Civil Service Statistics data browser (2022)

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

Status Year Sex Region_london Disability Age Headcount FTE Mean_salary Median_salary
In post 2022 Female London Declared disabled 16-19 [c] [c] [c] [c]
In post 2022 Female London Declared disabled 20-29 1060 1045 35480 33210
In post 2022 Female London Declared disabled 30-39 1110 1060 43890 40310
In post 2022 Female London Declared disabled 40-49 1235 1140 44000 38290
In post 2022 Female London Declared disabled 50-59 1790 1690 40190 34200
In post 2022 Female London Declared disabled 60-64 490 435 35650 31060
In post 2022 Female London Declared disabled 65+ 185 150 33370 29500
In post 2022 Female London Declared disabled Unknown [c] [c] [c] [c]
In post 2022 Female London Declared non-disabled 16-19 50 45 25320 25000
In post 2022 Female London Declared non-disabled 20-29 7615 7545 36680 34020
In post 2022 Female London Declared non-disabled 30-39 8880 8435 45670 42020
In post 2022 Female London Declared non-disabled 40-49 8680 7945 47820 42480
In post 2022 Female London Declared non-disabled 50-59 8610 8135 42620 35980
In post 2022 Female London Declared non-disabled 60-64 2175 1910 37680 31880
In post 2022 Female London Declared non-disabled 65+ 795 645 32870 28650
In post 2022 Female London Declared non-disabled Unknown [c] [c] [c] [c]
In post 2022 Female London Undeclared 16-19 [c] [c] [c] [c]
In post 2022 Female London Undeclared 20-29 395 395 36610 34020
In post 2022 Female London Undeclared 30-39 560 530 44860 41690
In post 2022 Female London Undeclared 40-49 580 545 44830 40280
Note: Data has been truncated to 20 rows, please download the data to view the remaining rows

Download the data

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 2023-02-15, with GIT 71a76ea.

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, Defence Electronics and Components Agency, 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.
Organisation specific notes on status: In late June 2021 around 7,000 employees from Community Rehabilitation Companies were transferred in from the private sector to HM Prison and Probation Service, counting as entrants. HM Land Registry do not record where their departing employees transfer to and so are unable to identify those that transfer to another Civil Service department.
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”.
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.
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).