About this dataset

Context

The dataset tabulates the data for the China, TX population pyramid, which represents the China 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 China, TX, is 25.5.
• Old-age dependency ratio, which is the number of persons aged 65 or over per 100 persons aged 15-64, for China, TX, is 39.1.
• Total dependency ratio for China, TX is 64.6.
• Potential support ratio, which is the number of youth (working age population) per elderly, for China, TX is 2.6.

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 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 for the selected age group is shown in the following column.
• Population (Female): The female population in the China for the selected age group is shown in the following column.
• Total Population: The total population of the China 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 China Population by Age. You can refer the same here

About this dataset

Context

The dataset tabulates the data for the China, Maine population pyramid, which represents the China town 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 China, Maine, is 26.6.
• Old-age dependency ratio, which is the number of persons aged 65 or over per 100 persons aged 15-64, for China, Maine, is 21.7.
• Total dependency ratio for China, Maine is 48.3.
• Potential support ratio, which is the number of youth (working age population) per elderly, for China, Maine is 4.6.

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

The United Nations General Assembly (UNGA) serves as a unique platform where countries have equal representation and can voice their positions on major global issues. Voting patterns in the UNGA often reveal underlying trends in political alliances, economic interdependencies, and shared values.

This project aims to uncover patterns in UNGA voting alignment with two major global powers: the United States and China. The final dataset used in this analysis was sourced from the United Nations Digital Library, which hosts official UN voting records ( https://digitallibrary.un.org ). By scraping data from the UN’s digital repository, this project focused specifically on the Voting Resolutions of the General Assembly.

The analysis compares the voting behavior of a target country to that of China and the United States on a yearly basis. For each resolution, I recorded how China and the U.S. voted—categorizing each as “Yes,” “No,” or “Abstain”—and then documented how the target country voted. Resolutions labeled "ADOPTED WITHOUT VOTE" were excluded from the analysis. This methodology enabled a detailed comparison of voting alignments (or discordances) between the target country and each of the two major powers.

To illustrate, consider the example of “Mexico 2019.” For each UNGA resolution in 2019, I recorded Mexico’s vote and compared it to the votes of both China and the United States. I then calculated the proportion of resolutions where Mexico’s vote aligned with China’s, and separately, the proportion aligned with the U.S. These proportions were calculated by dividing the number of aligned votes by the total number of resolutions Mexico voted on that year.

Notably, the analysis found that, on average, countries tend to align more closely with China than with the United States in UNGA voting.

The final output of this process was a dataset that quantifies each country’s diplomatic alignment with China and the U.S. within the United Nations, providing a useful measure for further geopolitical analysis.

Code and Processing Tools

All code can be found on https://github.com/jasonding15/cosIW

Context:

From World Health Organization - On 31 December 2019, WHO was alerted to several cases of pneumonia in Wuhan City, Hubei Province of China. The virus did not match any other known virus. This raised concern because when a virus is new, we do not know how it affects people.

So daily level information on the affected people can give some interesting insights when it is made available to the broader data science community.

Johns Hopkins University has made an excellent dashboard using the affected cases data. Data is extracted from the google sheets associated and made available here.

Edited:

Now data is available as csv files in the Johns Hopkins Github repository. Please refer to the github repository for the Terms of Use details. Uploading it here for using it in Kaggle kernels and getting insights from the broader DS community.

Content

2019 Novel Coronavirus (2019-nCoV) is a virus (more specifically, a coronavirus) identified as the cause of an outbreak of respiratory illness first detected in Wuhan, China. Early on, many of the patients in the outbreak in Wuhan, China reportedly had some link to a large seafood and animal market, suggesting animal-to-person spread. However, a growing number of patients reportedly have not had exposure to animal markets, indicating person-to-person spread is occurring. At this time, it’s unclear how easily or sustainably this virus is spreading between people - CDC

This dataset has daily level information on the number of affected cases, deaths and recovery from 2019 novel coronavirus. Please note that this is a time series data and so the number of cases on any given day is the cumulative number.

The data is available from 22 Jan, 2020.

Here’s a polished version suitable for a professional Kaggle dataset description:

Dataset Description

This dataset contains time-series and case-level records of the COVID-19 pandemic. The primary file is covid_19_data.csv, with supporting files for earlier records and individual-level line list data.

