Civil Service Statistics data browser (2022)

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

Status Year Region_london Disability Ethnicity Sex Headcount FTE Mean_salary Median_salary
In post 2022 London Declared disabled Asian Female 855 775 36570 31880
In post 2022 London Declared disabled Asian Male 540 520 37240 33210
In post 2022 London Declared disabled Asian Unknown [c] [c] [c] [c]
In post 2022 London Declared disabled Black Female 1010 955 34290 31060
In post 2022 London Declared disabled Black Male 335 330 35500 31880
In post 2022 London Declared disabled Black Unknown [c] [c] [c] [c]
In post 2022 London Declared disabled Mixed Female 310 290 38820 34380
In post 2022 London Declared disabled Mixed Male 180 180 41480 34900
In post 2022 London Declared disabled Mixed Unknown [c] [c] [c] [c]
In post 2022 London Declared disabled Other ethnicity Female 100 95 38020 33400
In post 2022 London Declared disabled Other ethnicity Male 75 75 42670 36650
In post 2022 London Declared disabled Other ethnicity Unknown [c] [c] [c] [c]
In post 2022 London Declared disabled Undeclared Female 215 195 35660 31080
In post 2022 London Declared disabled Undeclared Male 195 190 43060 36650
In post 2022 London Declared disabled Undeclared Unknown [c] [c] [c] [c]
In post 2022 London Declared disabled Unknown Female 130 125 39270 35180
In post 2022 London Declared disabled Unknown Male 125 125 41380 37110
In post 2022 London Declared disabled Unknown Unknown [c] [c] [c] [c]
In post 2022 London Declared disabled White Female 3255 3075 43610 38370
In post 2022 London Declared disabled White Male 2605 2535 45030 40050
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 2023-02-14, with GIT 71a76ea.

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.
Five 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, Defence Electronics and Components Agency, 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.
Organisation specific notes on status: In late June 2021 around 7,000 employees from Community Rehabilitation Companies were transferred in from the private sector to HM Prison and Probation Service, counting as entrants. HM Land Registry do not record where their departing employees transfer to and so are unable to identify those that transfer to another Civil Service department.
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”.
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).