Alternative data datasets
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The job-postings-raw dataset is a large-scale tabular collection of scraped job postings distributed in Parquet format. It aggregates records across multiple sources and locales, with US coverage indicated in the dataset metadata.
credit_card_transactions is a small tabular dataset published by aegisheld containing anonymized customer-level credit card account and spending summaries. It is distributed as CSV with a single training split of 8,950 rows.
About 1.5 million US patent claims split into training and test partitions in CSV, organized for claim-level classification and summarization work (Apache 2.0). A large, ready-split corpus for IP-claims modeling.
A component of the ALEA Institute's KL3M Data Project supplying training material cleared of copyright concerns. The dataset card is currently a placeholder, directing readers to the GitHub repo and project paper for full documentation.
The KL3M Data Project from the ALEA Institute supplies copyright-clean training material, and the dataset listed here is one component pending further documentation on its dedicated page.
The kl3m-index-edgar-filings dataset, published by ALEA Institute, is a Parquet-format index of SEC EDGAR filings distributed via the Hub datasets library. It contains roughly 20 million tabular records spanning the 10M–100M size category, with an unstated license.
The KL3M Index of EDGAR 10-K Filings is a tabular index published by the Alea Institute that catalogs SEC EDGAR filings with associated issuer metadata. It is distributed in Parquet format and is tagged for use with pandas, polars, and the mlcroissant dataset library.
The kl3m-index-edgar-filings-10-q dataset, published by the ALEA Institute, is a Parquet-formatted index of U.S. Securities and Exchange Commission Form 10-Q filings. It is distributed on the Hugging Face Hub with roughly 495,607 rows in a single 'train' split.
The kl3m-index-edgar-filings-8-k dataset is an indexed catalog of Form 8-K filings from the SEC's EDGAR system, published by the ALEA Institute. It provides structured metadata for over 1.8 million corporate event reports distributed in Parquet format.
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Dataset overview This is a dataset that contains restaurant reviews gathered in 2019 using a webscraping tool in Python. Reviews on restaurant visits and restaurant features were collected for Dutch restaurants. The dataset is formatted using the 🤗DatasetDict format and contains the following indices: train, 116693 records test, 14587 records validation, 14587 records The dataset holds both inform
EDGAR_FILINGS_DATASET_2016_2021 is a Hugging Face mirror of parsed SEC EDGAR filings spanning 2016 through 2021, distributed as a single train split of about 6 million rows in Parquet format. It is published by anonymous-md with an unstated license.
EDGAR_FILINGS_DATASET_2022_2026H1 is a Hugging Face dataset that compiles parsed SEC EDGAR filings into a single tabular corpus. It covers roughly 2022 through the first half of 2026 and is distributed as Parquet with about 1.7 million records.
A collection of restaurant reviews was assembled in 2019 through Python-based web scraping focused on Dutch establishments, capturing both visit experiences and feature-related information. It is organized in the DatasetDict format with three splits: 116,693 training records, 14,587 test records, and 14,587 validation records.
SEC Filings Structured Signals A structured dataset derived from real SEC EDGAR filings, containing information extracted from corporate disclosures submitted to the U.S. Securities and Exchange Commission. The dataset transforms filing text into structured signals covering financial risks, hedging strategies, litigation, supply-chain dependencies, causal relationships, entity relations, and manag
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ClinicalTrials.gov XML for studies registered between 2018 and 2024, parsed into CSV, hundreds of thousands of records under CC0. A clean, licensed point-in-time history of US clinical-trial registrations.
A large granted-patent text collection from the USPTO, tens of millions of records in Parquet (Apache 2.0). Broad coverage of claims and descriptions for IP-intensity and technology-trend measurement.
This dataset was created using LeRobot. Dataset Structure meta/info.json: { "codebase_version": "v3.0", "fps": 20, "features": { "observation.images.image": { "dtype": "video", "shape": [ 256, 256, 3 ], "names": [ "height", "width", "channels" ], "info": { "video.height":… See the full description on the dataset page: https://huggingface.co/datasets/edgarcancinoe/water_pour.
This dataset was created using LeRobot. Dataset Structure meta/info.json: { "codebase_version": "v3.0", "fps": 20, "features": { "observation.images.image": { "dtype": "video", "shape": [ 256, 256, 3 ], "names": [ "height", "width", "channels" ], "info": { "video.height":… See the full description on the dataset page: https://huggingface.co/datasets/edgarcancinoe/water_pour_anchor_dagger1.
