In 2023, the metropolitan area of New York-Newark-Jersey City had the biggest population in the United States. Based on annual estimates from the census, the metropolitan area had around 19.5 million inhabitants, which was a slight decrease from the previous year. The Los Angeles and Chicago metro areas rounded out the top three. What is a metropolitan statistical area? In general, a metropolitan statistical area (MSA) is a core urbanized area with a population of at least 50,000 inhabitants – the smallest MSA is Carson City, with an estimated population of nearly 56,000. The urban area is made bigger by adjacent communities that are socially and economically linked to the center. MSAs are particularly helpful in tracking demographic change over time in large communities and allow officials to see where the largest pockets of inhabitants are in the country. How many MSAs are in the United States? There were 421 metropolitan statistical areas across the U.S. as of July 2021. The largest city in each MSA is designated the principal city and will be the first name in the title. An additional two cities can be added to the title, and these will be listed in population order based on the most recent census. So, in the example of New York-Newark-Jersey City, New York has the highest population, while Jersey City has the lowest. The U.S. Census Bureau conducts an official population count every ten years, and the new count is expected to be announced by the end of 2030.

This data set describes metropolitan areas in the conterminous United States, developed from U.S. Bureau of the Census boundaries of Consolidated Metropolitan Statistical Areas (CMSA) and Metropolitan Statistical Areas (MSA), that have been processed to extract the largest contiguous urban area within each MSA or CMSA.

This statistic shows a ranking of metropolitan areas with the highest shares of lower-income adults in the United States in 2014. In 2014, the Laredo metropolitan area in Texas was ranked first with ** percent of adult population living in the lower-income tier.

This statistic shows ranking of metropolitan areas with the highest shares of middle-income adults in the United States in 2014. In 2014, the Wausau metropolitan area in Wisconsin was ranked first with ** percent of adult population living in the middle-income tier.

This statistics shows a list of the top 20 largest-metropolitan areas in the United States in 2010, by land area. Riverside-San Bernardino-Ontario in California was ranked first enclosing an area of 70,612 square kilometers.

This statistic depicts the list of top ten U.S. metro areas with the lowest levels of overall income segregation as of 2015. Source mentioned that economic segregation is not just about income; it reflects and drives our deeper class divisions. As of 2015, San Jose-Sunnyvale-Santa Clara metro area in California was ranked first in the list with an index value of *****.

This statistic shows the top 10 U.S. metropolitan statistical areas with the largest amount of employment in drugs and pharmaceuticals in 2023. New York-Newark-Jersey City (NY-NJ-PA) ranked second highest, with around ****** persons employed within this industry.

Users can obtain descriptions, maps, profiles, and ranks of U.S. metropolitan areas pertaining to quality of life, diversity, and opportunities for racial and ethnic groups in the U.S. BackgroundThe Diversity Data project operates a website for users to explore how U.S. metropolitan areas perform on evidence-based social measures affecting quality of life, diversity and opportunity for racial and ethnic groups in the United States. These indicators capture a broad definition of quality of life and health, including opportunities for good schools, housing, jobs, wages, health and social services, and safe neighborhoods. This is a useful resource for people inter ested in advocating for policy and social change regarding neighborhood integration, residential mobility, anti-discrimination in housing, urban renewal, school quality and economic opportunities. The Diversity Data project is an ongoing project of the Harvard School of Public Health (Department of Society, Human Development and Health). User FunctionalityUsers can obtain a description, profile and rank of U.S. metropolitan areas and compare ranks across metropolitan areas. Users can also generate maps which demonstrate the distribution of these measures across the United States. Demographic information is available by race/ethnicity. Data NotesData are derived from multiple sources including: the U.S. Census Bureau; National Center for Health Statistics' Vital Statistics Natality Birth Data; Natio nal Center for Education Statistics; Union CPS Utilities Data CD; National Low Income Housing Coalition; Freddie Mac Conventional Mortgage Home Price Index; Neighborhood Change Database; Joint Center for Housing Studies of Harvard University; Federal Financial Institutions Examination Council Home Mortgage Disclosure Act (HMD); Dr. Russ Lopez, Boston University School of Public Health, Department of Environmental Health; HUD State of the Cities Data Systems; Agency for Healthcare Research and Quality; and Texas Transportation Institute. Years in which the data were collected are indicated with the measure. Information is available for metropolitan areas. The website does not indicate when the data are updated.

