Among the 50 largest cities by population in the United States, Milwaukee, WI, had the largest homes in 2023. The average size of a home was over 2,000 square feet, while in Portland, OR, the average home was 1070 square feet. Since 1975, U.S. homes have grown substantially bigger.

How many incorporated places are registered in the U.S.?

There were 19,502 incorporated places registered in the United States as of July 31, 2019. 16,410 had a population under 10,000 while, in contrast, only 10 cities had a population of one million or more.

Small-town America

Suffice it to say, almost nothing is more idealized in the American imagination than small-town America. When asked where they would prefer to live, 30 percent of Americans reported that they would prefer to live in a small town. Americans tend to prefer small-town living due to a perceived slower pace of life, close-knit communities, and a more affordable cost of living when compared to large cities.

An increasing population

Despite a preference for small-town life, metropolitan areas in the U.S. still see high population figures, with the New York, Los Angeles, and Chicago metro areas being the most populous in the country. Metro and state populations are projected to increase by 2040, so while some may move to small towns to escape city living, those small towns may become more crowded in the upcoming decades.

This statistic shows the top 25 cities in the United States with the highest resident population as of July 1, 2022. There were about 8.34 million people living in New York City as of July 2022.

Henderson, Chesapeake, and Virginia Beach were the cities in the United States where the average size of rental apartments was the largest in 2024. In Henderson, NV, this measured at 984 square feet, whereas in Seattle, WA, the average apartment was much smaller at 689 square feet. When it comes to affordability, Wichita, KS, was the city where 1,500 U.S. dollars would get renters the largest apartment.

About this dataset

Context

This list ranks the 18 cities in the Bethel Census Area, AK by Non-Hispanic Native Hawaiian and Other Pacific Islander (NHPI) population, as estimated by the United States Census Bureau. It also highlights population changes in each cities over the past five years.

Content

When available, the data consists of estimates from the U.S. Census Bureau American Community Survey (ACS) 5-Year Estimates, including:

• 2019-2023 American Community Survey 5-Year Estimates
• 2018-2022 American Community Survey 5-Year Estimates
• 2017-2021 American Community Survey 5-Year Estimates
• 2016-2020 American Community Survey 5-Year Estimates
• 2015-2019 American Community Survey 5-Year Estimates

Variables / Data Columns

• Rank by Non-Hispanic Pacific Islander Population: This column displays the rank of cities in the Bethel Census Area, AK by their Non-Hispanic Native Hawaiian and Other Pacific Islander (NHPI) population, using the most recent ACS data available.
• cities: The cities for which the rank is shown in the previous column.
• Non-Hispanic Pacific Islander Population: The Non-Hispanic Pacific Islander population of the cities is shown in this column.
• % of Total cities Population: This shows what percentage of the total cities population identifies as Non-Hispanic Pacific Islander. Please note that the sum of all percentages may not equal one due to rounding of values.
• % of Total Bethel Census Area Non-Hispanic Pacific Islander Population: This tells us how much of the entire Bethel Census Area, AK Non-Hispanic Pacific Islander population lives in that cities. Please note that the sum of all percentages may not equal one due to rounding of values.
• 5 Year Rank Trend: TThis column displays the rank trend across the last 5 years.

Good to know

Margin of Error

Data in the dataset are based on the estimates and are subject to sampling variability and thus a margin of error. Neilsberg Research recommends using caution when presening these estimates in your research.

Custom data

If you do need custom data for any of your research project, report or presentation, you can contact our research staff at research@neilsberg.com for a feasibility of a custom tabulation on a fee-for-service basis.

Inspiration

Neilsberg Research Team curates, analyze and publishes demographics and economic data from a variety of public and proprietary sources, each of which often includes multiple surveys and programs. The large majority of Neilsberg Research aggregated datasets and insights is made available for free download at https://www.neilsberg.com/research/.

