Apple is one of the most influential and recognisable brands in the world, responsible for the rise of the smartphone with the iPhone. Valued at over $2 trillion in 2021, it is also the most valuable...

Apple revenue for the twelve months ending March 31, 2025 was $400.366B, a 4.91% increase year-over-year. Apple annual revenue for 2024 was $391.035B, a 2.02% increase from 2023. Apple annual revenue for 2023 was $383.285B, a 2.8% decline from 2022. Apple annual revenue for 2022 was $394.328B, a 7.79% increase from 2021.

In the first quarter of its 2025 fiscal year, Apple generated around ** billion U.S. dollars in revenue from the sales of iPhones. Apple iPhone revenue The Apple iPhone is one of the biggest success stories in the smartphone industry. Since its introduction to the market in 2007, Apple has sold more than *** billion units worldwide. As of the third quarter of 2024, the Apple iPhone’s market share of new smartphone sales was over ** percent. Much of its accomplishments can be attributed to Apple’s ability to keep the product competitive throughout the years, with new releases and updates. Apple iPhone growth The iPhone has shown to be a crucial product for Apple, considering that the iPhone’s share of the company’s total revenue has consistently grown over the years. In the first quarter of 2009, the iPhone sales were responsible for about ********* of Apple’s revenue. In the third quarter of FY 2024, this figure reached a high of roughly ** percent, equating to less than ** billion U.S. dollars in that quarter. In terms of units sold, Apple went from around **** million units in 2010 to about *** million in 2023, but registered a peak in the fourth quarter of 2020 with more than ** million iPhones sold worldwide.

Analysis of ‘Apple (AAPL) Historical Stock Data’ provided by Analyst-2 (analyst-2.ai), based on source dataset retrieved from https://www.kaggle.com/tarunpaparaju/apple-aapl-historical-stock-data on 28 January 2022.

--- Dataset description provided by original source is as follows ---

This dataset contains Apple's (AAPL) stock data for the last 10 years (from 2010 to date). I believe insights from this data can be used to build useful price forecasting algorithms to aid investment. I would like to thank Nasdaq for providing access to this rich dataset. I will make sure I update this dataset every few months.

--- Original source retains full ownership of the source dataset ---

Apple App Store dataset to explore detailed information on app popularity, user feedback, and monetization features. Popular use cases include market trend analysis, app performance evaluation, and consumer behavior insights in the mobile app ecosystem.

Use our Apple App Store dataset to gain comprehensive insights into the mobile app ecosystem, including app popularity, user ratings, monetization features, and user feedback. This dataset covers various aspects of apps, such as descriptions, categories, and download metrics, offering a full picture of app performance and trends.

Tailored for marketers, developers, and industry analysts, this dataset allows you to track market trends, identify emerging apps, and refine promotional strategies. Whether you're optimizing app development, analyzing competitive landscapes, or forecasting market opportunities, the Apple App Store dataset is an essential tool for making data-driven decisions in the ever-evolving mobile app industry.

Dataset Features

• url: The URL linking to the app’s page on the Apple App Store.
• title: The name of the app.
• sub_title: A brief subtitle or tagline for the app.
• developer: The name of the entity or individual that developed the app.
• top_charts: Indicates if the app appears in top charts.
• monetization_features: Information on monetization aspects (such as in-app purchases or advertisements).
• image: A reference to the main app image.
• screenshots: Contains screenshot images of the app.
• description: Detailed app description outlining main features.
• what_new: Details on the latest updates or new features.
• rating: The overall rating based on user reviews.
• number_of_raters: The total number of users who have rated the app.
• reviews_by_stars: Breakdown of the number of reviews by star rating.
• reviews: An aggregation of user reviews.
• events: Any associated events or promotions.
• data_linked_to_you: Indicates if any data is linked to the user.
• seller: The entity responsible for selling or distributing the app.
• category: The category or genre of the app.
• languages: Languages supported by the app.
• copyright: Copyright information provided by the developer.
• size: The file size of the app.
• compatibility: Device or OS compatibility details.
• age_rating: The recommended age rating for the app.
• price: The price of the app.
• In_app_purchases: Details on in-app purchase options.
• support: Information related to app support.
• more_by_this_developer: Suggestions for other apps by the same developer.
• you_might_also_like: Recommendations for similar apps.
• app_support: Additional support details.
• privacy_policy: Link or reference to the app’s privacy policy.
• developer_website: The website of the app developer.
• featured_in: Information on any features or showcases the app has being part of.
• country: The country from which the app’s data was sourced.
• timestamp: A timestamp indicating when the data record was last updated.
• latest_app_version: The most recent version of the app available.
• app_id: A unique identifier for the app.

