The statistic shows the share of U.S. population, by race and Hispanic origin, in 2016 and a projection for 2060. As of 2016, about 17.79 percent of the U.S. population was of Hispanic origin. Race and ethnicity in the U.S. For decades, America was a melting pot of the racial and ethnical diversity of its population. The number of people of different ethnic groups in the United States has been growing steadily over the last decade, as has the population in total. For example, 35.81 million Black or African Americans were counted in the U.S. in 2000, while 43.5 million Black or African Americans were counted in 2017.

The median annual family income in the United States in 2017 earned by Black families was about 50,870 U.S. dollars, while the average family income earned by the Asian population was about 92,784 U.S. dollars. This is more than 15,000 U.S. dollars higher than the U.S. average family income, which was 75,938 U.S. dollars.

The unemployment rate varies by ethnicity as well. In 2018, about 6.5 percent of the Black or African American population in the United States were unemployed. In contrast to that, only three percent of the population with Asian origin was unemployed.

In 2024, white Americans remained the largest racial group in the United States, numbering just over 254 million. Black Americans followed at nearly 47 million, with Asians totaling around 23 million. Hispanic residents, of any race, constituted the nation’s largest ethnic minority. Despite falling fertility, the U.S. population continues to edge upward and is expected to reach 342 million in 2025. International migrations driving population growth The United States’s population growth now hinges on immigration. Fertility rates have long been in decline, falling well below the replacement rate of 2.1. On the other hand, international migration stepped in to add some 2.8 million new arrivals to the national total that year. Changing demographics and migration patterns Looking ahead, the U.S. population is projected to grow increasingly diverse. By 2060, the Hispanic population is expected to grow to 27 percent of the total population. Likewise, African Americans will remain the largest racial minority at just under 15 percent.

This map is designed to work in the new ArcGIS Online Map Viewer. Open in Map Viewer to view map. What does this map show?This map shows the population in the US by race. The map shows this pattern nationwide for states, counties, and tracts. Open the map in the new ArcGIS Online Map Viewer Beta to see the dot density pattern. What is dot density?The density is visualized by randomly placing one dot per a given value for the desired attribute. Unlike choropleth visualizations, dot density can be mapped using total counts since the size of the polygon plays a significant role in the perceived density of the attribute.Where is the data from?The data in this map comes from the most current American Community Survey (ACS) from the U.S. Census Bureau. Table B03002. The layer being used if updated with the most current data each year when the Census releases new estimates. The layer can be found in ArcGIS Living Atlas of the World: ACS Race and Hispanic Origin Variables - Boundaries.What questions does this map answer?Where do people of different races live?Do people of a similar race live close to people of their own race?Which cities have a diverse range of different races? Less diverse?

According to the 2021 Census, London was the most ethnically diverse region in England and Wales – 63.2% of residents identified with an ethnic minority group.

This statistic shows the share of ethnic groups in Australia in the total population. 33 percent of the total population of Australia are english. Australia’s population Australia’s ethnic diversity can be attributed to their history and location. The country’s colonization from Europeans is a significant reason for the majority of its population being Caucasian. Additionally, being that Australia is one of the most developed countries closest to Eastern Asia; its Asian population comes as no surprise. Australia is one of the world’s most developed countries, often earning recognition as one of the world’s economical leaders. With a more recent economic boom, Australia has become an attractive country for students and workers alike, who seek an opportunity to improve their lifestyle. Over the past decade, Australia’s population has slowly increased and is expected to continue to do so over the next several years. A beautiful landscape, many work opportunities and a high quality of life helped play a role in the country’s development. In 2011, Australia was considered to have one of the highest life expectancies in the world, with the average Australian living to approximately 82 years of age. From an employment standpoint, Australia has maintained a rather low employment rate compared to many other developed countries. After experiencing a significant jump in unemployment in 2009, primarily due to the world economic crisis, Australia has been able to remain stable and slightly increase employment year-over-year.

