Free monthly CSV files showing all newly incorporated, reinstated, and dissolved UK companies. Updated monthly with official Companies House data.

Context:

The People with significant control (PSC) snapshot is a data snapshot containing the full list of PSC's provided to Companies House. The Prime Minister first put corporate transparency on the international agenda when he chaired the G8 summit in Lough Erne and secured commitment to action, the commitment to enhance corporate transparency in the UK was reaffirmed at London’s International Anti-Corruption Summit in May 2016. Since then the EU and G20 countries have also agreed to act. The UK is the first country in the G20 to create a public register of this kind.

The UK has high standards of business behaviour and corporate governance. The overwhelming majority of UK companies contribute productively to the UK economy, abide by the law and make a valuable contribution to society. But there are exceptions. Some of the features of the company structure which make it good for business also make it attractive to criminals. Companies can be misused to facilitate a range of criminal activities - from money laundering to tax evasion, corruption to terrorist financing. Sometimes those individuals running companies will not conduct themselves in accordance with the high standards we expect in the UK, posing a risk to other companies and consumers alike.

Information about the ownership and control of UK corporate entities will bring benefits for law enforcement, business, civil society and citizens. By making this information publicly available, free of charge, the government is setting a standard that we are persuading other countries to follow.

Content:

A person of significant control is someone that holds more than 25% of shares or voting rights in a company, has the right to appoint or remove the majority of the board of directors or otherwise exercises significant influence or control. This is a snapshot of data in zipped JSON form, as of Aug 23 2017. Daily updated snapshots and streaming API details can be found here. The People with Significant Control (PSC) register includes information about the individuals who own or control companies including their name, month and year of birth, nationality, and details of their interest in the company. From 30 June 2016, UK companies (except listed companies) and limited liability partnerships (LLPs) need to declare this information when issuing their annual confirmation statement to Companies House.

Acknowledgements:

Guidance here. The data is collected by UK government.

Inspiration:

• Who owns the most businesses? In certain areas?
• Any weird looking situations where ownership might be obscured?

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

A list of businesses located in London showing a range of information including company name, address, postcode, local authority, and SIC code (industry).

The Free Company Data Product is a downloadable data snapshot containing basic company data of live companies on the register. The version available from Companies House has all UK business and is available to download in a series of Zip folders.

The London cut available to download here, was created using a postcode list. Therefore, if there is an error in the postcode, or some other problem caused the postcode listed not to match a London postcode, those business will not be included in the file. Furthermore, inaccuracies in postcodes may mean that no local authority is listed for a company.

Each entry represents a financial accounts submission of either a whole company or part of one. Some businesses have more than one entry in the directory because they need to submit more than one set of accounts for different parts of their business. Therefore, the number of entries in the directory will be greater than the number of businesses.

Note, Large file size - the Excel file is almost 600MB.

Companies House update the latest snapshot within 5 working days of the previous month end. The London file available here was published on 1 May 2018.

Further metadata and user guidance is available here.

The Free Company Data Product is a downloadable data snapshot containing basic company data of live companies on the register. This dataset is just for Calderdale companies. The full download is here -http://download.companieshouse.gov.uk/en_output.html A list of the data fields contained in the snapshot can be found here - http://resources.companieshouse.gov.uk/toolsToHelp/pdf/freeDataProductDataset.pdf

The 20,000+ registered companies with a registered address in Glasgow. The information is extracted from Companies House. It includes the company name, number, category (private limited, partnership), registered address, postcode, industry (SIC code), status (ex: active or liquidation), incorporation date... It is likely that some companies may just lie off Glasgow City Council's boundary. If you find a problem in the data, you can check the source either in the full UK list or by looking up a company or let us know. The data dictionary supplied by Companies House can be viewed here. There is also a data dictionary with field names and meanings contained in the resources. This dataset does not imply: - a partnership with Companies House - an endorsement by Companies House - a product approval by Companies House Licence: None glasgow-post-codes-py.txt - https://dataservices.open.glasgow.gov.uk/Download/Organisation/cc57ac4b-12d5-43b1-ad25-434638eec18c/Dataset/3093e34f-6dcb-4980-840b-965421c1b091/File/c2634107-bd43-4537-adb8-9046aeed844e/Version/c8fde78e-5396-4293-ac35-6f6c96a5d642

Graph and download economic data for Finance Companies; Home Equity Lines of Credit; Asset, Transactions (BOGZ1FU613065200A) from 1971 to 2024 about HELOCs, home equity, finance companies, companies, finance, credits, transactions, financial, assets, and USA.

HM Land Registry’s UK Companies data contains entries made in the Title Register for property in England and Wales owned by Companies incorporated in the UK. The data includes the following ownership types: corporations aggregate, county councils, other local authorities, housing associations, industrial and provident societies, registered societies, limited companies, public limited companies, unlimited companies, limited liability partnerships, community interest companies, Societas Europaea (where registered at Companies House), UK companies with an overseas correspondence address. It is available for download as monthly files and contains approximately 3.2 million records

Introduction:

This analysis delves into the financial performance of top companies by examining key metrics such as revenue, earnings, market capitalisation, P/E ratio, and dividend yield. By comparing these metrics, we gain a comprehensive understanding of a company's scale, profitability, market value, and growth potential. Through visualisations, the analysis also explores correlations between these metrics and offers insights into country-level performance, highlighting economic dominance across various sectors. This holistic approach provides a multi-dimensional view of global financial powerhouses, investor confidence, and regional economic trends.

Key Metrics Used:

1. Revenue (Trailing Twelve Months - TTM): - Definition: This is the total income generated by a company from its operations in the last twelve months. - Potential Insights: High revenue often indicates market dominance or high sales volume. Comparing revenues can reveal which companies are the largest in terms of business volume.

