In 2024, approximately 127.8 million people lived in Guangdong province in China. That same year, only about 3.7 million people lived in the sparsely populated highlands of Tibet. Regional differences in China China is the world’s most populous country, with an exceptional economic growth momentum. The country can be roughly divided into three regions: Western, Eastern, and Central China. Western China covers the most remote regions from the sea. It also has the highest proportion of minority population and the lowest levels of economic output. Eastern China, on the other hand, enjoys a high level of economic development and international corporations. Central China lags behind in comparison to the booming coastal regions. In order to accelerate the economic development of Western and Central Chinese regions, the PRC government has ramped up several incentive plans such as ‘Rise of Central China’ and ‘China Western Development’. Economic power of different provinces When observed individually, some provinces could stand an international comparison. Jiangxi province, for example, a medium-sized Chinese province, had a population size comparable to Argentina or Spain in 2024. That year, the GDP of Zhejiang, an eastern coastal province, even exceeded the economic output of the Netherlands. In terms of per capita annual income, the municipality of Shanghai reached a level close to that of the Czech Republik. Nevertheless, as shown by the Gini Index, China’s economic spur leaves millions of people in dust. Among the various kinds of economic inequality in China, regional or the so-called coast-inland disparity is one of the most significant. Posing as evidence for the rather large income gap in China, the poorest province Heilongjiang had a per capita income similar to that of Sri Lanka that year.

China is a vast and diverse country and population density in different regions varies greatly. In 2024, the estimated population density of the administrative area of Shanghai municipality reached about 3,911 inhabitants per square kilometer, whereas statistically only around three people were living on one square kilometer in Tibet. Population distribution in China China's population is unevenly distributed across the country: while most people are living in the southeastern half of the country, the northwestern half – which includes the provinces and autonomous regions of Tibet, Xinjiang, Qinghai, Gansu, and Inner Mongolia – is only sparsely populated. Even the inhabitants of a single province might be unequally distributed within its borders. This is significantly influenced by the geography of each region, and is especially the case in the Guangdong, Fujian, or Sichuan provinces due to their mountain ranges. The Chinese provinces with the largest absolute population size are Guangdong in the south, Shandong in the east and Henan in Central China. Urbanization and city population Urbanization is one of the main factors which have been reshaping China over the last four decades. However, when comparing the size of cities and urban population density, one has to bear in mind that data often refers to the administrative area of cities or urban units, which might be much larger than the contiguous built-up area of that city. The administrative area of Beijing municipality, for example, includes large rural districts, where only around 200 inhabitants are living per square kilometer on average, while roughly 20,000 residents per square kilometer are living in the two central city districts. This is the main reason for the huge difference in population density between the four Chinese municipalities Beijing, Tianjin, Shanghai, and Chongqing shown in many population statistics.

In 2023, the ratio of urban to rural population varied greatly in different provinces of China. While Guangdong province had an urban population of around 95.8 million and a rural population of 31.2 million, Tibet had an urban population of only 1.4 million, but a rural population of around 2.2 million.

Content

The current population of China is 1,448,978,293 as of Wednesday, March 30, 2022, based on Worldometer elaboration of the latest United Nations data. This three datasets contain population data of China (2020 and historical), population forecast and population in major cities.

Attribute Information

• Year - Years from 2020-1955
• Population - Population in the respective year
• Yearly % Change - Percentage Yearly Change in Population
• Yearly Change - Yearly Change in Population
• Migrants (net) - Total number of migrants
• Median Age - Median age of the population
• Fertility Rate - Fertility rate
• Density (P/Km²)- Population density (population per square km)
• Urban Pop %- Percentage of urban population
• Urban Population- Urban population
• Country's Share of World Pop - Population share
• World Population - World Population in the respective year
• China Global Rank - Global Rank in Population

Source

Link : https://www.worldometers.info/world-population/china-population/

Updated Covid 19 and Other Datasets

Link : https://www.kaggle.com/anandhuh/datasets

If you find it useful, please support by upvoting ❤️

Thank You

This statistic shows the population density in urban areas of China in 2023, by region. In 2023, cities in Heilongjiang province had the highest population density in China with around ***** people living on one square kilometer on average. However, as the administrative areas of many Chinese cities reach beyond their contiguous built-up urban areas - and this by varying degree, the statistical significance of the given figures may be limited. By comparison, the Chinese province with the highest overall population density is Jiangsu province in Eastern China reaching about 7956 people per square kilometer in 2023.

