Industries in Jefferson Ave, Lakeland, Florida (Neighborhood)

Industry#1

Percentage of the civilian employed population aged 16 and older.
Scope: population of Lakeland and Jefferson Ave
Jefferson Ave
Lakeland
0%5%10%15%20%CountRetailEducationHealthcare1HospitalityOther ServicesConstructionManufacturingFinance & InsuranceEntertainment2Professional3InformationWholesalersGovernment4Administrative5TransportationUtilitiesReal estateAgriculture6Oil & Gas, and MiningOil & Gas, and Mi…Management724.607623%15.960601%24.607623%24.6%3020.627803%10.116875%20.627803%20.6%2510.930493%13.353588%10.930493%10.9%137.735426%7.968049%7.735426%7.7%97.286996%4.819543%7.286996%7.3%895.437220%5.841276%5.437220%5.4%675.437220%6.196555%5.437220%5.4%674.147982%5.184623%4.147982%4.1%53.307175%2.428148%3.307175%3.3%43.139013%5.701615%3.139013%3.1%342.578475%1.631833%2.578475%2.6%31.737668%3.496435%1.737668%1.7%21.177130%3.351873%1.177130%1.2%10.784753%6.174503%0.784753%0.8%010.448430%3.895818%0.448430%0.4%010.392377%0.541494%0.392377%0.4%00.224215%2.109622%0.224215%0.2%00.000000%0.000000%0.0%0.987430%00.000000%0.000000%0.0%0.196016%00.000000%0.000000%0.0%0.044104%0
Count number of people employed in given industry
1Healthcare and social assistance 2Entertainment, arts, and recreation 3Professional, scientific, and technical services 4Government not otherwise classified 5Administrative, support, and waste management services 6Agriculture, forestry, fishing, and hunting 7Management of companies

Relative Industry#2

Percentage more or less common in Jefferson Ave than in Lakeland, among the civilian employed population aged 16 and older.
Scope: population of Lakeland and Jefferson Ave
Less Common
More Common
100%0%100%%ref.EducationInformationRetailOther ServicesEntertainment1HospitalityConstructionManufacturingHealthcare2Finance & InsuranceUtilitiesProfessional3WholesalersGovernment4Administrative5TransportationReal estateAgriculture6Oil & Gas, and MiningOil & Gas, and Mi…Management7103.895014%103.895014%103.9%20.628%20.6%10.117%10.1%58.010982%58.010982%58.0%2.578%2.58%1.632%1.63%54.177300%54.177300%54.2%24.608%24.6%15.961%16.0%51.196822%51.196822%51.2%7.287%7.29%4.820%4.82%36.201543%36.201543%36.2%3.307%3.31%2.428%2.43%-2.919452%-2.919452%2.9%7.735%7.74%7.968%7.97%-6.917261%-6.917261%6.9%5.437%5.44%5.841%5.84%-12.254152%-12.254152%12.3%5.437%5.44%6.197%6.20%-18.145647%-18.145647%18.1%10.930%10.9%13.354%13.4%-19.994522%-19.994522%20.0%4.148%4.15%5.185%5.18%-27.538147%-27.538147%27.5%0.392%0.39%0.541%0.54%-44.945184%-44.945184%44.9%3.139%3.14%5.702%5.70%-50.301716%-50.301716%50.3%1.738%1.74%3.496%3.50%-64.881427%-64.881427%64.9%1.177%1.18%3.352%3.35%-87.290421%-87.290421%87.3%0.785%0.78%6.175%6.17%-88.489438%-88.489438%88.5%0.448%0.45%3.896%3.90%-89.371781%-89.371781%89.4%0.224%0.22%2.110%2.11%-100.000000%-100.000000%100.0%0.000%0%0.987%0.99%-100.000000%-100.000000%100.0%0.000%0%0.196%0.20%-100.000000%-100.000000%100.0%0.000%0%0.044%0.04%
% percentage of industry in Jefferson Ave
ref. percentage of industry in Lakeland
1Entertainment, arts, and recreation 2Healthcare and social assistance 3Professional, scientific, and technical services 4Government not otherwise classified 5Administrative, support, and waste management services 6Agriculture, forestry, fishing, and hunting 7Management of companies

