Context

More international students are flocking to China than ever before. According to a report, over 540,000 foreigners studied in China in 2018 – marking a 40 percent increase from 2012. China attracts more international students than any other Asian power and ranks third globally, behind the United States and the United Kingdom.

Content

In 2018 there were a total of 492,185 international students from 196 countries/areas pursuing their studies in 1,004 higher education institutions in China’s 31 provinces/autonomous regions/provincial-level municipalities, marking an increase of 3,013 students or 0.62% compared to 2017. International students in Hong Kong, Macau and Taiwan are not included in the datasets. The datasets contain three CSV files (Continent, Country, Province) with different data about international students in China.

Columns Description

@Continent (Number/percent of international students by continent) Continent- The name of continent Number - The number of total international students Deaths- The percentage of total international students

@Country (Number of international students by country of origin) Rank- The rank of the country based on total students in China Country- The name of the country Number- The number of total international students

@Province (The top provinces/cities with the largest number of international students) Province- The name of the city/province Number- The number of total international students

Acknowledgements

This data collected from moe.gov.cn.

Inspiration

Currently, I'm studying at a Chinese university. Every year many international students come to China for their higher study, and the ratio of international students is growing steadily. This data will help us to understand the ratio of international students in China.

Chinese students at Texas universities from 2020 to 2024

This series of 11 datasets is drawn from Rhoads, Edward J. M. Stepping Forth into the World: The Chinese Educational Mission to the United States, 1872-81. Hong Kong University Press, 2011. They document the 120 young Chinese who participated in the pioneering Chinese Educational Mission (CEM) in the United States (1872-1881). The first 8 files are drawn directly from the tables in Rhoads: Table 2.1 CEM students, by detachment (p.14-17) Table 5.1. Initial host family assignments (p.51-54) Table 7.1. CEM students in middle schools (by state and locality) (p. 90-94) Table 7.2 CEM students in public high schools (by state and locality) (p.96-99) Table 7.3 CEM students in private academies (by state and locality) (p.99-100) Table 8.1 CEM students in colleges (by academic year of enrollment) (p.116-118) Table 9.1 Deaths, dismissals, and withdrawals from the CEM (by date) (p.136) Table 9.2 CEM students in the June 1880 census (p.138-142) Based on these tables, I created three synthetic datasets which can be used for statistical and network analyses: cem_attributes: students' vital attributes, including their multiple names and transliteration, date and place of birth, and other attribute data (one row for each individual). cem_host: students' host families in the United States cem_education: students' educational curricula Each file contains two tabs, one for the data (data), one for the description of variables (key). Grey columns refer to the unstructured information given in the original source.

Overview: This dataset contains the names of foreign universities as extracted from 中国留学生大辞典, the CUSDOS dataset, and the MGZF_1944 dataset. The English names provided are canonical where known, but many have been translated using Google Translate. The verification of original names is ongoing, with U.S. universities being fully verified. The dataset includes 2,369 entries, though some universities appear multiple times due to variations in their Chinese names.

Structure: The dataset consists of the following key columns:

Univ_For_ZhT: The name of the university in Chinese.

Univ_Eng: The corresponding English name (canonical where available, otherwise translated).

Univ_For_Py: The pinyin transliteration of the Chinese university name.

City: The city in which the university is located.

State: The state or region (for countries where applicable).

Country: The country in which the university is located.

Country_ZhT: The country name in Chinese.

Latitude: The geographic latitude coordinate of the university (when available).

Longitude: The geographic longitude coordinate of the university (when available).

Purpose & Applications:

Historical Data Matching: Enables researchers to link foreign university names found in historical Chinese records to standardized names.

Multilingual Standardization: Provides bilingual reference data for academic institutions worldwide.

Geospatial Analysis: Facilitates mapping of foreign universities attended by Chinese students.

Database Integration: Helps integrate historical and modern university name records into structured datasets.

Data Quality Considerations:

Some universities appear multiple times due to variations in their recorded Chinese names.

