Civil Service Statistics data browser (2026)

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

Status Year Region_london Parent_department Organisation Sexual_orientation Headcount FTE Mean_salary Median_salary
In post 2026 London Attorney General’s Departments Attorney General’s Office Heterosexual / straight 10 10 [c] [c]
In post 2026 London Attorney General’s Departments Attorney General’s Office LGBO [c] [c] [c] [c]
In post 2026 London Attorney General’s Departments Attorney General’s Office Undeclared [c] [c] [c] [c]
In post 2026 London Attorney General’s Departments Attorney General’s Office Unknown 50 50 65280 66310
In post 2026 London Attorney General’s Departments Crown Prosecution Service Heterosexual / straight 1255 1190 52860 50000
In post 2026 London Attorney General’s Departments Crown Prosecution Service LGBO 85 80 51980 46800
In post 2026 London Attorney General’s Departments Crown Prosecution Service Undeclared 75 70 52570 46800
In post 2026 London Attorney General’s Departments Crown Prosecution Service Unknown 545 520 45330 34280
In post 2026 London Attorney General’s Departments Government Legal Department Heterosexual / straight 1620 1505 67910 67370
In post 2026 London Attorney General’s Departments Government Legal Department LGBO 165 155 68980 69460
In post 2026 London Attorney General’s Departments Government Legal Department Undeclared 140 135 67910 69460
In post 2026 London Attorney General’s Departments Government Legal Department Unknown 830 785 59130 63190
In post 2026 London Attorney General’s Departments HM Crown Prosecution Service Inspectorate Heterosexual / straight 5 5 [c] [c]
In post 2026 London Attorney General’s Departments HM Crown Prosecution Service Inspectorate LGBO [c] [c] [c] [c]
In post 2026 London Attorney General’s Departments HM Crown Prosecution Service Inspectorate Unknown 10 10 [c] [c]
In post 2026 London Attorney General’s Departments Serious Fraud Office Heterosexual / straight [c] [c] [c] [c]
In post 2026 London Attorney General’s Departments Serious Fraud Office LGBO [c] [c] [c] [c]
In post 2026 London Attorney General’s Departments Serious Fraud Office Unknown 610 595 50380 45470
In post 2026 London Cabinet Office Cabinet Office (excl. agencies) Heterosexual / straight 1935 1895 60930 63580
In post 2026 London Cabinet Office Cabinet Office (excl. agencies) LGBO 275 275 60770 62990
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".
Sexual_orientation Self reported sexual orientation.
"Undeclared" accounts for employees who have actively declared that they do not want to disclose their sexual orientation and "Unknown" accounts for employees who have not made an active declaration about their sexual orientation.
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).