US Social Demographics and Industry

Segment US Counties based on social demographics and industry data

Data contact: Richie Lionell

This dataset has 97 columns and 3136 rows.
The preview is meant for you to glance at the data and understand it.
This view shows all columns and the first 100 rows.

Choose one or more of these pre-defined feature groups to cluster by.

NameDescription
Basic demographics
High-level demographic information about districts
Fair or Poor Health %, Low Birth Weights %, Smokers %, Obese %, Physically Inactive %, Access to Exercise Opportunities %, Excessive Drinking %, Teen Birth Rate %, Uninsured %, PCP %, High School Graduation %, Post Secondary Education %, Unemployed %, Children in poverty %, Single-parent households %, Rate of Violent Crimes, Severe Housing Problems %, Diabetic %, Food Insecurity %, Insufficient Sleep %, Uninsured adults %, Uninsured children %, Eligible for reduced price or free lunch %, Young population %, Elderly population %, African American population %, American Indian or Native Alaskan %, Asian American population %, Native Hawaiian or Pacific Islander %, Non Hispanic White population %, Hispanic %, Not proficient in English %, Female population %, Rural population %, Hillary voters %, Trump voters %
Industry Presence
Proportion of district population for various religions
Retail Trade Establishments %, Educational Services Establishments %, Professional scientific and technical services Establishments %, Other services except public administration Establishments %, Management of companies and enterprises Establishments %, Real estate and rental and leasing Establishments %, Mining quarrying and oil and gas extraction Establishments %, Industries not classified Establishments %, Transportation and warehousing Establishments %, Arts entertainment and recreation Establishments %, Wholesale trade Establishments %, Utilities Establishments %, Agriculture forestry fishing and hunting Establishments %, Construction Establishments %, Manufacturing Establishments %, Administrative and support and waste management and remediation services Establishments %, Accommodation and food services Establishments %, Information Establishments %, Health care and social assistance Establishments %, Finance and insurance Establishments %
Workforce Presence
Proportion of households that own various assets
Retail Trade Workforce %, Educational Services Workforce %, Professional scientific and technical services Workforce %, Other services except public administration Workforce %, Management of companies and enterprises Workforce %, Real estate and rental and leasing Workforce %, Mining quarrying and oil and gas extraction Workforce %, Industries not classified Workforce %, Transportation and warehousing Workforce %, Arts entertainment and recreation %, Wholesale trade Workforce %, Utilities Workforce %, Agriculture forestry fishing and hunting Workforce %, Construction Workforce %, Manufacturing Workforce %, Administrative and support and waste management and remediation services Workforce %, Accommodation and food services Workforce %, Information Workforce %, Health care and social assistance Workforce %, Finance and insurance Workforce %
Payroll
Payroll breakup by geography
Retail Trade Payroll %, Educational Services Payroll %, Professional scientific and technical services Payroll %, Other services except public administration Payroll %, Management of companies and enterprises Payroll %, Real estate and rental and leasing Payroll %, Mining quarrying and oil and gas extraction Payroll %, Industries not classified Payroll %, Transportation and warehousing Payroll %, Arts entertainment and recreation Payroll %, Wholesale trade Payroll %, Utilities Payroll %, Agriculture forestry fishing and hunting Payroll %, Construction Payroll %, Manufacturing Payroll %, Administrative and support and waste management and remediation services Payroll %, Accommodation and food services Payroll %, Information Payroll %, Health care and social assistance Payroll %, Finance and insurance Payroll %

Choose individual features you want to cluster by. You should pick the features that will have the highest impact on your problem area. You can select between 2 – 40 features.

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