datasets
Training and evaluation data, with the modality, task and licence stated up front. Listed live from the Hugging Face Hub.
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: 2026-09-17. 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.High_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.timeseries-1m-QQQ-5ytimeseries-QQQ-1d-25yrfaang-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.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.store-sales-time-series-forecasting
taken from this Kaggle competition:
Dataset Description
In this competition, you will predict sales for the thousands of product families sold at Favorita stores located in Ecuador. The training data includes dates, store and product information, whether that item was being promoted, as well as the sales numbers. Additional files include supplementary information that may be useful in building your models.
File Descriptions and Data Field Information… See the full description on the dataset page: https://huggingface.co/datasets/mrcksggcfc/store-sales-time-series-forecasting.TimeSeriesDatatest
time_series_datasets
Tourism Monthly Time Series Dataset with Economic and Static Covariates
This dataset, originally sourced from Athanasopoulos et al. (2011), focuses on the tourism industry with a monthly frequency and has been enhanced with economic covariates (e.g., CPI, Inflation Rate, GDP) from official Australian government sources. We also perform some preprocessing to further increase the usability of the dataset with dynamic start dates for each series and static covariates for in-depth time… See the full description on the dataset page: https://huggingface.co/datasets/zaai-ai/time_series_datasets.drc_zones_timeseries-zonalmultimodal-time-series-forecastingseasonal_time_series_for_anomaly_detection
seasonal_time_series_for_anomaly_detection
This dataset contains seven CSV files with artificially generated, ordered, timestamped, single-valued metrics for three months divided by days of the week with no anomalies. Also, three CSV files are artificially generated, ordered, timestamped and have single-valued metrics with anomalies, and two CSV files have a week representation (one with anomalies).
Motivation
This dataset was created as a part of a bachelor's thesis. Our… See the full description on the dataset page: https://huggingface.co/datasets/pryshlyak/seasonal_time_series_for_anomaly_detection.Telangana_time_series_2023-2025The dataset was retrieved from Open Data Telangana, from February 1, 2023, to January 31, 2025 with daily granularity. The dataset contains various fields such as District, Mandal, Date, rainfall (in millimeters), minimum and maximum temperature (in Celsius), minimum and maximum wind speed, and humidity. It provides a District and Mandal wise distribution as well.
Total Rows - 4,45,213
Total Columns - 10
Telangana_time_series_2023-2025The dataset was retrieved from Open Data Telangana, from February 1, 2023, to January 31, 2025 with daily granularity. The dataset contains various fields such as District, Mandal, Date, rainfall (in millimeters), minimum and maximum temperature (in Celsius), minimum and maximum wind speed, and humidity. It provides a District and Mandal wise distribution as well.
Total Rows - 4,45,213
Total Columns - 10
ncdc_lassa_fever_timeseries
NCDC Lassa Fever Weekly Timeseries Dataset (Nigeria, 2020–2025)
Version: 1.0
Maintainer: Emmanuel Niyi-Oriolowo
License: CC BY 4.0
Last Updated: 01-12-2025
1. Overview
This repository provides a consolidated and standardized dataset of weekly Lassa fever surveillance data in Nigeria from 2020 to 2025. The dataset is derived from the Nigeria Centre for Disease Control (NCDC) Weekly Epidemiological Reports, which are published as PDF documents.
The primary objective of… See the full description on the dataset page: https://huggingface.co/datasets/EmanuelN/ncdc_lassa_fever_timeseries.Time-Series-Instruct-V1
Time Series Instruct
Синтетический датасет временных рядов с текстовыми описаниями паттернов
Synthetic dataset of time series with textual pattern descriptions
Описание / Description
Time Series Instruct — это крупный синтетический датасет, содержащий 500 000 уникальных временных рядов длиной ровно 50 точек каждый, с подробными текстовыми описаниями их паттернов.
Time Series Instruct is a large synthetic dataset containing 500,000 unique time series of exactly 50… See the full description on the dataset page: https://huggingface.co/datasets/Kostya165/Time-Series-Instruct-V1.Time-Series-Donations
Time-Series Donations Dataset
Overview
This repository provides a time-series dataset of donation dynamics over time.It is intended for experiments in:
Time-series forecasting
Trend and seasonality analysis
Anomaly detection on donation flows
Benchmarking classical and deep time-series models
The data are organized in a tabular time-series format, with each row representing a time step and each column representing a numerical or categorical feature related to donations.… See the full description on the dataset page: https://huggingface.co/datasets/VillanovaAI/Time-Series-Donations.Store-Sales-Time-Series-Forecasting-result-0.45607evm-pv-ev-ac-bac-timeseries
EVM PV/EV/AC/BAC Time-Series (Synthetic)
This dataset contains synthetic Earned Value Management (EVM) project time-series records.
Files
evm_train.csv
evm_test.csv
Columns
IDs: project_id, project, project_type, period
Core EVM: BAC, PV, EV, AC
Variances: SV, CV
Indices: SPI, CPI
Forecasts: EAC, ETC, VAC
Use
Supports calculating SPI/CPI/EAC and training ML models for cost and schedule forecasting.
time_series_dataset_residuals
Tourism Monthly Time Series Dataset with Economic and Static Covariates
This dataset, originally sourced from Athanasopoulos et al. (2011), focuses on the tourism industry with a monthly frequency and has been enhanced with economic covariates (e.g., CPI, Inflation Rate, GDP) from official Australian government sources. We also perform some preprocessing to further increase the usability of the dataset with dynamic start dates for each series and static covariates for in-depth time… See the full description on the dataset page: https://huggingface.co/datasets/zaai-ai/time_series_dataset_residuals.Telangana_time_series_2023-2025The dataset was retrieved from Open Data Telangana, from February 1, 2023, to January 31, 2025 with daily granularity. The dataset contains various fields such as District, Mandal, Date, rainfall (in millimeters), minimum and maximum temperature (in Celsius), minimum and maximum wind speed, and humidity. It provides a District and Mandal wise distribution as well.
Total Rows - 4,45,213
Total Columns - 10
onion_timeseries_dataseasonal_time_series_for_anomaly_detection
seasonal_time_series_for_anomaly_detection
This dataset contains seven CSV files with artificially generated, ordered, timestamped, single-valued metrics for three months divided by days of the week with no anomalies. Also, three CSV files are artificially generated, ordered, timestamped and have single-valued metrics with anomalies, and two CSV files have a week representation (one with anomalies).
Motivation
This dataset was created as a part of a bachelor's thesis. Our… See the full description on the dataset page: https://huggingface.co/datasets/awi69646/seasonal_time_series_for_anomaly_detection.timeseries_max1000_len10_sample100000_split0.8Time-Series-Toolkittime-series-ratingThis is the dataset used in the paper TSRating: Selecting High-Quality Time Series Data by Prompting LLMs
The datasets used in this project have been integrated from various sources for convenience. These datasets are not original to this project but are included to facilitate usage. If you wish to cite them, please refer to the corresponding sources listed in the paper.
license: apache-2.0