Sex Ratio by Industry#3

Sex ratio by industry among the civilian employed population aged 16 and older.
Scope: population of Lakeland and Jefferson Ave
Female Male
Lakeland
Jefferson Ave
2x1x0x1x2xFMHospitalityConstructionManufacturingOther ServicesWholesalersAll IndustriesProfessional1Finance & Insurance-1.000000x-1.000000x-1.000000x1.816327x1.092664x1.816327x1.82x36-1.000000x-1.000000x-1.000000x1.365854x9.986175x1.365854x1.37x2334-1.000000x-1.000000x-1.000000x1.365854x2.197219x1.365854x1.37x2334-1.000000x-1.000000x-1.000000x1.241379x1.001017x1.241379x1.24x3445-1.000000x-1.000000x-1.000000x1.066667x2.506143x1.066667x1.07x11-1.000000x-1.000000x-1.000000x1.043528x1.061783x1.043528x1.04x596062-1.434783x-1.000000x-1.434783x1.43x1.000000x1.136823x1.000000x212-2.363636x-1.681876x-2.363636x2.36x1.000000x1.000000x1.000000x3412
F number of females employed in given industry
M number of males employed in given industry
1Professional, scientific, and technical services

Part Timers by Industry#4

Part time and seasonal workers as a percentage of total workforce within an industry.
Scope: population of Lakeland and Jefferson Ave
Jefferson Ave
Lakeland
0%20%40%60%PartFullConstructionEntertainment1Administrative2WholesalersProfessional3EducationHospitalityRetailAll IndustriesFinance & InsuranceHealthcare4ManufacturingOther ServicesTransportationUtilitiesInformationReal estateGovernment564.948454%26.719799%64.948454%64.9%4259.322034%29.566095%59.322034%59.3%21257.142857%41.706349%57.142857%57.1%01032.258065%19.551507%32.258065%32.3%01132.142857%26.987538%32.142857%32.1%12329.076087%28.772100%29.076087%29.1%7171828.260870%46.525215%28.260870%28.3%236727.562642%34.924777%27.562642%27.6%8212226.457399%28.917257%26.457399%26.5%32899024.324324%11.531191%24.324324%24.3%13420.000000%27.761468%20.000000%20.0%2310117.216495%17.200474%7.216495%7.2%065.384615%35.892222%5.384615%5.4%080.000000%0.000000%0.0%25.597484%0010.000000%0.000000%0.0%4.524887%000.000000%0.000000%0.0%27.177177%030.000000%0.000000%0.0%38.211382%000.000000%0.000000%0.0%5.190058%01
Part number of part time workers employed in given industry
Full number of full time workers employed in given industry
1Entertainment, arts, and recreation 2Administrative, support, and waste management services 3Professional, scientific, and technical services 4Healthcare and social assistance 5Government not otherwise classified 6Agriculture, forestry, fishing, and hunting 7Management of companies

