Civil Service Statistics data browser (2025)

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

Status Year Sex Region_london Region_ITL2 Age Headcount FTE Mean_salary Median_salary
In post 2025 Female London Inner London - East 16-19 10 10 [c] [c]
In post 2025 Female London Inner London - East 20-29 2040 2010 39120 36400
In post 2025 Female London Inner London - East 30-39 2750 2620 50080 45770
In post 2025 Female London Inner London - East 40-49 2755 2555 52260 46720
In post 2025 Female London Inner London - East 50-59 2640 2500 49060 43170
In post 2025 Female London Inner London - East 60-64 1020 870 44080 36460
In post 2025 Female London Inner London - East 65+ 380 290 41050 35680
In post 2025 Female London Inner London - East Unknown [c] [c] [c] [c]
In post 2025 Female London Inner London - West 16-19 25 25 [c] [c]
In post 2025 Female London Inner London - West 20-29 8510 8460 44920 42960
In post 2025 Female London Inner London - West 30-39 9325 9035 57250 60200
In post 2025 Female London Inner London - West 40-49 6635 6165 62500 62250
In post 2025 Female London Inner London - West 50-59 5330 5090 57840 52130
In post 2025 Female London Inner London - West 60-64 1600 1455 50490 43450
In post 2025 Female London Inner London - West 65+ 590 500 44400 35680
In post 2025 Female London Inner London - West Unknown [c] [c] [c] [c]
In post 2025 Female London Outer London - East and North East 16-19 5 5 [c] [c]
In post 2025 Female London Outer London - East and North East 20-29 435 425 34870 35680
In post 2025 Female London Outer London - East and North East 30-39 435 395 37720 35680
In post 2025 Female London Outer London - East and North East 40-49 540 475 36990 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.
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).