Ilford Municipal Borough (UD/MB) : Persons Aged over 10 by Sex, Age & 1911 Occupational Order

Persons Aged over 10 by Sex, Age & 1911 Occupational Order

Data cube chart.

Data cube chart.

Data for 1911:

Sex = Male 1911 Occupation Tables Age Groups
1911 Occupational Classification 10-12 13 14 15 16 17 18 19 20-24 25-34 35-44 45-54 55-64 65 up
Government 0 Show data context 1 Show data context 20 Show data context 27 Show data context 19 Show data context 24 Show data context 31 Show data context 26 Show data context 116 Show data context 439 Show data context 493 Show data context 328 Show data context 79 Show data context 4 Show data context
Defence 0 Show data context 0 Show data context 1 Show data context 0 Show data context 0 Show data context 2 Show data context 2 Show data context 1 Show data context 8 Show data context 10 Show data context 19 Show data context 7 Show data context 2 Show data context 4 Show data context
Professional Occupations 0 Show data context 0 Show data context 5 Show data context 13 Show data context 16 Show data context 13 Show data context 26 Show data context 10 Show data context 109 Show data context 374 Show data context 378 Show data context 263 Show data context 94 Show data context 34 Show data context
Domestic Services 0 Show data context 0 Show data context 3 Show data context 5 Show data context 4 Show data context 5 Show data context 6 Show data context 2 Show data context 53 Show data context 119 Show data context 91 Show data context 66 Show data context 32 Show data context 11 Show data context
Commercial Occupations 0 Show data context 0 Show data context 38 Show data context 130 Show data context 194 Show data context 208 Show data context 189 Show data context 165 Show data context 750 Show data context 1,621 Show data context 1,462 Show data context 711 Show data context 288 Show data context 77 Show data context
Transport 9 Show data context 23 Show data context 121 Show data context 105 Show data context 76 Show data context 64 Show data context 48 Show data context 36 Show data context 205 Show data context 612 Show data context 665 Show data context 355 Show data context 172 Show data context 46 Show data context
Agriculture 0 Show data context 2 Show data context 8 Show data context 16 Show data context 28 Show data context 27 Show data context 27 Show data context 24 Show data context 94 Show data context 141 Show data context 133 Show data context 150 Show data context 111 Show data context 62 Show data context
Mines & Quarries
Metals, Machines 0 Show data context 0 Show data context 0 Show data context 0 Show data context 0 Show data context 1 Show data context 0 Show data context 0 Show data context 2 Show data context 10 Show data context 15 Show data context 12 Show data context 8 Show data context 4 Show data context
Jewelry, Instruments 0 Show data context 0 Show data context 12 Show data context 9 Show data context 37 Show data context 35 Show data context 27 Show data context 35 Show data context 148 Show data context 269 Show data context 293 Show data context 165 Show data context 72 Show data context 29 Show data context
Building 0 Show data context 0 Show data context 2 Show data context 2 Show data context 3 Show data context 10 Show data context 8 Show data context 3 Show data context 26 Show data context 81 Show data context 85 Show data context 42 Show data context 22 Show data context 12 Show data context
Wood, Furniture 0 Show data context 1 Show data context 9 Show data context 12 Show data context 12 Show data context 24 Show data context 21 Show data context 17 Show data context 123 Show data context 429 Show data context 364 Show data context 280 Show data context 147 Show data context 45 Show data context
Brick, Cement 0 Show data context 0 Show data context 1 Show data context 7 Show data context 4 Show data context 11 Show data context 14 Show data context 10 Show data context 56 Show data context 135 Show data context 127 Show data context 71 Show data context 43 Show data context 11 Show data context
Chemicals 0 Show data context 0 Show data context 1 Show data context 3 Show data context 0 Show data context 0 Show data context 1 Show data context 1 Show data context 3 Show data context 10 Show data context 22 Show data context 18 Show data context 3 Show data context 2 Show data context
Skins, Leather 0 Show data context 0 Show data context 5 Show data context 16 Show data context 11 Show data context 11 Show data context 8 Show data context 6 Show data context 30 Show data context 98 Show data context 116 Show data context 60 Show data context 28 Show data context 13 Show data context
Paper, Prints 0 Show data context 0 Show data context 1 Show data context 0 Show data context 1 Show data context 2 Show data context 4 Show data context 3 Show data context 11 Show data context 27 Show data context 39 Show data context 20 Show data context 9 Show data context 3 Show data context
Textile Fabrics 0 Show data context 0 Show data context 8 Show data context 12 Show data context 16 Show data context 12 Show data context 19 Show data context 13 Show data context 68 Show data context 174 Show data context 280 Show data context 164 Show data context 53 Show data context 24 Show data context
Dress 0 Show data context 1 Show data context 4 Show data context 11 Show data context 9 Show data context 21 Show data context 14 Show data context 9 Show data context 67 Show data context 123 Show data context 134 Show data context 65 Show data context 20 Show data context 8 Show data context
Food, Drink 0 Show data context 2 Show data context 4 Show data context 13 Show data context 24 Show data context 23 Show data context 29 Show data context 25 Show data context 89 Show data context 185 Show data context 229 Show data context 127 Show data context 57 Show data context 23 Show data context
Gas, Water 1 Show data context 0 Show data context 19 Show data context 36 Show data context 48 Show data context 57 Show data context 69 Show data context 58 Show data context 270 Show data context 520 Show data context 465 Show data context 253 Show data context 122 Show data context 28 Show data context
Other & Undefined 0 Show data context 0 Show data context 0 Show data context 0 Show data context 4 Show data context 1 Show data context 3 Show data context 3 Show data context 16 Show data context 41 Show data context 65 Show data context 33 Show data context 14 Show data context 3 Show data context
