Save any file in the same folder as your Python script or Jupyter notebook. Then use pd.read_csv("filename.csv") or pd.read_excel("filename.xlsx") to load it.
House prices and features (area, bedrooms, bathrooms, mainroad, guestroom, etc.). Used in Linear Regression and Statistics.
Hotel booking data. Used in Statistics (Chi-Square, T-Test), Hypothesis Testing, Missing Values & Outliers, Clustering.
A/B test results (conversion fractions for variant A and B over days). Used in A/B Testing lesson.
Market basket (shopping cart) transactions. Used in Market Basket Analysis with Apriori.
Excel file for Apriori / market basket practice. Used with Market Basket Analysis.
Car data: mpg, cylinders, horsepower, weight, etc. Used in Regularization (Ridge/Lasso) and Bias–Variance.
Car evaluation: buying price, maintenance, doors, persons, lug_boot, safety → class (unacc/acc/good/vgood). Used in Random Forest Code Walkthrough.
Health metrics and diabetes outcome. Used in Explainable AI (feature importance, SHAP).
Heart disease risk factors and outcome. Used in Logistic Regression (classification).
Alternative classification dataset (same structure as heart disease). Use for Logistic Regression practice.
Insurance-related data. Used in assignments and regression practice.
Titanic passenger data (Excel). Used in Statistics and practice.
Practice exercises in Excel. Used with Statistics and Maths lessons.
All datasets are part of the FKTI Data Science curriculum. Use them only for learning.