DATA DESCRIPTION:-

1- land_area : size in square miles

2-percent_city : percent of population in central city/cities

3-percent_senior : percent of population ≤ 65 years

4-physicians : number of professionally active physicians

5-hospital_beds : total number of hospital beds

6-graduates : percent of adults that finished high school

7-work_force : number of persons in work force in thousands

8-income : total income in 1976 in millions of dollars

9-crime_rate: Ratio of number of serious crimes by total population

10-region: geographic region according to US Census

We can see that the regions have 4 values, where:

1 = North-East

2 = North-Central

3 = South

4 = West

A dataset ranking the top metropolitan areas in the United States by nominal GDP for 2024, based on data from the U.S. Bureau of Economic Analysis (BEA).

United States Urban Areas Dataset

Spatial and attribute data for US urban areas

By Homeland Infrastructure Foundation [source]

About this dataset

The Urban Areas dataset provides comprehensive spatial and attribute data on urban areas in the United States. These urban areas represent densely developed territories consisting of residential, commercial, and other nonresidential land uses. The dataset includes geospatial information such as longitude and latitude coordinates, area measurements (land and water), shape length, and shape area for each urban area.

Each urban area is identified by a unique 5-character numeric census code, which distinguishes between two types of urban areas: urbanized areas (UAs) with populations of 50,000 or more people, and urban clusters (UCs) with populations ranging between 2,500 to 50,000 people (except in the U.S. Virgin Islands and Guam where some UCs have populations greater than 50,000).

Other important attributes provided include the functional status code indicating the functional classification of the urban area along with its name description. The land area measurement gives insight into the extent of developed territory in square meters for each urban area.

Furthermore, this dataset contains MAF/TIGER feature class codes that provide additional information about specific features within an urban area. These codes help in identifying various characteristics or components within an urban footprint.

By utilizing this dataset researchers can analyze different aspects related to population density patterns across various urbanscapes within the United States. This includes studying demographic trends as well as exploring correlations between land usage patterns - whether residential or commercial - in relation to geographical location.

Overall, this dataset serves as a valuable resource for conducting detailed spatial analysis on a wide range of topics related to population distribution and development across diverse metropolitan areas throughout the United States

How to use the dataset

1. Understanding the Urban Area Types

The dataset categorizes urban areas into two types: Urbanized Areas (UAs) and Urban Clusters (UCs). UAs are densely developed territories with populations of 50,000 or more people. UCs are also densely developed territories but have populations ranging from at least 2,500 people to fewer than 50,000 people.

2. Familiarize Yourself with Key Attributes

The dataset includes various attributes that provide valuable information about each urban area:

• NAME10: The name of the urban area.
• NAMELSAD10: The legal/statistical area description of the urban area.
• UACE10: A unique 5-character numeric census code that identifies each urban area.
• FUNCSTAT10: The functional status code for the urban area.
• ALAND10: The land area of the urban area in square meters.
• AWATER10: The water area of the urbareaan in square meters.
• INTPTLAT10: The latitude coordinate of an interior point within the geographic extent of an individual block group building footprint.(Numeric) -**INTPTLON150 longitude coordinate of an interior point within markset tabulation block group или Tract_LP tificatlpublic Land Survey System™ (PLSS)-based apices location

Understanding these attributes will allow you to gain insights into each specific type.

3. Analyzing Land and Water Area

By focusing on ALAND10 and AWATER10, you can explore the land and water areas of each urban area. This information could be valuable for understanding urban sprawl, planning infrastructure projects, or conducting environmental studies.

4. Exploring Functional Status

FUNCSTAT10 provides information about the functional status of an urban area. This attribute can help you identify whether an area serves as a single principal city or represents part of a larger metropolitan region.

5. Utilizing the Geographic Coordinates

INTPTLAT10 and INTPTLON10 provide latitude and longitude coordinates for each urban area's interior point. You can leverage this data to plot locations on maps

Research Ideas

• Urban Planning Analysis: This dataset can be used for urban planning analysis, such as identifying the land area and water area of different urban areas. It can help city officials and planners understand the spatial distribution of urban areas, assess population density, and make informed decisions regarding infrastructure development and resource allocation.
• Market Research: The dataset can be utilized for market research purposes by identifying different types of urban areas (UAs or UCs) based on their po...

