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.

The British Geological Survey has one of the largest databases in the world on the production and trade of minerals. The dataset contains annual production statistics by mass for more than 70 mineral commodities covering the majority of economically important and internationally-traded minerals, metals and mineral-based materials. For each commodity the annual production statistics are recorded for individual countries, grouped by continent. Import and export statistics are also available for years up to 2002. Maintenance of the database is funded by the Science Budget and output is used by government, private industry and others in support of policy, economic analysis and commercial strategy. As far as possible the production data are compiled from primary, official sources. Quality assurance is maintained by participation in such groups as the International Consultative Group on Non-ferrous Metal Statistics. Individual commodity and country tables are available for sale on request.

Quick Stats API is the programmatic interface to the National Agricultural Statistics Service's (NASS) online database containing results from the 1997, 2002, 2007, and 2012 Censuses of Agriculture as well as the best source of NASS survey published estimates. The census collects data on all commodities produced on U.S. farms and ranches, as well as detailed information on expenses, income, and operator characteristics. The surveys that NASS conducts collect information on virtually every facet of U.S. agricultural production.

Spreads, options on futures, auction data, and more from the largest commodities exchanges. Real-time and historical energy, agriculture, and metals futures data, all sourced directly from CME and ICE. Deliver straight to your application or download as flat files. Data is available in up to 15 formats.

Our continuous contract symbology is a notation that maps to an actual, tradable instrument on any given date. The prices returned are real, unadjusted prices. We do not create a synthetic time series by adjusting the prices to remove jumps during rollovers.

Databento is a licensed distributor and direct provider of market data for 70+ trading venues. We power research, trading, and risk management firms in the volatile physical commodities markets.

Release Date: 2020-07-16.Release Schedule:.The data in this file was released in July 2020. The data in this file was modified January 28, 2021...Source:.Suggested Citation: U.S. Department of Transportation, Bureau of Transportation Statistics; and, U.S. Department of Commerce, U.S. Census Bureau. (2021-01-28). Geographic Area Series: Shipment Characteristics by Mode of Transportation - Truck: 2017 [dataset]. 2017 Commodity Flow Survey. Accessed [enter date you accessed/downloaded this table here] from https://data.census.gov/cedsci/table?q=cf1700a03&hidePreview=true&tid=CFSAREA2017.CF1700A03...Key Table Information:.The estimates presented are based on data from the 2017 Commodity Flow Surveys (CFS) and supersede data previously released in the 2017 CFS Preliminary Report. These estimates only cover businesses with paid employees. All dollar values are expressed in current dollars, i.e., they are based on price levels in effect at the time of each sample. Estimates may not be additive due to rounding...Due to definitional and processing changes made each survey year, any data comparisons between one CFS survey and another should be made with caution. See the Comparability of Estimates section of the Survey Methodology for more details...Table CF1700A03, new for the 2017 CFS, details the breakdown by truck mode of transportation. Please note that the estimates in this table may differ from CF1700A01. Table CF1700A03 displays estimates where truck was used for any part of the distance...Note: For this table only, the following exceptions apply:."All modes" refers to the total of all Truck shipments, single-mode and multi-mode.. "Truck" refers to single-mode truck shipments only.. "Multiple modes" refers to only those multi-mode shipments which include a truck segment.. "Air" refers to only those Air shipments which include truck to/from airport.. "Other multiple modes" refers to only those Other multiple mode shipments which include a truck segment....Data Items and Other Identifying Records:.This file contains data on:.Value ($ Millions). Tons (Thousands). Ton-miles (Millions). Average miles per shipment (Number). Coefficient of variation or standard error for all above data items...Geography Coverage:.The data are shown at the U.S. only. For information on Commodity Flow Survey geographies, including changes for 2017, see Census Geographies...Industry Coverage:.N/A..Footnotes:.N/A..FTP Download:.Download the entire table at: https://www2.census.gov/programs-surveys/cfs/data/2017/CF1700A03.zip...API Information:.Commodity Flow Survey data are housed in the Census Bureau API. For more information, see https://api.census.gov/data/2017/cfsarea.html...Methodology:.The noise infusion data protection method has been applied to prevent data disclosure, and to protect respondent's confidentiality. Estimates are based on a sample of establishments and are subject to both sampling and nonsampling error. Estimated measures of sampling variability are provided in the tables. For information on confidentiality protection, sampling error, and nonsampling error see Survey Methodology...Symbols:. S - Estimate does not meet publication standards because of high sampling variability, poor response quality, or other concerns about the estimate quality. Unpublished estimates derived from this table by subtraction are subject to these same limitations and should not be attributed to the U.S. Census Bureau. For a description of publication standards and the total quantity response rate, see link to program methodology page.. Z - Rounds to Zero.. X - Not Applicable..For a complete list of all economic programs symbols, see the Symbols Glossary...Contact Information:.U.S. Census Bureau.Commodity Flow Survey.Tel: (301) 763 - 2108.Email: erd.cfs@census.gov

