LGAI-DILab/ReTabAD

Anomaly Detection Datasets

Collection of 20 preprocessed datasets for anomaly detection research.

Structure

Each dataset directory contains:

• {dataset}.csv - cleaned datapoints ready for analysis
• {dataset}.json - dataset description and metadata
• preprocess.py - data preparation script (filtering NA, normalization, etc.)

Datasets

25 datasets with varying characteristics:

• Size: 80 to 50,000 datapoints
• Features: 6 to 42 columns
• Anomaly ratio: 0.4% to 33.3%

See dataset_statistics.csv for complete overview.

Usage

import pandas as pd
data = pd.read_csv('final_data/{dataset_name}/{dataset_name}.csv')