The Core Based Statistical Areas (CBSA) dataset is as of August 9, 2019 and is from the United States Department of Commerce (USDOC), United States Census Bureau (USCB), and part of the U.S. Department of Transportation (USDOT)/Bureau of Transportation Statistics’ (BTS') National Transportation Atlas Database (NTAD). The TIGER/Line shapefiles and related database files (.dbf) are an extract of selected geographic and cartographic information from the U.S. Census Bureau's Master Address File / Topologically Integrated Geographic Encoding and Referencing (MAF/TIGER) Database (MTDB). The MTDB represents a seamless national file with no overlaps or gaps between parts, however, each TIGER/Line shapefile is designed to stand alone as an independent data set, or they can be combined to cover the entire nation. Metropolitan and Micropolitan Statistical Areas are together termed Core Based Statistical Areas (CBSAs) and are defined by the Office of Management and Budget (OMB) and consist of the county or counties or equivalent entities associated with at least one urban core (urbanized area or urban cluster) of at least 10,000 population, plus adjacent counties having a high degree of social and economic integration with the core as measured through commuting ties with the counties containing the core. Categories of CBSAs are: Metropolitan Statistical Areas, based on urbanized areas of 50,000 or more population; and Micropolitan Statistical Areas, based on urban clusters of at least10,000 population but less than 50,000 population. The CBSA boundaries are those defined by OMB based on the2010 Census, published in 2013, and updated in 2018.

Disclaimer: These data are updated by the author and are not an official product of the Federal Reserve Bank of Cleveland.This project provides two sets of migration estimates for the major US metro areas. The first series measures net migration of people to and from the urban neighborhoods of the metro areas. The second series covers all neighborhoods but breaks down net migration to other regions by four region types: (1) high-cost metros, (2) affordable, large metros, (3) midsized metros, and (4) small metros and rural areas. These series were introduced in a Cleveland Fed District Data Brief entitled “Urban and Regional Migration Estimates: Will Your City Recover from the Pandemic?"The migration estimates in this project are created with data from the Federal Reserve Bank of New York/Equifax Consumer Credit Panel (CCP). The CCP is a 5 percent random sample of the credit histories maintained by Equifax. The CCP reports the census block of residence for over 10 million individuals each quarter. Each month, Equifax receives individuals’ addresses, along with reports of debt balances and payments, from creditors (mortgage lenders, credit card issuers, student loan servicers, etc.). An algorithm maintained by Equifax considers all of the addresses reported for an individual and identifies the individual’s most likely current address. Equifax anonymizes the data before they are added to the CCP, removing names, addresses, and Social Security numbers (SSNs). In lieu of mailing addresses, the census block of the address is added to the CCP. Equifax creates a unique, anonymous identifier to enable researchers to build individuals’ panels. The panel nature of the data allows us to observe when someone has migrated and is living in a census block different from the one they lived in at the end of the preceding quarter. For more details about the CCP and its use in measuring migration, see Lee and Van der Klaauw (2010) and DeWaard, Johnson and Whitaker (2019). DefinitionsMetropolitan areaThe metropolitan areas in these data are combined statistical areas. This is the most aggregate definition of metro areas, and it combines Washington DC with Baltimore, San Jose with San Francisco, Akron with Cleveland, etc. Metro areas are combinations of counties that are tightly linked by worker commutes and other economic activity. All counties outside of metropolitan areas are tracked as parts of a rural commuting zone (CZ). CZs are also groups of counties linked by commuting, but CZ definitions cover all counties, both metropolitan and non-metropolitan. High-cost metropolitan areasHigh-cost metro areas are those where the median list price for a house was more than $200 per square foot on average between April 2017 and April 2022. These areas include San Francisco-San Jose, New York, San Diego, Los Angeles, Seattle, Boston, Miami, Sacramento, Denver, Salt Lake City, Portland, and Washington-Baltimore. Other Types of RegionsMetro areas with populations above 2 million and house price averages below $200 per square foot are categorized as affordable, large metros. Metro areas with populations between 500,000 and 2 million are categorized as mid-sized metros, regardless of house prices. All remaining counties are in the small metro and rural category.To obtain a metro area's total net migration, sum the four net migration values for the the four types of regions.Urban neighborhoodCensus tracts are designated as urban if they have a population density above 7,000 people per square mile. High density neighborhoods can support walkable retail districts and high-frequency public transportation. They are more likely to have the “street life” that people associate with living in an urban rather than a suburban area. The threshold of 7,000 people per square mile was selected because it was the average density in the largest US cities in the 1930 census. Before World War II, workplaces, shopping, schools and parks had to be accessible on foot. Tracts are also designated as urban if more than half of their housing units were built before WWII and they have a population density above 2,000 people per square mile. The lower population density threshold for the pre-war neighborhoods recognizes that many urban tracts have lost population since the 1960s. While the street grids usually remain, the area also needs su

The dataset comprises of 10 JSON files, each containing geographic metadata and a sentiment score collected from tweets between March 20, 2020 and December 1, 2020 pertaining to the COVID-19 global pandemic for ten of the most populous cities in the United States and Canada.

