Civil Service Statistics data browser (2023)

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

Status Year Sexual_orientation Region_london Age Disability Headcount FTE Mean_salary Median_salary
In post 2023 Heterosexual / straight London 16-19 Declared disabled [c] [c] [c] [c]
In post 2023 Heterosexual / straight London 16-19 Declared non-disabled 45 45 26410 25610
In post 2023 Heterosexual / straight London 16-19 Undeclared [c] [c] [c] [c]
In post 2023 Heterosexual / straight London 16-19 Unknown 20 20 [c] [c]
In post 2023 Heterosexual / straight London 20-29 Declared disabled 1060 1045 38070 35040
In post 2023 Heterosexual / straight London 20-29 Declared non-disabled 9230 9175 39080 35760
In post 2023 Heterosexual / straight London 20-29 Undeclared 375 370 38410 35550
In post 2023 Heterosexual / straight London 20-29 Unknown 2125 2120 38040 35010
In post 2023 Heterosexual / straight London 30-39 Declared disabled 1415 1365 46100 42590
In post 2023 Heterosexual / straight London 30-39 Declared non-disabled 12950 12560 48400 45560
In post 2023 Heterosexual / straight London 30-39 Undeclared 565 550 47920 46070
In post 2023 Heterosexual / straight London 30-39 Unknown 1720 1680 48280 45700
In post 2023 Heterosexual / straight London 40-49 Declared disabled 1710 1625 46950 41360
In post 2023 Heterosexual / straight London 40-49 Declared non-disabled 12135 11540 51320 45960
In post 2023 Heterosexual / straight London 40-49 Undeclared 590 565 48450 43650
In post 2023 Heterosexual / straight London 40-49 Unknown 1220 1170 53340 53500
In post 2023 Heterosexual / straight London 50-59 Declared disabled 2350 2245 43360 37670
In post 2023 Heterosexual / straight London 50-59 Declared non-disabled 12370 11970 47810 41950
In post 2023 Heterosexual / straight London 50-59 Undeclared 685 660 46470 39150
In post 2023 Heterosexual / straight London 50-59 Unknown 950 935 51780 45350
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 2023-07-26, 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).
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.
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.
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).