🐍 Python - Kiwilytics Project

This repository contains a Python project developed as part of the Kiwilytics Data Engineering Course.
The project demonstrates practical data analysis and manipulation techniques using Python and Pandas.

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📘 Project Overview

The goal of this project is to perform essential data engineering tasks, including:

• Handling missing values
• Calculating total prices and revenues
• Grouping and aggregating data
• Identifying insights such as top-selling products and highest-spending customers

All tasks were implemented in a Jupyter Notebook to demonstrate the workflow clearly.

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🧩 Main Tasks Performed

1. Data Cleaning and Handling Missing Values

   • Filled missing unit_price values using the average price per product.

2. Feature Engineering

   • Created a new column total_price by multiplying unit_price and quantity.

3. Revenue Calculation

   • Calculated total revenue across all orders.

4. Data Analysis and Insights

   • Identified which product has the highest total quantity sold.
   • Determined which customer has the highest total spending.

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🛠️ Tools and Libraries Used

• Python 3
• Pandas
• Jupyter Notebook

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🧠 Skills Demonstrated

• Data cleaning and transformation
• Use of groupby(), fillna(), and transform() in Pandas
• Logical problem solving for real-world data engineering tasks

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🧩 Dataset

The dataset used in this project is stored in the /data folder: data/kiwilytics_orders.csv

📝 The dataset was provided by the course instructors for educational purposes and does not contain any real or sensitive information.

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📂 Files in This Repository

File/Folder	Description
Kiwilytics-Python-Project.ipynb	Main Jupyter Notebook containing all Python code, data cleaning, and analysis
data/kiwilytics_orders.csv	Dataset used for the analysis (sample data provided by the course)
README.md	Project documentation, objectives, and instructions

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🚀 How to Run the Project

1. Clone or download this repository.
2. Open the Jupyter Notebook file: Kiwilytics-Python-Project.ipynb
3. Make sure the CSV file exists in the /data folder: data/kiwilytics_orders.csv
4. Run all notebook cells sequentially to reproduce the results.

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