This collection presents in computer-readable form the data items used to produce the corresponding printed volume of the COUNTY AND CITY DATA BOOK, 1988. Included is a broad range of statistical information, made available by federal agencies and national associations, for counties, cities, and places. Information also is provided for the 50 states, the District of Columbia, and for the United States as a whole. The dataset is comprised of seven files: a county file, a city file, and a place file, with footnote files and data dictionaries for both the county and the city files. The county data file contains information on areas such as age, agriculture, banking, construction, crime, education, federal expenditures, personal income, population, and vital statistics. The city data file includes variables such as city government, climate, crime, housing, labor force and employment, manufactures, retail trade, and service industries. Included in the place data file are items on population and money income.

This dataset tracks real-time progress toward a comprehensive City Data Inventory.

Data on European cities were collected in the Urban Audit and in the Large City Audit project. The projects' ultimate goal is to contribute towards the improvement of the quality of urban life: it supports the exchange of experience among European cities; it helps to identify best practices; it facilitates benchmarking at the European level and provides information on the dynamics within the cities and with their surroundings.

At the city level, the Urban Audit contains more than 130 variables and more than 50 indicators. These indicators are derived from the variables collected by the European Statistical System.

The data is published in 20 tables within 2 main groups, plus a perception survey table:

Cities and greater cities (urb_cgc)

Population on 1 January by age groups and sex - cities and greater cities (urb_cpop1)
Population structure - cities and greater cities (urb_cpopstr)
Population by citizenship and country of birth - cities and greater cities (urb_cpopcb)
Fertility and mortality - cities and greater cities (urb_cfermor)

Living conditions - cities and greater cities (urb_clivcon)

Education - cities and greater cities (urb_ceduc)

Culture and tourism - cities and greater cities (urb_ctour)
Labour market - cities and greater cities (urb_clma)
Economy and finance - cities and greater cities (urb_cecfi)
Transport - cities and greater cities (urb_ctran)
Environment - cities and greater cities (urb_cenv)

Functional Urban Area (urb_luz)

Population on 1 January by age groups and sex - Functional Urban Area (urb_lpop1)
Population structure - Functional Urban Area (urb_lpopstr)
Population by citizenship and country of birth - Functional Urban Area (urb_lpopcb)
Fertility and mortality - Functional Urban Area (urb_lfermor)
Living conditions - Functional Urban Area (urb_llivcon)
Education - Functional Urban Area (urb_leduc)
Labour market - Functional Urban Area (urb_llma)
Transport - Functional Urban Area (urb_ltran)
Environment - Functional Urban Area (urb_lenv)
Perception survey results (urb_percep)

Data has been collected on two spatial levels in the Urban Audit:

• The City (C) according to the administrative definition, as the basic level,
• The Functional Urban Area (FUA) being an approximation of the functional urban zone centered around the city

This city boundary shapefile was extracted from Esri Data and Maps for ArcGIS 2014 - U.S. Populated Place Areas. This shapefile can be joined to 500 Cities city-level Data (GIS Friendly Format) in a geographic information system (GIS) to make city-level maps.

World Cities provides a basemap layer for the cities of the world. The cities include national capitals, provincial capitals, major population centers, and landmark cities. Population estimates are provided for those cities listed in open source data from the United Nations Statistics Division, United Nations Human Settlements Programme, and U.S. Census Bureau.

This dataset contains city population yearly time series for female and male, and for both genders, collected by the United Nations Statistics Division and published by UNData.

The graph shows the proportion of the population in cities worldwide from 1985 to 2050. **** percent of the world's population lived in cities in the year of 2015. This percentage is forecasted to grow to **** percent in the year 2050.

Comprehensive demographic dataset for Mountain City, TN, US including population statistics, household income, housing units, education levels, employment data, and transportation with year-over-year changes.

2015, 2014. Data were provided by the Centers for Disease Control and Prevention (CDC), Division of Population Health, Epidemiology and Surveillance Branch. The project was funded by the Robert Wood Johnson Foundation (RWJF) in conjunction with the CDC Foundation. 500 cities project census city-level data in GIS-friendly format can be joined with city spatial data (https://chronicdata.cdc.gov/500-Cities/500-Cities-City-Boundaries/n44h-hy2j) in a geographic information system (GIS) to produce maps of 27 measures at the city-level. Because some questions are only asked every other year in the BRFSS, there are 7 measures in this 2017 release from the 2014 BRFSS that were the same as the 2016 release.

The median income indicates the income bracket separating the income earners into two halves of equal size.

About this dataset

Context

The dataset tabulates the population of Salt Lake City by gender, including both male and female populations. This dataset can be utilized to understand the population distribution of Salt Lake City across both sexes and to determine which sex constitutes the majority.

