Attribution 4.0 (CC BY 4.0)https://creativecommons.org/licenses/by/4.0/
License information was derived automatically
Rural population in World was reported at 3445666944 in 2023, according to the World Bank collection of development indicators, compiled from officially recognized sources. World - Rural population - actual values, historical data, forecasts and projections were sourced from the World Bank on June of 2025.
https://fred.stlouisfed.org/legal/#copyright-public-domainhttps://fred.stlouisfed.org/legal/#copyright-public-domain
Graph and download economic data for Population, Total for Spain (POPTOTESA647NWDB) from 1960 to 2024 about Spain and population.
Attribution-ShareAlike 3.0 (CC BY-SA 3.0)https://creativecommons.org/licenses/by-sa/3.0/
License information was derived automatically
World Development Indicators (WDI) by World Bank includes data spanning up to 56 years—from 1960 to 2016. WDI frames global trends with indicators on population, population density, urbanization, GNI, and GDP. These indicators measure the world’s economy and progress toward improving lives, achieving sustainable development, providing support for vulnerable populations, and reducing gender disparities.
World Development Indicators Data is the primary World Bank collection of development indicators, compiled from officially-recognized international sources. It presents the most current and accurate global development data available, and includes national, regional and global estimates.
“World Development Indicators” by the World Bank, used under CC BY 3.0 IGO.
Data Origin: https://bigquery.cloud.google.com/dataset/patents-public-data:worldbank_wdi
Banner photo by Joshua Rawson-Harris on Unsplash
https://creativecommons.org/publicdomain/zero/1.0/https://creativecommons.org/publicdomain/zero/1.0/
The World Bank is an international financial institution that provides loans to countries of the world for capital projects. The World Bank's stated goal is the reduction of poverty. Source: https://en.wikipedia.org/wiki/World_Bank
This dataset combines key health statistics from a variety of sources to provide a look at global health and population trends. It includes information on nutrition, reproductive health, education, immunization, and diseases from over 200 countries.
Update Frequency: Biannual
For more information, see the World Bank website.
Fork this kernel to get started with this dataset.
https://datacatalog.worldbank.org/dataset/health-nutrition-and-population-statistics
https://cloud.google.com/bigquery/public-data/world-bank-hnp
Dataset Source: World Bank. This dataset is publicly available for anyone to use under the following terms provided by the Dataset Source - http://www.data.gov/privacy-policy#data_policy - and is provided "AS IS" without any warranty, express or implied, from Google. Google disclaims all liability for any damages, direct or indirect, resulting from the use of the dataset.
Citation: The World Bank: Health Nutrition and Population Statistics
Banner Photo by @till_indeman from Unplash.
What’s the average age of first marriages for females around the world?
Population of countries (1960 to 2023) dataset from World Bank.
Attribution 4.0 (CC BY 4.0)https://creativecommons.org/licenses/by/4.0/
License information was derived automatically
Employment to population ratio, 15+, total (%) (modeled ILO estimate) in United States was reported at 59.4 % in 2024, according to the World Bank collection of development indicators, compiled from officially recognized sources. United States - Employment to population ratio, 15+, total - actual values, historical data, forecasts and projections were sourced from the World Bank on July of 2025.
Attribution 4.0 (CC BY 4.0)https://creativecommons.org/licenses/by/4.0/
License information was derived automatically
Population, total in Bangladesh was reported at 171466990 in 2023, according to the World Bank collection of development indicators, compiled from officially recognized sources. Bangladesh - Population, total - actual values, historical data, forecasts and projections were sourced from the World Bank on July of 2025.
Explore gender statistics data focusing on academic staff, employment, fertility rates, GDP, poverty, and more in the GCC region. Access comprehensive information on key indicators for Bahrain, China, India, Kuwait, Oman, Qatar, and Saudi Arabia.
academic staff, Access to anti-retroviral drugs, Adjusted net enrollment rate, Administration and Law programmes, Age at first marriage, Age dependency ratio, Cause of death, Children out of school, Completeness of birth registration, consumer prices, Cost of business start-up procedures, Employers, Employment in agriculture, Employment in industry, Employment in services, employment or training, Engineering and Mathematics programmes, Female headed households, Female migrants, Fertility planning status: mistimed pregnancy, Fertility planning status: planned pregnancy, Fertility rate, Firms with female participation in ownership, Fisheries and Veterinary programmes, Forestry, GDP, GDP growth, GDP per capita, gender parity index, Gini index, GNI, GNI per capita, Government expenditure on education, Government expenditure per student, Gross graduation ratio, Households with water on the premises, Inflation, Informal employment, Labor force, Labor force with advanced education, Labor force with basic education, Labor force with intermediate education, Learning poverty, Length of paid maternity leave, Life expectancy at birth, Mandatory retirement age, Manufacturing and Construction programmes, Mathematics and Statistics programmes, Number of under-five deaths, Part time employment, Population, Poverty headcount ratio at national poverty lines, PPP, Primary completion rate, Retirement age with full benefits, Retirement age with partial benefits, Rural population, Sex ratio at birth, Unemployment, Unemployment with advanced education, Urban population
Bahrain, China, India, Kuwait, Oman, Qatar, Saudi Arabia
Follow data.kapsarc.org for timely data to advance energy economics research.
