This dataset contains the population data for countries as of 1 July 2023, sourced from the United Nations via Wikipedia. Includes country names, population figures, percentage change, and continental regions. Ideal for demographic analysis, research, and visualization.

About this dataset

Context

The dataset tabulates the Portage population over the last 20 plus years. It lists the population for each year, along with the year on year change in population, as well as the change in percentage terms for each year. The dataset can be utilized to understand the population change of Portage across the last two decades. For example, using this dataset, we can identify if the population is declining or increasing. If there is a change, when the population peaked, or if it is still growing and has not reached its peak. We can also compare the trend with the overall trend of United States population over the same period of time.

Key observations

In 2023, the population of Portage was 38,513, a 0.45% increase year-by-year from 2022. Previously, in 2022, Portage population was 38,340, an increase of 0.22% compared to a population of 38,256 in 2021. Over the last 20 plus years, between 2000 and 2023, population of Portage increased by 4,946. In this period, the peak population was 38,513 in the year 2023. The numbers suggest that the population has not reached its peak yet and is showing a trend of further growth. Source: U.S. Census Bureau Population Estimates Program (PEP).

Content

When available, the data consists of estimates from the U.S. Census Bureau Population Estimates Program (PEP).

Data Coverage:

• From 2000 to 2023

Variables / Data Columns

• Year: This column displays the data year (Measured annually and for years 2000 to 2023)
• Population: The population for the specific year for the Portage is shown in this column.
• Year on Year Change: This column displays the change in Portage population for each year compared to the previous year.
• Change in Percent: This column displays the year on year change as a percentage. 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 Portage Population by Year. You can refer the same here

Population, female (% of total population) in World was reported at 49.71 % in 2023, according to the World Bank collection of development indicators, compiled from officially recognized sources. World - Population, female (% of total) - actual values, historical data, forecasts and projections were sourced from the World Bank on May of 2025.

World Population Data from the United Nations (UN), United Nations Department of Economic and Social Affairs Population Division World Population Prospects 2022

Notes
File (CSV, 6 KB) Location notes.

**Demographic Indicators ** Indicator reference (CSV, 4 KB) 1950-2100, medium (ZIP, 7.77 MB) 2022-2100, other scenarios (ZIP, 34.76 MB) Demographic Indicators:

Total Population, as of 1 January (thousands)
Total Population, as of 1 July (thousands)
Male Population, as of 1 July (thousands)
Female Population, as of 1 July (thousands)
Population Density, as of 1 July (persons per square km)
Population Sex Ratio, as of 1 July (males per 100 females)
Median Age, as of 1 July (years)
Natural Change, Births minus Deaths (thousands)
Rate of Natural Change (per 1,000 population)
Population Change (thousands)
Population Growth Rate (percentage)
Population Annual Doubling Time (years)
Births (thousands)
Births by women aged 15 to 19 (thousands)
Crude Birth Rate (births per 1,000 population)
Total Fertility Rate (live births per woman)
Net Reproduction Rate (surviving daughters per woman)
Mean Age Childbearing (years)
Sex Ratio at Birth (males per 100 female births)
Total Deaths (thousands)
Male Deaths (thousands)
Female Deaths (thousands)
Crude Death Rate (deaths per 1,000 population)
Life Expectancy at Birth, both sexes (years)
Male Life Expectancy at Birth (years)
Female Life Expectancy at Birth (years)
Life Expectancy at Age 15, both sexes (years)
Male Life Expectancy at Age 15 (years)
Female Life Expectancy at Age 15 (years)
Life Expectancy at Age 65, both sexes (years)
Male Life Expectancy at Age 65 (years)
Female Life Expectancy at Age 65 (years)
Life Expectancy at Age 80, both sexes (years)
Male Life Expectancy at Age 80 (years)
Female Life Expectancy at Age 80 (years)
Infant Deaths, under age 1 (thousands)
Infant Mortality Rate (infant deaths per 1,000 live births)
Live births Surviving to Age 1 (thousands)
Deaths under age 5 (thousands)
Under-five Mortality Rate (deaths under age 5 per 1,000 live births)
Mortality before Age 40, both sexes (deaths under age 40 per 1,000 live births)
Male mortality before Age 40 (deaths under age 40 per 1,000 male live births)
Female mortality before Age 40 (deaths under age 40 per 1,000 female live births)
Mortality before Age 60, both sexes (deaths under age 60 per 1,000 live births)
Male mortality before Age 60 (deaths under age 60 per 1,000 male live births)
Female mortality before Age 60 (deaths under age 60 per 1,000 female live births)
Mortality between Age 15 and 50, both sexes (deaths under age 50 per 1,000 alive at age 15)
Male mortality between Age 15 and 50 (deaths under age 50 per 1,000 males alive at age 15)
Female mortality between Age 15 and 50 (deaths under age 50 per 1,000 females alive at age 15)
Mortality between Age 15 and 60, both sexes (deaths under age 60 per 1,000 alive at age 15)
Male mortality between Age 15 and 60 (deaths under age 60 per 1,000 males alive at age 15)
Female mortality between Age 15 and 60 (deaths under age 60 per 1,000 females alive at age 15)
Net Number of Migrants (thousands)
Net Migration Rate (per 1,000 population)

