A 2021, study explored the minimum, average, and maximum annual salaries of those working in the restaurant industry in London, England. In that year, general managers earned an average of 40 thousand British pounds, with the potential to earn a maximum of 75 thousand pounds.

The median annual earnings in the United Kingdom was 39,039 British pounds per year in 2025. Annual earnings varied significantly by region, ranging from 49,692 pounds in London to 34,403 pounds in the North East. Along with London, only South East England and Scotland had earnings above the UK average, at 39,983 pounds and 39,719 pounds respectively. Regional Inequality in the UK Various other indicators highlight the degree of regional inequality in the UK, especially between London and the rest of the country. Productivity in London, as measured by output per hour, was 26.2 percent higher than the UK average. By comparison, every other UK region, except the South East, fell below the UK average for productivity. In gross domestic product per head, London was also an outlier. The average GDP per head in the UK was just over 37,000 pounds in 2023, but for London it was almost 64,000 pounds. Again, the South East's GDP per head was slightly above the UK average, with every other region below it. Within London itself, there is also a great degree of inequality. In 2023, for example, the average earnings in Kensington and Chelsea were 964 pounds per week, compared with 675 pounds in Barking and Dagenham. Wages continue to grow in 2025 In March 2025, weekly wages in the UK were growing by around 5.6 percent, or 1.8 percent when adjusted for inflation. For almost two years, wages have grown faster than inflation after a long period where prices were rising faster than wages between 2021 and 2023. This was due to a sustained period of high inflation in the UK, which peaked in October 2022 at 11.1 percent. Although inflation started to slow the following month, it wasn't until June 2023 that wages started to outpace inflation. By this point, the damage caused by high energy and food inflation had led to the the worst Cost of Living Crisis in the UK for a generation.

The Local Government Transparency Code 2015, issued by the Department for Communities & Local Government in September 2015, set out a number of principles for local authorities which were intended to underpin best practice in the creation of greater transparency through the publication of public data. One of the key requirements was the publication of data on senior employee salaries above £58,200.

Update 29-04-2020: The data is now split into two files based on the variable collection frequency (monthly and yearly). Additional variables added: area size in hectares, number of jobs in the area, number of people living in the area.

Context

I have been inspired by Xavier and his work on Barcelona to explore the city of London! 🇬🇧 💂

Content

The datasets is primarily centered around the housing market of London. However, it contains a lot of additional relevant data: - Monthly average house prices - Yearly number of houses - Yearly number of houses sold - Yearly percentage of households that recycle - Yearly life satisfaction - Yearly median salary of the residents of the area - Yearly mean salary of the residents of the area - Monthly number of crimes committed - Yearly number of jobs - Yearly number of people living in the area - Area size in hectares

The data is split by areas of London called boroughs (a flag exists to identify these), but some of the variables have other geographical UK regions for reference (like England, North East, etc.). There have been no changes made to the data except for melting it into a long format from the original tables.

Acknowledgements

The data has been extracted from London Datastore. It is released under UK Open Government License v2 and v3. The underlining datasets can be found here: https://data.london.gov.uk/dataset/uk-house-price-index https://data.london.gov.uk/dataset/number-and-density-of-dwellings-by-borough https://data.london.gov.uk/dataset/subjective-personal-well-being-borough https://data.london.gov.uk/dataset/household-waste-recycling-rates-borough https://data.london.gov.uk/dataset/earnings-place-residence-borough https://data.london.gov.uk/dataset/recorded_crime_summary https://data.london.gov.uk/dataset/jobs-and-job-density-borough https://data.london.gov.uk/dataset/ons-mid-year-population-estimates-custom-age-tables

Cover photo by Frans Ruiter from Unsplash

Inspiration

The dataset lends itself for extensive exploratory data analysis. It could also be a great supervised learning regression problem to predict house price changes of different boroughs over time.

This statistics shows the sources of income for working London households as a share of theirgross weekly household income. For working households in London, ** percent of income came from wages and salaries, with ** percent coming from self employment.

A 2021 study explored the minimum, average, and maximum annual salaries of those working in the hotel industry in London, England. In that year, general managers earned an average of ** thousand British pounds, with the potential to earn a maximum of *** thousand British pounds. In comparison, commis chefs only earned an average of ** thousand British pounds annually, and a maximum of ** thousand British pounds.

About this dataset

Context

The dataset presents the mean household income for each of the five quintiles in London, KY, as reported by the U.S. Census Bureau. The dataset highlights the variation in mean household income across quintiles, offering valuable insights into income distribution and inequality.

Key observations

• Income disparities: The mean income of the lowest quintile (20% of households with the lowest income) is 8,406, while the mean income for the highest quintile (20% of households with the highest income) is 144,994. This indicates that the top earners earn 17 times compared to the lowest earners.
• *Top 5%: * The mean household income for the wealthiest population (top 5%) is 249,623, which is 172.16% higher compared to the highest quintile, and 2969.58% higher compared to the lowest quintile.

https://i.neilsberg.com/ch/london-ky-mean-household-income-by-quintiles.jpeg" alt="Mean household income by quintiles in London, KY (in 2022 inflation-adjusted dollars))">

Content

When available, the data consists of estimates from the U.S. Census Bureau American Community Survey (ACS) 2017-2021 5-Year Estimates.

