Globally, about 25 percent of the population is under 15 years of age and 10 percent is over 65 years of age. Africa has the youngest population worldwide. In Sub-Saharan Africa, more than 40 percent of the population is below 15 years, and only three percent are above 65, indicating the low life expectancy in several of the countries. In Europe, on the other hand, a higher share of the population is above 65 years than the population under 15 years. Fertility rates The high share of children and youth in Africa is connected to the high fertility rates on the continent. For instance, South Sudan and Niger have the highest population growth rates globally. However, about 50 percent of the world’s population live in countries with low fertility, where women have less than 2.1 children. Some countries in Europe, like Latvia and Lithuania, have experienced a population decline of one percent, and in the Cook Islands, it is even above two percent. In Europe, the majority of the population was previously working-aged adults with few dependents, but this trend is expected to reverse soon, and it is predicted that by 2050, the older population will outnumber the young in many developed countries. Growing global population As of 2025, there are 8.1 billion people living on the planet, and this is expected to reach more than nine billion before 2040. Moreover, the global population is expected to reach 10 billions around 2060, before slowing and then even falling slightly by 2100. As the population growth rates indicate, a significant share of the population increase will happen in Africa.

About this dataset

Context

The dataset tabulates the data for the Live Oak, TX population pyramid, which represents the Live Oak 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 Live Oak, TX, is 28.9.
• Old-age dependency ratio, which is the number of persons aged 65 or over per 100 persons aged 15-64, for Live Oak, TX, is 19.1.
• Total dependency ratio for Live Oak, TX is 47.9.
• Potential support ratio, which is the number of youth (working age population) per elderly, for Live Oak, TX is 5.2.

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 Live Oak population analysis. Total expected values are 18 and are define above in the age groups section.
• Population (Male): The male population in the Live Oak for the selected age group is shown in the following column.
• Population (Female): The female population in the Live Oak for the selected age group is shown in the following column.
• Total Population: The total population of the Live Oak 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 Live Oak Population by Age. You can refer the same here

In 2022, India overtook China as the world's most populous country and now has almost 1.46 billion people. China now has the second-largest population in the world, still with just over 1.4 billion inhabitants, however, its population went into decline in 2023. Global population As of 2025, the world's population stands at almost 8.2 billion people and is expected to reach around 10.3 billion people in the 2080s, when it will then go into decline. Due to improved healthcare, sanitation, and general living conditions, the global population continues to increase; mortality rates (particularly among infants and children) are decreasing and the median age of the world population has steadily increased for decades. As for the average life expectancy in industrial and developing countries, the gap has narrowed significantly since the mid-20th century. Asia is the most populous continent on Earth; 11 of the 20 largest countries are located there. It leads the ranking of the global population by continent by far, reporting four times as many inhabitants as Africa. The Demographic Transition The population explosion over the past two centuries is part of a phenomenon known as the demographic transition. Simply put, this transition results from a drastic reduction in mortality, which then leads to a reduction in fertility, and increase in life expectancy; this interim period where death rates are low and birth rates are high is where this population explosion occurs, and population growth can remain high as the population ages. In today's most-developed countries, the transition generally began with industrialization in the 1800s, and growth has now stabilized as birth and mortality rates have re-balanced. Across less-developed countries, the stage of this transition varies; for example, China is at a later stage than India, which accounts for the change in which country is more populous - understanding the demographic transition can help understand the reason why China's population is now going into decline. The least-developed region is Sub-Saharan Africa, where fertility rates remain close to pre-industrial levels in some countries. As these countries transition, they will undergo significant rates of population growth

About this dataset

Context

The dataset tabulates the population of Live Oak by gender across 18 age groups. It lists the male and female population in each age group along with the gender ratio for Live Oak. The dataset can be utilized to understand the population distribution of Live Oak by gender and age. For example, using this dataset, we can identify the largest age group for both Men and Women in Live Oak. 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 Live Oak.

Key observations

Largest age group (population): Male # 0-4 years (465) | Female # 15-19 years (435). 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 Live Oak population analysis. Total expected values are 18 and are define above in the age groups section.
• Population (Male): The male population in the Live Oak is shown in the following column.
• Population (Female): The female population in the Live Oak 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 Live Oak 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 Live Oak Population by Gender. 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 July of 2025.

Analysis of ‘2021 World Population (updated daily)’ provided by Analyst-2 (analyst-2.ai), based on source dataset retrieved from https://www.kaggle.com/rsrishav/world-population on 28 January 2022.

