Civil Service Statistics data browser (2023)

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

Status Year Disability Region_london Sex Parent_department Headcount FTE Mean_salary Median_salary
In post 2023 Declared disabled London Female Attorney General’s Departments 310 285 49660 52020
In post 2023 Declared disabled London Female Cabinet Office 435 425 44300 35650
In post 2023 Declared disabled London Female Chancellor’s other departments 10 10 [c] [c]
In post 2023 Declared disabled London Female Charity Commission [c] [c] [c] [c]
In post 2023 Declared disabled London Female Competition and Markets Authority 25 25 [c] [c]
In post 2023 Declared disabled London Female Department for Business, Energy and Industrial Strategy 320 310 48740 44010
In post 2023 Declared disabled London Female Department for Digital, Culture, Media and Sport 90 90 49810 52760
In post 2023 Declared disabled London Female Department for Education 150 140 52410 55020
In post 2023 Declared disabled London Female Department for Environment, Food and Rural Affairs 185 175 45640 40260
In post 2023 Declared disabled London Female Department for International Trade 115 115 47880 42170
In post 2023 Declared disabled London Female Department for Levelling Up, Housing and Communities 135 135 47710 46920
In post 2023 Declared disabled London Female Department for Transport 105 100 47380 43750
In post 2023 Declared disabled London Female Department for Work and Pensions 1175 1050 34940 32520
In post 2023 Declared disabled London Female Department of Health and Social Care 165 160 46850 41950
In post 2023 Declared disabled London Female Food Standards Agency 15 15 [c] [c]
In post 2023 Declared disabled London Female Foreign, Commonwealth and Development Office 190 185 48200 42450
In post 2023 Declared disabled London Female HM Land Registry 15 15 [c] [c]
In post 2023 Declared disabled London Female HM Revenue and Customs 505 475 44360 39790
In post 2023 Declared disabled London Female HM Treasury 120 115 45490 41360
In post 2023 Declared disabled London Female Home Office 665 610 39870 36180
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 2023-07-27, 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".
Sex Self reported sex.
"Unknown" accounts for employees who were recorded with an unknown sex.
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).