数据集获取

git clone https://github.com/NSSAC/IDOBE.git

curl -L -o repo.zip https://github.com/NSSAC/IDOBE/archive/refs/heads/main.zip
unzip repo.zip

源站 README 摘录（使用方式）

IDOBE: Infectious Disease Outbreak forecasting Benchmark Ecosystem

Overview

IDOBE is a curated collection of epidemiological time series focused on outbreak forecasting. IDOBE compiles from multiple data repositories spanning over a century of surveillance and across U.S. states and global locations. This repository provides

• Over 10000 outbreak timeseries corresponding to different diseases
• Scripts for extracting analytical measures to analyze outbreaks
• A suite of trained baseline forecasting models (statistical and DNN models)
• Evaluation scripts of probabilistic forecasts

For more information about the dataset, data sources, outbreak segmentation techniques, and the baselines models, see https://arxiv.org/abs/2604.18521

Data

• raw_data/outbreaks_disease_location.csv

Data statistics

• stats/output/ - consists of entropy, permutation entropy, and shape statistics for the different outbreaks
• stats/stats_compute.ipynb - notebook for computing the different statistics

Baseline models

• baselines/src/ - folder contains different classes of models
  Shield: [![CC BY 4.0][cc-by-shield]][cc-by]
  This work is licensed under a
  [Creative Commons Attribution 4.0 International License][cc-by].
  [cc-by]: http://creativecommons.org/licenses/by/4.0/
  [cc-by-image]: https://i.creativecommons.org/l/by/4.0/88x31.png
  [cc-by-shield]: https://img.shields.io/badge/License-CC BY 4.0-lightgrey.svg

数据加载示例（表格/文本类）

import pandas as pd, glob, os

files = (glob.glob(os.path.join(path, "**", "*.csv"), recursive=True)
       + glob.glob(os.path.join(path, "**", "*.tsv"), recursive=True)
       + glob.glob(os.path.join(path, "**", "*.xlsx"), recursive=True))
print("数据文件:", files)
df = pd.read_csv(files[0])
print(df.shape); print(df.columns.tolist()); print(df.head(3))

完整仓库：github.com/NSSAC/IDOBE