Fertility
1950-2100, single age (ZIP, 78.01 MB) 1950-2100, 5-year age groups (ZIP, 22.38 MB)

Age-specific Fertility Rate (ASFR)
Percent Age-specific Fertility Rate (PASFR)
Births (thousands)

**Life Tables ** 1950-2021, medium (ZIP, 68.72 MB) 2022-2100, medium (ZIP, 74.62 MB) Abridged life tables up to age 100 by sex and both sexes combined providing a set of values showing the mortality experience of a hypothetical group of infants born at the same time and subject throughout their lifetime to the specific mortality rates of a given year, from 1950 to 2100. Only medium is available.

mx: Central death rate, nmx, for the age interval (x, x+n)
qx: Probability of dying (nqx), for an individual between age x and x+n
px: Probability of surviving, (npx), for an individual of age x to age x+n
lx: Number of survivors, (lx), at age (x) for 100000 births
dx: Number of deaths, (ndx), between ages x and x+n
Lx: Number of person-years lived, (nLx), between ages x and x+n
Sx: Survival ratio (nSx) corresponding to proportion of the life table population in age group (x, x+n) who are alive n year later
Tx: Person-years lived, (Tx), above age x
ex: Expectation of life (ex) at age x, i.e., average number of years lived subsequent to age x by those reaching age x
ax: Average number of years lived (nax) between ages x and x+n by those dying in the interval

Life Tables 1950-2021 (ZIP, 94.76 MB) 2022-2100 (ZIP, 101.66 MB) Single age life tables up to age 10...

Global Population of the World (GPW) translates census population data to a latitude-longitude grid so that population data may be used in cross-disciplinary studies. There are three data files with this data set for the reference years 1990 and 1995. Over 127,000 administrative units and population counts were collected and integrated from various sources to create the gridded data. In brief, GPW was created using the following steps: * Population data were estimated for the product reference years, 1990 and 1995, either by the data source or by interpolating or extrapolating the given estimates for other years. * Additional population estimates were created by adjusting the source population data to match UN national population estimates for the reference years. * Borders and coastlines of the spatial data were matched to the Digital Chart of the World where appropriate and lakes from the Digital Chart of the World were added. * The resulting data were then transformed into grids of UN-adjusted and unadjusted population counts for the reference years. * Grids containing the area of administrative boundary data in each cell (net of lakes) were created and used with the count grids to produce population densities.As with any global data set based on multiple data sources, the spatial and attribute precision of GPW is variable. The level of detail and accuracy, both in time and space, vary among the countries for which data were obtained.

The earliest point where scientists can make reasonable estimates for the population of global regions is around 10,000 years before the Common Era (or 12,000 years ago). Estimates suggest that Asia has consistently been the most populated continent, and the least populated continent has generally been Oceania (although it was more heavily populated than areas such as North America in very early years). Population growth was very slow, but an increase can be observed between most of the given time periods. There were, however, dips in population due to pandemics, the most notable of these being the impact of plague in Eurasia in the 14th century, and the impact of European contact with the indigenous populations of the Americas after 1492, where it took almost four centuries for the population of Latin America to return to its pre-1500 level. The world's population first reached one billion people in 1803, which also coincided with a spike in population growth, due to the onset of the demographic transition. This wave of growth first spread across the most industrially developed countries in the 19th century, and the correlation between demographic development and industrial or economic maturity continued until today, with Africa being the final major region to begin its transition in the late-1900s.

About this dataset

Context

The dataset tabulates the data for the Bicknell, IN population pyramid, which represents the Bicknell population distribution across age and gender, using estimates from the U.S. Census Bureau American Community Survey (ACS) 2019-2023 5-Year Estimates. It lists the male and female population for each age group, along with the total population for those age groups. Higher numbers at the bottom of the table suggest population growth, whereas higher numbers at the top indicate declining birth rates. Furthermore, the dataset can be utilized to understand the youth dependency ratio, old-age dependency ratio, total dependency ratio, and potential support ratio.

Key observations

• Youth dependency ratio, which is the number of children aged 0-14 per 100 persons aged 15-64, for Bicknell, IN, is 21.3.
• Old-age dependency ratio, which is the number of persons aged 65 or over per 100 persons aged 15-64, for Bicknell, IN, is 21.9.
• Total dependency ratio for Bicknell, IN is 43.2.
• Potential support ratio, which is the number of youth (working age population) per elderly, for Bicknell, IN is 4.6.

