Applied Data Science — teaching datasets

Public datasets for the Applied Data Science course. Load them directly in Google Colab or any Python session:

import pandas as pd
sales = pd.read_csv("https://ads.hockinhte.com/data/uci_online_retail_ii/online_retail_course_extract.csv",
                    parse_dates=["invoice_date"])

Files ending .gz are read the same way — pandas decompresses them automatically.

Files

Path	Used in
`sim_service_retention/service_retention.csv`	Session 1
`sim_service_retention/decision_context.csv`	Session 1
`sim_service_retention/oracle_benchmark.csv`	Session 1
`uci_online_retail_ii/online_retail_course_extract.csv`	Sessions 2, 3
`uci_online_retail_ii/online_retail_customer_history_extract.csv.gz`	Session 7
`sim_retail_operations/*.csv, supplier_status.html, support_events.json`	Session 3
`uci_seoul_bike/seoul_bike_hourly.csv`	Session 4
`uci_bank_marketing/bank_marketing_additional_full.csv.gz`	Sessions 5, 6
`uci_bank_marketing/feature_timing.csv, base_rate_by_split.csv`	Sessions 5, 6
`uci_har_smartphone/human_activity_windows.csv.gz`	Sessions 8, 9
`uci_har_smartphone/feature_catalog.csv, subject_assignment.csv`	Sessions 8, 9

Sources and licence

UCI Machine Learning Repository datasets (Online Retail II, Bank Marketing, Seoul Bike Sharing Demand, Human Activity Recognition) are redistributed under CC BY 4.0. The sim_ packages are simulated teaching data created for this course and are fictional.