datasets
Training and evaluation data, with the modality, task and licence stated up front. Listed live from the Hugging Face Hub.
Time-Series-Library
Time-Series-Library (TSLib)
TSLib is an open-source library for deep learning researchers, especially for deep time series analysis.
We provide a neat code base to evaluate advanced deep time series models or develop your model, which covers five mainstream tasks: long- and short-term forecasting, imputation, anomaly detection, and classification.
This benchmark collection is designed to evaluate and develop advanced deep time-series models. For an in-depth exploration of current… See the full description on the dataset page: https://huggingface.co/datasets/thuml/Time-Series-Library.time-series-datasettimeseries-daily-stocks
Dataset Card for "timeseries-daily-stocks"
More Information needed
africa-world-bank-economics-time-series
Africa World Bank Economics Labeled Time Series Data
This repository is part of the Africa Temporal Intelligence Corpus (ATIC). It contains sector-specific temporal corpus packages for African countries.
ATIC sector repositories are designed for machine consumption first: Parquet tables, stable IDs, reproducible metadata, explicit provenance, review status, and separable semantic layers.
Sector Scope
Temporal economic observations, proposed state labels, anomaly… See the full description on the dataset page: https://huggingface.co/datasets/africatic/africa-world-bank-economics-time-series.wikimedia-pageview-timeseries-raw
Wikimedia Pageview Time Series — full raw (wide format)
Full, unsampled Wikipedia pageview time series for every Wikimedia
project (Wikipedia, Wiktionary, Commons, etc.), stored as raw wide
parquet files: one row per article, one column per timestamp.
This is the complete derived output of the upstream pipeline —
the companion repo
jeremycochoy/wikimedia-pageview-timeseries
holds a sampled, reshaped version (3.7 M rows in HF long format
for training). Use this repo if you need the… See the full description on the dataset page: https://huggingface.co/datasets/jeremycochoy/wikimedia-pageview-timeseries-raw.africa-world-bank-governance-public-sector-time-series
Africa World Bank Governance and Public Sector Labeled Time Series Data
This repository is part of the Africa Temporal Intelligence Corpus (ATIC). It contains sector-specific temporal corpus packages for African countries.
ATIC sector repositories are designed for machine consumption first: Parquet tables, stable IDs, reproducible metadata, explicit provenance, review status, and separable semantic layers.
Sector Scope
Temporal governance, fragility, conflict, and… See the full description on the dataset page: https://huggingface.co/datasets/africatic/africa-world-bank-governance-public-sector-time-series.africa-world-bank-climate-environment-time-series
Africa World Bank Climate and Environment Labeled Time Series Data
This repository is part of the Africa Temporal Intelligence Corpus (ATIC). It contains sector-specific temporal corpus packages for African countries.
ATIC sector repositories are designed for machine consumption first: Parquet tables, stable IDs, reproducible metadata, explicit provenance, review status, and separable semantic layers.
Sector Scope
Temporal climate and environmental indicators for… See the full description on the dataset page: https://huggingface.co/datasets/africatic/africa-world-bank-climate-environment-time-series.us-layoffs-monthly-time-series-warn-act
US layoffs, month by month — 455 months of WARN notices, 1988-11 → 2026-09, rebuilt daily
Last rebuilt: 2026-09-25. One row per calendar month: how many US WARN Act layoff
notices were filed, how many workers they named, and how many states contributed —
as a regular series with every month present (zeros included), ready for pandas,
a chart or a forecasting model. A second table gives the same series per state.
455
consecutive months, 1988-11 → 2026-09, no gaps… See the full description on the dataset page: https://huggingface.co/datasets/APProjects/us-layoffs-monthly-time-series-warn-act.time-series-forecasting-datasetsmkdir -p dataset/ETT-small
mkdir -p dataset/electricity
mkdir -p dataset/traffic
mkdir -p dataset/weather
(
cd dataset
# -t 5: Retry up to 5 times on failure
# -nc: Skip download if file already exists (no-clobber)
# -q: Run quietly to suppress long logs (remove if not needed)
COMMON_ARGS="-t 5 -nc"
URL_PREFIX="https://huggingface.co/datasets/pkr7098/time-series-forecasting-datasets/blob/main"
wget $COMMON_ARGS $URL_PREFIX/ETTh1.csv &
wget $COMMON_ARGS… See the full description on the dataset page: https://huggingface.co/datasets/pkr7098/time-series-forecasting-datasets.africa-world-bank-energy-mining-time-series
Africa World Bank Energy and Mining Labeled Time Series Data
This repository is part of the Africa Temporal Intelligence Corpus (ATIC). It contains sector-specific temporal corpus packages for African countries.