FAS's PSD Online data for those commodities published in the WASDE Report are reviewed and updated monthly by an interagency committee chaired by USDA's World Agricultural Outlook Board (WAOB), and consisting of: the Foreign Agricultural Service (FAS), the Economic Research Service (ERS), the Farm Service Agency (FSA), and the Agricultural Marketing Service (AMS). The international portion of the data is updated with input from agricultural attachés stationed at U.S. embassies around the world, FAS commodity analysts, and country and commodity analysts with ERS. The U.S. domestic component is updated with input from analysts in FAS, ERS, the National Agricultural Statistical Service, and FSA. Interagency work on the database is carried out under the aegis of the WAOB. The official USDA supply and use data is published monthly in: WAOB, World Agricultural Supply and Demand Estimates (WASDE); in the foreign agricultural commodity circular series issued by FAS; and in the regional situation and outlook reports and monthly commodity newsletters of ERS (see keywords Crops and Animal Products) data for horticultural products are usually published twice a year. Resources in this dataset:Resource Title: PSD Web API. File Name: Web Page, url: https://apps.fas.usda.gov/psdonline/app/index.html#/app/about Programmatically access Production, Supply, and Distribution data via Web API.

S S T Commodities Fze Company Export Import Records. Follow the Eximpedia platform for HS code, importer-exporter records, and customs shipment details.

This dataset contains Saudi Arabia Exports According to commodities for 2000 - 2019 . Data from General Authority for Statistics . Export API data for more datasets to advance energy economics research. The information shown describe how much exported from a specific product, from which country, and the value with the volume for each. All rights reserved to General Authority for statistics © 2017

Xavvy Fuel is a global leader in Fuel Station POI and price data, specializing in data quality and enrichment across various sectors. We provide high-quality POI data on gas stations and fuel types throughout all European countries, tailored to our customers' specific needs, whether through one-time or regular data delivery, push or pull services, and in any data format.

In addition to Fuel Station data, our expertise extends across Energy Data, Places Data, Automotive Data, Fuel data, Competitive Data, Market Research Data, Oil & Gas Data, and Brand Data, enabling us to serve a wide range of industries with comprehensive market insights.

Our data addresses key questions like the total number of stations per country or region, market share distribution, and identifying prime locations for AdBlue stations or truck pumps. This provides an invaluable foundation for in-depth analyses, helping clients gain critical insights into the fuel market and beyond. With this data, businesses can make informed strategic decisions on business development, competition strategy, and market expansion.

Furthermore, our data enhances the accuracy and consistency of existing datasets, allowing for easy data mapping to detect and correct errors.

With over 130 sources—including governments, petroleum companies, fuel card providers, and crowd-sourcing—Xavvy offers extensive insights into AdBlue/DEF stations across Europe. For those displaying AdBlue station information on maps or applications, data quality is essential to delivering an exceptional customer experience. Our continuously refined processes ensure the highest data quality through: - Regular quality controls via monitoring dashboards - Geocoding systems to correct and refine geocoordinates - Cleaning and standardizing datasets - Keeping up with current developments and mergers - Expanding data sources to cross-reference and enrich data

Explore our additional data offerings across various sectors and gain deeper insights from experts in gas stations, AdBlue distribution, and more!

This dataset contains monthly historical prices of 10 different commodities from January 1980 to April 2023. The data was collected from the Alpha Vantage API using Python. The commodities included in the dataset are WTI crude oil, cotton, natural gas, coffee, sugar, aluminum, Brent crude oil, corn, copper, and wheat. Prices are reported in USD per unit of measurement for each commodity. The dataset contains 520 rows and 12 columns, with each row representing a monthly observation of the prices of the 10 commodities. The 'All_Commodities' column is new.

WTI: WTI crude oil price per unit of measurement (USD). COTTON: Cotton price per unit of measurement (USD). NATURAL_GAS: Natural gas price per unit of measurement (USD). ALL_COMMODITIES: A composite index that represents the average price of all 10 commodities in the dataset, weighted by their individual market capitalizations. Prices are reported in USD per unit of measurement. COFFEE: Coffee price per unit of measurement (USD). SUGAR: Sugar price per unit of measurement (USD). ALUMINUM: Aluminum price per unit of measurement (USD). BRENT: Brent crude oil price per unit of measurement (USD). CORN: Corn price per unit of measurement (USD). COPPER: Copper price per unit of measurement (USD). WHEAT: Wheat price per unit of measurement (USD).

Note that some values are missing in the dataset, represented by NaN. These missing values occur for some of the commodities in the earlier years of the dataset.

It may be useful for time series analysis and predictive modeling.

