Burnley District : Standard Industrial Classification (2007)

Standard Industrial Classification (2007)

Data cube chart.

Year A: Agriculture, forestry & fishing B: Mining & quarrying C: Manufacturing D: Electricity, gas, steam etc E: Water, sewerage & waste mgt F: Construction G: Wholesale & retail trade H: Transport & storage I: Accommodation & catering J: Information & communication K: Financial & insurance L: Real estate activities. M: Professional, scientific & technical N: Administrative & support O: Public administration & defence P: Education Q: Human health & social work R, S, T, U: Other services
1841 1,036 Show data context 365 Show data context 4,252 Show data context 1 Show data context 5 Show data context 359 Show data context 204 Show data context 150 Show data context 78 Show data context 0 Show data context 4 Show data context 5 Show data context 15 Show data context 92 Show data context 39 Show data context 41 Show data context 20 Show data context 835 Show data context
1861 1,305 Show data context 779 Show data context 7,816 Show data context 12 Show data context 17 Show data context 698 Show data context 509 Show data context 186 Show data context 200 Show data context 6 Show data context 8 Show data context 65 Show data context 31 Show data context 55 Show data context 51 Show data context 62 Show data context 24 Show data context 686 Show data context
1881 670 Show data context 2,308 Show data context 23,731 Show data context 48 Show data context 17 Show data context 1,633 Show data context 1,387 Show data context 812 Show data context 299 Show data context 22 Show data context 100 Show data context 35 Show data context 96 Show data context 323 Show data context 319 Show data context 262 Show data context 105 Show data context 3,311 Show data context
1911 1,610 Show data context 4,520 Show data context 48,459 Show data context 272 Show data context 132 Show data context 2,603 Show data context 4,589 Show data context 2,878 Show data context 1,008 Show data context 208 Show data context 461 Show data context 0 Show data context 176 Show data context 999 Show data context 634 Show data context 675 Show data context 387 Show data context 3,721 Show data context
1931 915 Show data context 3,223 Show data context 33,848 Show data context 628 Show data context 237 Show data context 1,262 Show data context 6,123 Show data context 2,457 Show data context 979 Show data context 19 Show data context 567 Show data context 65 Show data context 396 Show data context 2 Show data context 1,767 Show data context 759 Show data context 611 Show data context 2,628 Show data context
1951 662 Show data context 2,235 Show data context 30,825 Show data context 837 Show data context 82 Show data context 2,418 Show data context 6,557 Show data context 2,699 Show data context 1,538 Show data context 0 Show data context 649 Show data context 0 Show data context 498 Show data context 0 Show data context 1,825 Show data context 1,006 Show data context 1,149 Show data context 2,063 Show data context
1971 228 Show data context 729 Show data context 21,152 Show data context 613 Show data context 128 Show data context 2,055 Show data context 7,212 Show data context 2,529 Show data context 1,339 Show data context 763 Show data context 812 Show data context 29 Show data context 476 Show data context 78 Show data context 1,915 Show data context 2,170 Show data context 2,036 Show data context 1,177 Show data context
2011 92 Show data context 15 Show data context 6,821 Show data context 112 Show data context 268 Show data context 2,826 Show data context 6,386 Show data context 1,445 Show data context 1,842 Show data context 767 Show data context 1,035 Show data context 456 Show data context 1,310 Show data context 1,759 Show data context 2,043 Show data context 3,252 Show data context 6,000 Show data context 1,704 Show data context
2021 120 Show data context 26 Show data context 5,763 Show data context 128 Show data context 234 Show data context 3,117 Show data context 7,827 Show data context 1,793 Show data context 1,733 Show data context 1,075 Show data context 660 Show data context 492 Show data context 1,294 Show data context 2,118 Show data context 1,920 Show data context 3,458 Show data context 6,887 Show data context 1,388 Show data context
Date Source
1841 1841 Census of Great Britain, Occupations, Table [1] , 'Occupation Abstract'
1861 1861 Census of England and Wales, Ages, Table 17 , 'Occupations of Males aged 20 Years and upwards in Districts'
1881 Great Britain Historical GIS Project Computed from 1881 microdata
1911 1911 Census of England and Wales, Occupations Vol 1, Table 15 A, 'Grouped occupations of Males and Females aged 10 years and upwards, in Administrative Counties, County Boroughs, Metropolitan Boroughs, Urban Districts of which the population exceeded 5,000 persons, aggregates of other Urban Districts, and aggregates of Rural Districts; also proportion per 1,000 of unmarried, married, widowed, and of married and widowed women engaged in occupations, and proportion of female domestic servants to separate occupiers or families, 1911 - Males'
1931 1931 Census of England and Wales, Industry, Table 3 , 'Industries (condensed list) of Males and Females (exclusive of persons out of work)'
1951 1951 Census of England and Wales, Industry, Table 3 , 'Industries (Orders and Selected Units) and Status Aggregates. Occupied Males and Females aged 15 and over', for 'Urban Areas with population of less than 50,000, RD, NT'
1971 1971 Census of England and Wales, Economic activity County Leaflets, Table 3 , 'Industry and status by area of workplace and sex', for 'County, county boroughs, urban areas with populations of 50,000 or more, conurbation centres'
1991 Census of Population
2011 Office for National Statistics, NOMIS - Official Census and Labour Market Statistics (Table KS605UK - Industry)
2021 Office for National Statistics, ONS "Create a Custom Dataset" ("Industry (current)" (19 way))

This website exists to help people doing personal research projects on particular areas within a locality. So long as you are using our data for only a small number of units, you are not making money out of what you are doing, and you are not systematically re-publishing our data, you do not need to request permission from us, but you do need to acknowledge us as your source with the wording:

"This work is based on data provided through www.VisionofBritain.org.uk and uses historical material which is copyright of the Great Britain Historical GIS Project and the University of Portsmouth".

Where the above statement is included in a web page or similar online resource, the reference to "www.VisionofBritain.org.uk" must be a working hyperlink.

nCube definition


From 1896 onwards, Scottish poor law statistics divide Paupers into Sane and Lunatics. "Sane" covered those who were physically ill, elderly of otherwise needing relief, but not mentally ill.


How to reference this page:

GB Historical GIS / University of Portsmouth, Burnley District through time | Historical Statistics on Industry | Standard Industrial Classification (2007), A Vision of Britain through Time.

URL: https://www.visionofbritain.org.uk/unit/10057085/cube/INDUSTRY_GEN_2021

Date accessed: 05th June 2026