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

Variables / Data Columns

• Age Group: This column displays the age group for the Bicknell population analysis. Total expected values are 18 and are define above in the age groups section.
• Population (Male): The male population in the Bicknell for the selected age group is shown in the following column.
• Population (Female): The female population in the Bicknell for the selected age group is shown in the following column.
• Total Population: The total population of the Bicknell for the selected age group is shown in the following column.

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 Bicknell Population by Age. You can refer the same here

Key information about Spain population

• The Spain population reached 48.1 million people in Dec 2023, compared with the previously reported figure of 47.5 million people in Dec 2022
• The data reached an all-time high of 48.1 million people in Dec 2023 and a record low of 28.1 million people in Dec 1950

• In the latest reports, Spain Unemployment Rate dropped to 11.2 % in Sep 2024
• Monthly earnings of the Spain population was 2,545.5 USD in Sep 2024
• Spain Labour Force Participation Rate increased to 59.0 % in Sep 2024

FI: Population: Female: Ages 30-34: % of Female Population data was reported at 6.091 % in 2017. This records a decrease from the previous number of 6.155 % for 2016. FI: Population: Female: Ages 30-34: % of Female Population data is updated yearly, averaging 6.325 % from Dec 1960 (Median) to 2017, with 58 observations. The data reached an all-time high of 8.718 % in 1981 and a record low of 5.586 % in 2006. FI: Population: Female: Ages 30-34: % of Female Population data remains active status in CEIC and is reported by World Bank. The data is categorized under Global Database’s Finland – Table FI.World Bank: Population and Urbanization Statistics. Female population between the ages 30 to 34 as a percentage of the total female population.; ; World Bank staff estimates based on age/sex distributions of United Nations Population Division's World Population Prospects: 2017 Revision.; ;

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

Country Population (Admin0) using aggregated Facebook high resolution population density data (https://data.humdata.org/organization/facebook).The world population data sourced from Facebook Data for Good is some of the most accurate population density data in the world. The data is accumulated using highly accurate technology to identify buildings from satellite imagery and can be viewed at up to 30-meter resolution. This building data is combined with publicly available census data to create the most accurate population estimates. This data is used by a wide range of nonprofit and humanitarian organizations, for example, to examine trends in urbanization and climate migration or discover the impact of a natural disaster on a region. This can help to inform aid distribution to reach communities most in need. There is both country and region-specific data available. The data also includes demographic estimates in addition to the population density information. This population data can be accessed via the Humanitarian Data Exchange website.

Honduras: Percent of world population: The latest value from 2023 is 0.13 percent, unchanged from 0.13 percent in 2022. In comparison, the world average is 0.51 percent, based on data from 196 countries. Historically, the average for Honduras from 1960 to 2023 is 0.1 percent. The minimum value, 0.07 percent, was reached in 1960 while the maximum of 0.13 percent was recorded in 2014.

This dataset provides values for POPULATION reported in several countries. The data includes current values, previous releases, historical highs and record lows, release frequency, reported unit and currency.

United States US: Population: Male: Ages 50-54: % of Male Population data was reported at 6.741 % in 2017. This records a decrease from the previous number of 6.885 % for 2016. United States US: Population: Male: Ages 50-54: % of Male Population data is updated yearly, averaging 5.415 % from Dec 1960 (Median) to 2017, with 58 observations. The data reached an all-time high of 7.196 % in 2011 and a record low of 4.426 % in 1986. United States US: Population: Male: Ages 50-54: % of Male 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: Population and Urbanization Statistics. Male population between the ages 50 to 54 as a percentage of the total male population.; ; World Bank staff estimates based on age/sex distributions of United Nations Population Division's World Population Prospects: 2017 Revision.; ;

Vanuatu: Percent of world population: The latest value from 2023 is 0 percent, unchanged from 0 percent in 2022. In comparison, the world average is 0.51 percent, based on data from 196 countries. Historically, the average for Vanuatu from 1960 to 2023 is 0 percent. The minimum value, 0 percent, was reached in 1960 while the maximum of 0 percent was recorded in 1960.

