Datasets:
File size: 1,911 Bytes
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license: apache-2.0
tags:
- forecasting
- benchmark
- gifteval
- tsfile
- format:tsfile
- timeseries
task_categories:
- time-series-forecasting
pretty_name: temperature_rain_with_missing (GIFT-Eval, TsFile)
size_categories:
- 10K<n<100K
---
# temperature_rain_with_missing (TsFile)
Apache TsFile version of the **`temperature_rain_with_missing`** subset of
[GIFT-Eval](https://huggingface.co/datasets/Salesforce/GiftEval).
## Overview
GIFT-Eval is a benchmark for general time-series forecasting, covering 23 datasets
(≈144,000 series and 177M data points) across seven domains, ten frequencies, and a
range of forecast horizons. This repository contains a single subset of that benchmark.
**`temperature_rain_with_missing`** — Temperature and rainfall observations, including missing values (Monash).
All `.tsfile` files are stored under `data/`.
## Schema (TsFile structure)
- **Time** (INT64, milliseconds) — the timestamp of each observation.
- Each series is stored as a TsFile device; per-series identifiers from GIFT-Eval are
carried as TAG columns, and the observed values are FIELD columns.
## Usage
Read the `.tsfile` files with the Apache TsFile Java or Python SDK.
## Source & license
- Original dataset: [`Salesforce/GiftEval`](https://huggingface.co/datasets/Salesforce/GiftEval) — subset `temperature_rain_with_missing`
- Paper: [GIFT-Eval (arXiv:2410.10393)](https://arxiv.org/abs/2410.10393)
- Code: https://github.com/SalesforceAIResearch/gift-eval
- License: apache-2.0
If you use this data, please cite GIFT-Eval:
```bibtex
@article{aksu2024giftevalbenchmarkgeneraltime,
title={GIFT-Eval: A Benchmark For General Time Series Forecasting Model Evaluation},
author={Taha Aksu and Gerald Woo and Juncheng Liu and Xu Liu and Chenghao Liu and Silvio Savarese and Caiming Xiong and Doyen Sahoo},
journal={arXiv preprint arXiv:2410.10393},
year={2024}
}
```
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