I work with UK company information on a daily basis, and I thought it would be useful to publish a list of all active companies, in a way that could be used for machine learning.

There are 3,838,469 rows in the dataset, one for each active company. Each row, has the company name, date of incorporation and the Standard Industrial Classification Code.

The company list is from the publicly available 1st November 2017 Companies House snapshot.

The SIC code descriptions are from the gov.uk website.

In the file AllCompanies.csv each row is formatted as follows:

• CompanyName - Alpha numberic company name
• IncorporationDate - in British date format, dd/mm/yyyy
• SIC - 5 digits or if not known, None - see separate file for description of each code.

Inspiration

Possible uses for this data is to use ML to suggest a new unique but suitable name for a company based on what other companies of the same SIC are called.

Perhaps analyse how company names have evolved over time.

Using ML, perhaps determine what a typical company name looks like, maybe analyse if company names have got longer or more complicated over time.

I am sure there are many more possible uses for this data in ways, that I cannot imagine.

This is my second go (the first was published a few hours ago) at publishing a dataset on any medium, so any useful tips and hints would be extremely welcome.

Links to the raw data sources are here:

• Companies House http://download.companieshouse.gov.uk/en_output.html
• SIC Codes https://www.gov.uk/government/publications/standard-industrial-classification-of-economic-activities-sic

Provided by CorpSignals.com

Overview

This dataset offers a comprehensive overview of the export activities of UK companies in 2022 year. It includes detailed information on exported commodities, classification codes, trading periods, and associated companies. The data has been meticulously curated and processed to ensure accuracy and relevance, making it a valuable resource for economic analysis, market research, and supply chain management.

Play with this dataset at the BI app. (Free registration is required)

Contents

The dataset comprises the following tables:

1. companies
2. importers

Below is a detailed description of each table.

1. companies

Description: Contains detailed information about companies registered in the UK up to January 1, 2024.

Columns:

• company_number: Unique identifier for each company.
• company_type: Type of company (e.g., private limited, public limited).
• office_address: Registered office address.
• incorporation_date: Date of company incorporation.
• jurisdiction: Legal jurisdiction of the company.
• company_status: Current status (e.g., active, dissolved).
• account_type: Type of accounts filed.
• company_name: Official name of the company.
• sic_codes: Standard Industrial Classification codes.
• date_of_cessation: Date when the company ceased operations (if applicable).
• next_accounts_overdue: Indicator if the next accounts are overdue.
• confirmation_statement_overdue: Indicator if the confirmation statement is overdue.
• owners: Number of registered owners (persons with significant control).
• officers: Number of officers (directors, secretaries) associated with the company.
• average_number_employees_during_period: Average number of employees during the last accounting period.
• current_assets: Current assets as per the last accounts.
• last_accounts_period_end: End date of the last accounting period.
• company_url: Where you can check the up-to-date company information. Free registration is required.

Data Generation Process:

• Aggregated counts of owners and officers from the ch_psc and ch_officers tables.
• Joined with the ch_accounts table to include financial information.
• Filtered to include companies incorporated on or before January 1, 2024.

2. exported

Description: Contains detailed records of commodities exported by UK companies, including classification codes, descriptions, trading periods, and company information.

Columns:

• commodity_code: The specific code representing the commodity exported, following the Harmonized System (HS) nomenclature.
• sitc_code: Standard International Trade Classification code for the commodity.
• hs_description: Detailed description of the commodity as per the HS classification.
• hs_section: The section of the HS code that categorizes the commodity.
• company_number: Unique identifier for the exporting company.
• first_date: The date of the first recorded export transaction for the commodity by the company.
• last_date: The date of the most recent export transaction for the commodity by the company.
• months_traded: Total number of months the commodity was traded within the specified period.
• company_url: URL linking to the company's profile for more detailed information. (e.g., Wiedenmann UK Ltd)

Data Generation Process:

• Data Collection: Aggregated export records from UK customs and trade databases in the 2022 year.
• Data Cleaning: Removed incomplete or inconsistent entries to ensure data integrity.
• Classification: Assigned SITC and HS codes to each commodity for standardized classification.
• Aggregation: Calculated trading periods and total months traded for each commodity-company pair.
• Enrichment: Added company URLs for reference and further information.

