Zip Codes with the Largest Peruvian Community in Kenosha, WI

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Peruvian

Population

Highest Population Highest Population Density Lowest Population Density Male / Female Ratio Female / Male Ratio Oldest Population Oldest Population | Male Oldest Population | Female Youngest Population Youngest Population | Male Youngest Population | Female

Families and Households

Largest Family Size Largest Household Size Most Single Fathers Most Single Mothers Fewest Single Fathers Fewest Single Mothers Smallest Family Size Smallest Household Size

Female Fertility

Female Fertility (Unmarried)

Highest Illegitimacy | All Women Highest Illegitimacy | Women 35+Lowest Illegitimacy | All Women Lowest Illegitimacy | Women 35+

Race (Community Size)

Asian Black / African American Hawaiian / Pacific Hispanic or Latino Native / Alaskan White / Caucasian

Race (Percentage)

Asian Black / African American Hawaiian / Pacific Hispanic or Latino Native / Alaskan White / Caucasian

Ancestry (Community Size)

African Albanian American Apache Arab Argentinean Armenian Australian Austrian Bangladeshi Belgian Bhutanese Blackfeet British Burmese Cajun Canadian Central American Central American Indian Cherokee Chickasaw Chinese Chippewa Choctaw Colombian Croatian Cuban Czech Czechoslovakian Danish Dominican Dutch Eastern European English European Finnish French French Canadian German Greek Guatemalan Haitian Honduran Hungarian Icelander Indian (Asian)Iranian Irish Iroquois Italian Jamaican Korean Latvian Lebanese Lithuanian Luxembourger Macedonian Menominee Mexican Mexican American Indian Native Hawaiian Nicaraguan Nigerian Northern European Norwegian Palestinian Panamanian Pennsylvania GermanPeruvianPolish Portuguese Puerto Rican Romanian Russian Scandinavian Scotch-Irish Scottish Serbian Sioux Slavic Slovak Slovene South American Spaniard Spanish Sri Lankan Subsaharan African Swedish Swiss Thai Ukrainian Welsh Yugoslavian

Ancestry (Percentage)

African Albanian American Apache Arab Argentinean Armenian Australian Austrian Bangladeshi Belgian Bhutanese Blackfeet British Burmese Cajun Canadian Central American Central American Indian Cherokee Chickasaw Chinese Chippewa Choctaw Colombian Croatian Cuban Czech Czechoslovakian Danish Dominican Dutch Eastern European English European Finnish French French Canadian German Greek Guatemalan Haitian Honduran Hungarian Icelander Indian (Asian)Iranian Irish Iroquois Italian Jamaican Korean Latvian Lebanese Lithuanian Luxembourger Macedonian Menominee Mexican Mexican American Indian Native Hawaiian Nicaraguan Nigerian Northern European Norwegian Palestinian Panamanian Pennsylvania German Peruvian Polish Portuguese Puerto Rican Romanian Russian Scandinavian Scotch-Irish Scottish Serbian Sioux Slavic Slovak Slovene South American Spaniard Spanish Sri Lankan Subsaharan African Swedish Swiss Thai Ukrainian Welsh Yugoslavian

Immigrant Origin (Total)

Africa Argentina Asia Canada Caribbean Central America China Colombia Dominican Republic Eastern Africa Eastern Asia Eastern Europe Europe Germany Greece Guatemala Honduras India Italy Japan Jordan Kenya Korea Laos Latin America Malaysia Mexico Nigeria Northern Africa Northern Europe Oceania Panama Peru Philippines Poland Romania Russia Scotland Serbia South America South Central Asia South Eastern Asia Southern Europe Spain Vietnam Western Africa Western Asia Western Europe

Immigrant Origin (Percentage)

Income

Highest Per Capita Income Highest Earnings | Male Highest Earnings | Female Highest Wage/Income Gap ($)Highest Wage/Income Gap (%)Highest Inequality / Gini Index Lowest Per Capita Income Lowest Earnings | Male Lowest Earnings | Female Lowest Wage/Income Gap ($)Lowest Wage/Income Gap (%)Lowest Inequality / Gini Index

