Civil Service Statistics data browser (2026)

Data preview: All civil servants / Region_london / Responsibility_level_grouped / Ethnicity / Region_ITL1

Status Year Region_london Responsibility_level_grouped Ethnicity Region_ITL1 Headcount FTE Mean_salary Median_salary
In post 2026 London AA/AO Asian London 2465 2210 31910 31470
In post 2026 London AA/AO Black London 2645 2475 34460 31670
In post 2026 London AA/AO Mixed London 410 380 33510 31470
In post 2026 London AA/AO Other ethnicity London 195 180 32850 31470
In post 2026 London AA/AO Undeclared London 505 460 31880 30460
In post 2026 London AA/AO Unknown London 2110 2000 32990 31470
In post 2026 London AA/AO White London 3250 2980 33320 31640
In post 2026 London EO Asian London 5040 4680 37470 37020
In post 2026 London EO Black London 3660 3450 36970 37020
In post 2026 London EO Mixed London 785 740 37280 37020
In post 2026 London EO Other ethnicity London 390 375 37510 37020
In post 2026 London EO Undeclared London 1100 1005 37570 37020
In post 2026 London EO Unknown London 2920 2825 36780 35420
In post 2026 London EO White London 6085 5745 37850 37020
In post 2026 London G6/G7 Asian London 3355 3270 70130 68090
In post 2026 London G6/G7 Black London 1375 1350 68950 67370
In post 2026 London G6/G7 Mixed London 1150 1120 69990 67980
In post 2026 London G6/G7 Other ethnicity London 395 385 70340 67490
In post 2026 London G6/G7 Undeclared London 1290 1250 71630 69060
In post 2026 London G6/G7 Unknown London 5025 4900 69410 66540
Note:
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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 2026-07-16

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.
Year Year of data collection (as at 31 March).
Responsibility_level_grouped With the exception of the centrally managed Senior Civil Service, government departments have delegated pay and grading. For statistical purposes departments are asked to map their grades to a common framework by responsibility level.
This table shows staff in their substantive responsibility level unless on temporary promotion in which case staff are recorded at the higher responsibility level.
Responsibility_level_grouped combines the mapped grades into five broad responsibility levels. This is the headline measure for responsibility level for the Civil Service and is consistent with the published National Statistics.
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_ITL1 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 1 divides into Wales, Scotland, Northern Ireland, and the 9 statistical regions of England.
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.
The Serious Fraud Office have not reported any data for profession, function, ethnicity, disabilty and sexual orientation due to alignment concerns with these fields with external reporting criteria. The Serious Fraud Office is currently undertaking work to ensure a robust dataset is reported for the 2027 ACSES return.
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).