United States US: Population in Largest City: as % of Urban Population data was reported at 7.020 % in 2017. This records a decrease from the previous number of 7.065 % for 2016. United States US: Population in Largest City: as % of Urban Population data is updated yearly, averaging 8.675 % from Dec 1960 (Median) to 2017, with 58 observations. The data reached an all-time high of 11.200 % in 1960 and a record low of 7.020 % in 2017. United States US: Population in Largest City: as % of Urban Population data remains active status in CEIC and is reported by World Bank. The data is categorized under Global Database’s USA – Table US.World Bank.WDI: Population and Urbanization Statistics. Population in largest city is the percentage of a country's urban population living in that country's largest metropolitan area.; ; United Nations, World Urbanization Prospects.; Weighted average;

All cities with a population > 1000 or seats of adm div (ca 80.000)Sources and ContributionsSources : GeoNames is aggregating over hundred different data sources. Ambassadors : GeoNames Ambassadors help in many countries. Wiki : A wiki allows to view the data and quickly fix error and add missing places. Donations and Sponsoring : Costs for running GeoNames are covered by donations and sponsoring.Enrichment:add country name

VITAL SIGNS INDICATOR Population (LU1)

FULL MEASURE NAME Population estimates

LAST UPDATED October 2019

DESCRIPTION Population is a measurement of the number of residents that live in a given geographical area, be it a neighborhood, city, county or region.

DATA SOURCES U.S Census Bureau: Decennial Census No link available (1960-1990) http://factfinder.census.gov (2000-2010)

California Department of Finance: Population and Housing Estimates Table E-6: County Population Estimates (1961-1969) Table E-4: Population Estimates for Counties and State (1971-1989) Table E-8: Historical Population and Housing Estimates (2001-2018) Table E-5: Population and Housing Estimates (2011-2019) http://www.dof.ca.gov/Forecasting/Demographics/Estimates/

U.S. Census Bureau: Decennial Census - via Longitudinal Tract Database Spatial Structures in the Social Sciences, Brown University Population Estimates (1970 - 2010) http://www.s4.brown.edu/us2010/index.htm

U.S. Census Bureau: American Community Survey 5-Year Population Estimates (2011-2017) http://factfinder.census.gov

U.S. Census Bureau: Intercensal Estimates Estimates of the Intercensal Population of Counties (1970-1979) Intercensal Estimates of the Resident Population (1980-1989) Population Estimates (1990-1999) Annual Estimates of the Population (2000-2009) Annual Estimates of the Population (2010-2017) No link available (1970-1989) http://www.census.gov/popest/data/metro/totals/1990s/tables/MA-99-03b.txt http://www.census.gov/popest/data/historical/2000s/vintage_2009/metro.html https://www.census.gov/data/datasets/time-series/demo/popest/2010s-total-metro-and-micro-statistical-areas.html

CONTACT INFORMATION vitalsigns.info@bayareametro.gov

METHODOLOGY NOTES (across all datasets for this indicator) All legal boundaries and names for Census geography (metropolitan statistical area, county, city, and tract) are as of January 1, 2010, released beginning November 30, 2010, by the U.S. Census Bureau. A Priority Development Area (PDA) is a locally-designated area with frequent transit service, where a jurisdiction has decided to concentrate most of its housing and jobs growth for development in the foreseeable future. PDA boundaries are current as of August 2019. For more information on PDA designation see http://gis.abag.ca.gov/website/PDAShowcase/.

Population estimates for Bay Area counties and cities are from the California Department of Finance, which are as of January 1st of each year. Population estimates for non-Bay Area regions are from the U.S. Census Bureau. Decennial Census years reflect population as of April 1st of each year whereas population estimates for intercensal estimates are as of July 1st of each year. Population estimates for Bay Area tracts are from the decennial Census (1970 -2010) and the American Community Survey (2008-2012 5-year rolling average; 2010-2014 5-year rolling average; 2013-2017 5-year rolling average). Estimates of population density for tracts use gross acres as the denominator.

Population estimates for Bay Area PDAs are from the decennial Census (1970 - 2010) and the American Community Survey (2006-2010 5 year rolling average; 2010-2014 5-year rolling average; 2013-2017 5-year rolling average). Population estimates for PDAs are derived from Census population counts at the tract level for 1970-1990 and at the block group level for 2000-2017. Population from either tracts or block groups are allocated to a PDA using an area ratio. For example, if a quarter of a Census block group lies with in a PDA, a quarter of its population will be allocated to that PDA. Tract-to-PDA and block group-to-PDA area ratios are calculated using gross acres. Estimates of population density for PDAs use gross acres as the denominator.