AU: Population: Male: Ages 5-9: % of Male Population data was reported at 6.262 % in 2023. This records a decrease from the previous number of 6.385 % for 2022. AU: Population: Male: Ages 5-9: % of Male Population data is updated yearly, averaging 7.550 % from Dec 1960 (Median) to 2023, with 64 observations. The data reached an all-time high of 10.297 % in 1967 and a record low of 6.262 % in 2023. AU: Population: Male: Ages 5-9: % of Male Population data remains active status in CEIC and is reported by World Bank. The data is categorized under Global Database’s Australia – Table AU.World Bank.WDI: Population and Urbanization Statistics. Male population between the ages 5 to 9 as a percentage of the total male population.;United Nations Population Division. World Population Prospects: 2024 Revision.;;

As a source of animal and plant population data, The Global Population Dynamics Database is unrivalled. Nearly five thousand separate time series are available here. In addition to all the population counts, there are taxonomic details of over 1400 species. The type of data contained in the GPDD varies enormously, from annual counts of mammals or birds at individual sampling sites, to weekly counts of zooplankton and other marine fauna. The project commenced in October 1994, following discussions on ways in which the collaborating partners could make a practical and enduring contribution to research into population dynamics. A small team was assembled and, with assistance and advice from numerous interested parties we decided to construct the database using the popular Microsoft Access platform. After an initial design phase, the major task has been that of locating, extracting, entering and validating the data in all the various tables. Now, nearly 5000 individual datasets have been entered onto the GPDD. The Global Population Dynamics Database comprises six Tables of data and information. The tables are linked to each other as shown in the diagram shown at http://cpbnts1.bio.ic.ac.uk/gpdd/Structur.htm. Referential integrity is maintained through record ID numbers which are held, along with other information in the Main Table. It's structure obeys all the rules of a standard relational database.

The annual population growth in Algeria declined to 1.5 percent in 2023. As a result, the population growth in Algeria saw its lowest number in 2023 with 1.5 percent. Population growth refers to the annual change in population, and is based on the balance between birth and death rates, as well as migration.Find more key insights for the annual population growth in countries like Sudan and Tunisia.

Graph and download economic data for Resident Population in Chicago-Naperville-Elgin, IL-IN-WI (MSA) (CHIPOP) from 2000 to 2022 about Chicago, IL, IN, WI, residents, population, and USA.

Related article: Bergroth, C., Järv, O., Tenkanen, H., Manninen, M., Toivonen, T., 2022. A 24-hour population distribution dataset based on mobile phone data from Helsinki Metropolitan Area, Finland. Scientific Data 9, 39.

In this dataset:

We present temporally dynamic population distribution data from the Helsinki Metropolitan Area, Finland, at the level of 250 m by 250 m statistical grid cells. Three hourly population distribution datasets are provided for regular workdays (Mon – Thu), Saturdays and Sundays. The data are based on aggregated mobile phone data collected by the biggest mobile network operator in Finland. Mobile phone data are assigned to statistical grid cells using an advanced dasymetric interpolation method based on ancillary data about land cover, buildings and a time use survey. The data were validated by comparing population register data from Statistics Finland for night-time hours and a daytime workplace registry. The resulting 24-hour population data can be used to reveal the temporal dynamics of the city and examine population variations relevant to for instance spatial accessibility analyses, crisis management and planning.

Please cite this dataset as:

Bergroth, C., Järv, O., Tenkanen, H., Manninen, M., Toivonen, T., 2022. A 24-hour population distribution dataset based on mobile phone data from Helsinki Metropolitan Area, Finland. Scientific Data 9, 39. https://doi.org/10.1038/s41597-021-01113-4

Organization of data

The dataset is packaged into a single Zipfile Helsinki_dynpop_matrix.zip which contains following files:

HMA_Dynamic_population_24H_workdays.csv represents the dynamic population for average workday in the study area.

HMA_Dynamic_population_24H_sat.csv represents the dynamic population for average saturday in the study area.

HMA_Dynamic_population_24H_sun.csv represents the dynamic population for average sunday in the study area.

target_zones_grid250m_EPSG3067.geojson represents the statistical grid in ETRS89/ETRS-TM35FIN projection that can be used to visualize the data on a map using e.g. QGIS.

Column names

YKR_ID : a unique identifier for each statistical grid cell (n=13,231). The identifier is compatible with the statistical YKR grid cell data by Statistics Finland and Finnish Environment Institute.

H0, H1 ... H23 : Each field represents the proportional distribution of the total population in the study area between grid cells during a one-hour period. In total, 24 fields are formatted as “Hx”, where x stands for the hour of the day (values ranging from 0-23). For example, H0 stands for the first hour of the day: 00:00 - 00:59. The sum of all cell values for each field equals to 100 (i.e. 100% of total population for each one-hour period)

In order to visualize the data on a map, the result tables can be joined with the target_zones_grid250m_EPSG3067.geojson data. The data can be joined by using the field YKR_ID as a common key between the datasets.

License Creative Commons Attribution 4.0 International.

Related datasets

Järv, Olle; Tenkanen, Henrikki & Toivonen, Tuuli. (2017). Multi-temporal function-based dasymetric interpolation tool for mobile phone data. Zenodo. https://doi.org/10.5281/zenodo.252612

Tenkanen, Henrikki, & Toivonen, Tuuli. (2019). Helsinki Region Travel Time Matrix [Data set]. Zenodo. http://doi.org/10.5281/zenodo.3247564