Civil Service Statistics data browser (2023)

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

Status Year Parent_department Disability Ethnicity Sex Headcount FTE Mean_salary Median_salary
In post 2023 Attorney General’s Departments Declared disabled Asian Female 90 80 42590 36530
In post 2023 Attorney General’s Departments Declared disabled Asian Male 25 25 [c] [c]
In post 2023 Attorney General’s Departments Declared disabled Asian Unknown [c] [c] [c] [c]
In post 2023 Attorney General’s Departments Declared disabled Black Female 60 55 41090 35550
In post 2023 Attorney General’s Departments Declared disabled Black Male 20 20 [c] [c]
In post 2023 Attorney General’s Departments Declared disabled Black Unknown [c] [c] [c] [c]
In post 2023 Attorney General’s Departments Declared disabled Mixed Female 30 25 [c] [c]
In post 2023 Attorney General’s Departments Declared disabled Mixed Male 15 15 [c] [c]
In post 2023 Attorney General’s Departments Declared disabled Mixed Unknown [c] [c] [c] [c]
In post 2023 Attorney General’s Departments Declared disabled Other ethnicity Female 10 10 [c] [c]
In post 2023 Attorney General’s Departments Declared disabled Other ethnicity Male [c] [c] [c] [c]
In post 2023 Attorney General’s Departments Declared disabled Other ethnicity Unknown [c] [c] [c] [c]
In post 2023 Attorney General’s Departments Declared disabled Undeclared Female 15 15 [c] [c]
In post 2023 Attorney General’s Departments Declared disabled Undeclared Male 15 15 [c] [c]
In post 2023 Attorney General’s Departments Declared disabled Undeclared Unknown [c] [c] [c] [c]
In post 2023 Attorney General’s Departments Declared disabled Unknown Female 30 30 40600 30870
In post 2023 Attorney General’s Departments Declared disabled Unknown Male 5 5 [c] [c]
In post 2023 Attorney General’s Departments Declared disabled Unknown Unknown [c] [c] [c] [c]
In post 2023 Attorney General’s Departments Declared disabled White Female 585 535 43390 38860
In post 2023 Attorney General’s Departments Declared disabled White Male 300 290 45910 49050
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 2023-07-26, with GIT d545f65.

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.
Four 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, Scottish Forestry and Forest and Land Scotland. A further three organisations also could not provide entrants data in 2021. These are as follows: Department for International Development, Foreign and Commonwealth Office (excl. agencies) and Royal Fleet Auxiliary.
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.
Sex Self reported sex.
"Unknown" accounts for employees who were recorded with an unknown sex.
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).