Data Sources

• UK Customs and Trade Databases: Official records of export transactions and commodity classifications.
• Standard International Trade Classification (SITC): For categorizing traded commodities.
• Harmonized System (HS) Codes: International nomenclature for the classification of products.

Data Processing Details

• Time Frame: 2022
• Filtering Criteria: Included all import transactions by UK-registered companies within the specified period.
• Data Cleaning: Excluded records with missing or invalid commodity codes, company numbers, or transaction dates.
• Classification: Mapped commodities to SITC and HS codes based on official classification guidelines.
• Aggregation: Summarized trading activity by calculating the number of months each commodity was traded by each company.

Potential Uses

• Market Analysis: Identify trends and patterns in import...

These are downloadable open format versions of the complete monthly Overseas Trade Statistics (OTS) and Importers Details datasets, with a 6 year archive of past data. They are published by HM Revenue and Customs on its trade statistics website www.uktradeinfo.com. (See additional links below) The files contain commodity and partner country-level import and export information, organised in six sets of flat files: Control Files - including descriptions for each 8 digit commodity code and the standard abbreviations for units Exports - containing data for goods exported from the UK to all countries excluding the European Union (EU) Imports - containing data for goods imported to the UK from all countries excluding the EU Trader Files - names, addresses and post codes of UK importers of goods from countries excluding the EU Dispatches - containing data (including estimates) for goods exported from the UK to all EU countries Arrivals - containing data (including estimates) for goods imported to the UK from all EU countries

OS Open Names is an OpenData dataset that includes place names, road names and numbers and postcode for Great Britain and includes 2.5 million locations. The OS Open Names locator allows geocoding and searching against postcodes, street names, road numbers and places all in a single locator.

For more information about the OS Open Names dataset visit the following link: https://www.ordnancesurvey.co.uk/business-and-government/products/os-open-names.htmlData currency : January 2022

24729 United Kingdom export shipment records of Name, Badge to India with prices, volume & current Buyer's suppliers relationships based on actual United Kingdom export trade database.

The Annual Business Survey (ABS) is an annual survey of businesses covering the production, construction, distribution and service industries, which represents about two-thirds of the UK economy in terms of Gross Value Added (GVA).

Every year, ABS questionnaires are sent by the Office for National Statistics (ONS) to around 62,000 businesses in Great Britain, and by the Department for Finance and Personnel Northern Ireland (DFPNI) to around 9,000 businesses in Northern Ireland. Data for Northern Ireland are not available from the UK Data Archive.

The ABS is the largest business survey conducted by the ONS in terms of the combined number of respondents and variables it covers (62,000 questionnaires despatched in Great Britain, with around 600 different questions asked). It is the key resource for understanding the detailed structure and performance of businesses across the UK, and is a large contributor of business information to the UK National Accounts.

ABS provides a number of high-level indicators of economic activity such as the total value of sales and work completed by businesses, the value of purchases of goods, materials and services, stocks, capital expenditure, and total employment costs.

The contribution of different industries to the overall value of economic activity can be assessed and, although estimates of employment from each company are not now collected at the same time, by combining ABS with employment information from the Business Register and Employment Survey (BRES) it is also possible to get a measure of value added and costs per head to allow better comparison between industrial sectors of different sizes. The indicators in the ABS publications are collected and presented as monetary values or counts, for example, approximate Gross Value Added (aGVA), numbers of enterprises. They are essentially a snapshot of UK business activity, and can be used to understand the level of the contributions to the UK economy from different sectors of the economy at any one time.