Distribution

• Data Volume: 36 Columns and 68M Rows
• Format: CSV

Usage

This dataset is versatile and can be used for various applications: - Market Analysis: Analyze app pricing strategies, monetization features, and category distribution to understand market trends and opportunities in the App Store. This can help developers and businesses make informed decisions about their app development and pricing strategies. - User Experience Research: Study the relationship between app ratings, number of reviews, and app features to understand what drives user satisfaction. The detailed review data and ratings can provide insights into user preferences and pain points. - Competitive Intelligence: Track and analyze apps within specific categories, comparing features, pricing, and user engagement metrics to identify successful patterns and market gaps. Particularly useful for developers planning new apps or improving existing ones. - Performance Prediction: Build predictive models using features like app size, category, pricing, and language support to forecast potential app success metrics. This can help in making data-driven decisions during app development. - Localization Strategy: Analyze the languages supported and regional performance to inform decisions about app localization and international market expansion.

Coverage

• Geographic Coverage: Global

License

CUSTOM Please review the respective licenses below: 1. Data Provider's License - Bright Data Master Service Agreement

Who Can Use It

• Data Scientists: Can leverage this dataset for training machine learning algorithms and building predictive models concerning app tr

The number of Apple iPhone unit sales dramatically increased between 2007 and 2023. Indeed, in 2007, when the iPhone was first introduced, Apple shipped around *** million smartphones. By 2023, this number reached over *** million units. The newest models and iPhone’s lasting popularity Apple has ventured into its 17th smartphone generation with its Phone ** lineup, which, released in September 2023, includes the **, ** Plus, ** Pro and Pro Max. Powered by the A16 bionic chip and running on iOS **, these models present improved displays, cameras, and functionalities. On the one hand, such features come, however, with hefty price tags, namely, an average of ***** U.S. dollars. On the other hand, they contribute to making Apple among the leading smartphone vendors worldwide, along with Samsung and Xiaomi. In the first quarter of 2024, Samsung shipped over ** million smartphones, while Apple recorded shipments of roughly ** million units. Success of Apple’s other products Apart from the iPhone, which is Apple’s most profitable product, Apple is also the inventor of other heavy-weight players in the consumer electronics market. The Mac computer and the iPad, like the iPhone, are both pioneers in their respective markets and have helped popularize the use of PCs and tablets. The iPad is especially successful, having remained as the largest vendor in the tablet market ever since its debut. The hottest new Apple gadget is undoubtedly the Apple Watch, which is a line of smartwatches that has fitness tracking capabilities and can be integrated via iOS with other Apple products and services. The Apple Watch has also been staying ahead of other smart watch vendors since its initial release and secures around ** percent of the market share as of the latest quarter.

Apple App Store Key StatisticsApps & Games in the Apple App StoreApps in the Apple App StoreGames in the Apple App StoreMost Popular Apple App Store CategoriesPaid vs Free Apps in Apple App...

Browse Apple Inc (AAPL) market data. Get instant pricing estimates and make batch downloads of binary, CSV, and JSON flat files.

Consolidated last sale, exchange BBO and national BBO across all US equity options exchanges. Includes single name stock options (e.g. TSLA), options on ETFs (e.g. SPY, QQQ), index options (e.g. VIX), and some indices (e.g. SPIKE and VSPKE). This dataset is based on the newer, binary OPRA feed after the migration to SIAC's OPRA Pillar SIP in 2021. OPRA is notable for the size of its data and we recommend users to anticipate several TBs of data per day for the full dataset in its highest granularity (MBP-1).

