Civil Service Statistics data browser (2021)

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

Status	Year	Ethnicity	Region_london	Profession_of_post	Sex	Headcount	FTE	Mean_salary	Median_salary
In post	2021	Asian	London	Commercial	Female	60	55	40650	35870
In post	2021	Asian	London	Commercial	Male	45	45	43070	41000
In post	2021	Asian	London	Commercial	Unknown	[c]	[c]	[c]	[c]
In post	2021	Asian	London	Communications	Female	85	85	41100	37320
In post	2021	Asian	London	Communications	Male	50	50	41220	36160
In post	2021	Asian	London	Communications	Unknown	[c]	[c]	[c]	[c]
In post	2021	Asian	London	Corporate Finance	Female	10	10	[c]	[c]
In post	2021	Asian	London	Corporate Finance	Male	10	10	[c]	[c]
In post	2021	Asian	London	Corporate Finance	Unknown	[c]	[c]	[c]	[c]
In post	2021	Asian	London	Counter Fraud	Female	15	15	[c]	[c]
In post	2021	Asian	London	Counter Fraud	Male	15	15	[c]	[c]
In post	2021	Asian	London	Counter Fraud	Unknown	[c]	[c]	[c]	[c]
In post	2021	Asian	London	Digital, Data and Technology	Female	190	185	46210	42270
In post	2021	Asian	London	Digital, Data and Technology	Male	300	300	46880	43700
In post	2021	Asian	London	Digital, Data and Technology	Unknown	[c]	[c]	[c]	[c]
In post	2021	Asian	London	Economics	Female	65	60	47030	52500
In post	2021	Asian	London	Economics	Male	90	90	44260	41000
In post	2021	Asian	London	Economics	Unknown	[c]	[c]	[c]	[c]
In post	2021	Asian	London	Finance	Female	210	200	41480	36800
In post	2021	Asian	London	Finance	Male	220	220	45110	40980

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 2023-02-16, 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).
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”.
Profession_of_post	Professions relate to the post occupied by the person and are not dependent on qualifications the individual may have.
	The Department for Work and Pensions provided aggregated professions data for 2021, which are available in the Civil Service Statistics publication. However, figures in this browser are derived from individual level data and so are not available for this department in 2021.
	Of the 20 bodies under the Scottish Government, 16 did not report any professions information for their employees.
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).