Annual population estimates for metropolitan areas outside the Bay Area are from the Census and are benchmarked to each decennial Census. The annual estimates in the 1990s were not updated to match the 2000 benchmark.

The following is a list of cities and towns by geographical area: Big Three: San Jose, San Francisco, Oakland Bayside: Alameda, Albany, Atherton, Belmont, Belvedere, Berkeley, Brisbane, Burlingame, Campbell, Colma, Corte Madera, Cupertino, Daly City, East Palo Alto, El Cerrito, Emeryville, Fairfax, Foster City, Fremont, Hayward, Hercules, Hillsborough, Larkspur, Los Altos, Los Altos Hills, Los Gatos, Menlo Park, Mill Valley, Millbrae, Milpitas, Monte Sereno, Mountain View, Newark, Pacifica, Palo Alto, Piedmont, Pinole, Portola Valley, Redwood City, Richmond, Ross, San Anselmo, San Bruno, San Carlos, San Leandro, San Mateo, San Pablo, San Rafael, Santa Clara, Saratoga, Sausalito, South San Francisco, Sunnyvale, Tiburon, Union City, Vallejo, Woodside Inland, Delta and Coastal: American Canyon, Antioch, Benicia, Brentwood, Calistoga, Clayton, Cloverdale, Concord, Cotati, Danville, Dixon, Dublin, Fairfield, Gilroy, Half Moon Bay, Healdsburg, Lafayette, Livermore, Martinez, Moraga, Morgan Hill, Napa, Novato, Oakley, Orinda, Petaluma, Pittsburg, Pleasant Hill, Pleasanton, Rio Vista, Rohnert Park, San Ramon, Santa Rosa, Sebastopol, Sonoma, St. Helena, Suisun City, Vacaville, Walnut Creek, Windsor, Yountville Unincorporated: all unincorporated towns

Not many studies have documented climate and air quality changes of settlements at early stages of development. This is because high quality climate and air quality records are deficient for the periods of the early 18th century to mid 20th century when many U.S. cities were formed and grew. Dramatic landscape change induces substantial local climate change during the incipient stage of development. Rapid growth along the urban fringe in Phoenix, coupled with a fine-grained climate monitoring system, provide a unique opportunity to study the climate impacts of urban development as it unfolds. Generally, heat islands form, particularly at night, in proportion to city population size and morphological characteristics. Drier air is produced by replacement of the countryside's moist landscapes with dry, hot urbanized surfaces. Wind is increased due to turbulence induced by the built-up urban fabric and its morphology; although, depending on spatial densities of buildings on the land, wind may also decrease. Air quality conditions are worsened due to increased city emissions and surface disturbances. Depending on the diversity of microclimates in pre-existing rural landscapes and the land-use mosaic in cities, the introduction of settlements over time and space can increase or decrease the variety of microclimates within and near urban regions. These differences in microclimatic conditions can influence variations in health, ecological, architectural, economic, energy and water resources, and quality-of-life conditions in the city. Therefore, studying microclimatic conditions which change in the urban fringe over time and space is at the core of urban ecological goals as part of LTER aims. In analyzing Phoenix and Baltimore long-term rural/urban weather and climate stations, Brazel et al. (In progress) have discovered that long-term (i.e., 100 years) temperature changes do not correlate with populations changes in a linear manner, but rather in a third-order nonlinear response fashion. This nonlinear temporal change is consistent with the theories in boundary layer climatology that describe and explain the leading edge transition and energy balance theory. This pattern of urban vs. rural temperature response has been demonstrated in relation to spatial range of city sizes (using population data) for 305 rural vs. urban climate stations in the U.S. Our recent work on the two urban LTER sites has shown that a similar climate response pattern also occurs over time for climate stations that were initially located in rural locations have been overrun bu the urban fringe and subsequent urbanization (e.g., stations in Baltimore, Mesa, Phoenix, and Tempe). Lack of substantial numbers of weather and climate stations in cities has previously precluded small-scale analyses of geographic variations of urban climate, and the links to land-use change processes. With the advent of automated weather and climate station networks, remote-sensing technology, land-use history, and the focus on urban ecology, researchers can now analyze local climate responses as a function of the details of land-use change. Therefore, the basic research question of this study is: How does urban climate change over time and space at the place of maximum disturbance on the urban fringe? Hypotheses 1. Based on the leading edge theory of boundary layer climate change, largest changes should occur during the period of peak development of the land when land is being rapidly transformed from open desert and agriculture to residential, commercial, and industrial uses. 2. One would expect to observe, on average and on a temporal basis (several years), nonlinear temperature and humidity alterations across the station network at varying levels of urban development. 3. Based on past research on urban climate, one would expect to see in areas of the urban fringe, rapid changes in temperature (increases at night particularly), humidity (decreases in areas from agriculture to urban; increases from desert to urban), and wind speed (increases due to urban heating). 4. Changes of the surface climate on the urban fringe are expected to be altered as a function of various energy, moisture, and momentum control parameters, such as albedo, surface moisture, aerodynamic surface roughness, and thermal admittance. These parameters relate directly to population and land-use change (Lougeay et al. 1996).

