About this dataset

Context

The dataset tabulates the Indian Wells population distribution across 18 age groups. It lists the population in each age group along with the percentage population relative of the total population for Indian Wells. The dataset can be utilized to understand the population distribution of Indian Wells by age. For example, using this dataset, we can identify the largest age group in Indian Wells.

Key observations

The largest age group in Indian Wells, CA was for the group of age 55-59 years with a population of 708 (14.67%), according to the 2021 American Community Survey. At the same time, the smallest age group in Indian Wells, CA was the 0-4 years with a population of 39 (0.81%). Source: U.S. Census Bureau American Community Survey (ACS) 2017-2021 5-Year Estimates.

Content

When available, the data consists of estimates from the U.S. Census Bureau American Community Survey (ACS) 2017-2021 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 in consideration
• Population: The population for the specific age group in the Indian Wells is shown in this column.
• % of Total Population: This column displays the population of each age group as a proportion of Indian Wells 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 Indian Wells Population by Age. You can refer the same here

About this dataset

Context

The dataset tabulates the Indian Shores population over the last 20 plus years. It lists the population for each year, along with the year on year change in population, as well as the change in percentage terms for each year. The dataset can be utilized to understand the population change of Indian Shores across the last two decades. For example, using this dataset, we can identify if the population is declining or increasing. If there is a change, when the population peaked, or if it is still growing and has not reached its peak. We can also compare the trend with the overall trend of United States population over the same period of time.

Key observations

In 2023, the population of Indian Shores was 1,192, a 0.50% decrease year-by-year from 2022. Previously, in 2022, Indian Shores population was 1,198, a decline of 0.17% compared to a population of 1,200 in 2021. Over the last 20 plus years, between 2000 and 2023, population of Indian Shores decreased by 511. In this period, the peak population was 1,777 in the year 2004. The numbers suggest that the population has already reached its peak and is showing a trend of decline. Source: U.S. Census Bureau Population Estimates Program (PEP).

Content

When available, the data consists of estimates from the U.S. Census Bureau Population Estimates Program (PEP).

Data Coverage:

• From 2000 to 2023

Variables / Data Columns

• Year: This column displays the data year (Measured annually and for years 2000 to 2023)
• Population: The population for the specific year for the Indian Shores is shown in this column.
• Year on Year Change: This column displays the change in Indian Shores population for each year compared to the previous year.
• Change in Percent: This column displays the year on year change as a percentage. 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 Indian Shores Population by Year. You can refer the same here

About this dataset

Context

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

Key observations

The percent distribution of Indian Beach population by race (across all racial categories recognized by the U.S. Census Bureau): 98.22% are white, 1.33% are Black or African American and 0.44% are some other race.

Content

When available, the data consists of estimates from the U.S. Census Bureau American Community Survey (ACS) 2018-2022 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 Indian Beach
• Population: The population of the racial category (excluding ethnicity) in the Indian Beach is shown in this column.
• % of Total Population: This column displays the percentage distribution of each race as a proportion of Indian Beach 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 Indian Beach Population by Race & Ethnicity. You can refer the same here

Number of Overseas Indian Students: Destination: United States of America data was reported at 97,613.000 Person in 2014. This records an increase from the previous number of 92,597.000 Person for 2013. Number of Overseas Indian Students: Destination: United States of America data is updated yearly, averaging 84,865.500 Person from Dec 1999 (Median) to 2014, with 16 observations. The data reached an all-time high of 103,968.000 Person in 2010 and a record low of 34,504.000 Person in 1999. Number of Overseas Indian Students: Destination: United States of America data remains active status in CEIC and is reported by United Nations Educational, Scientific and Cultural Organization. The data is categorized under India Premium Database’s Education Sector – Table IN.EDE001: Memo Items: Major Destinations of Overseas Indian Students.

Access a comprehensive dataset of Indian agents and US customers discussing travel in English. Perfect for AI development, linguistics, and research.