This dataset was created using LeRobot. Dataset Structure meta/info.json: { "codebase_version": "v3.0", "fps": 20, "features": { "observation.images.image": { "dtype": "video", "shape": [ 256, 256, 3 ], "names": [ "height", "width", "channels" ], "info": { "video.height":… See the full description on the dataset page: https://huggingface.co/datasets/edgarcancinoe/water_pour_cheat.
This dataset was created using LeRobot. Dataset Structure meta/info.json: { "codebase_version": "v3.0", "fps": 20, "features": { "observation.images.image": { "dtype": "video", "shape": [ 256, 256, 3 ], "names": [ "height", "width", "channels" ], "info": { "video.height":… See the full description on the dataset page: https://huggingface.co/datasets/edgarcancinoe/water_pour_dagger1.
This dataset was created using LeRobot. Dataset Structure meta/info.json: { "codebase_version": "v3.0", "fps": 20, "features": { "observation.images.image": { "dtype": "video", "shape": [ 256, 256, 3 ], "names": [ "height", "width", "channels" ], "info": { "video.height":… See the full description on the dataset page: https://huggingface.co/datasets/edgarcancinoe/water_pour_dagger12.
This dataset was created using LeRobot. Dataset Structure meta/info.json: { "codebase_version": "v3.0", "fps": 20, "features": { "observation.images.image": { "dtype": "video", "shape": [ 256, 256, 3 ], "names": [ "height", "width", "channels" ], "info": { "video.height":… See the full description on the dataset page: https://huggingface.co/datasets/edgarcancinoe/water_pour_dagger1_cheat.
This dataset was created using LeRobot. Dataset Structure meta/info.json: { "codebase_version": "v3.0", "fps": 20, "features": { "observation.images.image": { "dtype": "video", "shape": [ 256, 256, 3 ], "names": [ "height", "width", "channels" ], "info": { "video.height":… See the full description on the dataset page: https://huggingface.co/datasets/edgarcancinoe/water_pour_dagger1_cheat5.
This dataset was created using LeRobot. Dataset Structure meta/info.json: { "codebase_version": "v3.0", "fps": 20, "features": { "observation.images.image": { "dtype": "video", "shape": [ 256, 256, 3 ], "names": [ "height", "width", "channels" ], "info": { "video.height":… See the full description on the dataset page: https://huggingface.co/datasets/edgarcancinoe/water_pour_dagger2.
This dataset was created using LeRobot. Dataset Structure meta/info.json: { "codebase_version": "v3.0", "fps": 20, "features": { "observation.images.image": { "dtype": "video", "shape": [ 256, 256, 3 ], "names": [ "height", "width", "channels" ], "info": { "video.height":… See the full description on the dataset page: https://huggingface.co/datasets/edgarcancinoe/water_pour_dart.
This dataset was created using LeRobot. Dataset Structure meta/info.json: { "codebase_version": "v3.0", "fps": 20, "features": { "observation.images.image": { "dtype": "video", "shape": [ 256, 256, 3 ], "names": [ "height", "width", "channels" ], "info": { "video.height":… See the full description on the dataset page: https://huggingface.co/datasets/edgarcancinoe/water_pour_dart_full-xl.
This dataset was created using LeRobot. Dataset Structure meta/info.json: { "codebase_version": "v3.0", "fps": 20, "features": { "observation.images.image": { "dtype": "video", "shape": [ 256, 256, 3 ], "names": [ "height", "width", "channels" ], "info": { "video.height":… See the full description on the dataset page: https://huggingface.co/datasets/edgarcancinoe/water_pour_dart_full-xxl.
This dataset was created using LeRobot. Dataset Structure meta/info.json: { "codebase_version": "v3.0", "fps": 20, "features": { "observation.images.image": { "dtype": "video", "shape": [ 256, 256, 3 ], "names": [ "height", "width", "channels" ], "info": { "video.height":… See the full description on the dataset page: https://huggingface.co/datasets/edgarcancinoe/water_pour_dart_full_anchor-xl.