--- Dataset description provided by original source is as follows ---

Context

2021 World Population dataset which gets updated daily.

Content

2021_population.csv: File contains data for only live 2021 population count which gets updated daily. Also contains more information about the country's growth rate, area, etc. timeseries_population_count.csv: File contains data for live population count which gets updated daily but it contains last updated data also. Data in this file is managed day-wise.

Inspiration

This type of data can be used for population-related use cases. Like, my own dataset COVID Vaccination in World (updated daily), which requires population data. I believe there are more use cases that I didn't explore yet but might other Kaggler needs this. Time-series related use-case can be implemented on this data but I know it will take time to compile that amount of data. So stay tuned.

--- Original source retains full ownership of the source dataset ---

The data included in this publication depict components of wildfire risk specifically for populated areas in the United States. These datasets represent where people live in the United States and the in situ risk from wildfire, i.e., the risk at the location where the adverse effects take place.National wildfire hazard datasets of annual burn probability and fire intensity, generated by the USDA Forest Service, Rocky Mountain Research Station and Pyrologix LLC, form the foundation of the Wildfire Risk to Communities data. Vegetation and wildland fuels data from LANDFIRE 2020 (version 2.2.0) were used as input to two different but related geospatial fire simulation systems. Annual burn probability was produced with the USFS geospatial fire simulator (FSim) at a relatively coarse cell size of 270 meters (m). To bring the burn probability raster data down to a finer resolution more useful for assessing hazard and risk to communities, we upsampled them to the native 30 m resolution of the LANDFIRE fuel and vegetation data. In this upsampling process, we also spread values of modeled burn probability into developed areas represented in LANDFIRE fuels data as non-burnable. Burn probability rasters represent landscape conditions as of the end of 2020. Fire intensity characteristics were modeled at 30 m resolution using a process that performs a comprehensive set of FlamMap runs spanning the full range of weather-related characteristics that occur during a fire season and then integrates those runs into a variety of results based on the likelihood of those weather types occurring. Before the fire intensity modeling, the LANDFIRE 2020 data were updated to reflect fuels disturbances occurring in 2021 and 2022. As such, the fire intensity datasets represent landscape conditions as of the end of 2022. The data products in this publication that represent where people live, reflect 2021 estimates of housing unit and population counts from the U.S. Census Bureau, combined with building footprint data from Onegeo and USA Structures, both reflecting 2022 conditions.The specific raster datasets included in this publication include:Building Count: Building Count is a 30-m raster representing the count of buildings in the building footprint dataset located within each 30-m pixel.Building Density: Building Density is a 30-m raster representing the density of buildings in the building footprint dataset (buildings per square kilometer [km²]).Building Coverage: Building Coverage is a 30-m raster depicting the percentage of habitable land area covered by building footprints.Population Count (PopCount): PopCount is a 30-m raster with pixel values representing residential population count (persons) in each pixel.Population Density (PopDen): PopDen is a 30-m raster of residential population density (people/km²).Housing Unit Count (HUCount): HUCount is a 30-m raster representing the number of housing units in each pixel.Housing Unit Density (HUDen): HUDen is a 30-m raster of housing-unit density (housing units/km²).Housing Unit Exposure (HUExposure): HUExposure is a 30-m raster that represents the expected number of housing units within a pixel potentially exposed to wildfire in a year. This is a long-term annual average and not intended to represent the actual number of housing units exposed in any specific year.Housing Unit Impact (HUImpact): HUImpact is a 30-m raster that represents the relative potential impact of fire to housing units at any pixel, if a fire were to occur. It is an index that incorporates the general consequences of fire on a home as a function of fire intensity and uses flame length probabilities from wildfire modeling to capture likely intensity of fire.Housing Unit Risk (HURisk): HURisk is a 30-m raster that integrates all four primary elements of wildfire risk - likelihood, intensity, susceptibility, and exposure - on pixels where housing unit density is greater than zero.

Estimated number of persons by quarter of a year and by year, Canada, provinces and territories.