Income Levels:

• Lowest Quintile
• Second Quintile
• Third Quintile
• Fourth Quintile
• Highest Quintile
• Top 5 Percent

Variables / Data Columns

• Income Level: This column showcases the income levels (As mentioned above).
• Mean Household Income: Mean household income, in 2022 inflation-adjusted dollars for the specific income level.

Good to know

Margin of Error

Data in the dataset are based on the estimates and are subject to sampling variability and thus a margin of error. Neilsberg Research recommends using caution when presening these estimates in your research.

Custom data

If you do need custom data for any of your research project, report or presentation, you can contact our research staff at research@neilsberg.com for a feasibility of a custom tabulation on a fee-for-service basis.

Inspiration

Neilsberg Research Team curates, analyze and publishes demographics and economic data from a variety of public and proprietary sources, each of which often includes multiple surveys and programs. The large majority of Neilsberg Research aggregated datasets and insights is made available for free download at https://www.neilsberg.com/research/.

Recommended for further research

This dataset is a part of the main dataset for London median household income. You can refer the same here

Dataset Overview:

This dataset represents a small structured dataset containing information about different job positions, their respective levels, salaries, departments, years of experience, and job locations. Although the dataset has only 20 rows and 6 columns, it provides valuable insights into salary structures across roles and industries.

Details

• Number of Rows: 20
• Number of Columns: 6
• Columns:
  1. Position – The job title (e.g., Business Analyst, Manager, CEO).
  2. Level – A numeric indicator of the position hierarchy (1 = entry-level, 10 = highest).
  3. Salary – The annual salary offered for the position.
  4. Department – The department where the position belongs (Analytics, Consulting, Management, etc.).
  5. YearsExperience – The average number of years of experience required or observed for that role.
  6. Location – The geographical location of the position (e.g., New York, London, Paris).

Key Observations

1. Position Hierarchy

   • The dataset has a Level column ranging from 1 (Business Analyst) up to 10 (CEO).
   • This indicates a clear career progression path.

2. Salary Distribution

   • Minimum salary: 45,000
   • Maximum salary: 1,000,000
   • Average salary: 221,900
   • Salaries increase significantly with higher levels, showing a non-linear relationship (CEO salary jumps much higher than mid-level positions).

3. Experience Levels

   • Minimum years of experience: 1 year
   • Maximum years of experience: 25 years
   • Median experience: 7.5 years
   • Higher positions generally require more years of experience.

4. Departments & Locations

   • Departments include Analytics, Consulting, Management, and Leadership roles.
   • Locations are spread across global cities such as New York, London, Berlin, and Paris, suggesting this dataset is international in scope.

Insights and Potential Uses

• Salary Prediction: The dataset can be used to model how salary changes with position Level or YearsExperience.
• Career Path Analysis: Shows how employees move up in hierarchy and compensation.
• Departmental Comparison: Compare salary trends across different departments.
• Location-based Trends: Explore how job location affects pay.

Limitations

• The dataset is very small (only 20 entries), which limits statistical power and generalizability.
• Some important features (e.g., gender, education, company size) are missing.
• It is more suitable for learning/demo purposes rather than real-world decision making.

Conclusion

Despite being a tiny dataset, position_salaries.csv provides a clean and structured representation of hierarchical job positions, salaries, and experience. It is especially useful for teaching machine learning concepts like regression, salary prediction, and visualization of career progression.

The Code of Recommended Practice for Local Authorities on Data Transparency, issued by the Department for Communities & Local Government in September 2011, set out a number of principles for local authorities which were intended to underpin best practice in the creation of greater transparency through the publication of public data. One of the key requirements was the publication of senior employee salaries above £58,200 together with names, job descriptions, responsibilities and budgets. View senior staff salaries for the GLA, together with links to job descriptions. A departmental organisation chart (PDF) is also available. It should be noted that the Code provided for individuals to be given the option to refuse consent for their name to be published and, where the name is given as 'withheld', this is because the individual concerned has expressly refused consent for their name to be included. The CSV file of the senior staff data is a basic format spreadsheet which permits analysis of the data.

About this dataset

Context

The dataset presents the detailed breakdown of the count of individuals within distinct income brackets, categorizing them by gender (men and women) and employment type - full-time (FT) and part-time (PT), offering valuable insights into the diverse income landscapes within London. The dataset can be utilized to gain insights into gender-based income distribution within the London population, aiding in data analysis and decision-making..

Key observations

• Employment patterns: Within London, among individuals aged 15 years and older with income, there were 366 men and 361 women in the workforce. Among them, 194 men were engaged in full-time, year-round employment, while 144 women were in full-time, year-round roles.
• Annual income under $24,999: Of the male population working full-time, 12.37% fell within the income range of under $24,999, while 15.28% of the female population working full-time was represented in the same income bracket.
• Annual income above $100,000: 19.07% of men in full-time roles earned incomes exceeding $100,000, while 2.78% of women in full-time positions earned within this income bracket.
• Refer to the research insights for more key observations on more income brackets ( Annual income under $24,999, Annual income between $25,000 and $49,999, Annual income between $50,000 and $74,999, Annual income between $75,000 and $99,999 and Annual income above $100,000) and employment types (full-time year-round and part-time)

Content

When available, the data consists of estimates from the U.S. Census Bureau American Community Survey (ACS) 2019-2023 5-Year Estimates.

