Update

Unfortunately, the API this dataset used to pull the stock data isn't free anymore. Instead of having this auto-updating, I dropped the last version of the data files in here, so at least the historic data is still usable.

Content

This dataset provides free end of day data for all stocks currently in the Dow Jones Industrial Average. For each of the 30 components of the index, there is one CSV file named by the stock's symbol (e.g. AAPL for Apple). Each file provides historically adjusted market-wide data (daily, max. 5 years back). See here for description of the columns: https://iextrading.com/developer/docs/#chart

Since this dataset uses remote URLs as files, it is automatically updated daily by the Kaggle platform and automatically represents the latest data.

Acknowledgements

List of stocks and symbols as per https://en.wikipedia.org/wiki/Dow_Jones_Industrial_Average

Thanks to https://iextrading.com for providing this data for free!

Terms of Use

Data provided for free by IEX. View IEX’s Terms of Use.

This dataset offers both live (delayed) prices and End Of Day time series on equity options

1/ Live (delayed) prices for options on European stocks and indices including: Reference spot price, bid/ask screen price, fair value price (based on surface calibration), implicit volatility, forward Greeks : delta, vega Canari.dev computes AI-generated forecast signals indicating which option is over/underpriced, based on the holders strategy (buy and hold until maturity, 1 hour to 2 days holding horizon...). From these signals is derived a "Canari price" which is also available in this live tables.
Visit our website (canari.dev ) for more details about our forecast signals.

The delay ranges from 15 to 40 minutes depending on underlyings.

2/ Historical time series: Implied vol Realized vol Smile Forward
See a full API presentation here : https://youtu.be/qitPO-SFmY4 .

These data are also readily accessible in Excel thanks the provided Add-in available on Github: https://github.com/canari-dev/Excel-macro-to-consume-Canari-API

If you need help, contact us at: contact@canari.dev

User Guide: You can get a preview of the API by typing "data.canari.dev" in your web browser. This will show you a free version of this API with limited data.

Here are examples of possible syntaxes:

For live options prices: data.canari.dev/OPT/DAI data.canari.dev/OPT/OESX/0923 The "csv" suffix to get a csv rather than html formating, for example: data.canari.dev/OPT/DB1/1223/csv For historical parameters: Implied vol : data.canari.dev/IV/BMW

data.canari.dev/IV/ALV/1224

data.canari.dev/IV/DTE/1224/csv

Realized vol (intraday, maturity expressed as EWM, span in business days): data.canari.dev/RV/IFX ... Implied dividend flow: data.canari.dev/DIV/IBE ... Smile (vol spread between ATM strike and 90% strike, normalized to 1Y with factor 1/√T): data.canari.dev/SMI/DTE ... Forward: data.canari.dev/FWD/BNP ...

List of available underlyings: Code Name OESX Eurostoxx50 ODAX DAX OSMI SMI (Swiss index) OESB Eurostoxx Banks OVS2 VSTOXX ITK AB Inbev ABBN ABB ASM ASML ADS Adidas AIR Air Liquide EAD Airbus ALV Allianz AXA Axa BAS BASF BBVD BBVA BMW BMW BNP BNP BAY Bayer DBK Deutsche Bank DB1 Deutsche Boerse DPW Deutsche Post DTE Deutsche Telekom EOA E.ON ENL5 Enel INN ING IBE Iberdrola IFX Infineon IES5 Intesa Sanpaolo PPX Kering LOR L Oreal MOH LVMH LIN Linde DAI Mercedes-Benz MUV2 Munich Re NESN Nestle NOVN Novartis PHI1 Philips REP Repsol ROG Roche SAP SAP SNW Sanofi BSD2 Santander SND Schneider SIE Siemens SGE Société Générale SREN Swiss Re TNE5 Telefonica TOTB TotalEnergies UBSN UBS CRI5 Unicredito SQU Vinci VO3 Volkswagen ANN Vonovia ZURN Zurich Insurance Group

The best choice for those looking for license-free US market data for commercial use is US Equities Basic, which includes data display, redistribution, professional trading, and more.

US Equities Basic is based upon a derived IEX feed. The volume coverage is 3-5% of the total trading volume in North America, which helps entities mitigate license expenses and start with real-time data.