The life-cycle age groups are:under 15 years15 to 29 years30 to 64 years65 years and over.Map shows the percentage change in the census usually resident population count for life-cycle age groups between the 2018 and 2023 Censuses.Download lookup file from Stats NZ ArcGIS Online or Stats NZ geographic data service.FootnotesGeographical boundariesStatistical standard for geographic areas 2023 (updated December 2023) has information about geographic boundaries as of 1 January 2023. Address data from 2013 and 2018 Censuses was updated to be consistent with the 2023 areas. Due to the changes in area boundaries and coding methodologies, 2013 and 2018 counts published in 2023 may be slightly different to those published in 2013 or 2018.Subnational census usually resident populationThe census usually resident population count of an area (subnational count) is a count of all people who usually live in that area and were present in New Zealand on census night. It excludes visitors from overseas, visitors from elsewhere in New Zealand, and residents temporarily overseas on census night. For example, a person who usually lives in Christchurch city and is visiting Wellington city on census night will be included in the census usually resident population count of Christchurch city. Caution using time seriesTime series data should be interpreted with care due to changes in census methodology and differences in response rates between censuses. The 2023 and 2018 Censuses used a combined census methodology (using census responses and administrative data), while the 2013 Census used a full-field enumeration methodology (with no use of administrative data).About the 2023 Census datasetFor information on the 2023 dataset see Using a combined census model for the 2023 Census. We combined data from the census forms with administrative data to create the 2023 Census dataset, which meets Stats NZ's quality criteria for population structure information. We added real data about real people to the dataset where we were confident the people who hadn’t completed a census form (which is known as admin enumeration) will be counted. We also used data from the 2018 and 2013 Censuses, administrative data sources, and statistical imputation methods to fill in some missing characteristics of people and dwellings. Data qualityThe quality of data in the 2023 Census is assessed using the quality rating scale and the quality assurance framework to determine whether data is fit for purpose and suitable for release. Data quality assurance in the 2023 Census has more information.Quality rating of a variableThe quality rating of a variable provides an overall evaluation of data quality for that variable, usually at the highest levels of classification. The quality ratings shown are for the 2023 Census unless stated. There is variability in the quality of data at smaller geographies. Data quality may also vary between censuses, for subpopulations, or when cross tabulated with other variables or at lower levels of the classification. Data quality ratings for 2023 Census variables has more information on quality ratings by variable. Age concept quality ratingAge is rated as very high quality. Age – 2023 Census: Information by concept has more information, for example, definitions and data quality.Using data for goodStats NZ expects that, when working with census data, it is done so with a positive purpose, as outlined in the Māori Data Governance Model (Data Iwi Leaders Group, 2023). This model states that "data should support transformative outcomes and should uplift and strengthen our relationships with each other and with our environments. The avoidance of harm is the minimum expectation for data use. Māori data should also contribute to iwi and hapū tino rangatiratanga".ConfidentialityThe 2023 Census confidentiality rules have been applied to 2013, 2018, and 2023 data. These rules protect the confidentiality of individuals, families, households, dwellings, and undertakings in 2023 Census data. Counts are calculated using fixed random rounding to base 3 (FRR3) and suppression of ‘sensitive’ counts less than six, where tables report multiple geographic variables and/or small populations. Individual figures may not always sum to stated totals. Applying confidentiality rules to 2023 Census data and summary of changes since 2018 and 2013 Censuses has more information about 2023 Census confidentiality rules.

In the middle of 2023, about 60 percent of the global population was living in Asia.The total world population amounted to 8.1 billion people on the planet. In other words 4.7 billion people were living in Asia as of 2023. Global populationDue to medical advances, better living conditions and the increase of agricultural productivity, the world population increased rapidly over the past century, and is expected to continue to grow. After reaching eight billion in 2023, the global population is estimated to pass 10 billion by 2060. Africa expected to drive population increase Most of the future population increase is expected to happen in Africa. The countries with the highest population growth rate in 2024 were mostly African countries. While around 1.47 billion people live on the continent as of 2024, this is forecast to grow to 3.9 billion by 2100. This is underlined by the fact that most of the countries wit the highest population growth rate are found in Africa. The growing population, in combination with climate change, puts increasing pressure on the world's resources.

Context

2021 World Population dataset which gets updated daily.

Content

2021_population.csv: File contains data for only live 2021 population count which gets updated daily. Also contains more information about the country's growth rate, area, etc. timeseries_population_count.csv: File contains data for live population count which gets updated daily but it contains last updated data also. Data in this file is managed day-wise.

Inspiration

This type of data can be used for population-related use cases. Like, my own dataset COVID Vaccination in World (updated daily), which requires population data. I believe there are more use cases that I didn't explore yet but might other Kaggler needs this. Time-series related use-case can be implemented on this data but I know it will take time to compile that amount of data. So stay tuned.

Historical chart and dataset showing total population for Japan by year from 1950 to 2025.