Files and Columns

1. covid_19_data.csv (Main File)

This is the primary dataset and contains aggregated COVID-19 statistics by location and date.

• Sno – Serial number of the record
• ObservationDate – Date of the observation (MM/DD/YYYY)
• Province/State – Province or state of the observation (may be missing for some entries)
• Country/Region – Country of the observation
• Last Update – Timestamp (UTC) when the record was last updated (not standardized, requires cleaning before use)
• Confirmed – Cumulative number of confirmed cases on that date
• Deaths – Cumulative number of deaths on that date
• Recovered – Cumulative number of recoveries on that date

2. 2019_ncov_data.csv (Legacy File)

This file contains earlier COVID-19 records. It is no longer updated and is provided only for historical reference. For current analysis, please use covid_19_data.csv.

3. COVID_open_line_list_data.csv

This file provides individual-level case information, obtained from an open data source. It includes patient demographics, travel history, and case outcomes.

4. COVID19_line_list_data.csv

Another individual-level case dataset, also obtained from public sources, with detailed patient-level information useful for micro-level epidemiological analysis.

✅ Use covid_19_data.csv for up-to-date aggregated global trends.

✅ Use the line list datasets for detailed, individual-level case analysis.

Country level datasets:

If you are interested in knowing country level data, please refer to the following Kaggle datasets:

India - https://www.kaggle.com/sudalairajkumar/covid19-in-india

South Korea - https://www.kaggle.com/kimjihoo/coronavirusdataset

Italy - https://www.kaggle.com/sudalairajkumar/covid19-in-italy

Brazil - https://www.kaggle.com/unanimad/corona-virus-brazil

USA - https://www.kaggle.com/sudalairajkumar/covid19-in-usa

Switzerland - https://www.kaggle.com/daenuprobst/covid19-cases-switzerland

Indonesia - https://www.kaggle.com/ardisragen/indonesia-coronavirus-cases

Acknowledgements :

Johns Hopkins University for making the data available for educational and academic research purposes

MoBS lab - https://www.mobs-lab.org/2019ncov.html

World Health Organization (WHO): https://www.who.int/

DXY.cn. Pneumonia. 2020. http://3g.dxy.cn/newh5/view/pneumonia.

BNO News: https://bnonews.com/index.php/2020/02/the-latest-coronavirus-cases/

National Health Commission of the People’s Republic of China (NHC): http://www.nhc.gov.cn/xcs/yqtb/list_gzbd.shtml

China CDC (CCDC): http://weekly.chinacdc.cn/news/TrackingtheEpidemic.htm

Hong Kong Department of Health: https://www.chp.gov.hk/en/features/102465.html

Macau Government: https://www.ssm.gov.mo/portal/

Taiwan CDC: https://sites.google....

BackgroundCardiovascular diseases (CVDs) are not only the primary cause of mortality in China but also represent a significant financial burden. The World Health Organization highlight that as China undergoes rapid socioeconomic development, its disease spectrum is gradually shifting towards that of developed countries, with increasing prevalence of lifestyle-related diseases such as ischemic heart disease and stroke. We reviewed the rates and trends of CVDs incidence, mortality and disability-adjusted life years (DALYs) burden in China and compared them with those in the United States (US) and Japan for formulating CVDs control policies.MethodsData on CVDs incidence, death and DALYs in China, the US and Japan were obtained from the GBD 2019 database. The Joinpoint regression model was used to analyze the trends in CVDs incidence and mortality in China, the US and Japan, calculate the annual percentage change and determine the best-fitting inflection points.ResultsIn 2019, there were approximately 12,341,074 new diagnosed cases of CVDs in China, with 4,584,273 CVDs related deaths, causing 91,933,122 DALYs. The CVDs age-standardized incidence rate (ASIR) in China (538.10/100,000) was lower than that in the US and globally, while age-standardized death rate (ASDR) (276.9/100,000) and age-standardized DALY rate (6,463.47/100,000) were higher than those in the two regions. Compared with the US and Japan, from 1990 to 2019, the CVDs incidence rate in China showed an increasing trend, with a lower annual decrease in ASDR and a younger age structure of disease burden. Furthermore, the disease spectrum in China changed minimally, with stroke, ischemic heart disease, and hypertensive heart disease being the top three leading CVDs diseases in terms of incidence and disease burden, also being the major causes of CVDs in the US and Japan.ConclusionThe prevention and control of CVDs is a global issue. The aging population and increasing unhealthy lifestyles will continue to increase the burden in China. Therefore, relevant departments in China should reference the established practices for CVDs control in developed countries while considering the diversity of CVDs in different regions when adjusting national CVDs control programs.

