Zip Codes with the Highest Percentage of Population Employed in Food Preparation & Serving in Woodland, CA

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Food Preparation & Serving

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 American Apache Arab Armenian Austrian Bangladeshi Bhutanese Blackfeet British Burmese Canadian Central American Cherokee Colombian Cree Czech Danish Dutch Eastern European English European Filipino French French Canadian German Greek Guatemalan Honduran Hungarian Indian (Asian)Iranian Irish Italian Jamaican Japanese Korean Laotian Maltese Mexican Mexican American Indian Native Hawaiian Navajo Nicaraguan Norwegian Pakistani Peruvian Polish Portuguese Puerto Rican Romanian Russian Salvadoran Samoan Scandinavian Scotch-Irish Scottish South American Spaniard Spanish Sri Lankan Subsaharan African Swedish Thai Ukrainian Welsh

Ancestry (Percentage)

Immigrant Origin (Total)

Africa Asia Cambodia Canada Caribbean Central America China Colombia Eastern Africa Eastern Asia Eastern Europe El Salvador England Europe Fiji Germany Guatemala Honduras Hong Kong India Jamaica Japan Korea Latin America Liberia Mexico Nepal Netherlands Northern Europe Oceania Pakistan Peru Philippines South America South Central Asia South Eastern Asia Southern Europe Taiwan Thailand 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 & PreventionFood Preparation & ServingHealth 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 Mining, Quarrying, & Extraction 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

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-less Heating Households without a Cars Households with 1 or more Cars Households with 2 or more Cars Households with 3 or more Cars

Woodland

United States

States

Alabama Alaska Arizona Arkansas California Colorado Connecticut Delaware District Of Columbia Florida Georgia Hawaii Idaho Illinois Indiana Iowa Kansas Kentucky Louisiana Maine Maryland Massachusetts Michigan Minnesota Mississippi Missouri Montana Nebraska Nevada New Hampshire New Jersey New Mexico New York North Carolina North Dakota Ohio Oklahoma Oregon Pennsylvania Puerto Rico Rhode Island South Carolina South Dakota Tennessee Texas Utah Vermont Virginia Washington West Virginia Wisconsin Wyoming

California Cities

Alameda Alhambra Anaheim Antioch Apple Valley Arcadia Auburn Bakersfield Berkeley Beverly Hills Brea Buena Park Burbank Camarillo Canoga Park Canyon Country Carlsbad Carson Castro Valley Chico Chino Chula Vista Citrus Heights Clovis Compton Concord Corona Costa Mesa Covina Culver City Daly City Danville Davis Desert Hot Springs Downey Duarte Edwards El Cajon El Monte Elk Grove Encino Escondido Eureka Fairfield Fontana Fremont Fresno Fullerton Garden Grove Gardena Glendale Glendora Grass Valley Hayward Hemet Hesperia Huntington Beach Indio Inglewood Irvine La Jolla La Mesa La Mirada La Puente Lake Elsinore Lakewood Lancaster Livermore Lodi Lompoc Long Beach Los Altos Los Angeles Los Gatos Madera Malibu Manteca Menifee Merced Mission Viejo Modesto Monterey Monterey Park Moraga Moreno Valley Mountain View Murrieta Napa Newport Beach North Hollywood Northridge Novato Oakland Oceanside Ontario Orange Oroville Oxnard Palm Desert Palm Springs Palmdale Palo Alto Pasadena Perris Petaluma Pleasanton Pomona Porterville Rancho Cordova Rancho Cucamonga Redding Redlands Redondo Beach Redwood City Rialto Richmond Riverside Rocklin Roseville Sacramento Salinas San Bernardino San Clemente San Diego San Francisco San Gabriel San Jacinto San Jose San Leandro San Luis Obispo San Marcos San Mateo San Pedro San Rafael San Ramon Santa Ana Santa Barbara Santa Clara Santa Clarita Santa Cruz Santa Maria Santa Monica Santa Rosa Sherman Oaks Simi Valley Spring Valley Stockton Sunnyvale Temecula Thousand Oaks Torrance Trabuco Canyon Tracy Turlock Tustin Twentynine Palms Upland Vacaville Valencia Vallejo Van Nuys Ventura Victorville Visalia Vista Walnut Creek West Covina West Sacramento WhittierWoodlandWoodland Hills Yorba Linda Yuba City

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Map of Zip Codes with the Highest Percentage of Population Employed in Food Preparation & Serving in Woodland

4.5%

5.8%

Zip Codes with the Highest Percentage of Population Employed in Food Preparation & Serving in Woodland Map

Zip Codes with the Highest Percentage of Population Employed in Food Preparation & Serving in Woodland, CA

	Zip Code	% Employed	vs State	vs National
1.	95776	5.8%	5.4% (+0.394)#588	5.3% (+0.490)#10,101
2.	95695	4.5%	5.4% (-0.904)#919	5.3% (-0.807)#15,106

Common Questions

What are the Top Zip Codes with the Highest Percentage of Population Employed in Food Preparation & Serving in Woodland, CA?

Top Zip Codes with the Highest Percentage of Population Employed in Food Preparation & Serving in Woodland, CA are:

95776

5.8%

95695

4.5%

What zip code has the Highest Percentage of Population Employed in Food Preparation & Serving in Woodland, CA?

95776 has the Highest Percentage of Population Employed in Food Preparation & Serving in Woodland, CA with 5.8%.

What is the Percentage of Population Employed in Food Preparation & Serving in Woodland, CA?

Percentage of Population Employed in Food Preparation & Serving in Woodland is 5.2%.

What is the Percentage of Population Employed in Food Preparation & Serving in California?

Percentage of Population Employed in Food Preparation & Serving in California is 5.4%.

What is the Percentage of Population Employed in Food Preparation & Serving in the United States?

Percentage of Population Employed in Food Preparation & Serving in the United States is 5.3%.