NaN values were included so that you as a Data Scientist can get some practice on dealing with NaN values.

https://www.alphavantage.co/documentation/

This dataset provides transport cost and trade flow metrics for Saudi Arabia as the destination, covering all commodities. It includes key indicators related to transport expenditures, freight rates, trade intensity, and shipment weight.Indicators:Transport Expenditure (US$) – Total transport costs.FOB Value (US$ in Thousands) – Value of goods before shipping costs.Per Unit Freight Rate (US$/kg) – Transport cost per kilogram.Transport Work (Ton-km) – Transport effort measured in ton-km.Transport Work (1000 km) – Transport effort per 1000 km.Transport Cost Intensity (US$/ton-km & US$/1000 km) – Cost per ton per km.Kilograms (Thousands) – Total shipment weight.Ad Valorem Freight Rate (%) – Freight costs as a percentage of FOB value.Unit Value (US$/kg) – Price per kilogram of goods.This dataset helps track shipping costs and trade logistics related to Saudi Arabia.

Welcome to the World Mineral Statistics archive API. The British Geological Survey (BGS) and its predecessor organisations have compiled production and trade statistics on a wide range of mineral commodities since 1913. Currently this tool permits access to data from the World Mineral Statistics archive for the years 1970 to 2022. Prior to 1970 the data are available in PDF files which you can download for free from the main archive page. Selected data from 1960 are also available from the main archive as a static table in MS Excel. For certain commodities data are not available for all years, for example the BGS commenced collation of data for primary aggregates in 1998 and consequently there are no data for earlier years for this particular commodity. Trade data (imports and exports) are available for all countries up to 2002, and for selected European countries only from 2003 to 2018. Please ensure that you have read and understand our terms and conditions for the data.

The Open Trade Statistics initiative was developed to ease access to international trade data by providing downloadable SQL database dumps, a public API, a dashboard, and an R package for data retrieval. This project was born out of the recognition that many academic institutions in Latin America lack access to academic subscriptions and comprehensive datasets like the United Nations Commodity Trade Statistics Database. The OTS project not only offers a solution to this problem regarding international trade data but also emphasizes the importance of reproducibility in data processing. Through the use of open-source tools, the project ensures that its datasets are accessible and easy to use for research and analysis.

OTS, based on the official correlation tables, provides a harmonized dataset where the values are converted to HS revision 2012 for the years 1980-2021 and it involved transforming some of the reported data to find equivalent codes between the different classifications. For instance, the HS revision 1992 code '271011' (aviation spirit) does not have a direct equivalent in HS revision 2012 and it can be converted to the more general code '271000' (oils petroleum, bituminous, distillates, except crude). The same process was applied to the SITC codes.

Country codes are also standardized in OTS. For instance, missing ISO-3 country codes in the raw data were replaced by the values expressed in UN COMTRADE documentation. For instance, the numeric code '490' corresponds to 'e-490' but it appears as a blank value in the raw data, and UN COMTRADE documentation
indicates that 'e-490' corresponds to 'Other Asia, Not Elsewhere Specified (NES)'.

Commercial purposes are strictly out of the boundaries of what you can do with this data according to UN Comtrade dissemination clauses.

Visit tradestatistics.io to access the dashboard and R package for data retrieval.

Altona Commodity Company Export Import Records. Follow the Eximpedia platform for HS code, importer-exporter records, and customs shipment details.

➡️A data set on select, monthly commodity prices made available by the World Bank in its so-called "pink sheet." These data are potentially useful for applications on data gathering, inflation adjustments, indexing, cointegration, general economic riff-raff, and more.

Details

All data are in nominal USD. Adjust (to taste) accordingly.

Data compiled by the World Bank for its historical data on commodity prices. The oil price data come from a combination of sources, supposedly Bloomberg, Energy Intelligence Group (EIG), Organization of Petroleum Exporting Countries (OPEC), and the World Bank. Data on coffee prices come from Bloomberg, Complete Coffee Coverage, the International Coffee Organization, Thomson Reuters Datastream, and the World Bank. Data on tea prices for Colombo auctions come the from International Tea Committee, Tea Broker's Association of London, Tea Exporters Association Sri Lanka, and the World Bank. Data on tea prices for Kolkata auctions come from the International Tea Committee, Tea Board India, Tea Broker's Association of London, and the World Bank. Tea prices for Mombasa/Nairobi auctions come from African Tea Brokers Limited, International Tea Committee, Tea Broker's Association of London, and the World Bank. EU sugar price data come from International Monetary Fund, World Bank. Sugar price data for the United States come from Bloomberg and World Bank. Global sugar price data come from Bloomberg, International Sugar Organization, Thomson Reuters Datastream, and the World Bank.

This data set effectively deprecates the sugar_price and coffee_price data sets in this package. Both may be removed at a later point.

American Commodity Company Llc Company Export Import Records. Follow the Eximpedia platform for HS code, importer-exporter records, and customs shipment details.

Commodity Quest Inc Company Export Import Records. Follow the Eximpedia platform for HS code, importer-exporter records, and customs shipment details.

Apex Commodities Company Export Import Records. Follow the Eximpedia platform for HS code, importer-exporter records, and customs shipment details.

Eximpedia Export import trade data lets you search trade data and active Exporters, Importers, Buyers, Suppliers, manufacturers exporters from over 209 countries

Eximpedia Export import trade data lets you search trade data and active Exporters, Importers, Buyers, Suppliers, manufacturers exporters from over 209 countries