pandas and Plotly and to build an interactive web interface using the Dash framework. This project incorporates various aspects of data analysis and web development, including data cleaning, data visualization, implementation of user interfaces, and hosting dashboards on a web interface.