Understanding Data

Description

Understanding Data is a comprehensive project aimed at showcasing various data analysis and visualization techniques using Python, HTML, CSS, Dockerfile, and Shell scripting. This project is designed to help users understand data manipulation, analysis, and presentation skills that are valuable for data science and web development roles.

Note

For Demo Watch the video on YouTube

Table of Contents

1. Installation
2. Usage
3. Features
4. Technology Stack
5. Skills Demonstrated

Installation

1. Clone the repository:

git clone https://github.com/VictoriousMango/Understanding-Data.git

2. Navigate to the project directory:

cd Understanding-Data

3. Install the required dependencies:

pip install -r requirements.txt

Usage

Run the main script to start the data analysis:

python main.py

Open the index.html file in your browser to view the visualizations.

Features

• Data Cleaning and Preprocessing
• Data Analysis
• Data Visualization
• Docker Containerization
• Shell Scripting for Automation

Technology Stack

• Python: Used for data manipulation, analysis, and visualization.
• HTML & CSS: Used for presenting the data visualizations in a web format.
• Dockerfile: Used for containerizing the application.
• Shell: Used for automating tasks.

Skills Demonstrated

• Python: Proficiency in data manipulation libraries such as Pandas and NumPy, as well as data visualization libraries like Matplotlib and Seaborn.
• Web Development: Skills in HTML and CSS for creating interactive and responsive data visualization web pages.
• Containerization: Experience with Docker to containerize applications for consistent environments across development, testing, and production.
• Automation: Proficiency in Shell scripting for automating repetitive tasks.