Median Income by Industry#5

For the full-time year-round civilian employed population aged 16 and older.
Scope: population of Lakeland and Jefferson Ave
Jefferson Ave
Lakeland
$0k$20k$40k$60k%CountProfessional1InformationFinance & InsuranceHealthcare2ManufacturingHospitalityEducationAll IndustriesWholesalersRetailOther Services$72,083.000000$50,895.000000$72,083.000000$72.1k3.139%3.14%34$67,946.000000$47,188.000000$67,946.000000$67.9k2.578%2.58%3$43,438.000000$42,247.000000$43,438.000000$43.4k4.148%4.15%5$42,308.000000$38,890.000000$42,308.000000$42.3k10.930%10.9%13$39,306.000000$39,715.000000$39,306.000000$39.3k5.437%5.44%67$32,716.000000$24,720.000000$32,716.000000$32.7k7.735%7.74%9$32,351.000000$40,346.000000$32,351.000000$32.4k20.628%20.6%25$31,696.000000$37,160.000000$31,696.000000$31.7k100.000%100%122$24,250.000000$39,113.000000$24,250.000000$24.3k1.738%1.74%2$24,063.000000$32,205.000000$24,063.000000$24.1k24.608%24.6%30$13,343.000000$33,060.000000$13,343.000000$13.3k7.287%7.29%89
% percent of the workforce employed in given industry
Count number of people employed in given industry
1Professional, scientific, and technical services 2Healthcare and social assistance 3Agriculture, forestry, fishing, and hunting 4Management of companies 5Administrative, support, and waste management services 6Entertainment, arts, and recreation 7Government not otherwise classified

Industries by Neighborhood in Lakeland

There are 48 neighborhoods in Lakeland. This section compares Jefferson Ave to all of the neighborhoods in Lakeland and to those entities that contain or substantially overlap with Jefferson Ave.

Agriculture1 Industry by Neighborhood#6

Percentage of the civilian employed population aged 16 and older.
Scope: population of Jefferson Ave, selected other neighborhoods in Lakeland, and entities that contain Jefferson Ave
0%2%4%6%Count#Lake Bonnet NeighborhoodLake BonnetNorth Lake Wire NeighborhoodN Lk WireCamphor NeighborhoodCamphorBeacon Hill NeighborhoodBeacon HillSouthwest NeighborhoodSouthwestParker Street NeighborhoodParker StreetJewel Avenue NeighborhoodJewel AvenueImperial NeighborhoodImperialCleveland Heights NeighborhoodCleveland HtsEdgewood NeighborhoodEdgewoodLakeland and Winter Haven Metro AreaLakeland AreaPolk CountyPolkPolk County School DistrictPolk CountyTigertown NeighborhoodTigertownN Martha NeighborhoodN MarthaLake Parker Park NeighborhoodLk Parker PkSwannanoa NeighborhoodSwannanoaZIP Code 33801ZIP 33801United States of AmericaUnited StatesKathleen NeighborhoodKathleenEast Lake Morton NeighborhoodE Lk MortonLake Hollingsworth NeighborhoodLk HollingsworthSouthLakelandFloridaSouth AtlanticLake Watkins NeighborhoodLake