US Equities Basic provides raw quotes, trades, aggregated time series (OHLCV), and snapshots. Both REST API and WebSocket API are available.

End-of-day price information disseminated after 12:00 AM EST does not require licensing in the United States by law. This applies to all exchanges, even those not included in the US Equities Basic. Finazon combines all price information after every trading day, meaning that while markets are open, real-time prices are available from a subset of exchanges, and when markets close, data is synced and contains 100% of US volume. All historical prices are adjusted for corporate actions and splits.

Tip: Individuals with non-professional usage are not required to get exchange licenses for real-time data and, hence, are better off with the US Equities Max dataset.

Cbonds collects and normalizes indices data, offering daily updated and historical data on over 40,000 indices, including macroeconomic indicators, yield curves and spreads, currency markets, stock and funds markets, and commodities. Using the Indices API, you can access an index's holdings, such as its assets, sectors, and weight, as well as basic data on the asset. You can obtain end-of-day, and historical API indicator prices in CSV, XLS, and JSON formats. Cbonds provides a free Indices API for a limited test period of two weeks or for a longer period with a limited number of instruments.

Bitcoin Historical Data (2018-2024) - 15M, 1H, 4H, and 1D Timeframes

Dataset Overview

This dataset contains historical price data for Bitcoin (BTC/USDT) from January 1, 2018, to the present. The data is sourced using the Binance API, providing granular candlestick data in four timeframes: - 15-minute (15M) - 1-hour (1H) - 4-hour (4H) - 1-day (1D)

This dataset includes the following fields for each timeframe: - Open time: The timestamp for when the interval began. - Open: The price of Bitcoin at the beginning of the interval. - High: The highest price during the interval. - Low: The lowest price during the interval. - Close: The price of Bitcoin at the end of the interval. - Volume: The trading volume during the interval. - Close time: The timestamp for when the interval closed. - Quote asset volume: The total quote asset volume traded during the interval. - Number of trades: The number of trades executed within the interval. - Taker buy base asset volume: The volume of the base asset bought by takers. - Taker buy quote asset volume: The volume of the quote asset spent by takers. - Ignore: A placeholder column from Binance API, not used in analysis.

Data Sources

Binance API: Used for retrieving 15-minute, 1-hour, 4-hour, and 1-day candlestick data from 2018 to the present.

File Contents

1. btc_15m_data_2018_to_present.csv: 15-minute interval data from 2018 to the present.
2. btc_1h_data_2018_to_present.csv: 1-hour interval data from 2018 to the present.
3. btc_4h_data_2018_to_present.csv: 4-hour interval data from 2018 to the present.
4. btc_1d_data_2018_to_present.csv: 1-day interval data from 2018 to the present.

Automated Daily Updates

This dataset is automatically updated every day using a custom Python program.
The source code for the update script is available on GitHub:
🔗 Bitcoin Dataset Kaggle Auto Updater

Licensing

This dataset is provided under the CC0 Public Domain Dedication. It is free to use for any purpose, with no restrictions on usage or redistribution.

According to Cognitive Market Research, the Global API intermediate Market Size will be USD XX Billion in 2023 and is set to achieve a market size of USD XX Billion by the end of 2031 growing at a CAGR of XX% from 2024 to 2031.

• The global APIs intermediate market will expand significantly by XX% CAGR between 2024 and 2031. • The bulk drug type segment accounts for the largest market share and is anticipated to a healthy growth over the approaching years. • The CMO segment by end user holds the largest share and is expected to grow in the coming years as well. • cardiology application is the market's largest contributor and is anticipated to expand at a CAGR of XX% during the projected period. • The sector has seen a transformation in indirect sales with the rise of e-commerce and online marketplaces • Asia Pacific region dominated the market and accounted for the highest revenue of XX% in 2022 and it is projected that it will grow at a CAGR of XX% in the future.

