Civil Service Statistics data browser (2026)

Data preview: All civil servants / Parent_department / Region_london / Function_of_post / Organisation

Status Year Parent_department Region_london Function_of_post Organisation Headcount FTE Mean_salary Median_salary
In post 2026 Attorney General’s Departments London Analysis Crown Prosecution Service [c] [c] [c] [c]
In post 2026 Attorney General’s Departments London Analysis Government Legal Department 5 5 [c] [c]
In post 2026 Attorney General’s Departments London Commercial Crown Prosecution Service 10 10 [c] [c]
In post 2026 Attorney General’s Departments London Communications Attorney General’s Office 10 10 [c] [c]
In post 2026 Attorney General’s Departments London Communications Crown Prosecution Service 35 30 47360 45600
In post 2026 Attorney General’s Departments London Communications Government Legal Department 10 10 [c] [c]
In post 2026 Attorney General’s Departments London Digital and Data Crown Prosecution Service 45 45 51300 45600
In post 2026 Attorney General’s Departments London Digital and Data Government Legal Department 25 25 59420 59170
In post 2026 Attorney General’s Departments London Finance Crown Prosecution Service 30 25 44270 39890
In post 2026 Attorney General’s Departments London Finance Government Legal Department 40 40 45950 36760
In post 2026 Attorney General’s Departments London Legal Attorney General’s Office 50 50 64390 66310
In post 2026 Attorney General’s Departments London Legal Crown Prosecution Service 1735 1645 51180 46800
In post 2026 Attorney General’s Departments London Legal Government Legal Department 2575 2405 66390 67370
In post 2026 Attorney General’s Departments London Legal HM Crown Prosecution Service Inspectorate 15 15 62860 67190
In post 2026 Attorney General’s Departments London No function Crown Prosecution Service [c] [c] [c] [c]
In post 2026 Attorney General’s Departments London People Crown Prosecution Service 55 55 46970 39890
In post 2026 Attorney General’s Departments London People Government Legal Department 65 65 47380 44830
In post 2026 Attorney General’s Departments London Project Delivery Attorney General’s Office [c] [c] [c] [c]
In post 2026 Attorney General’s Departments London Project Delivery Crown Prosecution Service 20 20 45130 39890
In post 2026 Attorney General’s Departments London Project Delivery Government Legal Department 15 10 61780 59970
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 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.
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".
Function_of_post Functions relate to the post occupied by the person and are not dependent on qualifications the individual may have.
Of the 21 bodies under the Scottish Government, 16 did not report any functions information for their employees.
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).