The ABS replaced the Annual Business Inquiry, Part 2 (ABI/2) in 2009, although ABS data are available for 2008. The BRES replaced the Annual Business Inquiry, Part 1 (ABI/1) in 2009. The BRES data for 2009 onwards are held separately under UK Data Archive SN 7463. ABI/1 and ABI/2 data for 2008 and earlier are held under UK Data Archive SN 6644, Annual Respondents Database: Secure Access (ARD). Researchers who are applying for access to the ABS and who also require data prior to 2008 are recommended to also apply for the ARD data under SN 6644.

Linking to other business studies
These data contain Inter-Departmental Business Register reference numbers. These are anonymous but unique reference numbers assigned to business organisations. Their inclusion allows researchers to combine different business survey sources together. Researchers may consider applying for other business data to assist their research.

For Secure Lab projects applying for access to this study as well as to SN 6697 Business Structure Database and/or SN 7683 Business Structure Database Longitudinal, only postcode-free versions of the data will be made available.

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Data Source:

• This dataset contains food hygiene ratings scraped from the Food Standards Agency (FSA) website: https://www.food.gov.uk/our-data

  License:

• This data is licensed under the Open Government Licence (OGL) v3.0 (https://www.nationalarchives.gov.uk/doc/open-government-licence/version/3/)

United Kingdom Imports of lamps and lighting fitting; illuminated signs, illuminated name-plates from Uzbekistan was US$11.99 Thousand during 2018, according to the United Nations COMTRADE database on international trade.

Marks And Spencer Plc Bradford Dc Uk Export Import Data. Follow the Eximpedia platform for HS code, importer-exporter records, and customs shipment details.

Marks And Spencer Plc Uk Maersk L Export Import Data. Follow the Eximpedia platform for HS code, importer-exporter records, and customs shipment details.

Abstract copyright UK Data Service and data collection copyright owner.

The Patents, Designs and Trade Marks, 2010: Secure Access dataset includes details on applications to the Intellectual Property Office (IPO) for patents, designs and trade marks by businesses or individuals.

The patent file holds the main information for all patents in Great Britain attained through the Department of Business, Innovation and Skills' Optics extract in June/July 2010. The file includes patent applications filed between 1978 and 2009. There should be no multiple observations due to the uniqueness and single occurrence of an application number within these datasets. A patent can have more than one IPC classification, depending on how many purposes it fulfils.

The trade mark analysable dataset was created using the trade mark licensee data, which relates to trademarks applied for with the IPO. The data were extracted in July 2010 and include applications filed between 1876 and 2010. The licensee data is that provided to the IPO's external customers and holds the same information as contained within the IPO website. This dataset represents one of four relating to trade marks; this covers all trade marks applied for within the UK - there are three other datasets relating to trade marks applied for via the Madrid UK/Madrid EP agreements and Office of Harmonization for the Internal Market.

The UK design data represent all designs applied for with the IPO between 1974 and 2010. The data were extracted in May 2010.

The patent, design and trade mark data provided are readily available from online sources. The data are provided for Secure Access so that users can link the data to Secure Access business surveys using Inter-Departmental Business Register (IDBR) reference numbers, which are anonymous but unique reference numbers assigned to business organisations. Other Secure Access business surveys with which users may wish to combine the IPO data include the Annual Respondents Database (SN 6644), the UK Innovation Survey (SN 6699), and the Business Expenditure on Research and Development survey (SN 6690).

In preparing the patent, design and trade mark data for release, certain variables that can lead to the identification of businesses or individuals on the IPO website have been anonymised. These variables include applicant numbers, application numbers and design numbers.

The patent data include postcodes for a proportion of the applicants. The trade mark data include the country of the proprietor. The design data include no spatial units.

For Secure Lab projects applying for access to this study as well as to SN 6697 Business Structure Database and/or SN 7683 Business Structure Database Longitudinal, only postcode-free versions of the data will be made available.

