Civil Service Statistics data browser (2023)

Data preview: All civil servants / Sex / Region_london / Region_ITL3 / Disability

Status Year Sex Region_london Region_ITL3 Disability Headcount FTE Mean_salary Median_salary
In post 2023 Female London Barking & Dagenham and Havering Declared disabled 80 70 33170 32520
In post 2023 Female London Barking & Dagenham and Havering Declared non-disabled 285 250 32730 32520
In post 2023 Female London Barking & Dagenham and Havering Undeclared 15 15 [c] [c]
In post 2023 Female London Barking & Dagenham and Havering Unknown 15 15 [c] [c]
In post 2023 Female London Barnet Declared disabled 80 75 35970 32520
In post 2023 Female London Barnet Declared non-disabled 615 575 38850 33330
In post 2023 Female London Barnet Undeclared 235 215 48430 41280
In post 2023 Female London Barnet Unknown 105 100 35180 32520
In post 2023 Female London Bexley and Greenwich Declared disabled 130 120 32680 32520
In post 2023 Female London Bexley and Greenwich Declared non-disabled 560 515 33620 32520
In post 2023 Female London Bexley and Greenwich Undeclared 70 65 32010 29870
In post 2023 Female London Bexley and Greenwich Unknown 140 135 31610 32110
In post 2023 Female London Brent Declared disabled 50 45 33460 32520
In post 2023 Female London Brent Declared non-disabled 255 225 32430 32520
In post 2023 Female London Brent Undeclared 20 15 [c] [c]
In post 2023 Female London Brent Unknown 40 40 33130 31540
In post 2023 Female London Bromley Declared disabled 95 90 32590 32520
In post 2023 Female London Bromley Declared non-disabled 300 265 33150 32520
In post 2023 Female London Bromley Undeclared 20 15 [c] [c]
In post 2023 Female London Bromley Unknown 30 30 36210 33820
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_ITL3 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 3 divides into counties, unitary authorities, or districts in England (some grouped), groups of unitary authorities in Wales, groups of council areas in Scotland, groups of districts in Northern Ireland.
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.
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).