Market Dynamics: API Intermediate

KEY DRIVERS

Rising in chronic disease drives the market for API intermediate--

The rising prevalence of chronic disease is expected to increase the need for pharmaceutical treatments, propelling the market's growth for active pharmaceutical components over the forecast period. In addition, some of the strategic measures being undertaken to maintain market stability include the introduction of new pharmaceuticals and biological products, partnerships, acquisitions, and regional expansions. For instance- According to WHO, cardiovascular diseases cause the death of 17.9 million people per day and are expected to cause approximately 25 million deaths by 2030. Increasing epidemiology of lifestyle, aided by the rising number of smokers globally, growing incidence of obesity, and increasing dietary irregularities, are factors likely responsible for propelling market growth. (source:https://www.contractpharma.com/contents/view_online-exclusives/2024-01-25/api-market-trends/) Furthermore, advancements in medical technology, an increase in the number of initiatives launched by public and private organizations to raise awareness, and an increase in government funding will all contribute to the growth of the active pharmaceutical ingredient (API) market. The market for active pharmaceutical ingredients (API) will also increase as disposable income levels grow.

Generics and therapeutics demand drives the market for API intermediate-

An escalating global chronic disease burden drives pharmaceutical production, increasing the need for APIs. Generic drugs, equivalent in efficacy to brand-name counterparts but cost-effective, witness high demand, particularly in the treatment of chronic ailments. The rise in age-related health issues contributes to elevating the demand for pharmaceuticals, influencing API market growth. Additionally, as biopharmaceuticals such as recombinant proteins and monoclonal antibodies have grown in popularity, so has the demand for bioprocess intermediates. These phases in the process are required to generate biologics, which is fueling industry growth. Hence the market of active pharmaceutical ingredients (API) is growing because of the rising demand for generics and therapeutics usage.

Restraint-

Availability of counterfeit drugs-

According to the World Health Organization (WHO), 10.5% of the world's medicines are counterfeits (substandard or falsified) reaching up to 50% of the supply in developing countries (World Health Organization). The availability of substandard and counterfeit drugs is expected to hinder the market’s growth over the forecast period. Also, Hazardous substances and reactions can be used in the chemical synthesis process. Counterfeit medicines are harmful to health because they generally: Contain incorrect amounts of APIs (or are missing APIs) and Contain dangerous substitutes, contaminants, and other toxic components instead of quality-controlled formulas and approved API percentages.

Strict Regulations and Supply Chain Disruptions-

Active Pharmaceutical ingredient is a crucial part of any drug product that can directly influence the safety and efficacy of the medicinal product which may endanger the life of the patient. ‘API’ takes into co...

Argus is a prominent source of pricing evaluations and business insights extensively utilized in the energy and commodity sectors, specifically for physical supply agreements and the settlement and clearing of financial derivatives. Argus pricing is also employed as a benchmark in swaps markets, for mark-to-market valuations, project financing, taxation, royalties, and risk management. Argus provides comprehensive services globally and continuously develops new assessments to mirror evolving market dynamics and trends. Covered assets encompass Energy, Oil, Refined Products, Power, Gas, Generation fuels, Petrochemicals, Transport, and Metals.

The Future Schedules API is perfect for: • Travel agency and flight booking websites where users are expected to submit a date and view available flights • Websites, tools or apps to display scheduled flights on a given date • Flight schedule and airway traffic analysis based on region or dates

We have developed many filters you can use in the input to request the exact data you need without having to filter the data on your end.

The data includes: - Departure and arrival airport information: IATA codes - Weekday: The day of the week of the flight, "1" being Monday - Terminal and gate: The most common terminal and the gate number of the departing/arriving flight - Take-off information: Scheduled departure or arrival time of the flight - Aircraft details: Model code and text - Airline details: Name, IATA and ICAO codes - Flight information: Flight number with flight IATA and ICAO codes

1) Request For the departure schedule of a certain airport on a certain future date.

GET http://aviation-edge.com/v2/public/flightsFuture?key=[API_KEY]&type=departure&iataCode=BER&date=YYYY-MM-DD

For the arrival schedule of a certain airport on a certain future date.

GET http://aviation-edge.com/v2/public/flightsFuture?key=[API_KEY]&type=arrival&iataCode=BER&date=YYYY-MM-DD

For the flights that are scheduled to arrive at a certain airport on a certain date (out of a departure schedule).

GET http://aviation-edge.com/v2/public/flightsFuture?key=[API_KEY]&type=departure&iataCode=BER&arr_iataCode=ORY&date=YYYY-MM-DD

For the flights that are scheduled to depart from a certain airport on a certain date (out of an arrival schedule).