Explore various maps to learn more about the population in the US based on how people respond to the American Community Survey (ACS). Based on how people responded, we can learn more about where different race and ethnicity groups live throughout the country. The pattern for each map portrays the most current 5-year ACS estimates, and is offered for states, counties, and tracts. Zoom and explore the map to see the patterns in your area.In this collection, you'll find various different topics:The predominant race in each area (which one has the largest count)Race by dot densityPeople of color (non-white population)Percent of the population by each raceWhere is the data from?The data in this map comes from the most current American Community Survey (ACS) from the U.S. Census Bureau. Table B03002. The layer being used if updated with the most current data each year when the Census releases new estimates. The layer can be found in ArcGIS Living Atlas of the World: ACS Race and Hispanic Origin Variables - Boundaries.

About this dataset

Context

The dataset presents the median household income across different racial categories in White Earth township. It portrays the median household income of the head of household across racial categories (excluding ethnicity) as identified by the Census Bureau. The dataset can be utilized to gain insights into economic disparities and trends and explore the variations in median houshold income for diverse racial categories.

Key observations

Based on our analysis of the distribution of White Earth township population by race & ethnicity, the population is predominantly American Indian and Alaska Native. This particular racial category constitutes the majority, accounting for 46% of the total residents in White Earth township. Notably, the median household income for American Indian and Alaska Native households is $17,375. Interestingly, despite the American Indian and Alaska Native population being the most populous, it is worth noting that Two or More Races households actually reports the highest median household income, with a median income of $88,036. This reveals that, while American Indian and Alaska Natives may be the most numerous in White Earth township, Two or More Races households experience greater economic prosperity in terms of median household income.

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 White Earth township.
• Median household income: Median household income, adjusting for inflation, 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 White Earth township median household income by race. You can refer the same here

The graph illustrates the number of victims of race-based hate crimes in the United States in 2025. The x-axis lists various ethnic groups, while the y-axis represents the corresponding number of victims. The data reveals that Anti-Black hate crimes were the most prevalent, with 1,743 victims, followed by Anti-Hispanic and Anti-Asian crimes with 629 and 201 victims respectively. Other categories include Anti-Other Race (308), Anti-American Indian (74), Anti-Arab (73), and Anti-Native Pacific (25). The data indicates a significant disparity in the number of victims across different ethnic groups, with Anti-Black hate crimes being the most prominent.

About this dataset

Context

The dataset presents the median household income across different racial categories in Black Earth. It portrays the median household income of the head of household across racial categories (excluding ethnicity) as identified by the Census Bureau. The dataset can be utilized to gain insights into economic disparities and trends and explore the variations in median houshold income for diverse racial categories.

Key observations

Based on our analysis of the distribution of Black Earth population by race & ethnicity, the population is predominantly White. This particular racial category constitutes the majority, accounting for 93.91% of the total residents in Black Earth. Notably, the median household income for White households is $72,054. Interestingly, despite the White population being the most populous, it is worth noting that Two or More Races households actually reports the highest median household income, with a median income of $131,250. This reveals that, while Whites may be the most numerous in Black Earth, Two or More Races households experience greater economic prosperity in terms of median household income.

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 Black Earth.
• Median household income: Median household income, adjusting for inflation, 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 Black Earth median household income by race. You can refer the same here

Leading Causes of Death US

1980–2009 by Sex, Race, and Hispanic Origin

By Health [source]

About this dataset

This fascinating dataset takes a look at the leading causes of death in the United States from 1980-2009, broken down by sex, race, and Hispanic origin. This data sheds light on how mortality in the US has changed over time among these categories. Accounting for everything from heart disease to cancer to suicide, this insight can be used by health researchers and policy makers to gain a better understanding of disparities in healthcare and deaths across different groups. Whether studying questions related to public health or more targeted population issues such as gender biases in death rates, this dataset provides an important resource for anyone interested in examining mortality across demographic lines

More Datasets

For more datasets, click here.

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How to use the dataset

This dataset can be used to explore some of the leading causes of death in the United States from 1980 to 2009, broken down by sex, race, and Hispanic origin. This data can be used to better understand mortality trends and risk factors associated with different populations in America.

By using this dataset you can compare and contrast mortality rates across different gender, racial, and ethnic groups during this time period. You can also compare different causes of death within these demographic categories to see if there are any patterns over time or notable differences between groups.

