Civil Service Statistics data browser (2025)

Data preview: All civil servants / Sex / Region_london / Ethnicity / Region_ITL2

Status Year Sex Region_london Ethnicity Region_ITL2 Headcount FTE Mean_salary Median_salary
In post 2025 Female London Asian Inner London - East 2150 1990 44310 38660
In post 2025 Female London Asian Inner London - West 4085 3910 49470 46170
In post 2025 Female London Asian Outer London - East and North East 640 540 34560 35680
In post 2025 Female London Asian Outer London - South 1295 1190 40700 35680
In post 2025 Female London Asian Outer London - West and North West 1615 1455 38400 35680
In post 2025 Female London Black Inner London - East 2080 1960 40150 35680
In post 2025 Female London Black Inner London - West 2880 2775 44770 40530
In post 2025 Female London Black Outer London - East and North East 580 535 35960 35680
In post 2025 Female London Black Outer London - South 1390 1310 39320 35680
In post 2025 Female London Black Outer London - West and North West 640 590 37080 35680
In post 2025 Female London Mixed Inner London - East 470 445 46330 40380
In post 2025 Female London Mixed Inner London - West 1315 1270 52220 48410
In post 2025 Female London Mixed Outer London - East and North East 90 85 37790 35680
In post 2025 Female London Mixed Outer London - South 320 300 42880 35900
In post 2025 Female London Mixed Outer London - West and North West 200 190 39940 35680
In post 2025 Female London Other ethnicity Inner London - East 200 185 43330 37300
In post 2025 Female London Other ethnicity Inner London - West 530 505 51020 46900
In post 2025 Female London Other ethnicity Outer London - East and North East 55 50 35270 35680
In post 2025 Female London Other ethnicity Outer London - South 95 90 40890 35680
In post 2025 Female London Other ethnicity Outer London - West and North West 100 90 37270 35680
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 2025-07-18

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, United Kingdom Statistics Authority, Scottish Forestry and Forest and Land Scotland.
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".
Region_ITL2 Workplace postcode data are used to derive geographical information using the International Territorial Level (ITL) classification standard.
Following the UK’s withdrawal from the EU, a new UK-managed international statistical geography - International Territorial Levels (ITL) - was introduced from 1st January 2021, replacing the former NUTS classification. They align with international standards, enabling comparability both over time and internationally. To ensure continued alignment, the ITLs mirror the NUTS system. They also follow a similar review timetable - every three years.
ITL 2 divides into Northern Ireland, counties in England (most grouped), groups of districts in Greater London, groups of unitary authorities in Wales, groups of council areas in Scotland.
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.
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).