Alternative data datasets
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Compiled by Electric Sheep Africa from MDPA, this 20-row dataset records quarterly hotel room occupancy rates in Mauritius for all hotel categories between 2019 and 2023 and is delivered as ML-ready Parquet.
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.
A Parquet file of annual inflation as measured by consumer prices for Africa, sourced from World Bank gender and regional statistics, indexed by Electric Sheep Africa for African data discovery and released in the 1K–10K row range.
A U.S. patent collection with a minimal placeholder card and no additional documentation provided.
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A curated collection of earnings call recordings broken into intelligent segments and paired with high-accuracy transcripts produced by Mistral's Voxtral model, intended for ASR benchmarking, transcription quality studies, and audio-to-text alignment research.
FINRA Short Interest, last 12 months Shares sold short for every exchange-listed and OTC security, twice a month, for the last 12 months (522,296 rows): short shares, change from the prior report, average daily volume and days to cover. import pandas as pd df = pd.read_parquet("hf://datasets/FinzData/finra-short-interest/data/short_interest.parquet") df[df.ticker == "GME"] In the full FinzData dat
Indian equity market price history covering NSE-listed stocks and indices from 2000 through 2026, offered in Parquet shards of roughly 1.5GB each for efficient streaming on the Hugging Face hub. The collection draws on more than 2,500 tickers and supports both minute-level and end-of-day intervals.
S&P 500 earnings-call transcripts preprocessed into optimized Parquet, tens of thousands of calls (MIT). Ready for sentiment, QA and summarization research on the large-cap earnings season.
🇮🇳 Indian Stock Market Data: Minute & Daily (2000 - 2026) 📌 Overview This is a high-performance financial dataset containing the historical price history of 2,500+ NSE Stocks and Indices. The dataset has been sharded and optimized for high-speed training. Instead of thousands of tiny files, it is grouped into large ~1.5GB Parquet shards, making it ideal for fast streaming with the Hugging Face dat
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FR-Patent-2025-Claims is a tabular dataset published by INPI-France containing individual patent claims from French patent publications. It is distributed in Parquet format with 102,748 rows in the provided training split.
Raw French patent publications from 2020 through 2026, pulled from original A1 XML records by an independent API/FTP extraction and delivered one-document-per-row in streaming-ready parquet.
A dataset card entry for restaurant reviews that flags the need for additional information beyond what is currently provided.
🇮🇳 Indian Stock Market Data: Minute & Daily (2000 - 2026) 📌 Overview This is a high-performance financial dataset containing the historical price history of 2,500+ NSE Stocks and Indices. The dataset has been sharded and optimized for high-speed training. Instead of thousands of tiny files, it is grouped into large ~1.5GB Parquet shards, making it ideal for fast streaming with the Hugging Face dat
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.
The mintic_linkedin-job-postings dataset aggregates LinkedIn job posting text into a single string column with roughly 124,000 rows. It is published on Hugging Face by user jmparejaz under an unstated license.
The Patent Legal IR GraphRAG release follows the Publicus retrieval format, providing dense corpus shards, BM25 documents with CID-keyed length and entry metadata, and BM25 postings arranged for inverted-index use.
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.
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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
Earnings-call transcripts for S&P 500 companies, tens of thousands of calls in English with timestamps, in Parquet (MIT). Direct input for call-tone and question-and-answer sentiment analysis across the large-cap earnings cycle.
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.
Metadata for hundreds of thousands of clinical trials in English, French and Spanish, structured in Parquet with study-level fields such as phase, condition, sponsor and status (Apache 2.0). Trial starts and phase transitions lead clinical development, so this works as an early indicator of biotech pipeline activity.
Minimal information is provided on this clinical-trials-embedded dataset, with additional details needed.
A corpus of around 1.3 million U.S. patent filings paired with human-authored abstractive summaries, organized into nine Cooperative Patent Classification categories ranging from human necessities to textiles and paper.
The clinical_trials dataset distributes ClinicalTrials.gov registry records in Parquet format for offline analysis. It contains a single training split of roughly 150,000 rows sourced from the public clinical-trial registry.
A collection featuring the primary independent claim of United States utility patents issued between 2005 and 2025 is provided. Because the opening claim usually establishes the widest legal boundaries of an invention, it carries particular significance, and each entry includes the patent identifier alongside its claim text.
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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.
Two Parquet files hold global patent publication records paired with quality indicators for Chinese invention patent families from 2003 to 2019, with each row representing a focal family and carrying cumulative measures such as semantic knowledge recombination, strict historical semantic novelty, and IPC-based robustness.
Over 1.3 million granted US patents from the BIGPATENT benchmark, each pairing its claims with an abstractive summary and full description text in English (CC BY 4.0, Parquet). Use it to track the technology areas where applicants are filing and to study how claim language has evolved over time.