The TIGER/Line shapefiles and related database files (.dbf) are an extract of selected geographic and cartographic information from the U.S. Census Bureau's Master Address File / Topologically Integrated Geographic Encoding and Referencing (MAF/TIGER) Database (MTDB). The MTDB represents a seamless national file with no overlaps or gaps between parts, however, each TIGER/Line shapefile is designed to stand alone as an independent data set, or they can be combined to cover the entire nation. American Indian tribal subdivisions are administrative subdivisions of federally recognized American Indian reservations/off-reservation trust lands or Oklahoma tribal statistical areas (OTSAs). These entities are internal units of self-government and/or administration that serve social, cultural, and/or economic purposes for the American Indian tribe or tribes on the reservations/off-reservation trust lands or OTSAs. The Census Bureau obtains the boundary and attribute information for tribal subdivisions on federally recognized American Indian reservations and off-reservation trust lands from federally recognized tribal governments through the Census Bureau's Boundary and Annexation Survey (BAS). For the 2020 Census, the boundaries for tribal subdivisions on OTSAs were also obtained from federally recognized tribal governments through the Participant Statistical Areas Program (PSAP). Note that tribal subdivisions do not exist on all reservations/off-reservation trust lands or OTSAs, rather only where they were submitted to the Census Bureau by the federally recognized tribal government for that area. The boundaries for American Indian tribal subdivisions are as of January 1, 2020, as reported by the federally recognized tribal governments through the Census Bureau's Boundary and Annexation Survey (BAS). The boundaries for tribal subdivisions on OTSAs are those reported as of January 1, 2020 through PSAP.

About this dataset

Context

The dataset presents median income data over a decade or more for males and females categorized by Total, Full-Time Year-Round (FT), and Part-Time (PT) employment in Indian Beach. It showcases annual income, providing insights into gender-specific income distributions and the disparities between full-time and part-time work. The dataset can be utilized to gain insights into gender-based pay disparity trends and explore the variations in income for male and female individuals.

Key observations: Insights from 2021

Based on our analysis ACS 2017-2021 5-Year Estimates, we present the following observations: - All workers, aged 15 years and older: In Indian Beach, the median income for all workers aged 15 years and older, regardless of work hours, was $54,046 for males and $24,321 for females.

These income figures highlight a substantial gender-based income gap in Indian Beach. Women, regardless of work hours, earn 45 cents for each dollar earned by men. This significant gender pay gap, approximately 55%, underscores concerning gender-based income inequality in the town of Indian Beach.

As income data for both males and females was unavailable, conducting a comprehensive analysis of gender-based pay disparity in the town of Indian Beach was not possible.

https://i.neilsberg.com/ch/indian-beach-nc-income-by-gender.jpeg" alt="Indian Beach, NC gender based income disparity">

Content

When available, the data consists of estimates from the U.S. Census Bureau American Community Survey (ACS) 2017-2021 5-Year Estimates. All incomes have been adjusting for inflation and are presented in 2022-inflation-adjusted dollars.

Gender classifications include:

• Male
• Female

Employment type classifications include:

• Full-time, year-round: A full-time, year-round worker is a person who worked full time (35 or more hours per week) and 50 or more weeks during the previous calendar year.
• Part-time: A part-time worker is a person who worked less than 35 hours per week during the previous calendar year.

Variables / Data Columns

• Year: This column presents the data year. Expected values are 2010 to 2022
• Male Total Income: Annual median income, for males regardless of work hours
• Male FT Income: Annual median income, for males working full time, year-round
• Male PT Income: Annual median income, for males working part time
• Female Total Income: Annual median income, for females regardless of work hours
• Female FT Income: Annual median income, for females working full time, year-round
• Female PT Income: Annual median income, for females working part time

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 Indian Beach median household income by gender. You can refer the same here