Income (Families)

Highest Family Income Lowest Family Income Family Income | $0-10k Family Income | $100k+Family Income | $200k+

Income (Households)

Highest Household Income Lowest Household Income Household Income | $0-10k Household Income | $200k+Household Income | $100k+

Poverty

Poverty (Families)

Unemployment

Employment Occupations

Architecture & Engineering Arts, Media & Entertainment Business & Financial Cleaning & Maintenance Community & Social Service Computer & Mathematics Computer, Engineering & Science Construction & Extraction Education Instruction & Library Education, Arts & Media Farming, Fishing & Forestry Firefighting & Prevention Food Preparation & Serving Health Diagnosing & Treating Health Technologists Healthcare Support Installation, Maintenance & Repair Law Enforcement Legal Services & Support Life, Physical & Social Science Management Material Moving Office & Administration Personal Care and Service Production Sales & Related Security & Protection Transportation

Employment Industries

Accommodation & Food Services Administrative & Support Services Agriculture, Fishing & Hunting Arts, Entertainment & Recreation Construction Educational Services Enterprise Management Finance & Insurance Health Care & Social Assistance Information & Technology Manufacturing Professional & Scientific Services Public Administration Real Estate, Rental & Leasing Retail Trade Transportation & Warehousing Utilities Wholesale Trade

Employer Class

Private Company Employees Self-Employed / Incorporated Self-Employed / Not Incorporated Not-for-profit Organizations Local Government Employees State Government Employees Federal Government Employees Unpaid Family Workers

Commute Time

Longest Commute Longest Commute | Male Longest Commute | Female Shortest Commute Shortest Commute | Male Shortest Commute | Female

Commute Means

Drive | Alone Drive | Carpool Public Transit Taxi / Cab Walk to Work Work from Home

School Enrollment

In Private School Nursery / Preschool Kindergarten Elementary School Middle School High School College University

Education by Degree Field

Computers and Mathematics Bio, Nature & Agricultural Physical and Health Sciences Psychology Social Sciences Engineering Multidisciplinary Studies Science and Engineering Business Education Literature and Languages Liberal Arts and History Visual and Performing Arts Communications Arts and Humanities

Occupancy

Highest Owner-Occupied Highest Renter-Occupied Lowest Owner-Occupied Lowest Renter-Occupied

Finances

Highest Median Housing Costs Highest Property Prices Highest Owner Housing Costs Highest Renter Housing Costs Highest Housing Costs / Income Lowest Median Housing Costs Lowest Property Prices Lowest Owner Housing Costs Lowest Renter Housing Costs Lowest Housing Costs / Income

Physical Characteristics

Detached Home Residency Condo/Apartment Residency Utility Gas Heating Bottled Gas / LP Heating Electrical Heating Fuel Oil Heating Coal / Coke Heating Fuel-less Heating Households without a Cars Households with 1 or more Cars Households with 2 or more Cars Households with 3 or more Cars

Kenosha

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Map of Zip Codes with the Largest Peruvian Community in Kenosha

Zip Codes with the Largest Peruvian Community in Kenosha Map

Zip Codes with the Largest Peruvian Community in Kenosha, WI

	Zip Code	Peruvian	vs State	vs National
1.	53144	21	2,770(0.76%)#35	712,740(0.00%)#4,441
2.	53142	13	2,770(0.47%)#56	712,740(0.00%)#5,103

Common Questions

What are the Top 3 Zip Codes with the Largest Peruvian Community in Kenosha, WI?

Top 3 Zip Codes with the Largest Peruvian Community in Kenosha, WI are:

53144

53142

53140

What zip code has the Largest Peruvian Community in Kenosha, WI?

53144 has the Largest Peruvian Community in Kenosha, WI with 21.

What is the Total Peruvian Population in Kenosha, WI?

Total Peruvian Population in Kenosha is 28.

What is the Total Peruvian Population in Wisconsin?

Total Peruvian Population in Wisconsin is 2,770.

What is the Total Peruvian Population in the United States?

Total Peruvian Population in the United States is 712,740.