GET https://aviation-edge.com/v2/public/flightsFuture?key=[API_KEY]&type=arrival&iataCode=BER&dep_iataCode=ory&date=YYYY-MM-DD

2) Filters &iata_code= (obligatory) Departure or arrival airport IATA code depending on the "&type=" value &type= (obligatory) Either "departure" or "arrival" as both within the same query is not possible &date= (obligatory) Future date in YYYY-MM-DD format

&dep_iataCode= filter of departure airport if "arrival" for "&type=" was chosen, based on the airport IATA code &dep_icaoCode= filter of departure airport if "arrival" for "&type=" was chosen, based on the airport ICAO code &arr_iataCode= filter of arrival airport if "departure" for "&type=" was chosen, based on the airport IATA code &arr_icaoCode= filter of arrival airport if "departure" for "&type=" was chosen, based on the airport ICAO code &airline_iata= option to filter airline based on airline IATA code &airline=icao= option to filter airline based on airline ICAO code &flight_num= option to filter a specific flight based on its flight number

3) Example Output: [ {"weekday": "1", "departure": { "iataCode": "mty", "icaoCode": "mmmy", "terminal": "c", "gate": "f2", "scheduledTime": "20:35" }, "arrival": {"iataCode": "iah", "icaoCode": "kiah", "terminal": "d", "gate": "d12", "scheduledTime": "22:00" }, "aircraft": {"modelCode": "a320", "modelText": "airbus a320-232" }, "airline": {"name": "vivaaerobus", "iataCode": "vb", "icaoCode": "viv"}, "flight": {"number": "616", "iataNumber": "vb616", "icaoNumber": "viv616"} } ]

Note: Schedules that are up to 1 year ahead of the current date are available.

Databento provides upcoming and historical corporate actions impacting over 310,000 global securities, including every company announcement and 61 events like dividends, splits, mergers & acquisitions, listings, and more.

Dividends: Upcoming and past dividends, declaration, ex-dividend, record, and payment dates.

Forward and reverse splits: Capital changes like forward splits and reverse splits with effective dates.

Adjustment factors: To back-adjust end-of-day prices, EPS, P/E and other prices for all corporate actions.

Mergers and acquisitions: Ticker changes caused by mergers, acquisitions, demergers, spinoffs, and more.

IPOs and new listings: Upcoming and historical listings like initial public offerings (IPOs), with listing dates.

Listing continuity: Listing continuity events like name changes, delistings, and description changes.

Capital changes: Such as share buybacks, redemptions, bonus issues, and rights issues.

Legal actions: Legal issues like bankruptcy and class action lawsuits, with filing and notice dates.

Announcements: Machine-readable announcements from over 400 sources, timestamped to the second.

Our reference API has the following structure:

Corporate actions provides point-in-time (PIT) corporate actions events with global coverage.

Adjustment factors provides end-of-day price adjustment factors for capital events, spanning multiple currencies for the same event.