About this dataset

Context

This list ranks the 7 cities in the Dillingham Census Area, AK by Hispanic Black or African American population, as estimated by the United States Census Bureau. It also highlights population changes in each cities over the past five years.

Content

When available, the data consists of estimates from the U.S. Census Bureau American Community Survey (ACS) 5-Year Estimates, including:

• 2019-2023 American Community Survey 5-Year Estimates
• 2018-2022 American Community Survey 5-Year Estimates
• 2017-2021 American Community Survey 5-Year Estimates
• 2016-2020 American Community Survey 5-Year Estimates
• 2015-2019 American Community Survey 5-Year Estimates

Variables / Data Columns

• Rank by Hispanic Black Population: This column displays the rank of cities in the Dillingham Census Area, AK by their Hispanic Black or African American population, using the most recent ACS data available.
• cities: The cities for which the rank is shown in the previous column.
• Hispanic Black Population: The Hispanic Black population of the cities is shown in this column.
• % of Total cities Population: This shows what percentage of the total cities population identifies as Hispanic Black. Please note that the sum of all percentages may not equal one due to rounding of values.
• % of Total Dillingham Census Area Hispanic Black Population: This tells us how much of the entire Dillingham Census Area, AK Hispanic Black population lives in that cities. Please note that the sum of all percentages may not equal one due to rounding of values.
• 5 Year Rank Trend: TThis column displays the rank trend across the last 5 years.

Good to know

Margin of Error

Data in the dataset are based on the estimates and are subject to sampling variability and thus a margin of error. Neilsberg Research recommends using caution when presening these estimates in your research.

Custom data

If you do need custom data for any of your research project, report or presentation, you can contact our research staff at research@neilsberg.com for a feasibility of a custom tabulation on a fee-for-service basis.

Inspiration

Neilsberg Research Team curates, analyze and publishes demographics and economic data from a variety of public and proprietary sources, each of which often includes multiple surveys and programs. The large majority of Neilsberg Research aggregated datasets and insights is made available for free download at https://www.neilsberg.com/research/.

A dataset listing Georgia cities by population for 2024.

A dataset listing Colorado cities by population for 2024.

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.

The Austin Parks and Recreation System's ranking on the Trust for Public Land ParkScore Index. This index ranks the park systems of the 100 largest cities in the U.S. based on park acreage, park size, park funding, park access, and a variety of other factors.

This data set supports HE.C.2 of SD23.

View more details and insights related to this data set on the story page: https://data.austintexas.gov/stories/s/Austin-s-ParkScore-Ranking-absolute-score-and-rank/rnwr-4s4u/

*If a cell is blank, that means PARD did not have a response for that year or TPL removed the question for that

Sustainable cities depend on urban forests. City trees -- a pillar of urban forests -- improve our health, clean the air, store CO2, and cool local temperatures. Comparatively less is known about urban forests as ecosystems, particularly their spatial composition, nativity statuses, biodiversity, and tree health. Here, we assembled and standardized a new dataset of N=5,660,237 trees from 63 of the largest US cities. The data comes from tree inventories conducted at the level of cities and/or neighborhoods. Each data sheet includes detailed information on tree location, species, nativity status (whether a tree species is naturally occurring or introduced), health, size, whether it is in a park or urban area, and more (comprising 28 standardized columns per datasheet). This dataset could be analyzed in combination with citizen-science datasets on bird, insect, or plant biodiversity; social and demographic data; or data on the physical environment. Urban forests offer a rare opportunity to intentionally design biodiverse, heterogenous, rich ecosystems. Methods See eLife manuscript for full details. Below, we provide a summary of how the dataset was collected and processed.