• dates for filing, registering, issue, expiry and renewal of applications
• descriptions
• International Patent Classifications
• anonymised identification numbers
• IDBR reference numbers
  

Zambia Imports from United Kingdom of Lamps and Lighting Fitting; Illuminated Signs, Illuminated Name-plates was US$16.09 Thousand during 2024, according to the United Nations COMTRADE database on international trade.

Techsalerator’s Import/Export Trade Data for Latin America

Techsalerator’s Import/Export Trade Data for Latin America delivers an extensive and detailed analysis of trade activities throughout the Latin American region. This comprehensive dataset provides valuable insights into import and export transactions involving companies across various sectors within Latin America.

Coverage Across All Latin American Countries

The dataset encompasses all countries in Latin America, including:

Argentina Bolivia Brazil Chile Colombia Ecuador Guyana Paraguay Peru Suriname Uruguay Venezuela Additionally, it includes countries in Central America and the Caribbean:

Belize Costa Rica El Salvador Guatemala Honduras Nicaragua Panama Cuba Dominican Republic Haiti Jamaica Trinidad and Tobago Comprehensive Data Features

Transaction Details: The dataset provides detailed information on individual trade transactions, including product descriptions, quantities, values, and dates. This allows for precise tracking of trade flows and patterns.

Company Information: It includes specific details about the companies involved in trade, such as company names, locations, and industry sectors, facilitating targeted market research and business analysis.

Categorization: Transactions are categorized by industry sectors, product types, and trade partners. This helps in understanding market dynamics and sector-specific trends within the region.

Trade Trends: Users can analyze historical data to observe trends and shifts in trade volumes, identify emerging markets, and assess the impact of economic or political events on trade patterns.

Geographical Insights: The data offers insights into regional trade flows and the relationships between Latin American countries and their global trade partners, including major trading nations outside the region.

Regulatory and Compliance Data: The dataset includes information on trade regulations, tariffs, and compliance requirements, aiding businesses in navigating the regulatory landscape of international trade within Latin America.

Applications and Benefits

Market Research: Businesses can utilize the data to uncover new market opportunities, analyze competitive landscapes, and understand consumer demand across various Latin American countries.

Strategic Planning: Companies can leverage insights from the data to refine trade strategies, optimize supply chains, and mitigate risks associated with international trade in the region.

Economic Analysis: Analysts and policymakers can use the data to monitor economic performance, evaluate trade balances, and make informed decisions on trade policies and economic development initiatives.

Investment Decisions: Investors can assess trade trends and market potentials to make informed decisions about investments in Latin America’s diverse economies.

Techsalerator’s Import/Export Trade Data for Latin America provides a crucial resource for organizations involved in international trade, offering a detailed, reliable, and expansive view of trade activities across the Latin American continent.

Trade Union Facilities for non-schools staff. This data set includes: Total number (absolute number and full time equivalent) of staff who are union representatives (including general, learning and health and safety representatives), Total number (absolute number and full time equivalent) of union representatives who devote at least 50 per cent of their time to union duties, and Names of all Trade Unions represented in Manchester City Council including a basic estimate of spending on unions as a percentage of the total pay bill (calculated as % spent on trade union facilities for full-time officers divided by the total pay bill). The data is derived from records held on trade union representatives both at branch and local level. The financial information has been derived from spend data assigned to the trade union facilities cost centre. The data on percentage of the total pay bill has been derived by dividing the total trade union facilities spend (2013/14) by the total pay bill (2013/14). The recognised Trade Unions represented in Manchester City Council are UNISON, GMB, UNITE, UCU and UCATT.

This file contains the names and codes for National Assembly Economic Regions in Wales as at 31 December 2017. (File Size - 16 KB)

Names of the Trade Unions represented in North Somerset Council

Credit report of Uk Trade And Shipping contains unique and detailed export import market intelligence with it's phone, email, Linkedin and details of each import and export shipment like product, quantity, price, buyer, supplier names, country and date of shipment.