About this dataset

Context

The dataset tabulates the data for the China Grove, TX population pyramid, which represents the China Grove 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 China Grove, TX, is 18.8.
• Old-age dependency ratio, which is the number of persons aged 65 or over per 100 persons aged 15-64, for China Grove, TX, is 31.7.
• Total dependency ratio for China Grove, TX is 50.5.
• Potential support ratio, which is the number of youth (working age population) per elderly, for China Grove, TX is 3.2.

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

About this dataset

Context

The dataset tabulates the population of China by race. It includes the population of China across racial categories (excluding ethnicity) as identified by the Census Bureau. The dataset can be utilized to understand the population distribution of China across relevant racial categories.

Key observations

The percent distribution of China population by race (across all racial categories recognized by the U.S. Census Bureau): 72.09% are white, 16.37% are Black or African American, 3.03% are Asian, 1.46% are some other race and 7.06% are multiracial.

Content

When available, the data consists of estimates from the U.S. Census Bureau American Community Survey (ACS) 2019-2023 5-Year Estimates.

Racial categories include:

• White
• Black or African American
• American Indian and Alaska Native
• Asian
• Native Hawaiian and Other Pacific Islander
• Some other race
• Two or more races (multiracial)

Variables / Data Columns

• Race: This column displays the racial categories (excluding ethnicity) for the China
• Population: The population of the racial category (excluding ethnicity) in the China is shown in this column.
• % of Total Population: This column displays the percentage distribution of each race as a proportion of China 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 Population by Race & Ethnicity. You can refer the same here

About this Dataset

Ecommerce data is typically proprietary and not shared by private companies. However, this dataset is sourced from Google Cloud's BigQuery public data. It comes from the "thelook_ecommerce" dataset, which consists of seven tables.

Content

This dataset contains transactional data spanning from 2019 to 2024, capturing all global consumer transactions. The company primarily sells a wide range of products, including clothing and accessories, catering to all age groups. The majority of its customers are based in the USA, China, and Brazil.

Table Creation

An additional data table was created from the Events table to track user sessions where a purchase was completed within the same session. This table includes details such as the date and time of the user's first interaction with the webpage, recorded as sequence number 1, as well as the date and time of the final purchase event, along with the corresponding sequence number for that session id.

About this dataset

Context

The dataset tabulates the population of China town by race. It includes the population of China town across racial categories (excluding ethnicity) as identified by the Census Bureau. The dataset can be utilized to understand the population distribution of China town across relevant racial categories.

Key observations

The percent distribution of China town population by race (across all racial categories recognized by the U.S. Census Bureau): 95.37% are white, 0.67% are Asian, 0.27% are some other race and 3.69% are multiracial.

Content

When available, the data consists of estimates from the U.S. Census Bureau American Community Survey (ACS) 2019-2023 5-Year Estimates.

Racial categories include:

• White
• Black or African American
• American Indian and Alaska Native
• Asian
• Native Hawaiian and Other Pacific Islander
• Some other race
• Two or more races (multiracial)

Variables / Data Columns

• Race: This column displays the racial categories (excluding ethnicity) for the China town
• Population: The population of the racial category (excluding ethnicity) in the China town is shown in this column.
• % of Total Population: This column displays the percentage distribution of each race 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 data for the East China Township, Michigan population pyramid, which represents the East China township 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 East China Township, Michigan, is 16.4.
• Old-age dependency ratio, which is the number of persons aged 65 or over per 100 persons aged 15-64, for East China Township, Michigan, is 56.3.
• Total dependency ratio for East China Township, Michigan is 72.6.
• Potential support ratio, which is the number of youth (working age population) per elderly, for East China Township, Michigan is 1.8.

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

About this dataset

Context

The dataset tabulates the Non-Hispanic population of China by race. It includes the distribution of the Non-Hispanic population of China across various race categories as identified by the Census Bureau. The dataset can be utilized to understand the Non-Hispanic population distribution of China across relevant racial categories.