The Bureau of the Census has released Census 2000 Summary File 1 (SF1) 100-Percent data. The file includes the following population items: sex, age, race, Hispanic or Latino origin, household relationship, and household and family characteristics. Housing items include occupancy status and tenure (whether the unit is owner or renter occupied). SF1 does not include information on incomes, poverty status, overcrowded housing or age of housing. These topics will be covered in Summary File 3. Data are available for states, counties, county subdivisions, places, census tracts, block groups, and, where applicable, American Indian and Alaskan Native Areas and Hawaiian Home Lands. The SF1 data are available on the Bureau's web site and may be retrieved from American FactFinder as tables, lists, or maps. Users may also download a set of compressed ASCII files for each state via the Bureau's FTP server. There are over 8000 data items available for each geographic area. The full listing of these data items is available here as a downloadable compressed data base file named TABLES.ZIP. The uncompressed is in FoxPro data base file (dbf) format and may be imported to ACCESS, EXCEL, and other software formats. While all of this information is useful, the Office of Community Planning and Development has downloaded selected information for all states and areas and is making this information available on the CPD web pages. The tables and data items selected are those items used in the CDBG and HOME allocation formulas plus topics most pertinent to the Comprehensive Housing Affordability Strategy (CHAS), the Consolidated Plan, and similar overall economic and community development plans. The information is contained in five compressed (zipped) dbf tables for each state. When uncompressed the tables are ready for use with FoxPro and they can be imported into ACCESS, EXCEL, and other spreadsheet, GIS and database software. The data are at the block group summary level. The first two characters of the file name are the state abbreviation. The next two letters are BG for block group. Each record is labeled with the code and name of the city and county in which it is located so that the data can be summarized to higher-level geography. The last part of the file name describes the contents . The GEO file contains standard Census Bureau geographic identifiers for each block group, such as the metropolitan area code and congressional district code. The only data included in this table is total population and total housing units. POP1 and POP2 contain selected population variables and selected housing items are in the HU file. The MA05 table data is only for use by State CDBG grantees for the reporting of the racial composition of beneficiaries of Area Benefit activities. The complete package for a state consists of the dictionary file named TABLES, and the five data files for the state. The logical record number (LOGRECNO) links the records across tables.

viber1/indian-law-dataset dataset hosted on Hugging Face and contributed by the HF Datasets community

The TIGER/Line shapefiles and related database files (.dbf) are an extract of selected geographic and cartographic information from the U.S. Census Bureau's Master Address File / Topologically Integrated Geographic Encoding and Referencing (MAF/TIGER) Database (MTDB). The MTDB represents a seamless national filewith no overlaps or gaps between parts, however, each TIGER/Line File is designed to stand alone as an independent dataset, or they can be combined to cover the entire nation. The Area Hydrography Shapefile contains the geometry and attributes of both perennial and intermittent area hydrography features, including ponds, lakes, oceans, swamps (up to the U.S. nautical three-mile limit), glaciers, and the area covered by large rivers, streams, and/or canals that are represented as double-line drainage. Single-line drainage water features can be found in the Linear Hydrography Shapefile (LINEARWATER.shp). Linear water features includes single-line drainage water features and artificial path features, where they exist, that run through double-line drainage features such as rivers, streams, and/or canals, and serve as a linear representation of these features.

Dataset Card for Indian Foods Dataset

  Dataset Summary

This is a multi-category(multi-class classification) related Indian food dataset showcasing The-massive-Indian-Food-Dataset. This card has been generated using this raw template.

  Supported Tasks and Leaderboards

[More Information Needed]

  Languages

English

  Dataset Structure

{ "image": "Image(decode=True, id=None)", "target": "ClassLabel(names=['biryani', 'cholebhature'… See the full description on the dataset page: https://huggingface.co/datasets/bharat-raghunathan/indian-foods-dataset.

About this dataset

Context

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

Key observations

The percent distribution of Ontario population by race (across all racial categories recognized by the U.S. Census Bureau): 69.39% are white, 0.67% are Black or African American, 3.18% are American Indian and Alaska Native, 2.19% are Asian, 6.40% are some other race and 18.17% 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 Ontario
• Population: The population of the racial category (excluding ethnicity) in the Ontario is shown in this column.
• % of Total Population: This column displays the percentage distribution of each race as a proportion of Ontario 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 Ontario Population by Race & Ethnicity. You can refer the same here

India Imports from United States was US$38.99 Billion during 2024, according to the United Nations COMTRADE database on international trade. India Imports from United States - data, historical chart and statistics - was last updated on September of 2025.

Legal Embedding Dataset

This dataset was created to finetune embedding models for generating domain-specific embeddings on Indian legal texts, specifically SEBI (Securities and Exchange Board of India) documents. Data SourcePublicly available SEBI PDF documents were parsed and processed. Data Preparation

PDFs were parsed to extract raw text, Text was chunked into manageable segments.
For each chunk, a question was generated using gpt-4o-mini.
Each question is directly… See the full description on the dataset page: https://huggingface.co/datasets/axondendriteplus/legal-rag-embedding-dataset.