You could even use this data to track changes across population groups as a whole or look at details for specific years or types of causes of death in particular groups. With this information one may gain insight into health disparities across population segments in America— aiding advocates for social change & public policy shifts toward improved health outcomes for all Americans!

Research Ideas

• Analyzing regional or state-level differences in mortality rates over time.
• Examining the beahvioral factors or risk factors associated with each cause of death for different genders and populations.
• Examining the prevalence of each cause of death as a proportion to an overall population trend in different socio-economic categories such as race or income level

Acknowledgements

If you use this dataset in your research, please credit the original authors. Data Source

License

License: Dataset copyright by authors - You are free to: - Share - copy and redistribute the material in any medium or format for any purpose, even commercially. - Adapt - remix, transform, and build upon the material for any purpose, even commercially. - You must: - Give appropriate credit - Provide a link to the license, and indicate if changes were made. - ShareAlike - You must distribute your contributions under the same license as the original. - Keep intact - all notices that refer to this license, including copyright notices.

Columns

File: Selected_Trend_Table_from_Health_United_States_2011._Leading_causes_of_death_and_numbers_of_deaths_by_sex_race_and_Hispanic_origin_United_States_1980_and_2009.csv | Column name | Description | |:-------------------|:---------------------------------------------------------------------------------------------------------| | Group | The group of people the cause of death applies to (e.g. men, women, whites, blacks, hispanics). (String) | | Year | The year the cause of death was recorded. (Integer) | | Cause of death | The cause of death. (String) | | Flag | A flag indicating whether the cause of death is considered a leading cause. (Boolean) | | Deaths | The number of deaths attributed to the cause of death. (Integer) |

Acknowledgements

If you use this dataset in your research, please credit the original authors. If you use this dataset in your research, please credit Health.

Globally, about 25 percent of the population is under 15 years of age and 10 percent is over 65 years of age. Africa has the youngest population worldwide. In Sub-Saharan Africa, more than 40 percent of the population is below 15 years, and only three percent are above 65, indicating the low life expectancy in several of the countries. In Europe, on the other hand, a higher share of the population is above 65 years than the population under 15 years. Fertility rates The high share of children and youth in Africa is connected to the high fertility rates on the continent. For instance, South Sudan and Niger have the highest population growth rates globally. However, about 50 percent of the world’s population live in countries with low fertility, where women have less than 2.1 children. Some countries in Europe, like Latvia and Lithuania, have experienced a population decline of one percent, and in the Cook Islands, it is even above two percent. In Europe, the majority of the population was previously working-aged adults with few dependents, but this trend is expected to reverse soon, and it is predicted that by 2050, the older population will outnumber the young in many developed countries. Growing global population As of 2025, there are 8.1 billion people living on the planet, and this is expected to reach more than nine billion before 2040. Moreover, the global population is expected to reach 10 billions around 2060, before slowing and then even falling slightly by 2100. As the population growth rates indicate, a significant share of the population increase will happen in Africa.

About this dataset

Context

The dataset presents the median household income across different racial categories in Globe. It portrays the median household income of the head of household across racial categories (excluding ethnicity) as identified by the Census Bureau. The dataset can be utilized to gain insights into economic disparities and trends and explore the variations in median houshold income for diverse racial categories.

Key observations

Based on our analysis of the distribution of Globe population by race & ethnicity, the population is predominantly White. This particular racial category constitutes the majority, accounting for 58.09% of the total residents in Globe. Notably, the median household income for White households is $65,261. Interestingly, despite the White population being the most populous, it is worth noting that Some Other Race households actually reports the highest median household income, with a median income of $98,333. This reveals that, while Whites may be the most numerous in Globe, Some Other Race households experience greater economic prosperity in terms of median household income.