Origin: Options Price Reporting Authority

Supported data encodings: DBN, JSON, CSV Learn more

Supported market data schemas: MBP-1, OHLCV-1s, OHLCV-1m, OHLCV-1h, OHLCV-1d, TBBO, Trades, Statistics, Definition Learn more

Resolution: Immediate publication, nanosecond-resolution timestamps

About this dataset

Context

The dataset presents the detailed breakdown of the count of individuals within distinct income brackets, categorizing them by gender (men and women) and employment type - full-time (FT) and part-time (PT), offering valuable insights into the diverse income landscapes within Apple River. The dataset can be utilized to gain insights into gender-based income distribution within the Apple River population, aiding in data analysis and decision-making..

Key observations

• Employment patterns: Within Apple River, among individuals aged 15 years and older with income, there were 93 men and 97 women in the workforce. Among them, 56 men were engaged in full-time, year-round employment, while 49 women were in full-time, year-round roles.
• Annual income under $24,999: Of the male population working full-time, 8.93% fell within the income range of under $24,999, while 8.16% of the female population working full-time was represented in the same income bracket.
• Annual income above $100,000: 1.79% of men in full-time roles earned incomes exceeding $100,000, while none of women in full-time positions earned within this income bracket.
• Refer to the research insights for more key observations on more income brackets ( Annual income under $24,999, Annual income between $25,000 and $49,999, Annual income between $50,000 and $74,999, Annual income between $75,000 and $99,999 and Annual income above $100,000) and employment types (full-time year-round and part-time)

Content

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

Income brackets:

• $1 to $2,499 or loss
• $2,500 to $4,999
• $5,000 to $7,499
• $7,500 to $9,999
• $10,000 to $12,499
• $12,500 to $14,999
• $15,000 to $17,499
• $17,500 to $19,999
• $20,000 to $22,499
• $22,500 to $24,999
• $25,000 to $29,999
• $30,000 to $34,999
• $35,000 to $39,999
• $40,000 to $44,999
• $45,000 to $49,999
• $50,000 to $54,999
• $55,000 to $64,999
• $65,000 to $74,999
• $75,000 to $99,999
• $100,000 or more

Variables / Data Columns

• Income Bracket: This column showcases 20 income brackets ranging from $1 to $100,000+..
• Full-Time Males: The count of males employed full-time year-round and earning within a specified income bracket
• Part-Time Males: The count of males employed part-time and earning within a specified income bracket
• Full-Time Females: The count of females employed full-time year-round and earning within a specified income bracket
• Part-Time Females: The count of females employed part-time and earning within a specified income bracket

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.

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

About this dataset

Context

The dataset tabulates the median household income in Apple Creek. It can be utilized to understand the trend in median household income and to analyze the income distribution in Apple Creek by household type, size, and across various income brackets.

Content

The dataset will have the following datasets when applicable

Please note: The 2020 1-Year ACS estimates data was not reported by the Census Bureau due to the impact on survey collection and analysis caused by COVID-19. Consequently, median household income data for 2020 is unavailable for large cities (population 65,000 and above).

• Apple Creek, OH Median Household Income Trends (2010-2021, in 2022 inflation-adjusted dollars)
• Median Household Income Variation by Family Size in Apple Creek, OH: Comparative analysis across 7 household sizes
• Income Distribution by Quintile: Mean Household Income in Apple Creek, OH
• Apple Creek, OH households by income brackets: family, non-family, and total, 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/.

Interested in deeper insights and visual analysis?

Explore our comprehensive data analysis and visual representations for a deeper understanding of Apple Creek median household income. You can refer the same here

Apple

## Overview

Apple is a dataset for object detection tasks - it contains Apples annotations for 284 images.

## Getting Started

You can download this dataset for use within your own projects, or fork it into a workspace on Roboflow to create your own model.

  ## License

  This dataset is available under the [MIT license](https://creativecommons.org/licenses/MIT).