This dataset was created using LeRobot. Dataset Structure meta/info.json: { "codebase_version": "v3.0", "fps": 20, "features": { "observation.images.image": { "dtype": "video", "shape": [ 256, 256, 3 ], "names": [ "height", "width", "channels" ], "info": { "video.height":… See the full description on the dataset page: https://huggingface.co/datasets/edgarcancinoe/water_pour_dart_xl.
This dataset was created using LeRobot. Dataset Structure meta/info.json: { "codebase_version": "v3.0", "fps": 20, "features": { "observation.images.image": { "dtype": "video", "shape": [ 256, 256, 3 ], "names": [ "height", "width", "channels" ], "info": { "video.height":… See the full description on the dataset page: https://huggingface.co/datasets/edgarcancinoe/water_pour_shift.
Prepared by Electric Sheep Africa, this MDPA-sourced dataset supplies 10 entries of hotel room occupancy rates for Mauritius over 2019-2023, delivered as ML-ready Parquet files accompanied by uniform Hugging Face metadata and source provenance.
A small Parquet-format collection from Electric Sheep Africa reporting room occupancy rates for large hotels in Mauritius from 2019 to 2023, containing ten records drawn from MDPA and packaged with Hugging Face metadata for machine learning workflows.
Assembled by Electric Sheep Africa from MDPA, this dataset provides 60 rows of monthly hotel room occupancy rates for Mauritius spanning 2019-2023, formatted as ML-ready Parquet with consistent Hugging Face metadata and source attribution.
Compiled by Electric Sheep Africa, this MDPA-derived dataset offers 20 records of quarterly hotel room occupancy rates for Mauritius across the 2019-2023 period, distributed in ML-ready Parquet format with standardized Hugging Face metadata and source traceability.
Electric Sheep Africa releases 60 quarterly observations from MDPA on hotel room occupancy for large establishments in Mauritius from 2019 through 2023, formatted as Parquet with consistent metadata.
Indeed Job Postings (2026) is a 1,000-row sample of US Indeed listings joined to company firmographics, published by fact-den on Apify. License terms are not stated, and the publisher directs users to a commercial source actor for fresh or filtered data.
HoldingsIntel Smart Money Open Data What hedge funds disclose to the SEC, as clean CSV files. A new 13F edition every quarter. Every row links to its SEC filing or to the HoldingsIntel page that shows it. Latest 13F edition: Q2 2026. The Q2 2026 Smart Money Report tells its story. What's inside Folder Edition Files data/13f/<quarter>/ Every 13F quarter, once the funds' filings are in stocks.csv, f
French patents published in 2024, split into chunks at the `<p>` XML tag level and saved in Parquet for streaming and distributed processing. The records come from public French patent filings (A1, 2024) and were independently extracted, structured, and segmented using access to PI API and FTP sources.
A cleaned collection of French patent documents published from 1981 through 2026, each row in the Parquet file representing one complete A1 publication parsed from the original XML. It was assembled independently by a contributor with direct access to the public patent source and is optimized for distributed loading.
European Residential Housing Prices Quarterly Price Indices and Growth Metrics for Cross-Country Analysis Dataset Info Source: Kaggle Original Size: 0.01 MB Kaggle Downloads: 67 Files: 1 Files european_housing_prices_clean.csv Mirrored from Kaggle
A collection of 2,000 Malaysian property transaction records spanning every state offers a detailed look at the national housing market in 2025. Compiled from Brickz, a recognized source for real estate transaction data, it covers location, tenure, property type, median pricing, and transaction volumes.
Earnings-call transcripts from an IBM research project, tens of thousands of records with finance tags, in CC0. A filings-adjacent corpus for call-tone and question-and-answer analysis.
10-K filings for S&P 500 companies retrieved from EDGAR, stored as Parquet with the filing text attached (MIT). A focused corpus for the large-cap annual disclosure cycle: risk factors, MD&A and segment detail for every S&P 500 name.
Metadata for every EDGAR filing submitted to the U.S. Securities and Exchange Commission from 1994 through December 14, 2024, derived from the quarterly master index files and including CIKs, issuer names, and form types.