Key observations

There is a slight majority of male population, with 51.52% of total population being male. Source: U.S. Census Bureau American Community Survey (ACS) 2019-2023 5-Year Estimates.

Content

When available, the data consists of estimates from the U.S. Census Bureau American Community Survey (ACS) 2019-2023 5-Year Estimates.

Scope of gender :

Please note that American Community Survey asks a question about the respondents current sex, but not about gender, sexual orientation, or sex at birth. The question is intended to capture data for biological sex, not gender. Respondents are supposed to respond with the answer as either of Male or Female. Our research and this dataset mirrors the data reported as Male and Female for gender distribution analysis. No further analysis is done on the data reported from the Census Bureau.

Variables / Data Columns

• Gender: This column displays the Gender (Male / Female)
• Population: The population of the gender in the Salt Lake City is shown in this column.
• % of Total Population: This column displays the percentage distribution of each gender as a proportion of Salt Lake City total population. Please note that the sum of all percentages may not equal one due to rounding of values.

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/.

Recommended for further research

This dataset is a part of the main dataset for Salt Lake City Population by Race & Ethnicity. You can refer the same here

About this dataset

Context

The dataset tabulates the population of Oklahoma City by gender across 18 age groups. It lists the male and female population in each age group along with the gender ratio for Oklahoma City. The dataset can be utilized to understand the population distribution of Oklahoma City by gender and age. For example, using this dataset, we can identify the largest age group for both Men and Women in Oklahoma City. Additionally, it can be used to see how the gender ratio changes from birth to senior most age group and male to female ratio across each age group for Oklahoma City.

Key observations

Largest age group (population): Male # 25-29 years (27,658) | Female # 25-29 years (27,174). Source: U.S. Census Bureau American Community Survey (ACS) 2019-2023 5-Year Estimates.

Content

When available, the data consists of estimates from the U.S. Census Bureau American Community Survey (ACS) 2019-2023 5-Year Estimates.

Age groups:

• Under 5 years
• 5 to 9 years
• 10 to 14 years
• 15 to 19 years
• 20 to 24 years
• 25 to 29 years
• 30 to 34 years
• 35 to 39 years
• 40 to 44 years
• 45 to 49 years
• 50 to 54 years
• 55 to 59 years
• 60 to 64 years
• 65 to 69 years
• 70 to 74 years
• 75 to 79 years
• 80 to 84 years
• 85 years and over

Scope of gender :

Please note that American Community Survey asks a question about the respondents current sex, but not about gender, sexual orientation, or sex at birth. The question is intended to capture data for biological sex, not gender. Respondents are supposed to respond with the answer as either of Male or Female. Our research and this dataset mirrors the data reported as Male and Female for gender distribution analysis.

Variables / Data Columns

• Age Group: This column displays the age group for the Oklahoma City population analysis. Total expected values are 18 and are define above in the age groups section.
• Population (Male): The male population in the Oklahoma City is shown in the following column.
• Population (Female): The female population in the Oklahoma City is shown in the following column.
• Gender Ratio: Also known as the sex ratio, this column displays the number of males per 100 females in Oklahoma City for each age group.

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/.

Recommended for further research

This dataset is a part of the main dataset for Oklahoma City Population by Gender. You can refer the same here

2014, 2013. Data were provided by the Centers for Disease Control and Prevention (CDC), Division of Population Health, Epidemiology and Surveillance Branch. The project was funded by the Robert Wood Johnson Foundation (RWJF) in conjunction with the CDC Foundation. 500 cities project census city-level data in GIS-friendly format can be joined with city spatial data (https://chronicdata.cdc.gov/500-Cities/500-Cities-City-Boundaries/n44h-hy2j) in a geographic information system (GIS) to produce maps of 27 measures at the city-level.

Mogadishu in Somalia led the ranking of cities with the highest population density in 2023, with ****** residents per square kilometer. When it comes to countries, Monaco is the most densely populated state worldwide.

France FR: Population in Largest City data was reported at 10,844,847.000 Person in 2017. This records an increase from the previous number of 10,789,031.000 Person for 2016. France FR: Population in Largest City data is updated yearly, averaging 9,226,364.500 Person from Dec 1960 (Median) to 2017, with 58 observations. The data reached an all-time high of 10,844,847.000 Person in 2017 and a record low of 7,410,735.000 Person in 1960. France FR: Population in Largest City data remains active status in CEIC and is reported by World Bank. The data is categorized under Global Database’s France – Table FR.World Bank: Population and Urbanization Statistics. Population in largest city is the urban population living in the country's largest metropolitan area.; ; United Nations, World Urbanization Prospects.; ;