▲ INSEE modernises its API portal, building on a new architecture ▲: The general conditions of use of the portal, as well as those of the APIs presented, remain unchanged. Under the URL of the new portal https://portail-api.insee.fr/, you will find INSEE’s dissemination APIs. Access to the SIRENE API: > To access the SIRENE API, you must first create an account on the new portal and then subscribe to the API. > Instructions for use here. > The same account can subscribe to several APIs, following the same procedure. !! Attention, we advise you to quickly integrate this new environment, by the end of the year, the Sirene API will be accessible only from this new portal. !! *** To subscribe to our newsletter Sirene open data news, click here To consult our newsletters Sirene open data news, click here Stock files > - On May 1st, a new monthly file stockDoublons is proposed, it consists of the list of siren and their duplicates with the date of last treatment always in CSV format. > - The final stock files in 3.11 format are published on 26 March 2024 instead of the previous 3.9 files. Six compacted monthly stock files (ZIP format) are available: - the stock file of legal units (active and discontinued legal units in their current state in the directory) - the stock file of the historical values of the legal units - the inventory file of establishments (active and closed establishments in their current state in the directory) - the stock file of the historical values of the establishments - the stock file of the succession links of the establishments - the stock file of duplicate siren Each compacted file (ZIP format) contains a data file in CSV format. Files uploaded from the 1st of the month are an image of the Sirene directory as of the last day of the previous month. A stock file of a given month replaces that of the previous month. Discontinued legal units and closed establishments are included, thus providing access to Sirene data since 1973. Updates Infra-monthly updates of these files, including daily updates, are possible: - using the SIRENE APIs available on the catalogue of the INSEE APIs. With the API, you have access to variables indicating, for both establishments and legal units, the date of the last processing carried out. These are the variables dateLastUniteLegalTreatment and dateLastEstablishmentTreatment. Since this date is different from the date of the same record in your stock file, you know that an update has been made. Documentation on Sirene API variables and services is available on the [Documentation] tab (https://porttail-api.insee.fr/catalog/api/2ba0e549-5587-3ef1-9082-99cd865de66f/doc?page=52d26f24-963b-4fc0-926f-24963b4fc021) of each API; - using "Build a list" on sirene.fr (select Update Date tab) to be able to download files consisting of daily updates. You can consult the Sirene letter open data news n°2. Siren database containing personal data, INSEE draws your attention to the legal obligations arising therefrom: - The processing of these data falls in particular under the obligations of the General Data Protection Regulation (GDPR), of Law 78-17 of 6 January 1978 as amended, known as CNIL Law - Depending on your use of the dataset, it is therefore your responsibility to take into account the most recent distribution status of each natural person, which takes into account the objections made by some of them, to the consultation or use of their SIRENE data by third parties other than authorized administrations or bodies. - Legal units or establishments which have a distribution status coded ‘P’ (resp. statusDiffusionUniteLegale or statusDiffusionEtablissement) are subject to partial dissemination of data following a request for opposition. For an objection by a natural person, the identity of the entrepreneur (surname, first names, etc.), the address in the municipality and the geolocation will be masked (i.e. not disseminated by the SIRENE API). In case of opposition by legal representatives of a legal person, the address of the establishment in the municipality and its geolocation will be hidden. It is understood that data relating to legal representatives are not disseminated by INSEE as Open Data, even in the absence of opposition, in accordance with**Article R 123-232** of the French Commercial Code. If you are a company: - ATTENTION , for any request to create, modify or change your administrative situation, please contact Guichet Unique - ATTENTION, no request of this type arriving on this site can be satisfied.

The IvyDB Signed Volume dataset, available as an add-on product for IvyDB US, contains daily data on detailed option trading volume. Trades in the IvyDB US dataset are assigned as either buyer-initiated or seller-initiated based on the trade price and the bid-ask quote at the time of the trade. The total assigned daily volume is aggregated and updated nightly.

View data of the S&P 500, an index of the stocks of 500 leading companies in the US economy, which provides a gauge of the U.S. equity market.

The system marginal price refers to the electricity market price (KRW/kWh) for the amount of electricity applied by trading hour, and you can search for the system marginal price information by hour, divided into the mainland and Jeju regions. ㅇ Note 1: The trading time 0:00 of the API indicates the period starting immediately after 0:00 and ending at 01:00. ㅇ Note 2: The API will be deleted in the future, and we recommend using the Korea Power Exchange_System Marginal Price and Demand Forecast (for one-day-ahead power generation plan) API. ㅇ Updated to OPENAPI User Guide v1.5 on 2024.11.29

Overall, this project was meant test the relationship between social media posts and their short-term effect on stock prices. We decided to use Reddit posts from financial specific subreddit communities like r/wallstreetbets, r/investing, and r/stocks to see the changes in the market associated with a variety of posts made by users. This idea came to light because of the GameStop short squeeze that showed the power of social media in the market. Typically, stock prices should purely represent the total present value of all the future value of the company, but the question we are asking is whether social media can impact that intrinsic value. Our research question was known from the start and it was do Reddit posts for or against a certain stock provide insight into how the market will move in a short window. To solve this problem, we selected five large tech companies including Apple, Tesla, Amazon, Microsoft, and Google. These companies would likely give us more data in the subreddits and would have less volatility day to day allowing us to simulate an experiment easier. They trade at very high values so a change from a Reddit post would have to be significant giving us proof that there is an effect.

