Civil Service Statistics data browser (2023)

Data preview: All civil servants / Region_london / Region_ITL1 / Age / Disability

Status Year Region_london Region_ITL1 Age Disability Headcount FTE Mean_salary Median_salary
In post 2023 London London 16-19 Declared disabled 5 5 [c] [c]
In post 2023 London London 16-19 Declared non-disabled 50 50 26500 26130
In post 2023 London London 16-19 Undeclared [c] [c] [c] [c]
In post 2023 London London 16-19 Unknown 70 65 27600 26770
In post 2023 London London 20-29 Declared disabled 1775 1760 37670 34820
In post 2023 London London 20-29 Declared non-disabled 11240 11175 39330 36000
In post 2023 London London 20-29 Undeclared 755 750 39260 35740
In post 2023 London London 20-29 Unknown 8930 8880 37350 34850
In post 2023 London London 30-39 Declared disabled 2015 1955 46010 42550
In post 2023 London London 30-39 Declared non-disabled 15450 15005 48560 45750
In post 2023 London London 30-39 Undeclared 1265 1235 47880 45560
In post 2023 London London 30-39 Unknown 6470 6345 47180 43650
In post 2023 London London 40-49 Declared disabled 2265 2155 46960 41540
In post 2023 London London 40-49 Declared non-disabled 14830 14070 51110 45960
In post 2023 London London 40-49 Undeclared 1405 1355 49750 45270
In post 2023 London London 40-49 Unknown 3965 3800 51370 46640
In post 2023 London London 50-59 Declared disabled 3110 2975 43640 37500
In post 2023 London London 50-59 Declared non-disabled 15705 15155 47150 40900
In post 2023 London London 50-59 Undeclared 1730 1680 46910 39880
In post 2023 London London 50-59 Unknown 3260 3155 48960 41950
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 2023-07-26, 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).
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.
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.
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).