WatkinsCrystal Lake NeighborhoodCrystal LakeDowntown NeighborhoodDowntownDixieland NeighborhoodDixielandLake Bonny NeighborhoodLake BonnyShore Acres NeighborhoodShore AcresEdgewater Beach NeighborhoodEdgewater BchLake Bonny Park NeighborhoodLk Bonny PkLime Street NeighborhoodLime StreetLakeshore NeighborhoodLakeshore010402Tract 010402Webster Park North NeighborhoodWebster Pk NLake Somerset NeighborhoodLake SomersetSouth Lake Morton NeighborhoodS Lk MortonPaul A. Diggs NeighborhoodPaul A. DiggsFlorida Southern College NeighborhoodFlorida S CollegeWestgate NeighborhoodWestgateCentral Avenue NeighborhoodCntrl AveLake Horney NeighborhoodLake HorneyWebster Park South NeighborhoodWebster Pk SLake Beulah NeighborhoodLake BeulahJohn Cox NeighborhoodJohn CoxLake Hunter Terrace NeighborhoodLk Hunter TerRaintree NeighborhoodRaintreePinehurst NeighborhoodPinehurstJefferson Ave NeighborhoodJefferson AveFrancis Blvd NeighborhoodFrancis BlvdOrangewood NeighborhoodOrangewoodCleveland Heights Golf Course NeighborhoodCleveland Hts Golf …Watson NeighborhoodWatsonValencia Heights NeighborhoodValencia HtsHarmony Hills NeighborhoodHarmony Hills7.162534%7.162534%7.2%1115.903336%5.903336%5.9%1825.861244%5.861244%5.9%272835.861244%5.861244%5.9%91044.511124%4.511124%4.5%515253.793551%3.793551%3.8%2063.321879%3.321879%3.3%972.464986%2.464986%2.5%1482.228412%2.228412%2.2%1792.194434%2.194434%2.2%1011101.992998%1.992998%2.0%5,0381.992998%1.992998%2.0%5,0381.992998%1.992998%2.0%5,0381.828571%1.828571%1.8%3111.828571%1.828571%1.8%1121.828571%1.828571%1.8%0131.828571%1.828571%1.8%3141.331497%1.331497%1.3%1741.326306%1.326306%1.3%1,962,9511.96M1.274622%1.274622%1.3%6151.157043%1.157043%1.2%34161.140115%1.140115%1.1%16171.020426%1.020426%1.0%550,178550k0.987430%0.987430%1.0%4030.978079%0.978079%1.0%85,63585.6k0.923262%0.923262%0.9%262,334262k0.889052%0.889052%0.9%89180.677427%0.677427%0.7%1415190.632729%0.632729%0.6%12200.558595%0.558595%0.6%5210.302480%0.302480%0.3%1220.302480%0.302480%0.3%01230.302480%0.302480%0.3%0240.302480%0.302480%0.3%0250.302480%0.302480%0.3%0260.057528%0.057528%0.1%0270.000000%0.000000%0.0%00.000000%0.000000%0.0%0280.000000%0.000000%0.0%0290.000000%0.000000%0.0%0300.000000%0.000000%0.0%0310.000000%0.000000%0.0%0320.000000%0.000000%0.0%0330.000000%0.000000%0.0%0340.000000%0.000000%0.0%0350.000000%0.000000%0.0%0360.000000%0.000000%0.0%0370.000000%0.000000%0.0%0380.000000%0.000000%0.0%0390.000000%0.000000%0.0%0400.000000%0.000000%0.0%0410.000000%0.000000%0.0%0420.000000%0.000000%0.0%0430.000000%0.000000%0.0%0440.000000%0.000000%0.0%0450.000000%0.000000%0.0%0460.000000%0.000000%0.0%0470.000000%0.000000%0.0%048
1Agriculture, forestry, fishing, and hunting