English names may be unverified translations, with ongoing efforts to confirm original names.

Geocoordinate data is available for only a subset of universities.

Some location fields (such as state and city) are incomplete and may require additional processing for structured use.

This table presents the bilingual typology of academic disciplines used in the Modern China Biographical Database. It is based mainly on the typology created by Yuan T'ung-li in his three bibliographical volumes about the doctoral dissertations by Chinese students in the United States, the United Kingdom, and continental Europe. We adapted this typology to include other disciplines that were present in historical sources.

Dataset Description: Typology of Disciplines (Level 2)

Overview: This dataset provides a bilingual typology of academic disciplines, specifically focusing on Level 2 classifications. The terms are extracted from various Chinese sources, with English translations provided. It is structured hierarchically, connecting each Level 2 discipline to broader categories (Level 1 and Level 0), facilitating multilingual academic classification.

Structure: The dataset consists of the following key columns:

• Level 2 Discipline (English & Chinese): The specific sub-discipline classification.

• Level 1 Discipline (English & Chinese): A broader category that groups multiple Level 2 disciplines.

• Level 0 Discipline (English & Chinese): The highest-level classification representing major academic domains.

• Level 1 Code: A numerical or coded identifier for Level 1 disciplines, supporting structured data processing.

Purpose & Applications:

• Hierarchical Classification: Enables structured categorization of academic fields across multiple levels.

• Multilingual Standardization: Supports bilingual terminology consistency in academic and research contexts.

Main sources:

Yuan, T’ung-li. A Guide to Doctoral Dissertations by Chinese Students in America, 1905-1960. Washington, D.C.: Published under the auspices of the Sino-American Cultural Society, 1961.

———. A Guide to Doctoral Dissertations by Chinese Students in Continental Europe, 1907-1962. S.l., 1964.

———. Doctoral dissertations by Chinese students in Great Britain and Northern Ireland, 1916-1961. Uden sted og forlag, 1963.

This dataset is derived from the Whoʻs Who of American Returned Students 遊美同學錄 [Youmei Tongxue Lu] published in Peking [Beijing] in 1917, compiled by the Returned Students’ Information Bureau (Liumei xuesheng tongxunchu 留美學生通訊處) established at Tsinghua School in 1915. This book is crucial for documenting the early liumei's experiences during the transitional period between the late Qing dynasty and the early years of the Republic (1911-).

The dataset records all the institutions to which the students were affiliated in the course of their lives, including the educational institutions in which they studied in China, the United States, and other countries; the public or private organizations in which they were employed; as well as their memberships in clubs and associations. The names of organizations were retrieved automatically from the Chinese biographies using named entity recognition (SpaCy model), then manually cleaned, classified, and validated by the author.

The attached file contains three tabs for (1) the list of affiliations (data); (2) the classification of organizations (class), and (3) the description of variables (key). The dataset records a total of 2,883 affiliations, linking 401 unique individuals to 1,344 unique institutions, distributed as followed:

    category
    n


    education
    565


    association
    271


    administration
    132


    business
    110


    facility
    92


    media
    66


    government
    49


    factory
    30


    other
    22


    military
    7

List of Chinese Students Receiving a Ph.D. in Chemistry between 1905 and 1964. Based on two books compiling doctoral dissertations by Chinese students in the United States. Includes disciplines; university; advisor; year degree awarded, birth and/or death date, dissertation title. Accompanies Chapter 5 : History of the Modern Chemistry Doctoral Program in Mainland China by Vera V. Mainz published in "Igniting the Chemical Ring of Fire : Historical Evolution of the Chemical Communities in the Countries of the Pacific Rim", Seth Rasmussen, Editor. Published by World Scientific. Expected publication 2017.

United States Imports from China was US$462.62 Billion during 2024, according to the United Nations COMTRADE database on international trade. United States Imports from China - data, historical chart and statistics - was last updated on September of 2025.

Imports from United States in China decreased to 11862668.27 USD Thousand in February from 14271016.33 USD Thousand in January of 2024. This dataset includes a chart with historical data for China Imports From Us.