ATIC sector repositories are designed for machine consumption first: Parquet tables, stable IDs, reproducible metadata, explicit provenance, review status, and separable semantic layers.
Sector Scope
Temporal energy indicators for African countries… See the full description on the dataset page: https://huggingface.co/datasets/africatic/africa-world-bank-energy-mining-time-series.timeseries-1m-QQQ-5yHigh_Dimensional_Time_Series
Dataset Card for Dataset Name
This dataset card aims to be a base template for new datasets. It has been generated using this raw template.
Dataset Details
Dataset Description
Curated by: [More Information Needed]
Funded by [optional]: [More Information Needed]
Shared by [optional]: [More Information Needed]
Language(s) (NLP): [More Information Needed]
License: [More Information Needed]
Dataset Sources [optional]
Repository: [More… See the full description on the dataset page: https://huggingface.co/datasets/Time-HD-Anonymous/High_Dimensional_Time_Series.africa-world-bank-agriculture-rural-time-series
Africa World Bank Agriculture and Rural Development Labeled Time Series Data
This repository is part of the Africa Temporal Intelligence Corpus (ATIC). It contains sector-specific temporal corpus packages for African countries.
ATIC sector repositories are designed for machine consumption first: Parquet tables, stable IDs, reproducible metadata, explicit provenance, review status, and separable semantic layers.
Sector Scope
Temporal agricultural indicators for… See the full description on the dataset page: https://huggingface.co/datasets/africatic/africa-world-bank-agriculture-rural-time-series.timeseries-daily-sp500africa-world-bank-health-population-time-series
Africa World Bank Health and Population Labeled Time Series Data
This repository is part of the Africa Temporal Intelligence Corpus (ATIC). It contains sector-specific temporal corpus packages for African countries.
ATIC sector repositories are designed for machine consumption first: Parquet tables, stable IDs, reproducible metadata, explicit provenance, review status, and separable semantic layers.
Sector Scope
Temporal health, nutrition, and population… See the full description on the dataset page: https://huggingface.co/datasets/africatic/africa-world-bank-health-population-time-series.NeuraxonLife2.5-100K-TimeSeries
NeuraxonLife2.5-100K-DeepTimeSeries: Artificial Life Neuraxon Neural Network Simulation Deep Time Series Dataset
Dataset Description
The NeuraxonLife 2.5 Deep Time Series Dataset is a massive, comprehensive collection of simulation data from the Neuraxon Game of Life environment. It tracks the evolution of over 100,000 autonomous agents ("NxErs") evolving biologically-plausible neural networks under survival pressures.
This dataset represents a significant expansion over… See the full description on the dataset page: https://huggingface.co/datasets/DavidVivancos/NeuraxonLife2.5-100K-TimeSeries.SP500-Financial-News-Articles-Time-SeriesTextual Time Series Dataset for finetuning / pretraining.
Json version of original dataset.
Original Dataset : https://www.kaggle.com/datasets/skywalker290/financial-news-article-and-stock-trend-dataset?select=stock_data_articles.csv
timeseries-QQQ-1d-25yrTime-Series-Library
Time-Series-Library (TSLib)
TSLib is an open-source library for deep learning researchers, especially for deep time series analysis.
We provide a neat code base to evaluate advanced deep time series models or develop your model, which covers five mainstream tasks: long- and short-term forecasting, imputation, anomaly detection, and classification.
This benchmark collection is designed to evaluate and develop advanced deep time-series models. For an in-depth exploration of… See the full description on the dataset page: https://huggingface.co/datasets/fluxae/Time-Series-Library.faang-engineered-time-series-features-2013-2025
FAANG Stocks Historical Raw and Engineered Time-Series Dataset (2013-2025)
Since this is a comprehensive ReadMe file with multiple sections and crosslinks to other documents and images, I wanted to start by providing a ToC with hyperlinks to simplify navigation for the readers. (special thanks to @csavur for this very helpful suggestion!)