This statistic depicts the list of top ten U.S. metros where the wealthy face the most level of segregation as of 2015. In 2015, Memphis metro in Tennessee was ranked first in the list with the index value of 0.582.

Price per Square: Multi-Family: Fort Leonard Wood, MO data was reported at 70.060 USD th in Jul 2020. This records a decrease from the previous number of 113.482 USD th for Jun 2020. Price per Square: Multi-Family: Fort Leonard Wood, MO data is updated monthly, averaging 66.855 USD th from Aug 2012 (Median) to Jul 2020, with 58 observations. The data reached an all-time high of 456.687 USD th in Dec 2018 and a record low of 4.254 USD th in Nov 2016. Price per Square: Multi-Family: Fort Leonard Wood, MO data remains active status in CEIC and is reported by Redfin. The data is categorized under Global Database’s United States – Table US.EB060: Price per Square: by Metropolitan Areas.

Median Home Sale Price: sa: Single Family: Philadelphia, PA data was reported at 329.000 USD th in Jul 2020. This records an increase from the previous number of 311.000 USD th for Jun 2020. Median Home Sale Price: sa: Single Family: Philadelphia, PA data is updated monthly, averaging 208.000 USD th from Feb 2012 (Median) to Jul 2020, with 102 observations. The data reached an all-time high of 347.000 USD th in May 2020 and a record low of 191.000 USD th in Dec 2014. Median Home Sale Price: sa: Single Family: Philadelphia, PA data remains active status in CEIC and is reported by Redfin. The data is categorized under Global Database’s United States – Table US.EB057: Median Home Sale Price: by Metropolitan Areas: Seasonally Adjusted.

The 2015 American Housing Survey marks the first release of a newly integrated national sample and independent metropolitan area samples. The 2015 release features many variable name revisions, as well as the integration of an AHS Codebook Interactive Tool available on the U.S. Census Bureau Web site. This data collection provides information on representative samples of each of the 15 largest metropolitan areas across the United States, which are also included in the integrated national sample (available as ICPSR 36801). The metropolitan area sample also features representative samples of 10 additional metropolitan areas that are not present in the national sample. The U.S. Department of Housing and Urban Development (HUD) and the U.S. Census Bureau intend to survey the 15 largest metropolitan areas once every 2 years. To ensure the sample was representative of all housing units within each metro area, the U.S. Census Bureau stratified all housing units into one of the following categories: (1) A HUD-assisted unit (as of 2013); (2) Trailer or mobile home; (3) Owner-occupied and one unit in structure; (4) Owner-occupied and two or more units in structure; (5) Renter-occupied and one unit in structure; (6) Renter-occupied and two or more units in structure; (7) Vacant and one unit in structure; (8) Vacant and two or more units in structure; and (9) Other units, such as houseboats and recreational vehicles. The data are presented in three separate parts: Part 1, Household Record (Main Record); Part 2, Person Record; and Part 3, Project Record. Household Record data includes questions about household occupancy and tenure, household exterior and interior structural features, household equipment and appliances, housing problems, housing costs, home improvement, neighborhood features, recent moving information, income, and basic demographic information. The Household Record data also features four rotating topical modules: Arts and Culture, Food Security, Housing Counseling, and Healthy Homes. Person Record data includes questions about personal disabilities, income, and basic demographic information. Finally, Project Record data includes questions about home improvement projects. Specific questions were asked about the types of projects, costs, funding sources, and year of completion.

Content

Data was pulled from a table in the following Wikipedia article: https://en.wikipedia.org/wiki/List_of_United_States_cities_by_population I used Microsoft Excel's PowerQuery function to pull the table from Wikipedia. Lists each city, its rank (based on 2020 population), some data on its area, and population in both 2020 and 2010.

Banner image source: https://unsplash.com/photos/wh-7GeXxItI

Median Home Sale Price: sa: Single Family: North Wilkesboro, NC data was reported at 165.000 USD th in Jul 2020. This records an increase from the previous number of 162.000 USD th for Jun 2020. Median Home Sale Price: sa: Single Family: North Wilkesboro, NC data is updated monthly, averaging 106.000 USD th from Feb 2012 (Median) to Jul 2020, with 102 observations. The data reached an all-time high of 223.000 USD th in Sep 2012 and a record low of 24.000 USD th in Mar 2016. Median Home Sale Price: sa: Single Family: North Wilkesboro, NC data remains active status in CEIC and is reported by Redfin. The data is categorized under Global Database’s United States – Table US.EB057: Median Home Sale Price: by Metropolitan Areas: Seasonally Adjusted.