I have data on the number of people of each age in each local authority. The problem at the moment is my data is separated by gender, but I would like totals of males and females of each age in each local authority at each time. I just want to sum the value for female+male when everything else is the same.
Thank You
Code:
* Example generated by -dataex-. To install: ssc install dataex clear input str36 name str9 code str7 gender int year float age long(allages noofpeople) float agecat "Shepway" "E07000112" "Female" 2015 0 55620 499 10 "Rossendale" "E07000125" "Female" 2013 0 34946 407 10 "Hertsmere" "E07000098" "Female" 2016 0 53812 656 10 "Kettering" "E07000153" "Female" 2015 0 49607 602 10 "Eastbourne" "E07000061" "Female" 2015 0 52873 588 10 "Carlisle" "E07000028" "Female" 2015 0 55330 558 10 "Epsom and Ewell" "E07000208" "Male" 2013 0 37224 475 10 "West Sussex" "E10000032" "Female" 2016 0 435167 4438 10 "Derby" "E06000015" "Male" 2015 0 125664 1802 10 "Wealden" "E07000065" "Male" 2015 0 75561 711 10 "Cheltenham" "E07000078" "Female" 2012 0 59204 689 10 "Barrow-in-Furness" "E07000027" "Male" 2015 0 33472 369 10 "Nottingham" "E06000018" "Male" 2016 0 164371 2253 10 "Islington" "E09000019" "Female" 2014 0 111195 1365 10 "City of London" "E09000001" "Female" 2014 0 2712 29 10 "Sheffield" "E08000019" "Male" 2016 0 285353 3376 10 "Exeter" "E07000041" "Male" 2014 0 60520 740 10 "Southampton" "E06000045" "Male" 2016 0 127762 1697 10 "Rugby" "E07000220" "Male" 2012 0 50339 692 10 "Northampton" "E07000154" "Female" 2016 0 113200 1625 10 "East Hertfordshire" "E07000242" "Female" 2012 0 70842 821 10 "North Norfolk" "E07000147" "Male" 2016 0 50372 394 10 "Surrey" "E10000030" "Female" 2012 0 583530 7026 10 "Daventry" "E07000151" "Male" 2016 0 40485 423 10 "Epsom and Ewell" "E07000208" "Female" 2015 0 40516 466 10 "Bolsover" "E07000033" "Male" 2016 0 38625 429 10 "Taunton Deane" "E07000190" "Female" 2016 0 59615 601 10 "Mansfield" "E07000174" "Female" 2013 0 53572 649 10 "Bexley" "E09000004" "Male" 2016 0 118293 1634 10 "Dover" "E07000108" "Male" 2016 0 56381 580 10 "Sedgemoor" "E07000188" "Male" 2016 0 59599 706 10 "Herefordshire, County of" "E06000019" "Female" 2013 0 94386 927 10 "Havering" "E09000016" "Male" 2014 0 118199 1616 10 "Bromley" "E09000006" "Male" 2015 0 156274 2096 10 "North Tyneside" "E08000022" "Female" 2013 0 104565 1105 10 "Broxbourne" "E07000095" "Female" 2012 0 48838 630 10 "North Somerset" "E06000024" "Male" 2012 0 99451 1190 10 "Rossendale" "E07000125" "Female" 2014 0 35225 416 10 "Harrow" "E09000015" "Female" 2016 0 124736 1799 10 "Corby" "E07000150" "Female" 2013 0 32753 455 10 "Torridge" "E07000046" "Male" 2015 0 32438 298 10 "Richmond upon Thames" "E09000027" "Male" 2013 0 92871 1453 10 "Northumberland" "E06000057" "Male" 2012 0 154470 1630 10 "Rushcliffe" "E07000176" "Male" 2015 0 56368 547 10 "Tendring" "E07000076" "Female" 2013 0 72382 642 10 "Wycombe" "E07000007" "Male" 2012 0 85087 1163 10 "Wyre Forest" "E07000239" "Female" 2013 0 49891 