Data Acquisition We limited our search to the 150 largest cities in the USA (by census population). To acquire raw data on street tree communities, we used a search protocol on both Google and Google Datasets Search (https://datasetsearch.research.google.com/). We first searched the city name plus each of the following: street trees, city trees, tree inventory, urban forest, and urban canopy (all combinations totaled 20 searches per city, 10 each in Google and Google Datasets Search). We then read the first page of google results and the top 20 results from Google Datasets Search. If the same named city in the wrong state appeared in the results, we redid the 20 searches adding the state name. If no data were found, we contacted a relevant state official via email or phone with an inquiry about their street tree inventory. Datasheets were received and transformed to .csv format (if they were not already in that format). We received data on street trees from 64 cities. One city, El Paso, had data only in summary format and was therefore excluded from analyses.

Data Cleaning All code used is in the zipped folder Data S5 in the eLife publication. Before cleaning the data, we ensured that all reported trees for each city were located within the greater metropolitan area of the city (for certain inventories, many suburbs were reported - some within the greater metropolitan area, others not). First, we renamed all columns in the received .csv sheets, referring to the metadata and according to our standardized definitions (Table S4). To harmonize tree health and condition data across different cities, we inspected metadata from the tree inventories and converted all numeric scores to a descriptive scale including “excellent,” “good”, “fair”, “poor”, “dead”, and “dead/dying”. Some cities included only three points on this scale (e.g., “good”, “poor”, “dead/dying”) while others included five (e.g., “excellent,” “good”, “fair”, “poor”, “dead”). Second, we used pandas in Python (W. McKinney & Others, 2011) to correct typos, non-ASCII characters, variable spellings, date format, units used (we converted all units to metric), address issues, and common name format. In some cases, units were not specified for tree diameter at breast height (DBH) and tree height; we determined the units based on typical sizes for trees of a particular species. Wherever diameter was reported, we assumed it was DBH. We standardized health and condition data across cities, preserving the highest granularity available for each city. For our analysis, we converted this variable to a binary (see section Condition and Health). We created a column called “location_type” to label whether a given tree was growing in the built environment or in green space. All of the changes we made, and decision points, are preserved in Data S9. Third, we checked the scientific names reported using gnr_resolve in the R library taxize (Chamberlain & Szöcs, 2013), with the option Best_match_only set to TRUE (Data S9). Through an iterative process, we manually checked the results and corrected typos in the scientific names until all names were either a perfect match (n=1771 species) or partial match with threshold greater than 0.75 (n=453 species). BGS manually reviewed all partial matches to ensure that they were the correct species name, and then we programmatically corrected these partial matches (for example, Magnolia grandifolia-- which is not a species name of a known tree-- was corrected to Magnolia grandiflora, and Pheonix canariensus was corrected to its proper spelling of Phoenix canariensis). Because many of these tree inventories were crowd-sourced or generated in part through citizen science, such typos and misspellings are to be expected. Some tree inventories reported species by common names only. Therefore, our fourth step in data cleaning was to convert common names to scientific names. We generated a lookup table by summarizing all pairings of common and scientific names in the inventories for which both were reported. We manually reviewed the common to scientific name pairings, confirming that all were correct. Then we programmatically assigned scientific names to all common names (Data S9). Fifth, we assigned native status to each tree through reference to the Biota of North America Project (Kartesz, 2018), which has collected data on all native and non-native species occurrences throughout the US states. Specifically, we determined whether each tree species in a given city was native to that state, not native to that state, or that we did not have enough information to determine nativity (for cases where only the genus was known). Sixth, some cities reported only the street address but not latitude and longitude. For these cities, we used the OpenCageGeocoder (https://opencagedata.com/) to convert addresses to latitude and longitude coordinates (Data S9). OpenCageGeocoder leverages open data and is used by many academic institutions (see https://opencagedata.com/solutions/academia). Seventh, we trimmed each city dataset to include only the standardized columns we identified in Table S4. After each stage of data cleaning, we performed manual spot checking to identify any issues.