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 Globe.
• Median household income: Median household income, adjusting for inflation, 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 Globe median household income by race. You can refer the same here

Nigeria has hundreds of ethnic groups that are usually divided and defined primarily by language. The country hosts more ethnic groups than any other African nation, ranking among the most ethnically-complex states in the world. Most of these ethnic groups are small and localized, with only a few playing a central role in Nigerian society. The major people groups of Nigeria are: Hausa, Fulani, Yoruba, and Igbo (Ibo).The advent of colonial rule in Nigeria brought the various ethnic groups increasingly into contact with one another. This integrative process was facilitated by the construction of connective infrastructure. This increasing development set in motion a process that led to greater contact and competition among the various ethnic groups for dominance and economic advantage. The Nigerian government has worked out tentative power-sharing arrangements to help ensure that its many ethnic groups have some say in society. However, cities remain largely segregated along ethno-religious lines and confrontation between ethnic groups is common. Often, ethnic clashes in one part of the country can set off a chain of reprisal riots and attacks in other parts of the country.Most major ethnic groups have seen the formation of ethnic-exclusive militias to protect alleged group interests and perpetrate violence against other ethnic groups. These vigilante groups continue to act with impunity for lack of stringent law enforcement in much of the state. These continued attacks and tensions among ethnic groups threaten to destabilize an already unsteady country.Hausa - Northern Nigeria is dominated by this ethnic group and is often considered unified with the Fulani through intermarriage of acculturation, generating the Hausa-Fulani as a single ethnic entity. The Hausa were predominately traders throughout the Sahara and Sahel regions but have become more concentrated in rural areas as farmers and herders. They are predominately Muslim with some of the smaller sub-groups such as the Maguzawa practicing indigenous faiths. Their religion is a key component to ethnic identity and continues to shape their role in modern Nigerian society and politics. The Hausa and Fulani were instrumental in establishing and maintaining Sharia in 11 of the country’s northern states.Fulani –The Fulani are an ethnic group of Muslims located in northern Nigeria that have often assimilated into the Hausa culture. At one point nomadic herders, they arrived in the Hausa states sometime in the early 13th century. Many have intermarried with the Hausa and have mostly adopted those customs and language, although some Fulani choose to stay "pure" by retaining a nomadic lifestyle, their own language, and cultural autonomy. The Fulani are most distinctively known for a dispute that developed between them and the local King of Gobir, which developed into a jihad ending with a Fulani conquest of the Hausa states in the early 1800s.Yoruba – The Yoruba are Christian/Muslims living in southwestern Nigeria united by their common belief that Ife is their place of origin and the Oni of Ife is their spiritual leader. Their mythology holds that "Oduduwa" created the earth and that royal houses of the Yoruba kingdoms can trace their ancestry back to "Oduduwa.” Yoruba society is organized into kingdoms, the greatest of which was called Oyo. The Oyo Empire collapsed in 1830, when Afonja, broke away from the rest of the Yoruba culture and lost his empire to the Fulani. This event occurred in close temporal proximity to the Fulani Jihad, but was not associated with it. As Islam and Christianity spread to Yorubaland over the past few centuries, the group embraced both faiths alongside its many traditional and animist beliefs. This blend and acceptance of religion survives in modern society and has mitigated some religious conflict in places where Yoruba form the majority.Igbo (Ibo) – The Igbo are the main ethnic group living in southeastern Nigeria. They have represented some of the staunchest opponents to the establishment of Sharia in the North where some minority Igbo populations exist. As opposed to Hausa-Fulani and Yoruba cultures, the Igbo were traditionally decentralized and non-hierarchical, making them more receptive to European conversion efforts.Under British colonial rule, many Igbo served in government and military roles and were later key players in the 1960 Nigerian independence movement. In January 1966, Igbo leader General Ironsi established a military coup in Nigeria to try and unify a fragmented, newly-independent Nigeria. The northern section of the country believed there was an Igbo conspiracy with the establishment of the new government. In July 1966, a counter-attack was staged by northern military officers in response to the constitution of another new government. Chaos ensued and about 50,000 Igbo were killed in northern Nigeria. To put an end to chaos and upheaval, groups in eastern Nigeria declared themselves as an independent sovereign state known as “Biafra" on 30 May 1967. The Igbo secessionist movement in Biafra led to a 30-month war (Biafran War) with the Nigerian government, in which hundreds of thousands of Igbo starved to death. After the war, Igbo were reintegrated into Nigerian society, but in a more marginalized role. Despite lingering ethnic tension, they now play an important part in southeastern Nigeria's oil trade.