Motivation

The data has been collected for COVID-19 analysis. You can use the data for getting the population of each province.

Data has been collected from: http://population.city/ manually.

About this dataset

Context

This list ranks the 19,348 cities in the United States by Chinese population, as estimated by the United States Census Bureau. It also highlights population changes in each city over the past five years.

Content

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

• 2019-2023 American Community Survey 5-Year Estimates
• 2014-2018 American Community Survey 5-Year Estimates
• 2009-2013 American Community Survey 5-Year Estimates

Variables / Data Columns

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

Good to know

Margin of Error

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

Custom data

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

Inspiration

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

About this dataset

Context

This list ranks the 50 states in the United States by Chinese population, as estimated by the United States Census Bureau. It also highlights population changes in each state over the past five years.

Content

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

• 2019-2023 American Community Survey 5-Year Estimates
• 2014-2018 American Community Survey 5-Year Estimates
• 2009-2013 American Community Survey 5-Year Estimates

Variables / Data Columns

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

Good to know

Margin of Error

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

Custom data

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

Inspiration

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

Context

The outbreak of COVID19 pushed Kaggle to launch several competitions to better understand how the new virus spreads.

The data provided by this competition is not only divided by nation (China, US, Canada...), but also sometimes by province/state/dependency/territory (California, Hubei, French Guiana, Saskatchewan...).

Although there are already several Kaggle datasets that provide population estimates by nation, I couldn't find any that provided a population estimate for each one of the constituent states ("provinces/states") included in the data for the 2nd week COVID19 Global Forecasting competition. So here they are, packaged in a super simple two-column CSV file.

Content

Each row in this dataset is a rough estimate of the population in each of the constituent states that appear in the COVID19 Global Forecasting competition. Each row is, of course, one of these inner states. By "constituent state" I mean one of: - the 54 United States of America - the 33 Chinese provinces - 10 Canadian provinces (plus a territory, Northwest Territories) - 11 French overseas territories - 10 British overseas territories - 6 Australian states (plus 2 internal territories) - 5 constituent countries of the Kingdom of the Netherlands - 2 autonomous Danish territories (Faroe Islands and Greenland)

In total, 134 states are listed.

Acknowledgements

The population estimates were collected from the following sources: - Australia: Wikipedia - Canada: worldpopulationreview.com - China: another Kaggle dataset - Denmark: worldpopulationreview.com - France: worldometers.info (retrieved 2020-04-02, 18:00 UTC) - Netherlands: worldometers.info (retrieved 2020-04-02, 18:00 UTC) - US: worldpopulationreview.com - Guam: worldpopulationreview.com - UK: worldometers.info (retrieved 2020-04-02, 18:00 UTC)

In 2023, the natural growth rate of the population across China varied between 7.96 people per 1,000 inhabitants (per mille) in Tibet and -6.92 per mille in Heilongjiang province. The national total population growth rate turned negative in 2022 and ranged at -1.48 per mille in 2023. Regional disparities in population growth The natural growth rate is the difference between the birth rate and the death rate of a certain region. In China, natural population growth reached the highest values in the western regions of the country. These areas have a younger population and higher fertility rates. Although the natural growth rate does not include the direct effects of migration, migrants are often young people in their reproductive years, and their movement may therefore indirectly affect the birth rates of their home and host region. This is one of the reasons why Guangdong province, which received a lot of immigrants over the last decades, has a comparatively high population growth rate. At the same time, Jilin, Liaoning, and Heilongjiang province, all located in northeast China, suffer not only from low fertility, but also from emigration of young people searching for better jobs elsewhere. The impact of uneven population growth The current distribution of natural population growth rates across China is most likely to remain in the near future, while overall population decline is expected to accelerate. Regions with less favorable economic opportunities will lose their inhabitants faster. The western regions with their high fertility rates, however, have only small total populations, which limits their effect on China’s overall population size.

About this dataset

Context

This list ranks the 365 cities in the Florida by Chinese population, as estimated by the United States Census Bureau. It also highlights population changes in each city over the past five years.

Content

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

• 2019-2023 American Community Survey 5-Year Estimates
• 2014-2018 American Community Survey 5-Year Estimates
• 2009-2013 American Community Survey 5-Year Estimates

Variables / Data Columns

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

Good to know

Margin of Error

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

Custom data

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

Inspiration

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

This polygon shapefile represents provincial boundaries of China for 2010. This layer is part of the 2010 China Province Population Census Dataset. These data were primarily based on the "The Administrative Maps of the People's Republic of China, published by China Map Press.