Population totals for groupings commonly used in other datasets. Not all values are available for all years. Note that because the "Citywide" rows roll up the values from the individual ZIP Codes and the "Age 0-4," "Age 5-11," "Age 12-17," "Age 5+," "Age 18+," and "Age 65+" columns overlap other age categories, as well as each other in some cases, care should be taken in summing values to avoid accidental double-counting. The "Age 5-11" and "Age 12-17" columns only include children who live in households. Data Sources: U.S. Census Bureau American Community Survey (ACS) 5-year estimates (ZIP Code) and 1-year estimates (Citywide). The U.S. Census Bureau did not release standard 1-year estimates from the 2020 ACS. In 2020 only, 5-year estimates were used for the Citywide estimates.

Total current population for Italy in 2025 is 58,518,843, a 0.3% decline from 2024.

<ul style='margin-top:20px;'>

<li>Total population for Italy in 2024 was <strong>58,697,744</strong>, a <strong>0.5% decline</strong> from 2023.</li>
<li>Total population for Italy in 2023 was <strong>58,993,475</strong>, a <strong>0.03% decline</strong> from 2022.</li>
<li>Total population for Italy in 2022 was <strong>59,013,667</strong>, a <strong>0.2% decline</strong> from 2021.</li>
</ul>Total population is based on the de facto definition of population, which counts all residents regardless of legal status or citizenship. The values shown are midyear estimates.

Thematic maps on the natural population movement and migration of the population in Rhineland-Palatinate at district, association and community level. It shows the number of live births and deaths per 1,000 inhabitants, the percentage change in the number of live births and deaths compared to previous years, the surplus of births and deaths and the net migration per 1,000 inhabitants. The data come from the statistics of births, deaths and migrations in relation to the average population in the respective reporting year. The update results are based on the 2011 census. :Natural population movements in 2023. Number of live births per 1,000 inhabitants, association level

As of February 2025, 5.56 billion individuals worldwide were internet users, which amounted to 67.9 percent of the global population. Of this total, 5.24 billion, or 63.9 percent of the world's population, were social media users. Global internet usage Connecting billions of people worldwide, the internet is a core pillar of the modern information society. Northern Europe ranked first among worldwide regions by the share of the population using the internet in 20254. In The Netherlands, Norway and Saudi Arabia, 99 percent of the population used the internet as of February 2025. North Korea was at the opposite end of the spectrum, with virtually no internet usage penetration among the general population, ranking last worldwide. Eastern Asia was home to the largest number of online users worldwide – over 1.34 billion at the latest count. Southern Asia ranked second, with around 1.2 billion internet users. China, India, and the United States rank ahead of other countries worldwide by the number of internet users. Worldwide internet user demographics As of 2024, the share of female internet users worldwide was 65 percent, five percent less than that of men. Gender disparity in internet usage was bigger in African countries, with around a ten percent difference. Worldwide regions, like the Commonwealth of Independent States and Europe, showed a smaller usage gap between these two genders. As of 2024, global internet usage was higher among individuals between 15 and 24 years old across all regions, with young people in Europe representing the most significant usage penetration, 98 percent. In comparison, the worldwide average for the age group 15–24 years was 79 percent. The income level of the countries was also an essential factor for internet access, as 93 percent of the population of the countries with high income reportedly used the internet, as opposed to only 27 percent of the low-income markets.

The average for 2023 based on 196 countries was 0.51 percent. The highest value was in India: 17.91 percent and the lowest value was in Andorra: 0 percent. The indicator is available from 1960 to 2023. Below is a chart for all countries where data are available.

Chart and table of population level and growth rate for the state of California from 1900 to 2024.

Live Births registered annually in Lincolnshire and Districts. The figures are shown as a Number and also as a Rate per 1000 women age 15-44 (inclusive), which is called the General Fertility Rate (GFR).

This ONS data is shown by the mother's area of usual residence, so in some cases a live birth might occur in an area but not be included in its figures. Low values below 5 are suppressed, so some figures may be missing (particularly for smaller geographies), and thus not tally to the numbers shown for larger areas.

This dataset is updated annually. Source: Office for National Statistics (ONS)

Total current population for China in 2025 is 1,424,381,924, a 0.06% decline from 2024.

<ul style='margin-top:20px;'>

<li>Total population for China in 2024 was <strong>1,425,178,782</strong>, a <strong>1.03% increase</strong> from 2023.</li>
<li>Total population for China in 2023 was <strong>1,410,710,000</strong>, a <strong>0.1% decline</strong> from 2022.</li>
<li>Total population for China in 2022 was <strong>1,412,175,000</strong>, a <strong>0.01% decline</strong> from 2021.</li>
</ul>Total population is based on the de facto definition of population, which counts all residents regardless of legal status or citizenship. The values shown are midyear estimates.