534 10 "Northumberland" "E06000057" "Male" 2016 0 154971 1471 10 "Gloucestershire" "E10000013" "Male" 2012 0 295517 3578 10 "South Somerset" "E07000189" "Male" 2015 0 81388 856 10 "Gedling" "E07000173" "Male" 2013 0 56125 622 10 "Crawley" "E07000226" "Female" 2016 0 55788 790 10 "Wyre" "E07000128" "Male" 2014 0 52846 511 10 "Colchester" "E07000071" "Female" 2012 0 89152 1116 10 "Lincolnshire" "E10000019" "Male" 2013 0 353402 3865 10 "Derbyshire Dales" "E07000035" "Male" 2013 0 35151 264 10 "Brentwood" "E07000068" "Male" 2014 0 36844 428 10 "Chorley" "E07000118" "Male" 2015 0 56591 610 10 "Cheshire West and Chester" "E06000050" "Male" 2015 0 162767 1855 10 "High Peak" "E07000037" "Female" 2013 0 46275 466 10 "Dartford" "E07000107" "Female" 2013 0 50809 731 10 "West Lancashire" "E07000127" "Male" 2015 0 54623 560 10 "Herefordshire, County of" "E06000019" "Female" 2016 0 95645 832 10 "Forest Heath" "E07000201" "Female" 2014 0 30975 478 10 "Slough" "E06000039" "Female" 2014 0 72095 1294 10 "Isle of Wight" "E06000046" "Female" 2013 0 70868 618 10 "Ryedale" "E07000167" "Male" 2012 0 25626 226 10 "Cannock Chase" "E07000192" "Female" 2012 0 49582 531 10 "Cheshire East" "E06000049" "Female" 2012 0 189804 1991 10 "East Hertfordshire" "E07000242" "Female" 2015 0 73613 785 10 "Milton Keynes" "E06000042" "Male" 2012 0 125061 2089 10 "South Tyneside" "E08000023" "Female" 2013 0 76738 813 10 "Winchester" "E07000094" "Female" 2013 0 61224 592 10 "East Northamptonshire" "E07000152" "Male" 2016 0 45226 488 10 "Barnsley" "E08000016" "Female" 2013 0 119713 1444 10 "Stevenage" "E07000243" "Female" 2012 0 43066 628 10 "Wellingborough" "E07000156" "Female" 2015 0 39476 447 10 "Lancashire" "E10000017" "Male" 2015 0 586252 6793 10 "Tameside" "E08000008" "Male" 2016 0 109506 1474 10 "Rochdale" "E08000005" "Male" 2013 0 103940 1573 10 "Herefordshire, County of" "E06000019" "Male" 2016 0 93887 916 10 "NORTH WEST" "E12000002" "Female" 2015 0 3640124 41715 10 "North Devon" "E07000043" "Male" 2015 0 46104 448 10 "Rother" "E07000064" "Female" 2012 0 47680 342 10 "Bromsgrove" "E07000234" "Male" 2015 0 47331 477 10 "St Albans" "E07000240" "Male" 2014 0 71081 931 10 "Darlington" "E06000005" "Male" 2016 0 51804 619 10 "NORTH EAST" "E12000001" "Male" 2013 0 1278374 15323 10 "Bolsover" "E07000033" "Male" 2012 0 37676 431 10 "South Bucks" "E07000006" "Male" 2013 0 32960 389 10 "Northamptonshire" "E10000021" "Female" 2013 0 357859 4479 10 "Warwick" "E07000222" "Male" 2012 0 69158 870 10 "Welwyn Hatfield" "E07000241" "Male" 2013 0 55876 697 10 "Spelthorne" "E07000213" "Female" 2012 0 48965 575 10 "Southend-on-Sea" "E06000033" "Female" 2015 0 91408 1106 10 "Bracknell Forest" "E06000036" "Female" 2012 0 57884 790 10 "Torridge" "E07000046" "Male" 2016 0 32837 359 10 "Worthing" "E07000229" "Female" 2013 0 55209 555 10 "Charnwood" "E07000130" "Female" 2013 0 84782 882 10 "Reigate and Banstead" "E07000211" "Male" 2012 0 68385 990 10 end
0 Response to Help summing data for men and women
Post a Comment