Civil Service Statistics data browser (2026)

Data preview: All civil servants / Region_london / Region_ITL1 / Ethnicity / Parent_department

Status Year Region_london Region_ITL1 Ethnicity Parent_department Headcount FTE Mean_salary Median_salary
In post 2026 London London Asian Attorney General’s Departments 705 665 55340 62490
In post 2026 London London Asian Cabinet Office 575 565 50500 41710
In post 2026 London London Asian Chancellor’s other departments 60 60 55930 51760
In post 2026 London London Asian Charity Commission 5 5 [c] [c]
In post 2026 London London Asian Competition and Markets Authority 120 120 58520 52750
In post 2026 London London Asian Department for Business and Trade 520 510 52020 48160
In post 2026 London London Asian Department for Culture, Media and Sport 55 55 54490 50410
In post 2026 London London Asian Department for Education 320 310 53260 48310
In post 2026 London London Asian Department for Energy Security and Net Zero 315 305 57580 53150
In post 2026 London London Asian Department for Environment, Food and Rural Affairs 275 270 46730 40650
In post 2026 London London Asian Department for Science, Innovation and Technology 285 280 58450 58040
In post 2026 London London Asian Department for Transport 305 300 53360 50010
In post 2026 London London Asian Department for Work and Pensions 2870 2575 38810 37020
In post 2026 London London Asian Department of Health and Social Care 1050 1020 51600 46750
In post 2026 London London Asian Food Standards Agency 30 30 48880 46200
In post 2026 London London Asian Foreign, Commonwealth and Development Office 370 360 51850 45560
In post 2026 London London Asian HM Land Registry 50 50 44380 43910
In post 2026 London London Asian HM Revenue and Customs 2255 2135 46220 42750
In post 2026 London London Asian HM Treasury 220 215 57380 60590
In post 2026 London London Asian Home Office 3865 3660 46210 43240
Note:
Data has been truncated to 20 rows, please download the data to view the remaining rows

Download the data

About: The Civil Service Statistics data browser is a pilot project by Cabinet Office to provide access to more detailed data on the Civil Service workforce from the Annual Civil Service Employment Survey. We welcome feedback or comments on this project, which can be addressed to civilservicestatistics@cabinetoffice.gov.uk

Notes: Summary figures are suppressed when information relates to less than 5 civil servants for FTE or Headcount, and less than 10 civil servants for median and mean salary (shown as [c]). Zero responses and salaries for less than 30 civil servants have been suppressed for GPDR special category data. FTE figures are not shown for entrants or leavers due to data quality concerns for these groups. Figures are rounded to the nearest 5, or £10 as appropriate.

Data source: All figures are aggregated from the Cabinet Office Annual Civil Service Employment Survey collection.

Version: Generated on 2026-07-16

Data column Description
Status Employment status of the civil servants.
In post - includes staff that were in post on the reference date (31 March).
New entrant CS - includes new entrants to the Civil Service over the year (1 April to 31 March).
Leaver CS - includes leavers from the Civil Service over the year (1 April to 31 March). This includes employees who have an Unknown leaving cause.
Leaver Dept. - includes leavers from the department over the year (1 April to 31 March), who did not leave the Civil Service.
Year Year of data collection (as at 31 March).
Parent_department Government Department, total figures for both Ministerial and Non-Ministerial Departments include all of their Executive Agencies.
Region_london Workplace postcode data are used to derive geographical information using the International Territorial Level (ITL) classification standard.
Region_london groups the ITL classifications into "London", "Outside London": all UK regions excluding London, "Overseas", and "Unknown".
Region_ITL1 Workplace postcode data are used to derive geographical information using the International Territorial Level (ITL) classification standard.
Following the UK’s withdrawal from the EU, a new UK-managed international statistical geography - International Territorial Levels (ITL) - was introduced from 1st January 2021, replacing the former NUTS classification. They align with international standards, enabling comparability both over time and internationally. To ensure continued alignment, the ITLs mirror the NUTS system. They also follow a similar review timetable - every three years.
ITL 1 divides into Wales, Scotland, Northern Ireland, and the 9 statistical regions of England.
Ethnicity Self reported ethnicity. "Undeclared" accounts for employees who have actively declared that they do not want to disclose their ethnicity and "Unknown" accounts for employees who have not made an active declaration about their ethnicity.
The Serious Fraud Office have not reported any data for profession, function, ethnicity, disabilty and sexual orientation due to alignment concerns with these fields with external reporting criteria. The Serious Fraud Office is currently undertaking work to ensure a robust dataset is reported for the 2027 ACSES return.
Headcount Total number of civil servants (rounded to nearest 5).
FTE Total full-time equivalent (FTE) employment numbers (rounded to nearest 5).
FTE figures are not shown for entrants or leavers due to data quality concerns for these groups.
Mean_salary Average salary (mean, rounded to nearest £10). For part-time employees, salaries represent the full-time equivalent earnings, while for full-time employees they are the actual annual gross salaries.
These figures should be interpreted with caution when the total number of employees in a group is small, as they will tend to show more variability than larger groups (i.e. may be much higher or lower than can be explained by the data shown).
Median_salary Median salary (rounded to nearest £10). For part-time employees, salaries represent the full-time equivalent earnings, while for full-time employees they are the actual annual gross salaries.
These figures should be interpreted with caution when the total number of employees in a group is small, as they will tend to show more variability than larger groups (i.e. may be much higher or lower than can be explained by the data shown).