ISO3 - International Organization for Standardization 3-digit country code

PEOPLEGP_1 - People group level one

PEOPLEGP_2 - People group level two

PEOPLEGP_3 - People group level three

ALT_NAME - Alternate names or spellings for people groups

SOURCE_DT - Primary source creation date

SOURCE - Primary source

Collection

This shapefile created by using Anthromapper consists of ethnic layers that have been primarily based on the 1959 Murdock map of Africa with an addition of the Anaang people group based on a general location provided by Ethnologue. Geographical terrain features, combined with a watershed model, were also used to predict the likely extent of ethnic and linguistic influence. The HGIS data and metadata were supplemented with anthropological information from peer-reviewed journals and published books. The interpretation of ethnic names often produces multiple spellings of the same people groups; therefore similarly spelled or phonetic titles may be referencing the same group.

The data included herein have not been derived from a registered survey and should be considered approximate unless otherwise defined. While rigorous steps have been taken to ensure the quality of each dataset, DigitalGlobe Analytics is not responsible for the accuracy and completeness of data compiled from outside sources.

Sources (HGIS)

Anthromapper. DigitalGlobe Analytics, March 2013.

Murdock, George Peter. Tribal Map of Africa from Africa: Its Peoples and Their Culture History. New York: McGraw-Hill Book Co., January 1959.

Interactive Murdock Map available at - http://worldmap.harvard.edu/africamap.

Ethnologue, “Anaang.” Last modified April 2013. Accessed April 2013. http://www.ethnologue.com

People Groups, “Nigeria.” Last modified April 2013. Accessed April 2013. http://peoplegroups.org.

Joshua Project, “Nigeria”. Last modified March 2013. Accessed April 2013. http://www.joshuaproject.net.

Sources (Metadata)

Walker, Andrew. United States Institute of Peace, "What is Boko Haram?." Last modified 2012. Accessed April 9, 2013. http://www.usip.org.

Buhayar, Noah. PBS, "Oil and Politics in Nigeria." Last modified 2007. Accessed April 8, 2013. www.pbs.org.

Bascom, William. Urbanization Among the Yoruba. Culture and Societies of Africa. Edited by Simon and Phoebe Ottenberg. New York: Random House, 1960.

Greenberg, Joseph H. Some Aspects of Negro-Mohammedan Culture Contact Among the Hausa. Culture and Societies of Africa. Edited by Simon and Phoebe Ottenberg. New York: Random House, 1960.

Levinson, David. Ethnic Groups Worldwide: A Ready Reference Handbook. Santa Barbara: Greenwood, 1998.

Ehwarieme, William. "Between the Devil and the Deep Blue Sea: The Displacement of Ethnicity by Corruption in Nigeria's Electoral Politics." Journal of Third World Studies. 26. no. 2 (2011): 181-206.

Paden, John. Religion and Political Culture in Kano. University of California Press: Berkeley and Los Angeles, 1973.

Suberu, Rotimi. Federalism and Ethnic Conflict in Nigeria. Washington D.C.: United States Institute of Peace, 2001.

Joshua Project, “Nigeria”. Last modified April 2013. Accessed April 2013. http://www.joshuaproject.net.

In the fiscal year of 2019, 21.39 percent of active-duty enlisted women were of Hispanic origin. The total number of active duty military personnel in 2019 amounted to 1.3 million people.

Ethnicities in the United States The United States is known around the world for the diversity of its population. The Census recognizes six different racial and ethnic categories: White American, Native American and Alaska Native, Asian American, Black or African American, Native Hawaiian and Other Pacific Islander. People of Hispanic or Latino origin are classified as a racially diverse ethnicity.

The largest part of the population, about 61.3 percent, is composed of White Americans. The largest minority in the country are Hispanics with a share of 17.8 percent of the population, followed by Black or African Americans with 13.3 percent. Life in the U.S. and ethnicity However, life in the United States seems to be rather different depending on the race or ethnicity that you belong to. For instance: In 2019, native Hawaiians and other Pacific Islanders had the highest birth rate of 58 per 1,000 women, while the birth rae of white alone, non Hispanic women was 49 children per 1,000 women.

