Civil Service Statistics data browser (2025)

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

Status Year Parent_department Ethnicity Disability Region_london Headcount FTE Mean_salary Median_salary
In post 2025 Attorney General’s Departments Asian Declared disabled London 75 70 52180 44470
In post 2025 Attorney General’s Departments Asian Declared disabled Outside London 70 65 40710 33940
In post 2025 Attorney General’s Departments Asian Declared disabled Overseas [c] [c] [c] [c]
In post 2025 Attorney General’s Departments Asian Declared non-disabled London 525 495 52160 59800
In post 2025 Attorney General’s Departments Asian Declared non-disabled Outside London 290 265 45710 42420
In post 2025 Attorney General’s Departments Asian Declared non-disabled Overseas [c] [c] [c] [c]
In post 2025 Attorney General’s Departments Asian Undeclared London 20 20 [c] [c]
In post 2025 Attorney General’s Departments Asian Undeclared Outside London [c] [c] [c] [c]
In post 2025 Attorney General’s Departments Asian Undeclared Overseas [c] [c] [c] [c]
In post 2025 Attorney General’s Departments Asian Unknown London 115 110 48040 44570
In post 2025 Attorney General’s Departments Asian Unknown Outside London 150 140 42670 42320
In post 2025 Attorney General’s Departments Asian Unknown Overseas [c] [c] [c] [c]
In post 2025 Attorney General’s Departments Black Declared disabled London 60 55 46610 35010
In post 2025 Attorney General’s Departments Black Declared disabled Outside London 15 15 [c] [c]
In post 2025 Attorney General’s Departments Black Declared disabled Overseas [c] [c] [c] [c]
In post 2025 Attorney General’s Departments Black Declared non-disabled London 345 330 49080 43580
In post 2025 Attorney General’s Departments Black Declared non-disabled Outside London 95 90 47630 54210
In post 2025 Attorney General’s Departments Black Declared non-disabled Overseas [c] [c] [c] [c]
In post 2025 Attorney General’s Departments Black Undeclared London 10 10 [c] [c]
In post 2025 Attorney General’s Departments Black Undeclared Outside London [c] [c] [c] [c]
Note: Data has been truncated to 20 rows, please download the data to view the remaining rows

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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 2025-07-21

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).
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".
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.
Disability Self reported disability.
"Undeclared" accounts for employees who have actively declared that they do not want to disclose their disability status and "Unknown" accounts for employees who have not made an active declaration about their disability status.
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).