About this dataset

Context

The dataset tabulates the population of China town by gender, including both male and female populations. This dataset can be utilized to understand the population distribution of China town across both sexes and to determine which sex constitutes the majority.

Key observations

There is a slight majority of female population, with 50.47% of total population being female. 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.

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. No further analysis is done on the data reported from the Census Bureau.

Variables / Data Columns

• Gender: This column displays the Gender (Male / Female)
• Population: The population of the gender in the China town is shown in this column.
• % of Total Population: This column displays the percentage distribution of each gender as a proportion of China town total population. Please note that the sum of all percentages may not equal one due to rounding of values.

Good to know

Margin of Error

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

Custom data

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

Inspiration

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

Recommended for further research

This dataset is a part of the main dataset for China town Population by Race & Ethnicity. You can refer the same here

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

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 July of 2025.

Data source: https://github.com/CVI-SZU/Linly/wiki/Linly-OpenLLaMA

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.

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 provides restaurant inspections, violations, grades and adjudication information

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.

China Exports to United States was US$525.65 Billion during 2024, according to the United Nations COMTRADE database on international trade. China Exports to United States - data, historical chart and statistics - was last updated on July 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 July of 2025.

Exports to United States in China decreased to 30786817 USD Thousand in February from 42633059 USD Thousand in January of 2024. This dataset includes a chart with historical data for China Exports To Us.

Chinese Vital Records from 2015 to 2016. This dataset is not publicly accessible because: EPA cannot release personally identifiable information regarding living individuals, according to the Privacy Act and the Freedom of Information Act (FOIA). This dataset contains information about human research subjects. Because there is potential to identify individual participants and disclose personal information, either alone or in combination with other datasets, individual level data are not appropriate to post for public access. Restricted access may be granted to authorized persons by contacting the party listed. It can be accessed through the following means: It cannot due to PII and Non-EPA data being used. Format: Chinese vital records data. This dataset is associated with the following publication: Luo, Q., C. Liu, E. Bei, Y. Deng, Y. Miao, Y. Qiu, W. Lu, J. Wright, c. chen, and Q. Zeng. Maternal exposure to nitrosamines in drinking water during pregnancy and birth outcomes in a Chinese cohort. CHEMOSPHERE. Elsevier Science Ltd, New York, NY, USA, (315): 137776, (2023).

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.

The USD/CNY exchange rate fell to 7.1703 on July 22, 2025, down 0.01% from the previous session. Over the past month, the Chinese Yuan has strengthened 0.07%, and is up by 1.64% over the last 12 months. Chinese Yuan - values, historical data, forecasts and news - updated on July of 2025.

Money Supply M2 in China increased to 330332.50 CNY Billion in June from 325783.81 CNY Billion in May of 2025. This dataset provides - China Money Supply M2 - actual values, historical data, forecast, chart, statistics, economic calendar and news.

The dataset contains WeChat posts uploaded by the 47 most influential public accounts from April 29, 2019, to May 31, 2019.

The Digital Surficial Geologic-GIS Map of the China Bend 7.5' Quadrangle, Washington is composed of GIS data layers and GIS tables, and is available in the following GRI-supported GIS data formats: 1.) a 10.1 file geodatabase (chbe_surficial_geology.gdb), and a 2.) Open Geospatial Consortium (OGC) geopackage. The file geodatabase format is supported with a 1.) ArcGIS Pro map file (.mapx) file (chbe_surficial_geology.mapx) and individual Pro layer (.lyrx) files (for each GIS data layer), as well as with a 2.) 10.1 ArcMap (.mxd) map document (chbe_surficial_geology.mxd) and individual 10.1 layer (.lyr) files (for each GIS data layer). Upon request, the GIS data is also available in ESRI 10.1 shapefile format. Contact Stephanie O'Meara (see contact information below) to acquire the GIS data in these GIS data formats. In addition to the GIS data and supporting GIS files, three additional files comprise a GRI digital geologic-GIS dataset or map: 1.) a readme file (laro_geology_gis_readme.pdf), 2.) the GRI ancillary map information document (.pdf) file (laro_geology.pdf) which contains geologic unit descriptions, as well as other ancillary map information and graphics from the source map(s) used by the GRI in the production of the GRI digital geologic-GIS data for the park, and 3.) a user-friendly FAQ PDF version of the metadata (chbe_surficial_geology_metadata_faq.pdf). Please read the laro_geology_gis_readme.pdf for information pertaining to the proper extraction of the GIS data and other map files. QGIS software is available for free at: https://www.qgis.org/en/site/. The data were completed as a component of the Geologic Resources Inventory (GRI) program, a National Park Service (NPS) Inventory and Monitoring (I&M) Division funded program that is administered by the NPS Geologic Resources Division (GRD). For a complete listing of GRI products visit the GRI publications webpage: https://www.nps.gov/subjects/geology/geologic-resources-inventory-products.htm. For more information about the Geologic Resources Inventory Program visit the GRI webpage: https://www.nps.gov/subjects/geology/gri.htm. At the bottom of that webpage is a "Contact Us" link if you need additional information. You may also directly contact the program coordinator, Jason Kenworthy (jason_kenworthy@nps.gov). Source geologic maps and data used to complete this GRI digital dataset were provided by the following: U.S. Bureau of Reclamation. Detailed information concerning the sources used and their contribution the GRI product are listed in the Source Citation section(s) of this metadata record (chbe_surficial_geology_metadata.txt or chbe_surficial_geology_metadata_faq.pdf). Users of this data are cautioned about the locational accuracy of features within this dataset. Based on the source map scale of 1:24,000 and United States National Map Accuracy Standards features are within (horizontally) 12.2 meters or 40 feet of their actual location as presented by this dataset. Users of this data should thus not assume the location of features is exactly where they are portrayed in ArcGIS, QGIS or other software used to display this dataset. All GIS and ancillary tables were produced as per the NPS GRI Geology-GIS Geodatabase Data Model v. 2.3. (available at: https://www.nps.gov/articles/gri-geodatabase-model.htm).

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.

Multiple choice question answering based on the United States Medical License Exams (USMLE). The dataset is collected from the professional medical board exams. It covers three languages: English, simplified Chinese, and traditional Chinese, and contains 12,723, 34,251, and 14,123 questions for the three languages, respectively.

Dataset Card for c4-chinese-zhtw_urls

This dataset provides the URLs and top-level domains associated with training records in erhwenkuo/c4-chinese-zhtw. It is part of a collection of datasets curated to make exploring LLM training datasets more straightforward and accessible.

  Dataset Details







  Dataset Description

This dataset was created by downloading the source data, extracting URLs and top-level domains, and retaining only those record identifiers.… See the full description on the dataset page: https://huggingface.co/datasets/nhagar/c4-chinese-zhtw_urls.