The Black population living in the United States has the highest poverty rate with of all Census races and ethnicities in the United States. About 19.5 percent of the Black population was living with an income lower than the 2020 poverty threshold. The Asian population has the smallest poverty rate in the United States, with about 8.1 percent living in poverty.

The median annual family income in the United States in 2020 earned by Black families was about 57,476 U.S. dollars, while the average family income earned by the Asian population was about 109,448 U.S. dollars. This is more than 25,000 U.S. dollars higher than the U.S. average family income, which was 84,008 U.S. dollars.

About this dataset

Context

The dataset presents the median household income across different racial categories in Blue Earth. It portrays the median household income of the head of household across racial categories (excluding ethnicity) as identified by the Census Bureau. The dataset can be utilized to gain insights into economic disparities and trends and explore the variations in median houshold income for diverse racial categories.

Key observations

Based on our analysis of the distribution of Blue Earth population by race & ethnicity, the population is predominantly White. This particular racial category constitutes the majority, accounting for 89.67% of the total residents in Blue Earth. Notably, the median household income for White households is $55,499. Interestingly, despite the White population being the most populous, it is worth noting that Some Other Race households actually reports the highest median household income, with a median income of $56,367. This reveals that, while Whites may be the most numerous in Blue Earth, Some Other Race households experience greater economic prosperity in terms of median household income.

https://i.neilsberg.com/ch/blue-earth-mn-median-household-income-by-race.jpeg" alt="Blue Earth median household income diversity across racial categories">

Content

When available, the data consists of estimates from the U.S. Census Bureau American Community Survey (ACS) 2017-2021 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 Blue Earth.
• Median household income: Median household income, adjusting for inflation, presented in 2022-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 Blue Earth median household income by race. You can refer the same here

The Formula 1 World Championship History (1950-2024) dataset offers a comprehensive exploration of Formula 1 racing, spanning over seven decades of competition. This dataset is designed to be a valuable resource for those interested in the evolution of Formula 1, covering every aspect of the sport from its inception in 1950 through the latest 2024 season.

Context

Formula 1, also known as F1, represents the pinnacle of single-seater auto racing. Governed by the Fédération Internationale de l'Automobile (FIA), it has grown into a globally recognized sport, drawing millions of fans around the world. The sport is known for its high-speed races, strategic depth, and the relentless pursuit of excellence both on the track and in the design and engineering of the cars.

This dataset captures the rich history of Formula 1 by providing detailed information on races, drivers, constructors (teams), circuits, and more. Whether you're a motorsport enthusiast, data analyst, or historian, this dataset is an excellent tool for deep diving into the data and uncovering insights about the sport.

Contents of the Dataset

The dataset is organized into multiple CSV files, each offering detailed data on different aspects of Formula 1:

1) Track_Information.csv: Contains details about the circuits where races have been held, including their location, length, and unique characteristics.

2) Team_Details.csv: Provides information about the constructors, including their history, achievements, and performance across different seasons.

3) Constructor_Performance.csv: Details the performance of constructors in individual races, showing how teams have evolved over the years.

4) Constructor_Rankings.csv: Offers annual standings of constructors, highlighting the competitive dynamics within the sport.

5) Driver_Details.csv: Includes comprehensive information about the drivers, such as their personal details, career statistics, and achievements.

6) Driver_Rankings.csv: Displays the yearly standings of drivers, showcasing who topped the charts and how tight the championship battles were.

7) Race_Schedule.csv: Lists all the races held from 1950 to 2024, along with details such as the date, location, and race name.

8) Race_Results.csv: Provides detailed results of each race, including finishing positions, points earned, and other key metrics.

9) Lap_Timings.csv: Contains data on lap times recorded by drivers during races, giving insights into their performance consistency.

10) Pit_Stop_Records.csv: Offers information on pit stops made during races, including timing and strategy, which often impact the outcome of the race.

11) Qualifying_Results.csv: Details the results of qualifying sessions, which determine the starting grid for each race.

