Overview

This assignment focuses on Exploratory Data Analysis (EDA), applying statistical and visualization techniques to understand the datasets.

Assignment Group: 39

Datasets

1. German Credit Risk Dataset (Kaggle Link)

• 1000 entries assessing individuals' credit risk (good/bad)
• Numerical & categorical attributes: age, job classification, housing, savings, credit amount, duration, purpose, etc.
• Reformatted for usability by omitting certain unclear columns.

2. Ultimate UFC Dataset

• ~5000+ UFC fights up to 2023
• 120+ features, including fighter metadata, fight metrics, event details, and outcomes
• Challenges: redundancy, missing values in fighter biographical data, early event inconsistencies

Key Objectives

• Perform univariate and bivariate analysis
• Utilize statistical summaries and visualizations
• Identify data quality issues (missing values, redundancy)
• Derive insights for decision-making