Key observations

Of the Non-Hispanic population in China, the largest racial group is White alone with a population of 487 (70.78% of the total Non-Hispanic population).

Content

When available, the data consists of estimates from the U.S. Census Bureau American Community Survey (ACS) 2019-2023 5-Year Estimates.

Racial categories include:

• White
• Black or African American
• American Indian and Alaska Native
• Asian
• Native Hawaiian and Other Pacific Islander
• Some other race
• Two or more races (multiracial)

Variables / Data Columns

• Race: This column displays the racial categories (for Non-Hispanic) for the China
• Population: The population of the racial category (for Non-Hispanic) in the China is shown in this column.
• % of Total Population: This column displays the percentage distribution of each race as a proportion of China total Non-Hispanic 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 Population by Race & Ethnicity. You can refer the same here

About this dataset

Context

The dataset tabulates the Non-Hispanic population of China town by race. It includes the distribution of the Non-Hispanic population of China town across various race categories as identified by the Census Bureau. The dataset can be utilized to understand the Non-Hispanic population distribution of China town across relevant racial categories.

Key observations

Of the Non-Hispanic population in China town, the largest racial group is White alone with a population of 4,231 (96.75% of the total Non-Hispanic population).

Content

When available, the data consists of estimates from the U.S. Census Bureau American Community Survey (ACS) 2019-2023 5-Year Estimates.

Racial categories include:

• White
• Black or African American
• American Indian and Alaska Native
• Asian
• Native Hawaiian and Other Pacific Islander
• Some other race
• Two or more races (multiracial)

Variables / Data Columns

• Race: This column displays the racial categories (for Non-Hispanic) for the China town
• Population: The population of the racial category (for Non-Hispanic) in the China town is shown in this column.
• % of Total Population: This column displays the percentage distribution of each race as a proportion of China town total Non-Hispanic 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 Grove by race. It includes the population of China Grove across racial categories (excluding ethnicity) as identified by the Census Bureau. The dataset can be utilized to understand the population distribution of China Grove across relevant racial categories.

Key observations

The percent distribution of China Grove population by race (across all racial categories recognized by the U.S. Census Bureau): 71.83% are white, 4.10% are Black or African American, 0.42% are American Indian and Alaska Native, 1.89% are Asian, 9.63% are some other race and 12.12% are multiracial.

Content

When available, the data consists of estimates from the U.S. Census Bureau American Community Survey (ACS) 2019-2023 5-Year Estimates.

Racial categories include:

• White
• Black or African American
• American Indian and Alaska Native
• Asian
• Native Hawaiian and Other Pacific Islander
• Some other race
• Two or more races (multiracial)

Variables / Data Columns

• Race: This column displays the racial categories (excluding ethnicity) for the China Grove
• Population: The population of the racial category (excluding ethnicity) in the China Grove is shown in this column.
• % of Total Population: This column displays the percentage distribution of each race as a proportion of China Grove 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 Grove Population by Race & Ethnicity. You can refer the same here

About this dataset

Context

The dataset tabulates the Non-Hispanic population of China Grove by race. It includes the distribution of the Non-Hispanic population of China Grove across various race categories as identified by the Census Bureau. The dataset can be utilized to understand the Non-Hispanic population distribution of China Grove across relevant racial categories.

Key observations

Of the Non-Hispanic population in China Grove, the largest racial group is White alone with a population of 3,059 (89% of the total Non-Hispanic population).

Content

When available, the data consists of estimates from the U.S. Census Bureau American Community Survey (ACS) 2019-2023 5-Year Estimates.

Racial categories include:

• White
• Black or African American
• American Indian and Alaska Native
• Asian
• Native Hawaiian and Other Pacific Islander
• Some other race
• Two or more races (multiracial)

Variables / Data Columns

• Race: This column displays the racial categories (for Non-Hispanic) for the China Grove
• Population: The population of the racial category (for Non-Hispanic) in the China Grove is shown in this column.
• % of Total Population: This column displays the percentage distribution of each race as a proportion of China Grove total Non-Hispanic 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 Grove Population by Race & Ethnicity. You can refer the same here

About this dataset

Context

The dataset tabulates the population of China township by race. It includes the population of China township across racial categories (excluding ethnicity) as identified by the Census Bureau. The dataset can be utilized to understand the population distribution of China township across relevant racial categories.