Attribution 4.0 (CC BY 4.0)https://creativecommons.org/licenses/by/4.0/
License information was derived automatically
Employment to population ratio, 15+, female (%) (modeled ILO estimate) in World was reported at 46.59 % in 2024, according to the World Bank collection of development indicators, compiled from officially recognized sources. World - Employment to population ratio, 15+, female - actual values, historical data, forecasts and projections were sourced from the World Bank on June of 2025.
https://fred.stlouisfed.org/legal/#copyright-public-domainhttps://fred.stlouisfed.org/legal/#copyright-public-domain
Graph and download economic data for Population, Total for the United Arab Emirates (POPTOTAEA647NWDB) from 1960 to 2024 about United Arab Emirates and population.
https://fred.stlouisfed.org/legal/#copyright-public-domainhttps://fred.stlouisfed.org/legal/#copyright-public-domain
Graph and download economic data for Population Ages 15 to 64 for China (SPPOP1564TOZSCHN) from 1960 to 2023 about 15 to 64 years, China, and population.
Attribution 4.0 (CC BY 4.0)https://creativecommons.org/licenses/by/4.0/
License information was derived automatically
Population, total in Austria was reported at 9131761 in 2023, according to the World Bank collection of development indicators, compiled from officially recognized sources. Austria - Population, total - actual values, historical data, forecasts and projections were sourced from the World Bank on July of 2025.
The household registration system known as ho khau has been a part of the fabric of life in Vietnam for over 50 years. The system was used as an instrument of public security, economic planning, and control of migration, at a time when the state played a stronger role in direct management of the economy and the life of its citizens. Although the system has become less rigid over time, concerns persist that ho khau limits the rights and access to public services of those who lack permanent registration in their place of residence. Due largely to data constraints, however, previous discussions about the system have relied largely on anecdotal or partial information.
Drawing from historical roots as well as the similar model of China’s hukou, the ho khau system was established in Vietnam in 1964. The 1964 law established the basic parameters of the system: every citizen was to be registered as a resident in one and only household at the place of permanent residence, and movements could take place only with the permission of authorities. Controlling migration to cities was part of the system’s early motivation, and the system’s ties to rationing, public services, and employment made it an effective check on unsanctioned migration. Transfer of one’s ho khau from one place to another was possible in principle but challenging in practice.
The force of the system has diminished since the launch of Doi Moi as well as a series of reforms starting in 2006. Most critically, it is no longer necessary to obtain permission from the local authorities in the place of departure to register in a new location. Additionally, obtaining temporary registration status in a new location is no longer difficult. However, in recent years the direction of policy changes regarding ho khau has been varied. A 2013 law explicitly recognized the authority of local authorities to set their own policies regarding registration, and some cities have tightened the requirements for obtaining permanent status.
Understanding of the system has been hampered by the fact that those without permanent registration have not appeared in most conventional sources of socioeconomic data. To gather data for this project, a survey of 5000 respondents in five provinces was done in June-July 2015. The samples are representative of the population in 5 provinces – Ho Chi Minh City, Ha Noi, Da Nang, Binh Duong and Dak Nong. Those five provinces/cities are among the provinces with the highest rate of migration as estimated using data from Population Census 2009.
5 provinces – Ho Chi Minh City, Ha Noi, Da Nang, Binh Duong and Dak Nong.
Household
Sample survey data [ssd]
Sampling for the Household Registration Survey was conducted in two stages. The two stages were selection of 250 enumeration areas (50 EAs in each of 5 provinces) and then selection of 20 households in each selected EA, resulting in a total sample size of 5000 households. The EAs were selected using Probability Proportional to Size (PPS) method based on the square number of migrants in each EA, with the aim to increase the probability of being selected for EAs with higher number of migrants. “Migrants” were defined using the census data as those who lived in a different province five years previous to the census. The 2009 Population Census data was used as the sample frame for the selection of EAs. To make sure the sampling frame was accurate and up to date, EA leaders of the sampled EAs were asked to collection information of all households regardless of registration status at their ward a month before the actual fieldwork. Information collected include name of head of household, address, gender, age of household’s head, household phone number, residence registration status of household, and place of their registration 5 years ago. All households on the resulting lists were found to have either temporary or permanent registration in their current place of residence.