Total Apple

## Overview

Total Apple is a dataset for object detection tasks - it contains Apple Data annotations for 700 images.

## Getting Started

You can download this dataset for use within your own projects, or fork it into a workspace on Roboflow to create your own model.

  ## License

  This dataset is available under the [CC BY 4.0 license](https://creativecommons.org/licenses/CC BY 4.0).

Only Apple

## Overview

Only Apple is a dataset for object detection tasks - it contains Apple annotations for 205 images.

## Getting Started

You can download this dataset for use within your own projects, or fork it into a workspace on Roboflow to create your own model.

  ## License

  This dataset is available under the [MIT license](https://creativecommons.org/licenses/MIT).

About this dataset

Context

The dataset presents the distribution of median household income among distinct age brackets of householders in Apple River town. Based on the latest 2019-2023 5-Year Estimates from the American Community Survey, it displays how income varies among householders of different ages in Apple River town. It showcases how household incomes typically rise as the head of the household gets older. The dataset can be utilized to gain insights into age-based household income trends and explore the variations in incomes across households.

Key observations: Insights from 2023

In terms of income distribution across age cohorts, in Apple River town, the median household income stands at $113,438 for householders within the 25 to 44 years age group, followed by $92,167 for the 45 to 64 years age group. Notably, householders within the 65 years and over age group, had the lowest median household income at $46,607.

Content

When available, the data consists of estimates from the U.S. Census Bureau American Community Survey (ACS) 2019-2023 5-Year Estimates. All incomes have been adjusting for inflation and are presented in 2023-inflation-adjusted dollars.

Age groups classifications include:

• Under 25 years
• 25 to 44 years
• 45 to 64 years
• 65 years and over

Variables / Data Columns

• Age Of The Head Of Household: This column presents the age of the head of household
• Median Household Income: Median household income, in 2023 inflation-adjusted dollars for the specific age group

Good to know

Margin of Error

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

Custom data

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

Inspiration

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

Recommended for further research

This dataset is a part of the main dataset for Apple River town median household income by age. You can refer the same here

About this dataset

Context

The dataset tabulates the median household income in Apple Valley. It can be utilized to understand the trend in median household income and to analyze the income distribution in Apple Valley by household type, size, and across various income brackets.

Content

The dataset will have the following datasets when applicable

Please note: The 2020 1-Year ACS estimates data was not reported by the Census Bureau due to the impact on survey collection and analysis caused by COVID-19. Consequently, median household income data for 2020 is unavailable for large cities (population 65,000 and above).

• Apple Valley, MN Median Household Income Trends (2010-2021, in 2022 inflation-adjusted dollars)
• Median Household Income Variation by Family Size in Apple Valley, MN: Comparative analysis across 7 household sizes
• Income Distribution by Quintile: Mean Household Income in Apple Valley, MN
• Apple Valley, MN households by income brackets: family, non-family, and total, 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/.

Interested in deeper insights and visual analysis?

Explore our comprehensive data analysis and visual representations for a deeper understanding of Apple Valley median household income. You can refer the same here

Apple 75

## Overview

Apple 75 is a dataset for object detection tasks - it contains Objects annotations for 432 images.

## Getting Started

You can download this dataset for use within your own projects, or fork it into a workspace on Roboflow to create your own model.

  ## License

  This dataset is available under the [CC BY 4.0 license](https://creativecommons.org/licenses/CC BY 4.0).

About this dataset

Context

The dataset presents the mean household income for each of the five quintiles in Apple River, IL, as reported by the U.S. Census Bureau. The dataset highlights the variation in mean household income across quintiles, offering valuable insights into income distribution and inequality.

Key observations

• Income disparities: The mean income of the lowest quintile (20% of households with the lowest income) is 22,193, while the mean income for the highest quintile (20% of households with the highest income) is 119,015. This indicates that the top earners earn 5 times compared to the lowest earners.
• *Top 5%: * The mean household income for the wealthiest population (top 5%) is 164,201, which is 137.97% higher compared to the highest quintile, and 739.88% higher compared to the lowest quintile.