Poland PL: Population in Largest City data was reported at 1,758,551.000 Person in 2017. This records an increase from the previous number of 1,749,352.000 Person for 2016. Poland PL: Population in Largest City data is updated yearly, averaging 1,618,666.000 Person from Dec 1960 (Median) to 2017, with 58 observations. The data reached an all-time high of 1,758,551.000 Person in 2017 and a record low of 1,119,181.000 Person in 1960. Poland PL: Population in Largest City data remains active status in CEIC and is reported by World Bank. The data is categorized under Global Database’s Poland – Table PL.World Bank.WDI: Population and Urbanization Statistics. Population in largest city is the urban population living in the country's largest metropolitan area.; ; United Nations, World Urbanization Prospects.; ;

City, Population Size, African American, Asian/Pacific Islander, Latino, White, Foreign-born, Speaks a language other than English at home, Single parent households, Households with children, Average household size, 0-5 years, 6-11 years, 12-17 years, 18-24 years, 25-34 years, 35-44 years, 45-54 years, 55-64 years,Ages 65 and older, Ages 17 and younger. Percentages unless otherwise noted. Source information provided at: https://www.sccgov.org/sites/phd/hi/hd/Documents/City%20Profiles/Methodology/Neighborhood%20profile%20methodology_082914%20final%20for%20web.pdf

About this dataset

Context

The dataset tabulates the Arkansas City population distribution across 18 age groups. It lists the population in each age group along with the percentage population relative of the total population for Arkansas City. The dataset can be utilized to understand the population distribution of Arkansas City by age. For example, using this dataset, we can identify the largest age group in Arkansas City.

Key observations

The largest age group in Arkansas City, AR was for the group of age 50-54 years with a population of 70 (15.52%), according to the 2021 American Community Survey. At the same time, the smallest age group in Arkansas City, AR was the 35-39 years with a population of 4 (0.89%). Source: U.S. Census Bureau American Community Survey (ACS) 2017-2021 5-Year Estimates.

Content

When available, the data consists of estimates from the U.S. Census Bureau American Community Survey (ACS) 2017-2021 5-Year Estimates.

Age groups:

• Under 5 years
• 5 to 9 years
• 10 to 14 years
• 15 to 19 years
• 20 to 24 years
• 25 to 29 years
• 30 to 34 years
• 35 to 39 years
• 40 to 44 years
• 45 to 49 years
• 50 to 54 years
• 55 to 59 years
• 60 to 64 years
• 65 to 69 years
• 70 to 74 years
• 75 to 79 years
• 80 to 84 years
• 85 years and over

Variables / Data Columns

• Age Group: This column displays the age group in consideration
• Population: The population for the specific age group in the Arkansas City is shown in this column.
• % of Total Population: This column displays the population of each age group as a proportion of Arkansas City total population. Please note that the sum of all percentages may not equal one due to rounding of values.

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/.

Recommended for further research

This dataset is a part of the main dataset for Arkansas City Population by Age. You can refer the same here

This dataset contains a selection of six socioeconomic indicators of public health significance and a “hardship index,” by Chicago community area, for the years 2008 – 2012. The indicators are the percent of occupied housing units with more than one person per room (i.e., crowded housing); the percent of households living below the federal poverty level; the percent of persons in the labor force over the age of 16 years that are unemployed; the percent of persons over the age of 25 years without a high school diploma; the percent of the population under 18 or over 64 years of age (i.e., dependency); and per capita income. Indicators for Chicago as a whole are provided in the final row of the table. See the full dataset description for more information at: https://data.cityofchicago.org/api/views/fwb8-6aw5/files/A5KBlegGR2nWI1jgP6pjJl32CTPwPbkl9KU3FxlZk-A?download=true&filename=P:\EPI\OEPHI\MATERIALS\REFERENCES\ECONOMIC_INDICATORS\Dataset_Description_socioeconomic_indicators_2012_FOR_PORTAL_ONLY.pdf

mart city movements are growing all over the world. The un-dertaking is expected to solve a plethora of problems arising from urbanization. Indonesia is one of the countries who march toward the development of sustainable smart cities. However, before the government can start a smart city project, they need to assess the readiness of each target city. Data in this article illustrate the readiness of six major cities in Indonesia, which are Semarang, Makassar, Jakarta, Samarinda, Medan, and Surabaya. They repre-sent the four biggest islands in Indonesia. The readiness assess-ment was based on three main elements and six Smart City Pillars taken from Smart City Master Plan Preparation Guidance Book prepared by Ministry of Communication and Information Tech-nology of the Republic of Indonesia. Those elements serve as a checklist to determine the readiness of the cities. Data for quali-tative analysis were gathered through interviews and triangulated through secondary sources, such as publication from Statistics Indonesia and the assessment reports. The dataset contains in-formation on the readiness assessment is presented in this article. The indices of the six region's readiness assessment are presented in percentages.