2. Earnings (TTM): - Definition: This refers to the company's profit after taxes and expenses over the trailing twelve months. - Potential Insights: Companies with high earnings are more efficient at converting revenue into profit, suggesting better profitability or cost management. A comparison of earnings provides insight into profitability rather than just scale.

3. Market Capitalisation (Market Cap): - Definition: Market cap is the total value of a company's outstanding shares of stock, calculated as stock price multiplied by the number of shares. It indicates the company’s size in the stock market. - Potential Insights: High market cap usually indicates investor confidence in the company. Comparing market cap among the top 15 companies reveals their relative size in financial markets.

4. P/E Ratio (TTM): - Definition: Price-to-Earnings (P/E) ratio measures a company's current share price relative to its per-share earnings. - Potential Insights: A high P/E ratio may indicate that investors expect high growth in the future, while a low P/E ratio could imply undervaluation or scepticism about growth. Companies are compared by their growth prospects or current valuation.

5. Dividend Yield (TTM): - Definition: Dividend yield is a financial ratio that shows how much a company pays out in dividends each year relative to its share price. - Potential Insights: High dividend yield may indicate that a company returns more income to shareholders. It’s particularly useful for income-focused investors.

In this combined analysis, we will integrate the observations from the visualisations with the key financial metrics definitions and insights, to offer a comprehensive view of the top companies and country-level analysis across various financial dimensions.

Data Visualisations

Visualisation 1: https://www.googleapis.com/download/storage/v1/b/kaggle-user-content/o/inbox%2F13231939%2F2296eddd53ddd4b84346b1ea1324ec0a%2FScreenshot%202024-10-01%2015.16.51.png?generation=1727864461164331&alt=media" alt=""> Visualisation 2: https://www.googleapis.com/download/storage/v1/b/kaggle-user-content/o/inbox%2F13231939%2Fb35516c91e54eda75a03ff073e94dd73%2FScreenshot%202024-10-01%2015.17.53.png?generation=1727864511265917&alt=media" alt=""> Visualisation 3: https://www.googleapis.com/download/storage/v1/b/kaggle-user-content/o/inbox%2F13231939%2F506ca2428d34b15cd46e4a31261763d7%2FScreenshot%202024-10-01%2015.18.37.png?generation=1727864562835491&alt=media" alt=""> Visualisation 4: https://www.googleapis.com/download/storage/v1/b/kaggle-user-content/o/inbox%2F13231939%2F41e7a3e28c757239d26226f6a0ccdca9%2FScreenshot%202024-10-01%2015.19.20.png?generation=1727864614352037&alt=media" alt=""> A Markdown document with the R code for the above visualisations. link

1. Revenue (Trailing Twelve Months - TTM)

• Definition: The total income generated from a company’s operations over the last 12 months.
• Insights from Charts:
  • Revenue vs Earnings (Visualisation 2): Companies like Saudi Aramco are massive outliers with high revenues and even higher earnings, indicating impressive profitability despite their revenue volume.
  • Top 10 Countries by Average Revenue (Visualisation 3): China, South Korea, and Japan are at the top, with companies generating significant business volumes.
  • Analysis: High revenue companies like Walmart dominate the market but may not always convert this into proportional earnings or market cap growth. This could be due to operational costs or sector-specific challenges (retail margins being lower than tech).

2. Earnings (TTM)

• Definition: Profits...

Graph and download economic data for Finance Companies; Home Equity Lines of Credit; Asset, Transactions (BOGZ1FA613065200Q) from Q3 1970 to Q2 2025 about HELOCs, home equity, finance companies, companies, finance, credits, transactions, financial, assets, and USA.

Graph and download economic data for Rest of the World; Foreign Depository Institution Other Investment by Holding Companies; Liability, Revaluation (BOGZ1FR263194763A5I3) from 1946 to 2024 about revaluation, companies, foreign, liabilities, World, investment, depository institutions, and USA.

Graph and download economic data for Rest of the World; Foreign Depository Institution Other Investment by Holding Companies; Liability, Revaluation (BOGZ1FR263194763QMV6) from Q4 1946 to Q2 2025 about revaluation, companies, foreign, liabilities, World, investment, depository institutions, and USA.

Graph and download economic data for Rest of the World; Foreign Nonbank Affiliate Other Investment by Holding Companies, Excluding Foreign Deposits; Liability, Level (BOGZ1FL263194715Q) from Q4 1945 to Q2 2025 about nonbank, companies, foreign, liabilities, deposits, World, investment, and USA.

Graph and download economic data for Rest of the World; Other Investments by Holding Companies, Excluding Foreign Deposits; Liability, Transactions (ROWNTHA027N) from 1946 to 2024 about fees, IMA, companies, transactions, liabilities, and Net.

Graph and download economic data for Rest of the World; Other Investments by Holding Companies, Excluding Foreign Deposits; Liability, Transactions (ROWNTHQ027S) from Q4 1946 to Q2 2025 about fees, IMA, companies, transactions, liabilities, and Net.

Graph and download economic data for Rest of the World; Foreign Bank Subsidiaries Transactions Due to Holding Companies; Liabilities, Transactions (BOGZ1FA263194763A) from 1946 to 2021 about fees, foreign, transactions, liabilities, banks, and depository institutions.

Graph and download economic data for Rest of the World; Foreign Nonbank Affiliate Other Investment by Holding Companies, Excluding Foreign Deposits; Liability, Transactions (BOGZ1FU263194715A) from 1946 to 2024 about nonbank, companies, foreign, transactions, liabilities, deposits, World, investment, and USA.