About this dataset

Context

This list ranks the 2 cities in the Southeast Fairbanks Census Area, AK by Hispanic American Indian and Alaska Native (AIAN) population, as estimated by the United States Census Bureau. It also highlights population changes in each cities over the past five years.

Content

When available, the data consists of estimates from the U.S. Census Bureau American Community Survey (ACS) 5-Year Estimates, including:

• 2019-2023 American Community Survey 5-Year Estimates
• 2018-2022 American Community Survey 5-Year Estimates
• 2017-2021 American Community Survey 5-Year Estimates
• 2016-2020 American Community Survey 5-Year Estimates
• 2015-2019 American Community Survey 5-Year Estimates

Variables / Data Columns

• Rank by Hispanic Native American Population: This column displays the rank of cities in the Southeast Fairbanks Census Area, AK by their Hispanic American Indian and Alaska Native (AIAN) population, using the most recent ACS data available.
• cities: The cities for which the rank is shown in the previous column.
• Hispanic Native American Population: The Hispanic Native American population of the cities is shown in this column.
• % of Total cities Population: This shows what percentage of the total cities population identifies as Hispanic Native American. Please note that the sum of all percentages may not equal one due to rounding of values.
• % of Total Southeast Fairbanks Census Area Hispanic Native American Population: This tells us how much of the entire Southeast Fairbanks Census Area, AK Hispanic Native American population lives in that cities. Please note that the sum of all percentages may not equal one due to rounding of values.
• 5 Year Rank Trend: TThis column displays the rank trend across the last 5 years.

Good to know

Margin of Error

Data in the dataset are based on the estimates and are subject to sampling variability and thus a margin of error. Neilsberg Research recommends using caution when presening these estimates in your research.

Custom data

If you do need custom data for any of your research project, report or presentation, you can contact our research staff at research@neilsberg.com for a feasibility of a custom tabulation on a fee-for-service basis.

Inspiration

Neilsberg Research Team curates, analyze and publishes demographics and economic data from a variety of public and proprietary sources, each of which often includes multiple surveys and programs. The large majority of Neilsberg Research aggregated datasets and insights is made available for free download at https://www.neilsberg.com/research/.

A dataset listing Washington cities by population for 2024.

A dataset listing Maine cities by population for 2024.

In 2025, approximately 23 million people lived in the São Paulo metropolitan area, making it the biggest in Latin America and the Caribbean and the sixth most populated in the world. The homonymous state of São Paulo was also the most populous federal entity in the country. The second place for the region was Mexico City with 22.75 million inhabitants. Brazil's cities Brazil is home to two large metropolises, only counting the population within the city limits, São Paulo had approximately 11.45 million inhabitants, and Rio de Janeiro around 6.21 million inhabitants. It also contains a number of smaller, but well known cities such as Brasília, Salvador, Belo Horizonte and many others, which report between 2 and 3 million inhabitants each. As a result, the country's population is primarily urban, with nearly 88 percent of inhabitants living in cities. Mexico City Mexico City's metropolitan area ranks sevenths in the ranking of most populated cities in the world. Founded over the Aztec city of Tenochtitlan in 1521 after the Spanish conquest as the capital of the Viceroyalty of New Spain, the city still stands as one of the most important in Latin America. Nevertheless, the preeminent economic, political, and cultural position of Mexico City has not prevented the metropolis from suffering the problems affecting the rest of the country, namely, inequality and violence. Only in 2023, the city registered a crime incidence of 52,723 reported cases for every 100,000 inhabitants and around 24 percent of the population lived under the poverty line.

Data for the number of: (a) Consulate Generals, (b) International city organizations/networks, and (c) active Sister City relationships in each of the 100 largest metro areas in the United States (in 2019) from 1783-2024. The Main tab has the total for each of the measures of city diplomacy by year. The other tabs have each of the city diplomacy measures by metro area by year. The Graphs tab contains two line graphs depicting the data on the Main tab. The Sources tab contains information about the source data