Manufacturing Income by Neighborhood#26

Median income for the full-time year-round civilian employed population aged 16 and older.
Scope: population of Jefferson Ave, selected other neighborhoods in Lakeland, and entities that contain Jefferson Ave
$0k$50k%Count#Lake Hollingsworth NeighborhoodLk HollingsworthLake Watkins NeighborhoodLake WatkinsCleveland Heights NeighborhoodCleveland HtsEdgewood NeighborhoodEdgewoodImperial NeighborhoodImperialUnited States of AmericaUnited StatesLake Somerset NeighborhoodLake SomersetRaintree NeighborhoodRaintreeCleveland Heights Golf Course NeighborhoodCleveland Hts Golf …Southwest NeighborhoodSouthwestSouthNorth Lake Wire NeighborhoodN Lk WireSouth AtlanticFloridaParker Street NeighborhoodParker StreetCamphor NeighborhoodCamphorBeacon Hill NeighborhoodBeacon HillDowntown NeighborhoodDowntownEast Lake Morton NeighborhoodE Lk MortonLakeland and Winter Haven Metro AreaLakeland AreaPolk CountyPolkPolk County School DistrictPolk CountyLakeland010402Tract 010402South Lake Morton NeighborhoodS Lk MortonFlorida Southern College NeighborhoodFlorida S CollegeLake Horney NeighborhoodLake HorneyJefferson Ave NeighborhoodJefferson AveFrancis Blvd NeighborhoodFrancis BlvdJohn Cox NeighborhoodJohn CoxWatson NeighborhoodWatsonLakeshore NeighborhoodLakeshoreCrystal Lake NeighborhoodCrystal LakeZIP Code 33801ZIP 33801Shore Acres NeighborhoodShore AcresLake Bonny NeighborhoodLake BonnyEdgewater Beach NeighborhoodEdgewater BchLake Bonny Park NeighborhoodLk Bonny PkLime Street NeighborhoodLime StreetDixieland NeighborhoodDixielandLake Beulah NeighborhoodLake BeulahLake Hunter Terrace NeighborhoodLk Hunter TerWestgate NeighborhoodWestgateCentral Avenue NeighborhoodCntrl AveSwannanoa NeighborhoodSwannanoaTigertown NeighborhoodTigertownN Martha NeighborhoodN MarthaLake Parker Park NeighborhoodLk Parker PkWebster Park North NeighborhoodWebster Pk NPaul A. Diggs NeighborhoodPaul A. DiggsPinehurst NeighborhoodPinehurstOrangewood NeighborhoodOrangewoodValencia Heights NeighborhoodValencia HtsHarmony Hills NeighborhoodHarmony Hills$84,984.712512$84,984.712512$85.0k2.298%2.30%32331$74,388.275146$74,388.275146$74.4k2.429%2.43%242$50,909.000000$50,909.000000$50.9k4.457%4.46%343$50,840.082262$50,840.082262$50.8k4.470%4.47%21224$50,302.000000$50,302.000000$50.3k8.683%8.68%49505$47,819.000000$47,819.000000$47.8k10.349%10.3%15,316,35515.3M$46,161.000000$46,161.000000$46.2k5.352%5.35%686$46,161.000000$46,161.000000$46.2k5.352%5.35%167$46,161.000000$46,161.000000$46.2k5.352%5.35%48$45,921.464018$45,921.464018$45.9k9.866%9.87%1121139$44,473.000000$44,473.000000$44.5k9.320%9.32%5,024,8035.02M$44,375.000000$44,375.000000$44.4k2.288%2.29%710$44,242.000000$44,242.000000$44.2k8.134%8.13%2,311,0782.31M$43,860.000000$43,860.000000$43.9k5.162%5.16%451,950452k$43,769.462767$43,769.462767$43.8k3.242%3.24%1711$43,214.000000$43,214.000000$43.2k10.646%10.6%505112$43,214.000000$43,214.000000$43.2k10.646%10.6%1713$41,909.652927$41,909.652927$41.9k3.255%3.26%8914$41,753.526183$41,753.526183$41.8k4.762%4.76%151615$40,165.000000$40,165.000000$40.2k6.279%6.28%15,87215.9k$40,165.000000$40,165.000000$40.2k6.279%6.28%15,87215.9k$40,165.000000$40,165.000000$40.2k6.279%6.28%15,87215.9k$39,715.000000$39,715.000000$39.7k6.197%6.20%2,529$39,306.000000$39,306.000000$39.3k5.437%5.44%97$39,306.000000$39,306.000000$39.3k2.926%2.93%272816$39,306.000000$39,306.000000$39.3k5.437%5.44%2417$39,306.000000$39,306.000000$39.3k5.437%5.44%2118$39,306.000000$39,306.000000$39.3k5.437%5.44%6719$39,306.000000$39,306.000000$39.3k5.437%5.44%4520$36,250.000000$36,250.000000$36.3k3.776%3.78%821$36,250.000000$36,250.000000$36.3k3.776%3.78%122$36,069.908077$36,069.908077$36.1k3.947%3.95%151623$31,906.820553$31,906.820553$31.9k8.406%8.41%18218324$31,776.000000$31,776.000000$31.8k6.856%6.86%896$30,893.000000$30,893.000000$30.9k1.996%2.00%525$30,893.000000$30,893.000000$30.9k1.996%2.00%8926$30,893.000000$30,893.000000$30.9k1.996%2.00%227$30,893.000000$30,893.000000$30.9k1.996%2.00%228$30,893.000000$30,893.000000$30.9k1.996%2.00%029$28,227.138959$28,227.138959$28.2k14.535%14.5%13530$26,875.000000$26,875.000000$26.9k14.944%14.9%343531$26,875.000000$26,875.000000$26.9k14.944%14.9%3232$24,345.000000$24,345.000000$24.3k3.204%3.20%1233$24,345.000000$24,345.000000$24.3k3.204%3.20%1134$22,500.000000$22,500.000000$22.5k9.200%9.20%1735$22,500.000000$22,500.000000$22.5k9.200%9.20%1636$22,500.000000$22,500.000000$22.5k9.200%9.20%6737$22,500.000000$22,500.000000$22.5k9.200%9.20%1238$8,380.000000$8,380.000000$8.4k7.758%7.76%6339$8,380.000000$8,380.000000$8.4k8.114%8.11%5340$8,380.000000$8,380.000000$8.4k8.482%8.48%91041$8,380.000000$8,380.000000$8.4k8.482%8.48%542$8,380.000000$8,380.000000$8.4k8.482%8.48%143$8,380.000000$8,380.000000$8.4k8.482%8.48%144
% percent of the workforce employed in given industry
Count number of people employed in given industry
# rank of neighborhood out of 44 by income in given industry