Higher education plays a critical role in driving an innovative economy by equipping students with knowledge and skills demanded by the workforce.While researchers and practitioners have developed data systems to track detailed occupational skills, such as those established by the U.S. Department of Labor (DOL), much less effort has been made to document which of these skills are being developed in higher education at a similar granularity.Here, we fill this gap by presenting Course-Skill Atlas -- a longitudinal dataset of skills inferred from over three million course syllabi taught at nearly three thousand U.S. higher education institutions. To construct Course-Skill Atlas, we apply natural language processing to quantify the alignment between course syllabi and detailed workplace activities (DWAs) used by the DOL to describe occupations. We then aggregate these alignment scores to create skill profiles for institutions and academic majors. Our dataset offers a large-scale representation of college education's role in preparing students for the labor market.Overall, Course-Skill Atlas can enable new research on the source of skills in the context of workforce development and provide actionable insights for shaping the future of higher education to meet evolving labor demands, especially in the face of new technologies.

This data package includes the PIIE dataset to replicate the data and charts presented in The rise of US economic sanctions on China: Analysis of a new PIIE dataset by Martin Chorzempa, Mary E. Lovely, and Christine Wan, PIIE Policy Brief 24-14.

If you use the dataset, please cite as: Chorzempa, Martin, Mary E. Lovely, and Christine Wan. 2024. The rise of US economic sanctions on China: Analysis of a new PIIE dataset, PIIE Policy Brief 24-14. Washington, DC: Peterson Institute for International Economics.

This dataset tracks annual american indian student percentage from 2008 to 2023 for Milwaukee Academy Of Chinese Language vs. Wisconsin and Milwaukee School District

The USD/CNY exchange rate rose to 7.1389 on September 2, 2025, up 0.08% from the previous session. Over the past month, the Chinese Yuan has strengthened 0.58%, but it's down by 0.29% over the last 12 months. Chinese Yuan - values, historical data, forecasts and news - updated on September of 2025.

China Imports from United States was US$164.59 Billion during 2024, according to the United Nations COMTRADE database on international trade. China Imports from United States - data, historical chart and statistics - was last updated on September of 2025.