Using these lists, selection of survey households was stratified at the EA level to ensure a substantial surveyed population of households without permanent registration. In each EA random selection was conducted of 12 households with temporary registration status and 8 households with permanent registration status. For EAs where the number of temporary registration households was less than 12, all of the temporary registration households were selected and additional permanent registration households were selected to ensure that each EA had 20 survey households. Sampling weights were calculated taking into the account the selection rules for the first and second stages of the survey.
Computer Assisted Personal Interview [capi]
The questionnaire was mostly adapted from the Vietnam Household Living Standard Survey (VHLSS), and the Urban Poverty Survey (UPS) with appropriate adjustment and supplement of a number of questions to follow closely the objectives of this survey. The household questionnaire consists of a set of questions on the following contents:
• Demographic characteristics of household members with emphasis on their residence status in terms of both administrative management (permanent/temporary residence book) and real residential situation. • Education of household members. Beside information on education level, the respondents are asked whether a household member attend school as “trai-tuyen” , how much “trai-tuyen” fee/enrolment fee, and difficulty in attending schools without permanent residence status. • Health and health care, collecting information on medical status and health insurance card of household members. • Labour and employment, asking household member’s employment status in the last 30 days; their most and second-most time-consuming employment during the last 30 days; and whether they had been asked about residence status when looking for job. • Assets and housing conditions. This section collects information on household’s living conditions such as assets, housing types and areas, electricity, water and energy. • Income and expenditure of households. • Social inclusion and protection. The respondents are asked whether their household members participate in social organizations, activities, services, contribution; whether they benefit from any social project/policy; do they have any loans within the last 12 months; and to provide information about five of their friends at their residential area. • Knowledge on the Law of Residence, current regulations on conditions for obtaining permanent residence, experience dealing with residence issues, and opinion on current household registration system of the respondents.
Managing and Cleaning the Data
Data were managed and cleaned each day immediately upon being received, which occurred at the same time as the fieldwork surveys. At the end of each workday, the survey teams were required to review all of the interviews conducted and transfer collected data to the server. The data received by the main server were downloaded and monitored by MDRI staff.
At this stage, MDRI assigned a technical team to work on the data. First, the team listened to interview records and used an application to detect enumerators’ errors. In this way, MDRI quickly identified and corrected the mistakes of the interviewers. Then the technical team proceeded with data cleaning by questionnaire, based on the following quantity and quality checking criteria.
• Quantity checking criteria: The number of questionnaires must be matched with the completed interviews and the questionnaires assigned to each individual in the field. According to the plan, each survey team conducted 20 household questionnaires in each village. All questionnaires were checked to ensure that they contained all essential information, and duplicated entries were eliminated. • Quality checking criteria: Our staff performed a thorough examination of the practicality and logic of the data. If there was any suspicious or inconsistent information, the data management team re – listened to the records or contacted the respondents and survey teams for clarification via phone call. Necessary revisions would then be made.
Data cleaning was implemented by the following stages: 1. Identification of illogical values; 2. Software – based detection of errors for clarification and revision; 3. Information re-checking with respondents and/or enumerators via phone or through looking at the records; 4. Development and implementation of errors correction algorithms; The list of detected and adjusted errors is attached in Annex 6.
Outlier detection methods The data team applied a popular non - parametric method for outlier detection, which can be done with the following procedure: 1. Identify the first quartile Q1 (the 25th percentile data point) 2. Identify the third quartile Q3 (the 75th percentile data point) 3. Identify the inter-quartile range(IQR): IQR=Q3-Q1 4. Calculate lower limits (L) and upper limits (U) by the following formulas: o L=Q1-1.5*IQR o U=Q3+1.5*IQR 5. Detect outliers by the rule: An observation is an outlier if it lies below the lower bound or beyond the upper bound (i.e. less than L or greater than U)
Data Structure The completed dataset for the “Household registration survey 2015” includes 9 files in STATA format (.dta): • hrs_maindata: Information on the households, including: assets, housing, income, expenditures, social inclusion and social protection issues, household registration procedures • hrs_muc1: Basic information on the
Attribution 4.0 (CC BY 4.0)https://creativecommons.org/licenses/by/4.0/
License information was derived automatically
Population, total in Sri Lanka was reported at 22037000 in 2023, according to the World Bank collection of development indicators, compiled from officially recognized sources. Sri Lanka - Population, total - actual values, historical data, forecasts and projections were sourced from the World Bank on July of 2025.
The World Bank Enterprise Survey (WBES) is a firm-level survey of a representative sample of an economy's private sector. The surveys cover a broad range of topics related to the business environment including access to finance, corruption, infrastructure, competition, and performance.
National coverage
The primary sampling unit of the study is the establishment. An establishment is a physical location where business is carried out and where industrial operations take place or services are provided. A firm may be composed of one or more establishments. For example, a brewery may have several bottling plants and several establishments for distribution. For the purposes of this survey an establishment must make its own financial decisions and have its own financial statements separate from those of the firm. An establishment must also have its own management and control over its payroll.