Dragons' Den dataset of UK/British TV programm, business reality television series. Currently, the data set has information from United Kingdom Dragons' Den series 1 to series 22. The dataset has 56 fields and 1460+ rows.

• Season Number - Season number
• Episode Number - Episode number within the season
• Startup Name - Company name or product name, at the time of pitch
• Pitch Number - Overall pitch number
• Season Start - Season first aired date
• Season End - Season last aired date
• Original Air Date - Episode original/first aired date, on OTT/TV
• Industry - Industry name or type
• Business Description - Business Description
• Company Website - Website of startup/company
• UK Viewership - Viewership in UK, TRP rating, in millions
• Channel Name - Channel or network name
• Pitchers Gender - Gender of pitchers
• Pitchers Average Age - Average age of all pitchers, <30 young, 30-50 middle, >50 old
• Pitchers City - UK city of pitchers or place where company head office exists
• Pitchers State - UK state or country of pitchers where company head office exists
• Entrepreneur Names - Pitcher names
• Multiple Entrepreneurs - Multiple entrepreneurs are present ? 1-yes, 0-no
• Original Ask Amount - Original Ask Amount, in GBP
• Original Offered Equity - Original Offered Equity, in percentages
• Valuation Requested - Valuation Requested, in GBP
• Received Offer - Received offer or not, 1-received, 0-not received
• Accepted Offer - Accepted offer or not, 1-accepted, 0-rejected
• Deal Successful - Deal Successful/materialized or not, 1-yes, 0-no
• Total Deal Amount - Total Deal Amount, in GBP, including debt/loan amount
• Total Deal Equity - Total Deal Equity, in percentages
• Deal Valuation - Deal Valuation, in GBP
• Number of Dragons in Deal - Number of Dragons in deal
• Investment Amount Per Dragon - Investment Amount Per Dragon
• Equity Per Dragon - Equity received by each Dragon
• Royalty Deal - Is it royalty deal or not (1-yes)
• Advisory Shares Equity - Deal with Advisory shares or equity, in percentages
• Loan - Loan/debt (line of credit) amount given by Dragons, in GBP
• Deal Has Conditions - Deal has conditions or not? (yes or no)
• Peter Jones Investment Amount - Amount Invested by Peter Jones
• Peter Jones Investment Equity - Equity received by Peter Jones
• Deborah Meaden Investment Amount - Amount Invested by Deborah Meaden
• Deborah Meaden Investment Equity - Equity received by Deborah Meaden
• Duncan Bannatyne Investment Amount - Amount Invested by Duncan Bannatyne
• Duncan Bannatyne Investment Equity - Equity received by Duncan Bannatyne
• Theo Paphitis Investment Amount - Amount Invested by Theo Paphitis
• Theo Paphitis Investment Equity - Equity received by Theo Paphitis
• Touker Suleyman Investment Amount - Amount Invested by Touker Suleyman
• Touker Suleyman Investment Equity - Equity received by Touker Suleyman
• Sara Davies Investment Amount - Amount Invested by Sara Davies
• Sara Davies Investment Equity - Equity received by Sara Davies
• Guest Investment Amount - Amount Invested by Guests
• Guest Investment Equity - Equity received by Guests
• Invested Guest Name - Name of Guest Dragon(s), if invested in deal
• Peter Jones Present - Whether Peter Jones present in episode or not
• Deborah Meaden Present - Whether Deborah Meaden present in episode or not
• Duncan Bannatyne Present - Whether Duncan Bannatyne present in episode or not
• Theo Paphitis Present - Whether Theo Paphitis present in episode or not
• Touker Suleyman Present - Whether Touker Suleyman present in episode or not
• Sara Davies Present - Whether Sara Davies present in episode or not
• Guest Present - Whether Guest(s) present in episode or not

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