Civil Service Statistics data browser (2022)

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

Explore further: Parent_department, Organisation, Responsibility_level_grouped, Responsibility_level_ungrouped, Region_ITL1, Region_ITL2, Region_ITL3, Profession_of_post, Function_of_post, Sex, Sexual_orientation, Age

Status Year Region_london Ethnicity Disability Headcount FTE Mean_salary Median_salary
In post 2022 London Asian Declared disabled 1395 1295 36830 31880
In post 2022 London Asian Declared non-disabled 11505 10905 38010 33400
In post 2022 London Asian Undeclared 600 570 38230 33570
In post 2022 London Asian Unknown 1305 1260 41650 37700
In post 2022 London Black Declared disabled 1345 1285 34590 31060
In post 2022 London Black Declared non-disabled 7985 7730 35210 31170
In post 2022 London Black Undeclared 500 475 34470 32000
In post 2022 London Black Unknown 665 650 38660 35010
In post 2022 London Mixed Declared disabled 490 470 39810 34550
In post 2022 London Mixed Declared non-disabled 2620 2540 41850 37100
In post 2022 London Mixed Undeclared 160 150 41290 35090
In post 2022 London Mixed Unknown 325 315 43570 40050
In post 2022 London Other ethnicity Declared disabled 175 170 40030 34260
In post 2022 London Other ethnicity Declared non-disabled 945 905 40450 35050
In post 2022 London Other ethnicity Undeclared 50 45 38110 34500
In post 2022 London Other ethnicity Unknown 140 135 44910 40170
In post 2022 London Undeclared Declared disabled 410 385 39210 33020
In post 2022 London Undeclared Declared non-disabled 2070 1955 40790 35200
In post 2022 London Undeclared Undeclared 1545 1495 44910 40600
In post 2022 London Undeclared Unknown 400 380 46250 40810
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”.
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).