Unoccupied 4 Show data context 7 Show data context 12 Show data context 15 Show data context 11 Show data context 17 Show data context 12 Show data context 9 Show data context 45 Show data context 138 Show data context 177 Show data context 115 Show data context 52 Show data context 34 Show data context
Sex = Female 1911 Occupation Tables Age Groups
1911 Occupational Classification 10-12 13 14 15 16 17 18 19 20-24 25-34 35-44 45-54 55-64 65 up
Government 0 Show data context 0 Show data context 0 Show data context 1 Show data context 2 Show data context 8 Show data context 17 Show data context 21 Show data context 54 Show data context 58 Show data context 22 Show data context 3 Show data context 2 Show data context 1 Show data context
Defence
Professional Occupations 0 Show data context 0 Show data context 1 Show data context 3 Show data context 10 Show data context 18 Show data context 23 Show data context 16 Show data context 202 Show data context 392 Show data context 236 Show data context 138 Show data context 69 Show data context 11 Show data context
Domestic Services 0 Show data context 9 Show data context 99 Show data context 208 Show data context 247 Show data context 233 Show data context 265 Show data context 242 Show data context 962 Show data context 633 Show data context 324 Show data context 211 Show data context 120 Show data context 31 Show data context
Commercial Occupations 0 Show data context 0 Show data context 3 Show data context 26 Show data context 51 Show data context 91 Show data context 75 Show data context 76 Show data context 326 Show data context 228 Show data context 48 Show data context 17 Show data context 0 Show data context 1 Show data context
Transport 0 Show data context 1 Show data context 0 Show data context 0 Show data context 9 Show data context 8 Show data context 5 Show data context 4 Show data context 16 Show data context 25 Show data context 5 Show data context 2 Show data context 1 Show data context 0 Show data context
Agriculture 0 Show data context 0 Show data context 0 Show data context 1 Show data context 2 Show data context 1 Show data context 1 Show data context 1 Show data context 10 Show data context 4 Show data context 5 Show data context 7 Show data context 7 Show data context 2 Show data context
Mines & Quarries
Metals, Machines
Jewelry, Instruments 0 Show data context 0 Show data context 1 Show data context 1 Show data context 0 Show data context 2 Show data context 5 Show data context 0 Show data context 2 Show data context 7 Show data context 4 Show data context 1 Show data context 1 Show data context 0 Show data context
Building 0 Show data context 0 Show data context 0 Show data context 1 Show data context 2 Show data context 1 Show data context 1 Show data context 2 Show data context 5 Show data context 4 Show data context 4 Show data context 2 Show data context 0 Show data context 0 Show data context
Wood, Furniture
Brick, Cement 0 Show data context 0 Show data context 1 Show data context 0 Show data context 0 Show data context 1 Show data context 0 Show data context 2 Show data context 5 Show data context 5 Show data context 6 Show data context 3 Show data context 1 Show data context 0 Show data context
Chemicals 0 Show data context 0 Show data context 0 Show data context 0 Show data context 1 Show data context 0 Show data context 0 Show data context 1 Show data context 1 Show data context 1 Show data context 4 Show data context 0 Show data context 1 Show data context 0 Show data context
Skins, Leather 0 Show data context 0 Show data context 3 Show data context 1 Show data context 5 Show data context 3 Show data context 3 Show data context 2 Show data context 12 Show data context 6 Show data context 12 Show data context 3 Show data context 0 Show data context 2 Show data context
Paper, Prints 0 Show data context 0 Show data context 0 Show data context 0 Show data context 2 Show data context 2 Show data context 3 Show data context 1 Show data context 2 Show data context 7 Show data context 4 Show data context 3 Show data context 2 Show data context 0 Show data context
Textile Fabrics 0 Show data context 0 Show data context 3 Show data context 6 Show data context 10 Show data context 9 Show data context 9 Show data context 9 Show data context 33 Show data context 35 Show data context 23 Show data context 6 Show data context 9 Show data context 1 Show data context
Dress 0 Show data context 0 Show data context 4 Show data context 15 Show data context 24 Show data context 22 Show data context 24 Show data context 25 Show data context 115 Show data context 90 Show data context 28 Show data context 16 Show data context 9 Show data context 0 Show data context
Food, Drink 0 Show data context 0 Show data context 42 Show data context 56 Show data context 61 Show data context 83 Show data context 65 Show data context 70 Show data context 266 Show data context 243 Show data context 160 Show data context 91 Show data context 37 Show data context 11 Show data context
Gas, Water 0 Show data context 0 Show data context 3 Show data context 7 Show data context 14 Show data context 17 Show data context 18 Show data context 26 Show data context 87 Show data context 113 Show data context 85 Show data context 56 Show data context 31 Show data context 11 Show data context
Other & Undefined
Unoccupied 0 Show data context 0 Show data context 5 Show data context 5 Show data context 3 Show data context 10 Show data context 5 Show data context 7 Show data context 21 Show data context 20 Show data context 11 Show data context 20 Show data context 7 Show data context 0 Show data context

Click on the triangles for all about a particular number

nCube definition

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


All persons of working age (12 or above in 1921), categorised by gender and the system of 31 occupational 'Orders' used by the 1921 Census of Population (we exclude Order 32 which covered the retired or otherwise unoccupied).


How to reference this page:

GB Historical GIS / University of Portsmouth, Ilford Municipal Borough (UD/MB) through time | Historical Statistics on Industry | Persons Aged over 10 by Sex, Age & 1911 Occupational Order, A Vision of Britain through Time.

URL: https://www.visionofbritain.org.uk/unit/10108159/cube/OCC_ORD1911_AGESEX

Date accessed: 08th June 2026