12) Sprint_Race_Results.csv: Includes data on sprint races, shorter races introduced to decide starting positions for the main race.

13) Season_Summaries.csv: Summarizes each season, including the number of races, champions, and key moments.

14) Race_Status.csv: Contains codes and descriptions related to the status of cars during a race, such as if a car finished, retired, or was disqualified.

Data Source

The dataset is sourced from the Ergast Motor Racing Data API, a trusted and frequently updated source for Formula 1 data. The API has been reliably providing data over the years, ensuring the dataset is accurate and up-to-date. Each file in this dataset has been carefully compiled to offer a thorough overview of Formula 1’s history, making it an essential resource for anyone interested in the sport.

Potential Use Cases

This dataset is versatile and can be used for a wide range of applications, including:

1) Historical Analysis: Study the changes and trends in Formula 1 over the years, including the evolution of teams, drivers, and circuits.

2) Performance Trends: Analyze trends in driver and constructor performances, and identify key factors contributing to success in Formula 1.

3) Race Strategy Insights: Investigate the impact of different strategies, such as pit stops and qualifying positions, on race outcomes and championships.

4) Data Visualization: Create compelling visualizations to illustrate the history and key events in Formula 1, such as championship rivalries, race victories, and more.

5) Fan Engagement: Engage with Formula 1 fans by providing them with in-depth data-driven insights about their favorite teams, drivers, and races.

The Formula 1 World Championship History (1950-2024) dataset is a rich and detailed resource that offers extensive insights into one of the world’s most popular motorsports. Whether you are looking to conduct in-depth analysis, create visualizations, or simply explore the history of Formula 1, this dataset is an excellent starting point. ...

39.8% of workers from the Indian ethnic group were in 'professional' jobs in 2021 – the highest percentage out of all ethnic groups in this role.

BackgroundThe IRONMAN® (IM) triathlon is a popular multi-sport, where age group athletes often strive to qualify for the IM World Championship in Hawaii. The aim of the present study was to investigate the location of the fastest IM racecourses for age group IM triathletes. This knowledge will help IM age group triathletes find the best racecourse, considering their strengths and weaknesses, to qualify.ObjectiveTo determine the fastest IM racecourse for age group IM triathletes using descriptive and predictive statistical methods.MethodsWe collected and analyzed 677,702 age group IM finishers’ records from 228 countries participating in 444 IM competitions held between 2002 and 2022 across 66 event locations. Locations were ranked by average race speed (performance), and countries were sorted by number of records in the sample (participation). A predictive model was built with race finish time as the predicted variable and the triathlete’s gender, age group, country of origin, event location, average air, and water temperatures in each location as predictors. The model was trained with 75% of the available data and was validated against the remaining 25%. Several model interpretability tools were used to explore how each predictor contributed to the model’s predictive power, from which we intended to infer whether one or more predictors were more important than the others.ResultsThe average race speed ranking showed IM Vitoria-Gasteiz (1 race only), IM Copenhagen (8 races), IM Hawaii (18 races), IM Tallinn (4 races) and IM Regensburg (2 races) in the first five positions. The XG Boost Regressor model analysis indicated that the IM Hawaii course was the fastest race course and that male athletes aged 35 years and younger were the fastest. Most of the finishers were competing in IM triathlons held in the US, such as IM Wisconsin, IM Florida, IM Lake Placid, IM Arizona, and IM Hawaii, where the IM World Championship took place. However, the fastest average times were achieved in IM Vitoria-Gasteiz, IM Copenhagen, IM Hawaii, IM Tallin, IM Regensburg, IM Brazil Florianopolis, IM Barcelona, or IM Austria with the absolutely fastest race time in IM Hawaii. Most of the successful IM finishers originated from the US, followed by athletes from the UK, Canada, Australia, Germany, and France. The best mean IM race times were achieved by athletes from Austria, Germany, Belgium, Switzerland, Finland, and Denmark. Regarding environmental conditions, the best IM race times were achieved at an air temperature of ∼27°C and a water temperature of ∼24°C.ConclusionsIM age group athletes who intend to qualify for IM World Championship in IM Hawaii are encouraged to participate in IM Austria, IM Copenhagen, IM Brazil Florianopolis, and/or IM Barcelona in order to achieve a fast race time to qualify for the IM World Championship in IM Hawaii where the top race times were achieved. Most likely these races offer the best ambient temperatures for a fast race time.