The TIGER/Line shapefiles and related database files (.dbf) are an extract of selected geographic and cartographic information from the U.S. Census Bureau's Master Address File / Topologically Integrated Geographic Encoding and Referencing (MAF/TIGER) Database (MTDB). The MTDB represents a seamless national file with no overlaps or gaps between parts, however, each TIGER/Line shapefile is designed to stand alone as an independent data set, or they can be combined to cover the entire nation. The American Indian/Alaska Native/Native Hawaiian (AIANNH) Areas Shapefile includes the following legal entities: federally recognized American Indian reservations and off-reservation trust land areas, state-recognized American Indian reservations, and Hawaiian home lands (HHLs). The statistical entities included are Alaska Native village statistical areas (ANVSAs), Oklahoma tribal statistical areas (OTSAs), tribal designated statistical areas (TDSAs), and state designated tribal statistical areas (SDTSAs). Joint use areas are also included in this shapefile refer to areas that are administered jointly and/or claimed by two or more American Indian tribes. The Census Bureau designates both legal and statistical joint use areas as unique geographic entities for the purpose of presenting statistical data. Note that tribal subdivisions and Alaska Native Regional Corporations (ANRCs) are additional types of American Indian/Alaska Native areas stored by the Census Bureau, but are displayed in separate shapefiles because of how they fall within the Census Bureau's geographic hierarchy. The State of Hawaii's Office of Hawaiian Home Lands provides the legal boundaries for the HHLs. The boundaries for ANVSAs, OTSAs, and TDSAs were delineated for the 2020 Census through the Participant Statistical Areas Program (PSAP) by participants from the federally recognized tribal governments. The Bureau of Indian Affairs (BIA) within the U.S. Department of the Interior (DOI) provides the list of federally recognized tribes and only provides legal boundary information when the tribes need supporting records, if a boundary is based on treaty or another document that is historical or open to legal interpretation, or when another tribal, state, or local government challenges the depiction of a reservation or off-reservation trust land. The boundaries for federally recognized American Indian reservations and off-reservation trust lands are as of January 1, 2022, as reported by the federally recognized tribal governments through the Census Bureau's Boundary and Annexation Survey (BAS). The boundaries for state-recognized American Indian reservations and for SDTSAs were delineated by a state governor-appointed liaisons for the 2020 Census through the State American Indian Reservation Program and PSAP respectively.

About this dataset

Context

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

Key observations

There is a majority of female population, with 56.64% 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 Indian Village is shown in this column.
• % of Total Population: This column displays the percentage distribution of each gender as a proportion of Indian Village 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 Indian Village Population by Race & Ethnicity. You can refer the same here

This dataset contains 1,196 unique Indian development cooperation projects worth US$14.58 billion geocoded to over 4,000 locations in 169 countries between 2007 and 2014.

The dataset shows Exchange Rate of the Indian Rupee vis-a-vis the SDR, US Dollar, Pound Sterling (High and Low During the Month)

Note: 1. The exchange rate for Japanese Yen is in Rupees per 100 Yen. 2. Data are based on FEDAI (Foreign Exchange Dealers' Association of India) indicative rates. 3. The Euro replaced the Deutsche Mark w.e.f. January 1, 1999. 4. From May , 2012 onwards data are based on RBI reference rate.

This Dataset comprises historic Data on the exchange rate between the United States dollar and Indian Rupees. The daily exchange rate is mentioned on a daily basis.

The Dataset comprises only 2 columns: 1. Date (DATE): span between 01-01-2000 to 31-12-2016. 2. The exchange rate between USD and Rupees (RATE): The exchange rate between USD and INR on any given day.

Indian Domestic Airline Flights (2018–2025) This dataset contains Indian domestic airline [103 - Airports] data covering the years 2018 to 2025. It includes flight numbers, airlines, and other relevant attributes for domestic routes within India. This dataset can be used for:

Flight delay prediction Airline trend analysis Route popularity insights

Column Descriptions

Column Name Descriptions

Airline Name of the airline operating the flight (e.g., IndiGo, Air India).

FlightNumber… See the full description on the dataset page: https://huggingface.co/datasets/Kabil007/IndianDomesticAirlineDataset.