Definitions

An industry describe the kind of business conducted by a person’s employing organization. On this page, all employed persons are categorized as working in one of the following industries (bolded terms are used in the charts and maps on this page):

  • Agriculture, forestry, fishing and hunting, and mining:
    • Agriculture: Agriculture, forestry, fishing and hunting
    • Oil & Gas, and Mining: Mining, quarrying, and oil and gas extraction
  • Construction: Construction
  • Manufacturing: Manufacturing
  • Wholesalers: Wholesale trade
  • Retail: Retail trade
  • Transportation and warehousing, and utilities:
    • Transportation: Transportation and warehousing
    • Utilities: Utilities
  • Information: Information
  • Finance and insurance, and real estate and rental and leasing:
    • Finance & Insurance: Finance and insurance
    • Real estate: Real estate and rental and leasing
  • Professional, scientific, and management, and administrative and waste management services:
    • Professional: Professional, scientific, and technical services
    • Management: Management of companies and enterprises
    • Administrative: Administrative and support and waste management services
  • Educational services, and health care and social assistance:
    • Education: Educational services
    • Healthcare: Health care and social assistance
  • Arts, entertainment, and recreation, and accommodation and food services:
    • Entertainment: Arts, entertainment, and recreation
    • Hospitality: Accommodation and food services
  • Other Services: Other services, except public administration
  • Government: Public administration

Unlike the other geographical entities detailed on this site, neighborhoods are not recognized by the U.S. Census Bureau. To overcome this we have computed reasonable estimates of the same statistics that are presented for other the entity types. Each statistic is computed as the weighted sum or average of the census tracts or block groups that overlap the neighborhood. A weighted sum is used for counts of people or households, and a weighted average is used for statistics that are themselves some form of average, such as median household income. Census block groups are preferred when the statistic in question is available on the block group level. The weight for a given tract (or block group) is computed as the population of the census tabulation blocks that occupy the intersection between the tract and the neighborhood as a fraction of the total population of the neighborhood.

For additional information about the data presented on this site, including our sources, please see the About Page.

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State:
Florida
County:
Polk
Metro Area:
Lakeland Area
City:
Lakeland
ZIP Code:
33801
Unified School District:
Polk County
Congressional District:
FL-15
State Senate District:
FL-22
State House District:
FL-40
Neighboring Neighborhoods:
East Lake Morton, Florida Southern College, Francis Blvd, Lake Horney, South Lake Morton
Nearby Neighborhoods:
Beacon Hill, Crystal Lake, Downtown, Edgewater Beach, John Cox, Lake Bonny Park, Lake Hollingsworth, Lime Street, Parker Street, Shore Acres