Civil Service Statistics data browser (2021)

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

Status Year Region_london Parent_department Sex Ethnicity Headcount FTE Mean_salary Median_salary
In post 2021 London Attorney General’s Departments Female Asian 405 370 44160 50500
In post 2021 London Attorney General’s Departments Female Black 315 300 39850 31640
In post 2021 London Attorney General’s Departments Female Chinese 25 20 [c] [c]
In post 2021 London Attorney General’s Departments Female Mixed 120 110 49370 51250
In post 2021 London Attorney General’s Departments Female Other ethnicity 65 60 50250 52730
In post 2021 London Attorney General’s Departments Female Undeclared 40 40 50280 51120
In post 2021 London Attorney General’s Departments Female Unknown 400 370 51130 51940
In post 2021 London Attorney General’s Departments Female White 1560 1430 52450 51830
In post 2021 London Attorney General’s Departments Male Asian 185 180 44730 40000
In post 2021 London Attorney General’s Departments Male Black 125 120 42350 32960
In post 2021 London Attorney General’s Departments Male Chinese 10 10 [c] [c]
In post 2021 London Attorney General’s Departments Male Mixed 55 55 48560 51250
In post 2021 London Attorney General’s Departments Male Other ethnicity 40 40 55590 60710
In post 2021 London Attorney General’s Departments Male Undeclared 50 45 47310 50520
In post 2021 London Attorney General’s Departments Male Unknown 250 245 51290 52560
In post 2021 London Attorney General’s Departments Male White 1035 1015 52970 51830
In post 2021 London Attorney General’s Departments Unknown Asian [c] [c] [c] [c]
In post 2021 London Attorney General’s Departments Unknown Black [c] [c] [c] [c]
In post 2021 London Attorney General’s Departments Unknown Chinese [c] [c] [c] [c]
In post 2021 London Attorney General’s Departments Unknown Mixed [c] [c] [c] [c]
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 2023-02-18, 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.
Year Year of data collection (as at 31 March).
Parent_department Government Department, total figures for both Ministerial and Non-Ministerial Departments include all of their Executive Agencies.
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.
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.
For consistency with Civil Service Statistics, ‘Chinese’ is shown separately in the 2021 figures, but counted within ‘Asian’ from 2022 onwards.
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).