Key observations

The percent distribution of China township population by race (across all racial categories recognized by the U.S. Census Bureau): 97.13% are white, 1.17% are Black or African American and 1.71% are multiracial.

Content

When available, the data consists of estimates from the U.S. Census Bureau American Community Survey (ACS) 2019-2023 5-Year Estimates.

Racial categories include:

• White
• Black or African American
• American Indian and Alaska Native
• Asian
• Native Hawaiian and Other Pacific Islander
• Some other race
• Two or more races (multiracial)

Variables / Data Columns

• Race: This column displays the racial categories (excluding ethnicity) for the China township
• Population: The population of the racial category (excluding ethnicity) in the China township is shown in this column.
• % of Total Population: This column displays the percentage distribution of each race as a proportion of China township 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 township Population by Race & Ethnicity. You can refer the same here

About this dataset

Context

The dataset tabulates the Non-Hispanic population of China township by race. It includes the distribution of the Non-Hispanic population of China township across various race categories as identified by the Census Bureau. The dataset can be utilized to understand the Non-Hispanic population distribution of China township across relevant racial categories.

Key observations

With a zero Hispanic population, China township is 100% Non-Hispanic. Among the Non-Hispanic population, the largest racial group is White alone with a population of 3,413 (97.13% of the total Non-Hispanic population).

Content

When available, the data consists of estimates from the U.S. Census Bureau American Community Survey (ACS) 2019-2023 5-Year Estimates.

Racial categories include:

• White
• Black or African American
• American Indian and Alaska Native
• Asian
• Native Hawaiian and Other Pacific Islander
• Some other race
• Two or more races (multiracial)

Variables / Data Columns

• Race: This column displays the racial categories (for Non-Hispanic) for the China township
• Population: The population of the racial category (for Non-Hispanic) in the China township is shown in this column.
• % of Total Population: This column displays the percentage distribution of each race as a proportion of China township total Non-Hispanic 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 township Population by Race & Ethnicity. You can refer the same here

About this dataset

Context

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

Key observations

There is a slight majority of female population, with 51.87% of total population being female. 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.

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 East China township is shown in this column.
• % of Total Population: This column displays the percentage distribution of each gender as a proportion of East China township 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 East China township Population by Race & Ethnicity. You can refer the same here

About this dataset

Context

The dataset presents the median household incomes over the past decade across various racial categories identified by the U.S. Census Bureau in China town. It portrays the median household income of the head of household across racial categories (excluding ethnicity) as identified by the Census Bureau. It also showcases the annual income trends, between 2013 and 2023, providing insights into the economic shifts within diverse racial communities.The dataset can be utilized to gain insights into income disparities and variations across racial categories, aiding in data analysis and decision-making..

Key observations

• White: In China town, the median household income for the households where the householder is White increased by $36,339(62.56%), between 2013 and 2023. The median household income, in 2023 inflation-adjusted dollars, was $58,083 in 2013 and $94,422 in 2023.
• Black or African American: As per the U.S. Census Bureau population data, in China town, there are no households where the householder is Black or African American; hence, the median household income for the Black or African American population is not applicable.
• Refer to the research insights for more key observations on American Indian and Alaska Native, Asian, Native Hawaiian and Other Pacific Islander, Some other race and Two or more races (multiracial) households

Content

When available, the data consists of estimates from the U.S. Census Bureau American Community Survey (ACS) 2019-2023 5-Year Estimates.

Racial categories include:

• White
• Black or African American
• American Indian and Alaska Native
• Asian
• Native Hawaiian and Other Pacific Islander
• Some other race
• Two or more races (multiracial)

Variables / Data Columns

• Race of the head of household: This column presents the self-identified race of the household head, encompassing all relevant racial categories (excluding ethnicity) applicable in China town.
• 2010: 2010 median household income
• 2011: 2011 median household income
• 2012: 2012 median household income
• 2013: 2013 median household income
• 2014: 2014 median household income
• 2015: 2015 median household income
• 2016: 2016 median household income
• 2017: 2017 median household income
• 2018: 2018 median household income
• 2019: 2019 median household income
• 2020: 2020 median household income
• 2021: 2021 median household income
• 2022: 2022 median household income
• 2023: 2023 median household income
• Please note: All incomes have been adjusted for inflation and are presented in 2023-inflation-adjusted dollars.

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 median household income by race. You can refer the same here