TUDelft-Electricity-Consumption-1.0 is a high-resolution, open-source time series dataset of household electricity load published on Hugging Face by OpenSynth. It draws on multi-country trials covering thousands of households under different tariff regimes and is distributed in Parquet format.
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Clinical-trials records combining structured metadata and narrative text, hundreds of thousands of studies in Parquet. An early read on pharmaceutical pipeline activity and trial design trends.
Clinical-trial protocol documents from Parexel, tens of thousands of studies. Protocol text, covering inclusion criteria, endpoints and timelines, is a leading indicator for enrollment pace and pipeline risk.
ClinicalTrialSummary is a Hugging Face dataset published under the pat-jj account that pairs long-form clinical trial article text with shorter plain-language summaries. It is distributed in Parquet format with predefined train, validation, and test splits totaling 77,516 rows.
Dataset Card for "ClinicalTrialSummary_Simple" More Information needed
Dataset card entry for "AIPD_nlp_granted_claims" with additional details required.
Patent_FR_US_Merge_Radix_65536 is a Hugging Face dataset by publisher PhysiQuanty that merges French and US patent documents into a single text corpus. It is distributed in Parquet format and is tagged with an Apache-2.0 license, though the README provides no further description.
patent-ate termhood on HUPD This dataset is a ranked phrase table: each row is a multiword (or surface) key, a nested-frequency C-value, and how many filings contain that key (df). patent-ate corpus then score built it from the Harvard USPTO Patent Dataset (HUPD). It is not HUPD itself. Start with the slice (3,393 rows, tens of kilobytes). The full table is 88,607,764 keys from 4,518,254 filings a
Dataset Card for "zephyr_pi0_gen_57k_for_offline_dpo_ipo" More Information needed
Minute- and daily-resolution price histories for more than 2,500 National Stock Exchange securities and indices from 2000 through 2026 are consolidated into roughly 1.5 gigabyte Parquet shards to enable rapid streaming on Hugging Face infrastructure.
clinicaltrials.gov-summary_and_eligibility is a small Parquet mirror of selected ClinicalTrials.gov records, distributed on the Hugging Face Hub under the rjac publisher. It packages study identifiers, recruitment status, titles, brief summaries, and eligibility criteria into a single tidy table of roughly three thousand rows.
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.
feather, hdf5, jay, parquet, pickle
S&P 500 earnings call episodes from 2005 to 2025 are released as static tabular rows, each identified by a company-quarter episode identifier and containing full transcripts along with SEC press materials, suited to supervised or reinforcement-style experiments.
Indian stock market price history spanning 2000 to 2026 for over 2,500 NSE-listed stocks and indices, packaged in large Parquet shards around 1.5 GB each for efficient streaming.
sec-filings is a Hugging Face dataset published by Sicheng-Chroma that distributes pre-chunked U.S. SEC filings paired with dense vector embeddings. It is distributed in optimized Parquet format and is intended for retrieval and similarity research over regulatory disclosures.
Vector embeddings of Apple patent text totalling about 4 million entries, stored as parquet shards with a 768-dimensional float64 feature per record.
Parquet and csv files associating CIK (Central Index Key) with filing entities
PatentPulse PatentPulse is a provenance-preserving corpus of USPTO grants and published patent applications extracted from official weekly XML bulk releases. This immutable Parquet snapshot normalizes the project's historical append-only JSONL into one schema. Historical partial snapshot. This release was captured on 2026-08-28 while the upstream backfill was still in progress. It is a stable, cit
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A collection of Parquet files providing one record per Chinese invention patent family granted between 2003 and 2019, capturing a cumulative quality assessment pipeline that includes metrics such as semantic knowledge recombination, strict historical semantic novelty, and IPC-based robustness measures across global patent publications.
Dataset details:- This dataset is the 2nd iteration following bugs in 1st dataset. The initial data suffered with followoing cases:- (i) The failed reference_answers generation(due error totalling 23) primarly because of 2 reasons/exceptions:- (a) There was normal limit(300 in 1st request) and worst case limit(450 in 3rd request) number of tokens for consolidated 4 refernce_answers per chunk and i
Dataset details:- This dataset is basically mapping of final anchor-positive pair data with their refernce answer. The given input data considered because:- (i) it had the had purest anchor-positive pairs with semantically bound anchors with context/positive. (ii) gave us the best result on final embedding fine tuning model. The anchor-context(positive)-reference_answer data has been generated via
A knowledge graph assembled from 575,778 ClinicalTrials.gov registrations and their associated arms, outcomes, sites, sponsors, conditions, interventions, MeSH codes, and PubMed citations, containing 7,628,735 nodes and 15,531,427 edges, delivered as 623 MB of Parquet files (compared to about 7 GB of raw JSON) and built using Samyama Graph.
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A 10% sample of over 573,000 ClinicalTrials.gov studies augmented with AI-classified therapeutic areas, sponsor categorization, outcome groupings, and duration metrics, offered for portfolio and market landscape analysis.