The universe of inference includes all formal (i.e., registered) private sector businesses (with at least 1% private ownership) and with at least five employees. In terms of sectoral criteria, all manufacturing businesses (ISIC Rev 4. codes 10-33) are eligible; for services businesses, those corresponding to the ISIC Rev 4 codes 41-43, 45-47, 49-53, 55-56, 58, 61-62, 69-75, 79, and 95 are included in the Enterprise Surveys. Cooperatives and collectives are excluded from the Enterprise Surveys. All eligible establishments must be registered with the registration agency. In the case of Viet Nam, the listing from the General Statistics Office of Vietnam, the 2021 Economic Census, was used. The registration agency is the Department of Planning and investment.
Sample survey data [ssd]
The WBES use stratified random sampling, where the population of establishments is first separated into non-overlapping groups, called strata, and then respondents are selected through simple random sampling from each stratum. The detailed methodology is provided in the Sampling Note (https://www.enterprisesurveys.org/content/dam/enterprisesurveys/documents/methodology/Sampling_Note-Consolidated-2-16-22.pdf). Stratified random sampling has several advantages over simple random sampling. In particular, it:
The WBES typically use three levels of stratification: industry classification, establishment size, and subnational region (used in combination). Starting in 2022, the WBES bases the industry classification on ISIC Rev. 4 (with earlier surveys using ISIC Rev. 3.1). For regional coverage within a country, the WBES has national coverage.
Note: Refer to Sampling Structure section in "The Viet Nam 2023 World Bank Enterprise Survey Implementation Report" for detailed methodology on sampling.
Face-to-face [f2f]
The standard WBES questionnaire covers several topics regarding the business environment and business performance. These topics include general firm characteristics, infrastructure, sales and supplies, management practices, competition, innovation, capacity, land and permits, finance, business-government relations, exposure to bribery, labor, and performance. Information about the general structure of the questionnaire is available in the Enterprise Surveys Manual and Guide (https://www.enterprisesurveys.org/content/dam/enterprisesurveys/documents/methodology/Enterprise-Surveys-Manual-and-Guide.pdf).
The questionnaire implemented in the Viet Nam 2023 WBES included additional questions tailored for the Business Ready Report covering infrastructure, trade, government regulations, finance, labor, and other topics.
Overall survey response rate was 31.7%.
Attribution 4.0 (CC BY 4.0)https://creativecommons.org/licenses/by/4.0/
License information was derived automatically
Population, total in Azerbaijan was reported at 10153958 in 2023, according to the World Bank collection of development indicators, compiled from officially recognized sources. Azerbaijan - Population, total - actual values, historical data, forecasts and projections were sourced from the World Bank on July of 2025.
Attribution 4.0 (CC BY 4.0)https://creativecommons.org/licenses/by/4.0/
License information was derived automatically
Individuals using the Internet (% of population) in Turkey was reported at 87.3 % in 2024, according to the World Bank collection of development indicators, compiled from officially recognized sources. Turkey - Individuals using the Internet (% of population) - actual values, historical data, forecasts and projections were sourced from the World Bank on June of 2025.
Attribution 4.0 (CC BY 4.0)https://creativecommons.org/licenses/by/4.0/
License information was derived automatically
Access to electricity (% of population) in Swaziland was reported at 86.4 % in 2023, according to the World Bank collection of development indicators, compiled from officially recognized sources. Swaziland - Access to electricity (% of population) - actual values, historical data, forecasts and projections were sourced from the World Bank on July of 2025.
Attribution 4.0 (CC BY 4.0)https://creativecommons.org/licenses/by/4.0/
License information was derived automatically
Employment to population ratio, ages 15-24, male (%) (national estimate) in Mali was reported at 56.44 % in 2022, according to the World Bank collection of development indicators, compiled from officially recognized sources. Mali - Employment to population ratio, ages 15-24, male (national estimate) - actual values, historical data, forecasts and projections were sourced from the World Bank on July of 2025.
Attribution 4.0 (CC BY 4.0)https://creativecommons.org/licenses/by/4.0/
License information was derived automatically
Population growth (annual %) in World was reported at 0.89981 % in 2023, according to the World Bank collection of development indicators, compiled from officially recognized sources. World - Population growth (annual %) - actual values, historical data, forecasts and projections were sourced from the World Bank on July of 2025.
Attribution 4.0 (CC BY 4.0)https://creativecommons.org/licenses/by/4.0/
License information was derived automatically
Rural population in World was reported at 3445666944 in 2023, according to the World Bank collection of development indicators, compiled from officially recognized sources. World - Rural population - actual values, historical data, forecasts and projections were sourced from the World Bank on June of 2025.