Next, we had to choose our data sources for to have data to test with. First, we tried to locate the Reddit data using a Reddit API, but due to circumstances regarding Reddit requiring approval to use their data we switched to a Kaggle dataset that contained metadata from Reddit. For our second data set we had planned to use Yahoo Finance through yfinance, but due to the large amount of data we were pulling from this public API our IP address was temporarily blocked. This caused us to switch our second data to pull from Alpha Vantage. While this was a large switch in the public it was a minor roadblock and fixing the Finance pulling section allowed for everything else to continue to work in succession. Once we had both of our datasets programmatically pulled into our local vs code, we implemented a pipeline to clean, merge, and analyze all the data. At the end, we implement a Snakemake workflow to ensure the project was easily reproducible. To continue, we utilized Textblob to label our Reddit posts with a sentiment value of positive, negative, or neutral and provide us with a correlation value to analyze with. We then matched the time frame of each post with the stock data and computed any possible changes, found a correlation coefficient, and graphed our findings.

To conclude the data analysis, we found that there is relatively small or no correlation between the total companies, but Microsoft and Google do show stronger correlations when analyzed on their own. However, this may be due to other circumstances like why the post was made or if the market had other trends on those dates already. A larger analysis with more data from other social media platforms would be needed to conclude for our hypothesis that there is a strong correlation.

Global Sanction Screening and Access Options

Our Global Sanction Lists Database is a powerful tool designed for quick and easy global sanction screening and verification of both individuals and organizations listed on international sanction lists. This service emphasizes the fight against money laundering and terrorism financing (AML-CFT), ensuring your business stays in line with global regulations. We keep our database up to date every day, processed into a professional and secure system, giving you access to the most current information.

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EU-Level PEP Screening and Access Options

Our service provides exclusive access to a database for EU-level PEP screening of Politically Exposed Persons at the European Union level. It empowers obligated entities to efficiently identify individuals with significant public roles within EU institutions and bodies. This database provides insights into persons currently in or those who have held significant public positions in Brussels and other EU institutions in the last 12 months. It spans not only individuals in key positions but also their relatives, broadening the scope for risk assessment. With daily updates from diverse public sources and careful manual processing, our database aids organizations in effectively navigating compliance and mitigating PEP-related risks.

PEP Group 1: Significant Public Functions

Includes individuals currently in or who have in the last 12 months held function of significant public role as defined by the Directive of the European Parliament and of the Council EU 2015/849 and further detailed in the Commission Decision C/2002/3105. Profiles generally include the exact date of birth and usually the domicile. In cases where the full date of birth is not available, the indication "Partially Identified PEP" is displayed. Individuals with enduring risks are recorded for up to five years after ending their function, especially for positions of pan-European significance or extended duration.

Specific Positions within PEP Group 1: Executive Authority Leaders Legislative Members Judges Members of the European Central Bank Bodies Members of the Court of Auditors Ambassadors and Chargés d’Affaires

PEP Groups 2 - 4 and 7: Family and Close Associates

Includes spouses/partners, children (including sons-in-law and daughters-in-law), and parents of individuals in Group PEP1, as well as individuals in a familial or similar relationship.

Specification PEP2: Spouse/partner PEP3: Child/son-in-law/daughter-in-law PEP4: Parent PEP7: Individuals in a long-term familial or similar relationship

A passenger flight schedule information service that displays information such as airline name, airport name, airport code, start date, end date, flight number, day of the week information, season code value, code type, master flight number, etc. of passenger flights departing/arriving at Incheon Airport in multiple languages (Korean, English, Japanese, Chinese) using the airport code value as a search condition. ※ It may differ from the information on MASTER FLIGHT/SLAVE flight numbers provided by the open daily flight API. Please be informed that the data is for one season (summer: late March to late October/winter: late October to late March of the following year) and the update cycle is different from the daily flight API below. * Passenger flight operation status detailed inquiry service API, passenger flight weekly operation status API, passenger flight operation status (multilingual) API

(Korean, English, Japanese, Chinese) Regular passenger flight schedule information service that displays information such as airline name, airport name, airport code, start date, end date, flight number, day of the week information, season code value, codeshare classification, and master flight number for passenger flights departing/arriving at Incheon Airport using the airport code value as a search condition. ※ It may differ from the information on MASTER FLIGHT/SLAVE flight numbers provided by the open daily flight status API. Please be informed that the data is for one season (summer: late March to late October/winter: late October to late March of the following year) and the update cycle is different from the API below. * Passenger flight operation status detailed inquiry service API, passenger flight weekly operation status API, passenger flight operation status (multilingual) API, etc.