Income brackets:

• $1 to $2,499 or loss
• $2,500 to $4,999
• $5,000 to $7,499
• $7,500 to $9,999
• $10,000 to $12,499
• $12,500 to $14,999
• $15,000 to $17,499
• $17,500 to $19,999
• $20,000 to $22,499
• $22,500 to $24,999
• $25,000 to $29,999
• $30,000 to $34,999
• $35,000 to $39,999
• $40,000 to $44,999
• $45,000 to $49,999
• $50,000 to $54,999
• $55,000 to $64,999
• $65,000 to $74,999
• $75,000 to $99,999
• $100,000 or more

Variables / Data Columns

• Income Bracket: This column showcases 20 income brackets ranging from $1 to $100,000+..
• Full-Time Males: The count of males employed full-time year-round and earning within a specified income bracket
• Part-Time Males: The count of males employed part-time and earning within a specified income bracket
• Full-Time Females: The count of females employed full-time year-round and earning within a specified income bracket
• Part-Time Females: The count of females employed part-time and earning within a specified income bracket

Employment type classifications include:

• Full-time, year-round: A full-time, year-round worker is a person who worked full time (35 or more hours per week) and 50 or more weeks during the previous calendar year.
• Part-time: A part-time worker is a person who worked less than 35 hours per week during the previous calendar year.

Good to know

Margin of Error

Data in the dataset are based on the estimates and are subject to sampling variability and thus a margin of error. Neilsberg Research recommends using caution when presening these estimates in your research.

Custom data

If you do need custom data for any of your research project, report or presentation, you can contact our research staff at research@neilsberg.com for a feasibility of a custom tabulation on a fee-for-service basis.

Inspiration

Neilsberg Research Team curates, analyze and publishes demographics and economic data from a variety of public and proprietary sources, each of which often includes multiple surveys and programs. The large majority of Neilsberg Research aggregated datasets and insights is made available for free download at https://www.neilsberg.com/research/.

Recommended for further research

This dataset is a part of the main dataset for London median household income by race. You can refer the same here

The London Fire Brigade (LFB) publishes details of certain senior staff as required by the Accounts and Audit Regulations 2015 (Statutory Instrument 2015/234) as part of its annual accounts:

• the number of employees whose remuneration in that year was at least £50,000 in brackets of £5,000
• details of remuneration and job title of certain senior employees whose salary is at least £50,000, and
• employees whose salaries are £150,000 or more must also be identified by name.

This information is included in the published accounts which are available here for 2018/19 on the LFB website.

The 'senior staff' prescribed by the regulations for the Brigade comprise four officers namely: the Director of Corporate Services, the Director (Deputy Commissioner) of Safety and Assurance, and the Director (Deputy Commissioner) of Operations and General Counsel.

Under the Local Government Transparency Code 2015, the Brigade must also publish a list of responsibilities (for example, the services and functions they are responsible for, budget held and number of staff) and details of bonuses and ‘benefits-in-kind’, for all senior employees whose salary exceeds £50,000. And, in the interests of transparency, the Brigade publishes details of all staff who are designated as heads of service (assistant directors and assistant commissioners) in addition to the four officers required by the Accounts and Audit Regulations, and this information is available on this page.

Details of gifts, hospitality and expenses for senior LFB staff are published quarterly here.

Note: For Commissioner/Director roles, the budget and staffing figures have been aggregated from the budgets/staff held by Heads of Service under each Director, so there is some double counting.

LFB staff are employed by the London Fire Commissioner who is the fire and rescue authority for London; the London Fire Commissioner is not an employee of the LFB and is employed by the Greater London Authority. Details for LFC are included on this page for completeness.

Graph and download economic data for Personal Income in New London County, CT (PI09011) from 1969 to 2023 about New London County, CT; Norwich; CT; personal income; personal; income; and USA.

OPDC Senior salaries and pay multiple are published in line with the Local Government Transparency Code (see pages 76-78 of the GLA’s ‘Appendices to the Mayor of London’s Annual Report’). https://www.london.gov.uk/sites/default/files/annual_report_2015-2016_appendices.pdf

The average weekly wage for full-time workers resident in Greater London was *** British pounds in 2023, with wages highest for residents of Kensington and Chelsea at *** pounds per week, and lowest in Barking and Dagenham at *** pounds a week.

Graph and download economic data for Estimated Mean Real Household Wages Adjusted by Cost of Living for New London County, CT (MWACL09011) from 2009 to 2021 about New London County, CT; Norwich; CT; adjusted; average; wages; real; and USA.

Count of the number of employees earning over £50k.

Graph and download economic data for Estimate of Median Household Income for New London County, CT (MHICT09011A052NCEN) from 1989 to 2021 about New London County, CT; Norwich; CT; households; median; income; and USA.