The world's population first reached one billion people in 1805, and reached eight billion in 2022, and will peak at almost 10.2 billion by the end of the century. Although it took thousands of years to reach one billion people, it did so at the beginning of a phenomenon known as the demographic transition; from this point onwards, population growth has skyrocketed, and since the 1960s the population has increased by one billion people every 12 to 15 years. The demographic transition sees a sharp drop in mortality due to factors such as vaccination, sanitation, and improved food supply; the population boom that follows is due to increased survival rates among children and higher life expectancy among the general population; and fertility then drops in response to this population growth. Regional differences The demographic transition is a global phenomenon, but it has taken place at different times across the world. The industrialized countries of Europe and North America were the first to go through this process, followed by some states in the Western Pacific. Latin America's population then began growing at the turn of the 20th century, but the most significant period of global population growth occurred as Asia progressed in the late-1900s. As of the early 21st century, almost two-thirds of the world's population lives in Asia, although this is set to change significantly in the coming decades. Future growth The growth of Africa's population, particularly in Sub-Saharan Africa, will have the largest impact on global demographics in this century. From 2000 to 2100, it is expected that Africa's population will have increased by a factor of almost five. It overtook Europe in size in the late 1990s, and overtook the Americas a few years later. In contrast to Africa, Europe's population is now in decline, as birth rates are consistently below death rates in many countries, especially in the south and east, resulting in natural population decline. Similarly, the population of the Americas and Asia are expected to go into decline in the second half of this century, and only Oceania's population will still be growing alongside Africa. By 2100, the world's population will have over three billion more than today, with the vast majority of this concentrated in Africa. Demographers predict that climate change is exacerbating many of the challenges that currently hinder progress in Africa, such as political and food instability; if Africa's transition is prolonged, then it may result in further population growth that would place a strain on the region's resources, however, curbing this growth earlier would alleviate some of the pressure created by climate change.

According to the Wikipedia, an ultramarathon, also called ultra distance or ultra running, is any footrace longer than the traditional marathon length of 42.195 kilometres (26 mi 385 yd). Various distances are raced competitively, from the shortest common ultramarathon of 31 miles (50 km) to over 200 miles (320 km). 50k and 100k are both World Athletics record distances, but some 100 miles (160 km) races are among the oldest and most prestigious events, especially in North America.}

The data in this file is a large collection of ultra-marathon race records registered between 1798 and 2022 (a period of well over two centuries) being therefore a formidable long term sample. All data was obtained from public websites.

Despite the original data being of public domain, the race records, which originally contained the athlete´s names, have been anonymized to comply with data protection laws and to preserve the athlete´s privacy. However, a column Athlete ID has been created with a numerical ID representing each unique runner (so if Antonio Fernández participated in 5 races over different years, then the corresponding race records now hold his unique Athlete ID instead of his name). This way I have preserved valuable information.

The dataset contains 7,461,226 ultra-marathon race records from 1,641,168 unique athletes.

The following columns (with data types) are included:

• Year of event (int64)
• Event dates (object)
• Event name (object)
• Event distance/length (object)
• Event number of finishers (int64)
• Athlete performance (object)
• Athlete club (object)
• Athlete country (object)
• Athlete year of birth (float64)
• Athlete gender (object)
• Athlete age category (object)
• Athlete average speed (object)
• Athlete ID (int64)

The Event name column include country location information that can be derived to a new column, and similarly seasonal information can be found in the Event dates column beyond the Year of event (these can be extracted with a bit of processing).

The Event distance/length column describes the type of race, covering the most popular UM race distances and lengths, and some other specific modalities (multi-day, etc.):

• Distances: 50km, 100km, 50mi, 100mi
• Lengths: 6h, 12h, 24h, 48h, 72h, 6d, 10d

Additionally, there is information of age, gender and speed (in km/h) in other columns.