Civil Service Statistics data browser (2023)

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

Status Year Parent_department Region_london Disability Age Headcount FTE Mean_salary Median_salary
In post 2023 Attorney General’s Departments London Declared disabled 16-19 [c] [c] [c] [c]
In post 2023 Attorney General’s Departments London Declared disabled 20-29 65 65 33120 30160
In post 2023 Attorney General’s Departments London Declared disabled 30-39 85 85 47040 52020
In post 2023 Attorney General’s Departments London Declared disabled 40-49 105 100 53420 55170
In post 2023 Attorney General’s Departments London Declared disabled 50-59 155 140 56070 58820
In post 2023 Attorney General’s Departments London Declared disabled 60-64 50 50 52000 57260
In post 2023 Attorney General’s Departments London Declared disabled 65+ 10 10 [c] [c]
In post 2023 Attorney General’s Departments London Declared non-disabled 16-19 5 5 [c] [c]
In post 2023 Attorney General’s Departments London Declared non-disabled 20-29 530 525 34090 29680
In post 2023 Attorney General’s Departments London Declared non-disabled 30-39 840 805 50460 52730
In post 2023 Attorney General’s Departments London Declared non-disabled 40-49 925 845 56920 58820
In post 2023 Attorney General’s Departments London Declared non-disabled 50-59 830 790 56390 60080
In post 2023 Attorney General’s Departments London Declared non-disabled 60-64 185 165 54650 59640
In post 2023 Attorney General’s Departments London Declared non-disabled 65+ 65 55 47470 43280
In post 2023 Attorney General’s Departments London Undeclared 20-29 15 15 [c] [c]
In post 2023 Attorney General’s Departments London Undeclared 30-39 40 40 50880 53740
In post 2023 Attorney General’s Departments London Undeclared 40-49 45 40 60490 66130
In post 2023 Attorney General’s Departments London Undeclared 50-59 45 40 59620 66620
In post 2023 Attorney General’s Departments London Undeclared 60-64 5 5 [c] [c]
In post 2023 Attorney General’s Departments London Undeclared 65+ [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 2023-07-29, 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.
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".
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.
Age Age in 10 year bands. Age is calculated as at the reference date in each year (31st March), so entrants or leavers may have been up to one year younger at the date of exit or entry.
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).