Civil Service Statistics data browser (2025)

Data preview: All civil servants / Region_london / Sex / Organisation / Region_ITL1

Status Year Region_london Sex Organisation Region_ITL1 Headcount FTE Mean_salary Median_salary
In post 2025 London Female Active Travel England London [c] [c] [c] [c]
In post 2025 London Female Advisory, Conciliation and Arbitration Service London 85 80 46270 42490
In post 2025 London Female Animal and Plant Health Agency London 55 55 42180 37820
In post 2025 London Female Attorney General’s Office London 30 30 53060 44000
In post 2025 London Female Building Digital UK London 70 70 53800 58600
In post 2025 London Female Cabinet Office (excl. agencies) London 1945 1890 58750 61740
In post 2025 London Female Central Civil Service Fast Stream London 685 685 33670 32890
In post 2025 London Female Charity Commission London 40 40 51630 53910
In post 2025 London Female Companies House London [c] [c] [c] [c]
In post 2025 London Female Competition and Markets Authority London 435 415 69360 63630
In post 2025 London Female Crown Commercial Service London 20 20 [c] [c]
In post 2025 London Female Crown Prosecution Service London 1210 1130 49230 44570
In post 2025 London Female Defence Equipment and Support London 35 35 37100 32510
In post 2025 London Female Defence Science and Technology Laboratory London [c] [c] [c] [c]
In post 2025 London Female Department for Business and Trade (excl. agencies) London 2030 1985 54920 52380
In post 2025 London Female Department for Culture, Media and Sport London 460 435 57390 58100
In post 2025 London Female Department for Education (excl. agencies) London 1325 1255 56070 60370
In post 2025 London Female Department for Energy Security and Net Zero London 1685 1630 58640 61300
In post 2025 London Female Department for Environment, Food and Rural Affairs (excl. agencies) London 1370 1315 51980 45320
In post 2025 London Female Department for Science, Innovation and Technology (excl. agencies) London 905 875 59130 59300
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 2025-07-16

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.
Five organisations do not report when their employees first entered the Civil Service and so entrants data for these organisations is not available . These are as follows: Foreign Commonwealth and Development Office (excl. agencies), Foreign Commonwealth and Development Office Services, United Kingdom Statistics Authority, Scottish Forestry and Forest and Land Scotland.
Year Year of data collection (as at 31 March).
Organisation Executive Agencies, Ministerial and Non-Ministerial Departments, Crown Non-departmental Public Bodies.
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.
Sex Self reported sex.
"Unknown" accounts for employees who were recorded with an unknown sex.
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).