Earnings Call LLM Insights 📚 Read the Full Story: For a deep dive into the methodology, the wildest moments we found, and key takeaways, check out the blog post:KnowTrend.ai: Auto-Grading Ten Years of Earnings Calls for Prescience and Delusion This dataset contains LLM-generated analysis of ~70,000+ earnings call transcripts. The analysis was performed using Kimi k2-0905-preview, focusing on extra
The patents-publications-dataset is a large-scale tabular collection of patent publication records distributed in Parquet format. Hosted by publisher labofsahil on the Hugging Face Hub under an unstated license, it is sized in the 100M–1B row range.
AlphaAI's near-real-time parse of SEC EDGAR Form 4 filings, providing 20,832 individual insider transaction tranches and 8,538 grouped economic events for US public-company officers, directors, and 10% owners.
google-patents-data-preview is a community-uploaded preview of Google Patents bibliographic records, distributed in Parquet format through the Hugging Face Hub. The single training split contains roughly 340,000 rows covering patent identifiers, classifications, and localized text fields.
Global Job Postings – Multi-ATS is a single dated snapshot of 112,816 job listings aggregated from 23 applicant tracking systems and parsed into a 47-column schema by NextGig-Rocks. It is distributed as Parquet via the Hugging Face datasets library and targets labor-market research, not production job boards.
India IPO GMP vs actual listing: an open track record How well does the grey market premium (GMP) predict an Indian IPO's listing? This dataset records the GMP of every mainboard IPO before it listed and compares it with the actual listing-day result. No values are back-filled. Live, auto-updating version: https://paisatools.co.in/ipo/gmp-accuracy What it shows so far 35 mainboard IPOs listed betw
Dataset card entry for "AIPD_nlp_granted_claims" with additional details required.
专利无效检索评测数据集 面向专利无效证据检索系统的公开 Benchmark，以权利要求文本为检索输入， 以真实无效案件中使用的证据文献为标准答案。 简体中文 · English 下载公开数据集 数据集简介 本数据集用于评估 AI Agent、检索模型和传统专利检索系统发现无效证据文献的能力。 每条样本包含待分析的权利要求、案件最终结果、证据文献，以及证据角色和法律依据等 结构化标注。 公开版本包含 80 条 Benchmark 样本，CN 与 US 各 40 条，覆盖 IPC 的 A–H 八个部。它既可以衡量系统能否找到至少一篇有效证据，也可以衡量系统对核心文献和 全部证据文献的覆盖程度。 这份数据可以用来评估什么 能力 说明 无效证据检索 给定权利要求文本，系统能否从专利文献中找到真实案件使用的无效证据 核心与完整召回 分别评估主要证据 primary_reference 和全部证据文献
This dataset was created using LeRobot. Dataset Structure meta/info.json: { "codebase_version": "v2.1", "robot_type": "so100", "total_episodes": 50, "total_frames": 29874, "total_tasks": 1, "total_videos": 100, "total_chunks": 1, "chunks_size": 1000, "fps": 30, "splits": { "train": "0:50" }, "data_path": "data/chunk-{episode_chunk:03d}/episode_{episode_index:06d}.parquet", "video_path":… See the f
This dataset was created using LeRobot. Dataset Structure meta/info.json: { "codebase_version": "v2.1", "robot_type": "so100", "total_episodes": 50, "total_frames": 44746, "total_tasks": 1, "total_videos": 100, "total_chunks": 1, "chunks_size": 1000, "fps": 30, "splits": { "train": "0:50" }, "data_path": "data/chunk-{episode_chunk:03d}/episode_{episode_index:06d}.parquet", "video_path":… See the f
This dataset was created using LeRobot. Dataset Structure meta/info.json: { "codebase_version": "v2.1", "robot_type": "so100", "total_episodes": 20, "total_frames": 11940, "total_tasks": 1, "total_videos": 40, "total_chunks": 1, "chunks_size": 1000, "fps": 30, "splits": { "train": "0:20" }, "data_path": "data/chunk-{episode_chunk:03d}/episode_{episode_index:06d}.parquet", "video_path":… See the fu
The nj-housing-prices-tabular dataset is a small tabular collection of New Jersey residential property listings, published on Hugging Face under an unstated license. It contains roughly 7,000 rows split across train, validation, and test partitions.
An English-language NLP corpus of cleaned earnings call transcripts gathered from public investor-relations pages, sized between 10,000 and 100,000 documents for financial analysis and LLM work.
A resource built for forecasting patent approval outcomes, introduced in research employing domain-specific fine-grained claim dependency graphs, with further documentation to be supplied later.