This dataset is intended for researchers, students, and policy makers for reference and mapping purposes, and may be used for basic applications such as viewing, querying, and map output production, or to provide a basemap to support graphical overlays and analysis with other spatial data.

Panel data of indicators in 30 provinces of China from 2000 to 2021, including: resident population, gross domestic product, transportation industry output value, transportation energy consumption, passenger/goods turnover, etc., a total of 18 indicators.

V1 dataset:Under the global framework of Shared Socioeconomic Pathways (SSPs), based on localized population and economic parameters, a Population Development Environment (PDE) model is adopted to construct population grid data for SSPs from 2020 to 2100; Using the Cobb Douglas model, construct economic data for SSPs from 2020 to 2100.The v1 dataset includes:Population grid data of the world, The Belt and Road region, and China, with a spatial resolution of 0.5°GDP grid data of the world, The Belt and Road region, and China, with a spatial resolution of 0.5 °Grid data on the output value of three industries in the Chinese region, with a spatial resolution of 0.1 °V2 dataset:Based on the data from the 7th National Population Census of China, starting from 2020, the parameters such as fertility rate, mortality rate, migration rate, and education level in the Population Development Environment (PDE) model were updated. Under the Shared Socioeconomic Pathways (SSP1-5), a new version (v2) of the total population and age and gender specific population projection dataset for China and its provinces from 2020 to 2100 was created. Based on the data from the 7th National Population Census and the 4th Economic Census of China, with 2020 as the starting year, the parameters of total factor productivity, capital stock, labor input, and capital elasticity coefficient in the Cobb Douglas model were updated. Under the shared SSP1-5, a new version (v2) of China and its provincial GDP projectiondataset from 2020 to 2100 was created.The v2 (2024 version) dataset includes:Total Population Data of China and Provinces (2020-2100)Population data by age and gender in China (2020-2100)China and Provincial GDP Data (2020-2100)

About this dataset

Context

This list ranks the 473 cities in the California by Chinese population, as estimated by the United States Census Bureau. It also highlights population changes in each city over the past five years.

Content

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

• 2019-2023 American Community Survey 5-Year Estimates
• 2014-2018 American Community Survey 5-Year Estimates
• 2009-2013 American Community Survey 5-Year Estimates

Variables / Data Columns

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

Good to know

Margin of Error

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

Custom data

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

Inspiration

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

About this dataset

Context

This list ranks the 3,057 counties in the United States by Chinese population, as estimated by the United States Census Bureau. It also highlights population changes in each county over the past five years.

Content

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

• 2019-2023 American Community Survey 5-Year Estimates
• 2014-2018 American Community Survey 5-Year Estimates
• 2009-2013 American Community Survey 5-Year Estimates

Variables / Data Columns

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

Good to know

Margin of Error

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

Custom data

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

Inspiration

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

1, TitleA dataset of district/county-level population distribution of China's six national censuses2, Data corresponding authorGao Liang (lianggao@bjtu.edu.cn)3, Data author(s)WU Haoran, GAO Liang, SONG Dongdong, YANG Yitao, XU Changxing, YANG Xiaobao4, Time range1953, 1964, 1982, 1990, 2000, 20105, Geographical scopeChinese mainland6, Data volume67.6MB7, Data format（*.shp, *.cpg, *.dbf, *.prj, *.sbn, *.sbx, *.shx）8, Source(s) of fundingNational Natural Science Foundation of China (71571017, 91646124, 71621001, 91746201)9, Dataset/Database compositionThe data set consists of one part: Dataset Map.zip contains the coded and attributed links to form a district/county level GIS population database of 31 provinces (municipalities, autonomous regions) (excluding Hong Kong, Macao, and Taiwan). The amount of data is 67.6MB.

The GIS map layer include the province map with comparable variables from 2000 and 2010 population Census data.

About this dataset

Context

This list ranks the 123 cities in the Maryland by Chinese population, as estimated by the United States Census Bureau. It also highlights population changes in each city over the past five years.

Content

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

• 2019-2023 American Community Survey 5-Year Estimates
• 2014-2018 American Community Survey 5-Year Estimates
• 2009-2013 American Community Survey 5-Year Estimates

Variables / Data Columns

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

Good to know

Margin of Error

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

Custom data

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

Inspiration

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