Water samples from the Zackenberg River is collected near the Hydrometric station at 08:00 and 20:00 o'clock every day in the period 1997-2011 and three times a week from 2012-present. The water samples are filtered onto a Whatman GF/F filter (0.7 um) and dried at 105 degrees Celcius. After the end of the season the filters are brought to the Department of Geosciences and Natural Resource Management and analyzed for organic matter, using loss on ignition.

Comprehensive Federal Tax Lien Data by CompCurve Unlock unparalleled insights into tax lien records with CompCurve Federal Tax Lien Data, a robust dataset sourced directly from IRS records. This dataset is meticulously curated to provide detailed information on federal tax liens, unsecured liens, and tax-delinquent properties across the United States. Whether you're a real estate investor, financial analyst, legal professional, or data scientist, this dataset offers a treasure trove of actionable data to fuel your research, decision-making, and business strategies. Available in flexible formats like .json, .csv, and .xls, it’s designed for seamless integration via bulk downloads or API access, ensuring you can harness its power in the way that suits you best.

IRS Tax Lien Data: Unsecured Liens in Focus At the heart of this offering is the IRS Tax Lien Data, capturing critical details about unsecured federal tax liens. Each record includes key fields such as taxpayer full name, taxpayer address (broken down into street number, street name, city, state, and ZIP), tax type (e.g., payroll taxes under Form 941), unpaid balance, date of assessment, and last day for refiling. Additional fields like serial number, document ID, and lien unit phone provide further granularity, making this dataset a goldmine for tracking tax liabilities. With a history spanning 5 years, this data offers a longitudinal view of tax lien trends, enabling users to identify patterns, assess risk, and uncover opportunities in the tax lien market.

Detailed Field Breakdown for Precision Analysis The Federal Tax Lien Data is structured with precision in mind. Every record includes a document_id (e.g., 2025200700126004) as a unique identifier, alongside the IRS-assigned serial_number (e.g., 510034325). Taxpayer details are comprehensive, featuring full name (e.g., CASTLE HILL DRUGS INC), and, where applicable, parsed components like first name, middle name, last name, and suffix. Address fields are equally detailed, with street number, street name, unit, city, state, ZIP, and ZIP+4 providing pinpoint location accuracy. Financial fields such as unpaid balance (e.g., $15,704.43) and tax period ending (e.g., 09/30/2024) offer a clear picture of tax debt, while place of filing and prepared_at_location tie the data to specific jurisdictions and IRS offices.

National Coverage and Historical Depth Spanning the entire United States, this dataset ensures national coverage, making it an essential resource for anyone needing a coast-to-coast perspective on federal tax liens. With 5 years of historical data, users can delve into past tax lien activity, track refiling deadlines (e.g., 01/08/2035), and analyze how tax debts evolve over time. This historical depth is ideal for longitudinal studies, predictive modeling, or identifying chronic tax delinquents—key use cases for real estate professionals, lien investors, and compliance experts.

Expanded Offerings: Secured Real Property Tax Liens Beyond unsecured IRS liens, CompCurve enhances its portfolio with the Real Property Tax Lien File, focusing on secured liens tied to real estate. This dataset includes detailed records of property tax liens, featuring fields like tax year, lien year, lien number, sale date, interest rate, and total due. Property-specific data such as property address, APN (Assessor’s Parcel Number), FIPS code, and property type ties liens directly to physical assets. Ownership details—including owner first name, last name, mailing address, and owner-occupied status—add further context, while financial metrics like face value, tax amount, and estimated equity empower users to assess investment potential.