DOCUMENT NAVIGATION GUIDE (ToC)
1 - Summary2 - Usage & Reproducability3 - Practical Uses of this Dataset
3.1 - A real-world ML… See the full description on the dataset page: https://huggingface.co/datasets/ML-Owl/faang-engineered-time-series-features-2013-2025.Time-Series-Library
Time-Series-Library (TSLib)
TSLib is an open-source library for deep learning researchers, especially for deep time series analysis.
We provide a neat code base to evaluate advanced deep time series models or develop your model, which covers five mainstream tasks: long- and short-term forecasting, imputation, anomaly detection, and classification.
This benchmark collection is designed to evaluate and develop advanced deep time-series models. For an in-depth exploration of current… See the full description on the dataset page: https://huggingface.co/datasets/Geenn2026/Time-Series-Library.TimeSeriesExam1
Dataset Card for TimeSeriesExam-1
This dataset provides Question-Answer (QA) pairs for the paper TimeSeriesExam: A Time Series Understanding Exam. Example inference code can be found here.
📖Introduction
Large Language Models (LLMs) have recently demonstrated a remarkable ability to model time series data. These capabilities can be partly explained if LLMs understand basic time series concepts. However, our knowledge of what these models understand about time series data… See the full description on the dataset page: https://huggingface.co/datasets/AutonLab/TimeSeriesExam1.timeseries-finance-ETFtimeseries-1m-QQQ-10yTime-Series-Library
Time-Series-Library (TSLib)
TSLib is an open-source library for deep learning researchers, especially for deep time series analysis.
We provide a neat code base to evaluate advanced deep time series models or develop your model, which covers five mainstream tasks: long- and short-term forecasting, imputation, anomaly detection, and classification.
This benchmark collection is designed to evaluate and develop advanced deep time-series models. For an in-depth exploration of current… See the full description on the dataset page: https://huggingface.co/datasets/zxyang7/Time-Series-Library.Time-Series-Library
Time-Series-Library (TSLib)
TSLib is an open-source library for deep learning researchers, especially for deep time series analysis.
We provide a neat code base to evaluate advanced deep time series models or develop your model, which covers five mainstream tasks: long- and short-term forecasting, imputation, anomaly detection, and classification.
This benchmark collection is designed to evaluate and develop advanced deep time-series models. For an in-depth exploration of current… See the full description on the dataset page: https://huggingface.co/datasets/lalababa/Time-Series-Library.memmaped_2048len_PretrainGiftEvalTimeseries-QA
Timeseries-QA
This is a dataset for Timeseries Instruction Tuning.
It was created using the following steps:
Extracted features from time series data in AutonLab/Timeseries-PILE
microsoft/Phi-3-medium-4k-instruct generated the QA pairs
Timeseries Instruction Tuning用のデータセットです。
以下の手順で作成しました。
AutonLab/Timeseries-PILE の時系列データの特徴を抽出
microsoft/Phi-3-medium-4k-instruct がQAを作成
Dataset Details
Dataset Description
Curated by: HachiMLLanguage(s) (NLP): English… See the full description on the dataset page: https://huggingface.co/datasets/HachiML/Timeseries-QA.timeseries_trending_youtube_videos_2019-04-15_to_2020-04-15Timeseries Trending YouTube Videos: 2019-04-15 to 2020-04-15
This dataset is a csv of one of the archived historical database tables queried from my non public database that contains time series data for period of 2019-04-15 to 2020-04-15. Video data was captured from the time they first appeared on trending list, and TSD exists until the video is removed from trending list.
This snapshot contains data for the 11,369 videos that appeared on trending within the timeframe, with 1,541,128 records… See the full description on the dataset page: https://huggingface.co/datasets/jettisonthenet/timeseries_trending_youtube_videos_2019-04-15_to_2020-04-15.time-series-benchmark
Four-Domain Real-World Forecasting Benchmark
Release r2026_10, schema 1.0, data version 2026-09-26.4, evaluator 0.5. What changed since
r2026_09 is listed under "Changes in r2026_10" below.
This is a small evaluation corpus for general-purpose time-series forecasting models.
It contains real observations in four domains: electricity load, road traffic, river
discharge and near-surface weather. There are 13 datasets, 1,049 entities, 23.0M rows
and 43.2M measurement slots (41.5M… See the full description on the dataset page: https://huggingface.co/datasets/alinurdin/time-series-benchmark.