Civil Service Statistics data browser (2023)

Data preview: All civil servants / Region_london / Ethnicity / Region_ITL2 / Sex

Status Year Region_london Ethnicity Region_ITL2 Sex Headcount FTE Mean_salary Median_salary
In post 2023 London Asian Inner London - East Female 1735 1605 39400 34370
In post 2023 London Asian Inner London - East Male 1400 1370 41380 37500
In post 2023 London Asian Inner London - East Unknown [c] [c] [c] [c]
In post 2023 London Asian Inner London - West Female 3935 3775 44180 41060
In post 2023 London Asian Inner London - West Male 2640 2610 44720 41060
In post 2023 London Asian Inner London - West Unknown [c] [c] [c] [c]
In post 2023 London Asian Outer London - East and North East Female 565 475 30750 32520
In post 2023 London Asian Outer London - East and North East Male 315 310 31800 32520
In post 2023 London Asian Outer London - East and North East Unknown [c] [c] [c] [c]
In post 2023 London Asian Outer London - South Female 1170 1070 36050 32520
In post 2023 London Asian Outer London - South Male 745 730 39170 36180
In post 2023 London Asian Outer London - South Unknown [c] [c] [c] [c]
In post 2023 London Asian Outer London - West and North West Female 1565 1395 33570 32520
In post 2023 London Asian Outer London - West and North West Male 985 945 33860 30610
In post 2023 London Asian Outer London - West and North West Unknown [c] [c] [c] [c]
In post 2023 London Black Inner London - East Female 1745 1660 35820 32520
In post 2023 London Black Inner London - East Male 890 870 37320 33800
In post 2023 London Black Inner London - East Unknown [c] [c] [c] [c]
In post 2023 London Black Inner London - West Female 2910 2815 39660 35410
In post 2023 London Black Inner London - West Male 1385 1370 40690 36620
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 2023-07-29, 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_ITL2 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 2 divides into Northern Ireland, counties in England (most grouped), groups of districts in Greater London, groups of unitary authorities in Wales, groups of council areas in Scotland.
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.
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).