Content

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

Income Levels:

• Lowest Quintile
• Second Quintile
• Third Quintile
• Fourth Quintile
• Highest Quintile
• Top 5 Percent

Variables / Data Columns

• Income Level: This column showcases the income levels (As mentioned above).
• Mean Household Income: Mean household income, in 2023 inflation-adjusted dollars for the specific income level.

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 Apple River median household income. You can refer the same here

About this dataset

Context

The dataset tabulates the median household income in Apple River town. It can be utilized to understand the trend in median household income and to analyze the income distribution in Apple River town by household type, size, and across various income brackets.

Content

The dataset will have the following datasets when applicable

Please note: The 2020 1-Year ACS estimates data was not reported by the Census Bureau due to the impact on survey collection and analysis caused by COVID-19. Consequently, median household income data for 2020 is unavailable for large cities (population 65,000 and above).

• Apple River, Wisconsin Median Household Income Trends (2010-2021, in 2022 inflation-adjusted dollars)
• Median Household Income Variation by Family Size in Apple River, Wisconsin: Comparative analysis across 7 household sizes
• Income Distribution by Quintile: Mean Household Income in Apple River, Wisconsin
• Apple River, Wisconsin households by income brackets: family, non-family, and total, 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/.

Interested in deeper insights and visual analysis?

Explore our comprehensive data analysis and visual representations for a deeper understanding of Apple River town median household income. You can refer the same here

About this dataset

Context

The dataset presents the distribution of median household income among distinct age brackets of householders in Apple Creek. Based on the latest 2019-2023 5-Year Estimates from the American Community Survey, it displays how income varies among householders of different ages in Apple Creek. It showcases how household incomes typically rise as the head of the household gets older. The dataset can be utilized to gain insights into age-based household income trends and explore the variations in incomes across households.

Key observations: Insights from 2023

In terms of income distribution across age cohorts, in Apple Creek, householders within the 45 to 64 years age group have the highest median household income at $89,167, followed by those in the 25 to 44 years age group with an income of $74,107. Meanwhile householders within the under 25 years age group report the second lowest median household income of $63,438. Notably, householders within the 65 years and over age group, had the lowest median household income at $44,375.

Content

When available, the data consists of estimates from the U.S. Census Bureau American Community Survey (ACS) 2019-2023 5-Year Estimates. All incomes have been adjusting for inflation and are presented in 2023-inflation-adjusted dollars.

Age groups classifications include:

• Under 25 years
• 25 to 44 years
• 45 to 64 years
• 65 years and over

Variables / Data Columns

• Age Of The Head Of Household: This column presents the age of the head of household
• Median Household Income: Median household income, in 2023 inflation-adjusted dollars for the specific age group

Good to know

Margin of Error

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

Custom data

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

Inspiration

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

Recommended for further research

This dataset is a part of the main dataset for Apple Creek median household income by age. You can refer the same here

About this dataset

Context

The dataset presents the mean household income for each of the five quintiles in Apple Creek, OH, as reported by the U.S. Census Bureau. The dataset highlights the variation in mean household income across quintiles, offering valuable insights into income distribution and inequality.

Key observations

• Income disparities: The mean income of the lowest quintile (20% of households with the lowest income) is 27,123, while the mean income for the highest quintile (20% of households with the highest income) is 146,301. This indicates that the top earners earn 5 times compared to the lowest earners.
• *Top 5%: * The mean household income for the wealthiest population (top 5%) is 179,412, which is 122.63% higher compared to the highest quintile, and 661.48% higher compared to the lowest quintile.

Content

When available, the data consists of estimates from the U.S. Census Bureau American Community Survey (ACS) 2017-2021 5-Year Estimates.

Income Levels:

• Lowest Quintile
• Second Quintile
• Third Quintile
• Fourth Quintile
• Highest Quintile
• Top 5 Percent

Variables / Data Columns

• Income Level: This column showcases the income levels (As mentioned above).
• Mean Household Income: Mean household income, in 2022 inflation-adjusted dollars for the specific income level.

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 Apple Creek median household income. You can refer the same here