Midlothian Council : 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 2,283 Show data context 618 Show data context 1,889 Show data context 2 Show data context 9 Show data context 528 Show data context 269 Show data context 220 Show data context 111 Show data context 0 Show data context 12 Show data context 3 Show data context 50 Show data context 267 Show data context 53 Show data context 79 Show data context 42 Show data context 1,819 Show data context
1861 3,302 Show data context 1,052 Show data context 3,642 Show data context 18 Show data context 11 Show data context 901 Show data context 706 Show data context 772 Show data context 110 Show data context 58 Show data context 28 Show data context 164 Show data context 125 Show data context 142 Show data context 220 Show data context 174 Show data context 106 Show data context 2,250 Show data context
1881 2,546 Show data context 2,082 Show data context 5,541 Show data context 32 Show data context 35 Show data context 1,529 Show data context 1,184 Show data context 1,012 Show data context 127 Show data context 61 Show data context 107 Show data context 11 Show data context 217 Show data context 378 Show data context 500 Show data context 263 Show data context 177 Show data context 3,235 Show data context
1911 2,098 Show data context 4,592 Show data context 4,229 Show data context 31 Show data context 34 Show data context 806 Show data context 1,047 Show data context 1,087 Show data context 142 Show data context 23 Show data context 146 Show data context 13 Show data context 148 Show data context 477 Show data context 233 Show data context 251 Show data context 279 Show data context 2,130 Show data context
1931 1,851 Show data context 5,643 Show data context 6,020 Show data context 145 Show data context 38 Show data context 1,006 Show data context 3,185 Show data context 1,355 Show data context 396 Show data context 17 Show data context 291 Show data context 142 Show data context 311 Show data context 1 Show data context 870 Show data context 527 Show data context 411 Show data context 2,242 Show data context
1951 1,950 Show data context 6,310 Show data context 6,326 Show data context 320 Show data context 32 Show data context 1,967 Show data context 2,805 Show data context 1,334 Show data context 629 Show data context 0 Show data context 314 Show data context 0 Show data context 217 Show data context 0 Show data context 1,737 Show data context 734 Show data context 640 Show data context 1,196 Show data context
1971 1,005 Show data context 3,844 Show data context 7,261 Show data context 419 Show data context 45 Show data context 2,497 Show data context 3,282 Show data context 1,409 Show data context 812 Show data context 465 Show data context 410 Show data context 24 Show data context 507 Show data context 44 Show data context 1,945 Show data context 2,014 Show data context 862 Show data context 911 Show data context
2011 325 Show data context 124 Show data context 2,196 Show data context 254 Show data context 359 Show data context 3,769 Show data context 6,261 Show data context 2,104 Show data context 1,921 Show data context 798 Show data context 3,157 Show data context 443 Show data context 2,037 Show data context 1,801 Show data context 3,226 Show data context 3,275 Show data context 6,446 Show data context 2,206 Show data context
2021 394 Show data context 166 Show data context 2,760 Show data context 277 Show data context 390 Show data context 4,115 Show data context 5,595 Show data context 2,182 Show data context 2,765 Show data context 1,234 Show data context 3,416 Show data context 462 Show data context 2,840 Show data context 2,253 Show data context 5,329 Show data context 4,277 Show data context 7,871 Show data context 3,379 Show data context

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nCube definition


Numbers of the two sexes tend to be balanced. Military bases led to higher proportions of men, while large numbers of domestic servants created concentrations of women.


How to reference this page:

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

URL: https://www.visionofbritain.org.uk/unit/10039721/cube/INDUSTRY_GEN_2021

Date accessed: 10th April 2026