Tax Delinquent Properties: A Wealth of Insights The Real Property Tax Delinquency File rounds out this offering, delivering a deep dive into tax-delinquent properties. With fields like tax delinquent flag, total due, years delinquent, and delinquent years, this dataset identifies properties at risk of lien escalation or foreclosure. Additional indicators such as bankruptcy flag, foreclosure flag, tax deed status, and payment plan flag provide a multi-dimensional view of delinquency status. Property details—property class, building sqft, bedrooms, bathrooms, and estimated value—combined with ownership and loan data (e.g., total open loans, estimated LTV) make this a powerhouse for real estate analysis, foreclosure tracking, and tax lien investment.

Versatile Formats and Delivery Options CompCurve ensures accessibility with data delivered in .json, .csv, and .xls formats, catering to a wide range of technical needs. Whether you prefer bulk downloads for offline analysis or real-time API access for dynamic applications, this dataset adapts to your workflow. The structured fields and consistent data types—such as varchar, decimal, date, and boolean—ensure compatibility with databases, spreadsheets, and programming environments, making it easy to integrate into your ...

DRAKO is a Mobile Location Audience Targeting provider with a programmatic trading desk specialising in geolocation analytics and programmatic advertising. Through our customised approach, we offer business and consumer insights as well as addressable audiences for advertising.

Mobile Location Data can be meaningfully transformed into Audience Targeting when used in conjunction with other dataset. Our expansive POI Data allows us to segment users by visitation to major brands and retailers as well as categorizes them into syndicated segments. Beyond POI visits, our proprietary Home Location Model determines residents of geographic areas such as Designated Market Areas, Counties, or States. Relatedly, our Home Location Model also fuels our Geodemographic Census Data segments as we are able to determine residents of the smallest census units. Additionally, we also have audiences of: ticketed event and venue visitors; survey data; and retail data.

All of our Audience Targeting is 100% deterministic in that it only includes high-quality, real visits to locations as defined by a POIs satellite imagery buildings contour. We never use a radius when building an audience unless requested. We have a horizontal accuracy of 5m.

Additionally, we can always cross reference your audience targeting with our syndicated segments:

Overview of our Syndicated Audience Data Segments: - Brand/POI segments (specific named stores and locations) - Categories (behavioural segments - revealed habits) - Census demographic segments (HH income, race, religion, age, family structure, language, etc.,) - Events segments (ticketed live events, conferences, and seminars) - Resident segments (State/province, CMAs, DMAs, city, county, sub-county) - Political segments (Canadian Federal and Provincial, US Congressional Upper and Lower House, US States, City elections, etc.,) - Survey Data (Psychosocial/Demographic survey data) - Retail Data (Receipt/transaction data)

All of our syndicated segments are customizable. That means you can limit them to people within a certain geography, remove employees, include only the most frequent visitors, define your own custom lookback, or extend our audiences using our Home, Work, and Social Extensions.

In addition to our syndicated segments, we’re also able to run custom queries return to you all the Mobile Ad IDs (MAIDs) seen at in a specific location (address; latitude and longitude; or WKT84 Polygon) or in your defined geographic area of interest (political districts, DMAs, Zip Codes, etc.,)

Beyond just returning all the MAIDs seen within a geofence, we are also able to offer additional customizable advantages: - Average precision between 5 and 15 meters - CRM list activation + extension - Extend beyond Mobile Location Data (MAIDs) with our device graph - Filter by frequency of visitations - Home and Work targeting (retrieve only employees or residents of an address) - Home extensions (devices that reside in the same dwelling from your seed geofence) - Rooftop level address geofencing precision (no radius used EVER unless user specified) - Social extensions (devices in the same social circle as users in your seed geofence) - Turn analytics into addressable audiences - Work extensions (coworkers of users in your seed geofence)

Data Compliance: All of our Audience Targeting Data is fully CCPA compliant and 100% sourced from SDKs (Software Development Kits), the most reliable and consistent mobile data stream with end user consent available with only a 4-5 day delay. This means that our location and device ID data comes from partnerships with over 1,500+ mobile apps. This data comes with an associated location which is how we are able to segment using geofences.

Data Quality: In addition to partnering with trusted SDKs, DRAKO has additional screening methods to ensure that our mobile location data is consistent and reliable. This includes data harmonization and quality scoring from all of our partners in order to disregard MAIDs with a low quality score.