CHCP Overview:The human behavior and brain are shaped by genetic, environmental and cultural interactions. Recent advances in neuroimaging integrate multimodal imaging data from a large population and start to explore the large-scale structural and functional connectomic architectures of the human brain. One of the major pioneers is the Human Connectome Project (HCP) that developed sophisticated imaging protocols and has built a collection of high-quality multimodal neuroimaging, behavioral and genetic data from US population. A large-scale neuroimaging project parallel to the HCP, but with a focus on the East Asian population, will allow comparisons of brain-behavior associations across different ethnicities and cultures. The Chinese Human Connectome Project (CHCP) is launched in 2017 and led by Professor Jia-Hong GAO at Peking University, Beijing, China. CHCP aims to provide large sets of multimodal neuroimaging, behavioral and genetic data on the Chinese population that are comparable to the data of the HCP. The CHCP protocols were almost identical to those of the HCP, including the procedure for 3T MRI scanning, the data acquisition parameters, and the task paradigms for functional brain imaging. The CHCP also collected behavioral and genetic data that were compatible with the HCP dataset. The first public release of the CHCP dataset is in 2022. CHCP dataset includes high-resolution structural MR images (T1W and T2W), resting-state fMRI (rfMRI), task fMRI (tfMRI), and high angular resolution diffusion MR images (dMRI) of the human brain as well as behavioral data based on Chinese population. The unprocessed "raw" images of CHCP dataset (about 1.85 TB) have been released on the platform and can be downloaded. Considering our current cloud-storage service, sharing full preprocessed images (up to 70 TB) requires further construction. We will be actively cooperating with researchers who contact us for academic request, offering case-by-case solution to access the preprocessed data in a timely manner, such as by mailing hard disks or a third-party trusted cloud-storage service. V2 Release (Date: January 16, 2023):Here, we released the seven major domains task fMRI EVs files, including: 1) visual, motion, somatosensory, and motor systems; 2) category specific representations; 3) working memory/cognitive control systems; 4) language processing (semantic and phonological processing); 5) social cognition (Theory of Mind); 6) relational processing; and 7) emotion processing.V3 Release (Date: January 12, 2024):This version of data release primarily discloses the CHCP raw MRI dataset that underwent “HCP minimal preprocessing pipeline”, located in CHCP_ScienceDB_preproc folder (about 6.90 TB). In this folder, preprocessed MRI data includes T1W, T2W, rfMRI, tfMRI, and dMRI modalities for all young adulthood participants, as well as partial results for middle-aged and older adulthood participants in the CHCP dataset. Following the data sharing strategy of the HCP, we have eliminated some redundant preprocessed data, resulting in a final total size of the preprocessed CHCP dataset is about 6.90 TB in zip files. V4 Release (Date: December 4, 2024):In this update, we have fixed the issue with the corrupted compressed file of preprocessed data for subject 3011, and removed the incorrect preprocessed results for subject 3090. Additionally, we have updated the subject file information list. Additionally, this release includes the update of unprocessed "raw" images of the CHCP dataset in CHCP_ScienceDB_unpreproc folder (about 1.85 TB), addressing the previously insufficient anonymization of T1W and T2W modalities data for some older adulthood participants in versions V1 and V2. For more detailed information, please refer to the data descriptions in versions V1 and V2.CHCP Summary:Subjects:366 healthy adults (Chinese Han)Imaging Scanner:3T MR (Siemens Prisma)Institution:Peking University, Beijing, ChinaFunding Agencies:Beijing Municipal Science & Technology CommissionChinese Institute for Brain Research (Beijing)National Natural Science Foundation of ChinaMinistry of Science and Technology of China CHCP Citations:Papers, book chapters, books, posters, oral presentations, and all other printed and digital presentations of results derived from CHCP data should contain the following wording in the acknowledgments section: "Data were provided [in part] by the Chinese Human Connectome Project (CHCP, PI: Jia-Hong Gao) funded by the Beijing Municipal Science & Technology Commission, Chinese Institute for Brain Research (Beijing), National Natural Science Foundation of China, and the Ministry of Science and Technology of China."

Comprehensive dataset of 126 Chinese tea houses in United States as of July, 2025. Includes verified contact information (email, phone), geocoded addresses, customer ratings, reviews, business categories, and operational details. Perfect for market research, lead generation, competitive analysis, and business intelligence. Download a complimentary sample to evaluate data quality and completeness.

This dataset is provided by AIxBlock, an unified platform for AI development and AI workflows automation. This dataset contains ~500k sentences in Chinese, making it a valuable resource for a wide range of language technology applications. All data has undergone quality assurance (QA) checks to ensure clarity, correctness, and natural phrasing. The dataset is well-suited for: Speech data generation (e.g., recording short audio clips lasting 8–30 seconds per sentence) Natural Language… See the full description on the dataset page: https://huggingface.co/datasets/AIxBlock/Chinese-short-sentences.

Exports in China increased to 325.18 USD Billion in June from 316.10 USD Billion in May of 2025. This dataset provides - China Exports - actual values, historical data, forecast, chart, statistics, economic calendar and news.

This dataset tracks annual american indian student percentage from 2013 to 2018 for Hope Chinese Charter School vs. Oregon and Beaverton SD 48j School District

About this dataset

Context

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

Key observations

Largest age group (population): Male # 15-19 years (53) | Female # 30-34 years (103). Source: U.S. Census Bureau American Community Survey (ACS) 2018-2022 5-Year Estimates.

Content

When available, the data consists of estimates from the U.S. Census Bureau American Community Survey (ACS) 2018-2022 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 China population analysis. Total expected values are 18 and are define above in the age groups section.
• Population (Male): The male population in the China is shown in the following column.
• Population (Female): The female population in the China 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 China 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 China Population by Gender. You can refer the same here