Pizza Sales Data Analysis

# ? Pizza Sales Data Analysis (Python & Excel)

## ? Project Overview

This project analyzes a pizza sales dataset using **Python and Excel** to uncover key business insights such as revenue trends, best-selling pizzas, and customer behavior.

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## ? Dataset Description

The dataset includes:

* `order_id` → Unique ID for each order

* `pizza_name` → Name of the pizza

* `pizza_category` → Category (Classic, Supreme, Chicken, Veggie)

* `pizza_size` → Size (S, M, L, XL)

* `quantity` → Number of pizzas ordered

* `unit_price` → Price per pizza

* `total_price` → Total order value

* `order_date` → Order date

* `order_time` → Order time

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## ? Objectives

* Identify most popular pizzas ?

* Analyze revenue by category ?

* Detect peak order times ⏰

* Track monthly sales trends ?

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## ?️ Tools Used

### ? Python

* Pandas → Data cleaning & analysis

* Matplotlib → Visualization

### ? Excel

* Pivot Tables

* Charts (Bar, Line, Pie)

* Data Cleaning

* Basic KPIs

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## ? Analysis Performed

### In Python:

* Top 5 pizzas by revenue

* Top 5 pizzas by quantity

* Revenue by category

* Sales by month, day, and hour

### In Excel:

* Pivot tables for category & revenue

* Monthly sales trends

* Category distribution charts

* KPI dashboard

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## ? Key Insights

* Classic category generates the highest revenue

* Some pizzas are popular but low in profit

* Peak ordering hours are in the evening

* Sales show variation across months

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## ? How to Use

### Python:

1. Load dataset using Pandas

2. Clean and transform data

3. Run analysis scripts

4. Visualize results

### Excel:

1. Open the dataset in Excel

2. Create Pivot Tables

3. Build charts for insights

4. Design a simple dashboard

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## ? Future Improvements

* Build interactive dashboard (Power BI)

* Apply Machine Learning for predictions

* Automate reports

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## ?‍? Author

Ismail Wassal (Python)

Mohamed Abdelghany (Excel)