"Data Cleaning & Exploratory Data Analysis Project"

Alexandria University

Faculty of Computers and Data Science

Data Science Methodology Fall 2025

Final Project

Project Overview:

In this project, teams of 3-5 members will collaborate to collect, inspect, clean, and analyze a dataset.

Tasks:

1. Data Collection:

Collect data using web scraping or APIs. Ensure that the data is realistic and may contain

inconsistencies or errors that require cleaning.

2. Data Inspection:

Examine the collected data to identify issues such as missing values, outliers, duplicates, or

inaccurate entries.

3. Data Cleaning:

Apply appropriate cleaning techniques to correct or handle the issues found during your data

inspection and document the cleaning process.

4. Exploratory Data Analysis (EDA):

Perform an in-depth analysis to explore the structure and characteristics of the data. Use

descriptive statistics and visualizations to identify patterns, trends, anomalies, and relationships

between features.

Deliverables:

Your submitted notebook must include:

i. Data collection process.

ii. An overview of the dataset, explaining the types and nature of features.

iii. A summary of the data inspection process and identified issues.

iv. A comparison of the dataset before and after cleaning.

v. Insights and visualizations from the EDA.

Deadline and Discussion:

Project Deadline: Friday, December 5th at 11:59 PM.

The discussions will be held between December 6th and December 11th. Exact time slots will be

announced later.