Employee-Reviews Description Context Over 67k employee reviews for Google, Amazon, Facebook, Apple, and Microsoft

Content This dataset contains employee reviews separated into the following categories:

Index: index Company: Company name Location : This dataset is global, as such it may include the country's name in parenthesis [i.e "Toronto, ON(Canada)"]. However, if the location is in the USA then it will only include the city and state[i.e "Los Angeles, CA" ] Date Posted: in the following format MM DD, YYYY Job-Title: This string will also include whether the reviewer is a 'Current' or 'Former' Employee at the time of the review Summary: Short summary of employee review Pros: Pros Cons: Cons Overall Rating: 1-5 Work/Life Balance Rating: 1-5 Culture and Values Rating: 1-5 Career Opportunities Rating: 1-5 Comp & Benefits Rating: 1-5 Senior Management Rating: 1-5 Helpful Review Count: A count of how many people found the review to be helpful Link to Review : This will provide you with a direct link to the page that contains the review. However it is likely that this link will be outdated NOTE: 'none' is placed in all cells where no data value was found.

Acknowledgements This data was scraped from Glassdoor

3 Inspiration To inspire people to create ML models to search for meaningful trends within this dataset

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 Valley. The dataset can be utilized to gain insights into gender-based income distribution within the Apple Valley population, aiding in data analysis and decision-making..

Key observations

• Employment patterns: Within Apple Valley, among individuals aged 15 years and older with income, there were 528 men and 447 women in the workforce. Among them, 283 men were engaged in full-time, year-round employment, while 136 women were in full-time, year-round roles.
• Annual income under $24,999: Of the male population working full-time, 11.31% fell within the income range of under $24,999, while 13.97% of the female population working full-time was represented in the same income bracket.
• Annual income above $100,000: 30.04% of men in full-time roles earned incomes exceeding $100,000, while 6.62% 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 Valley median household income by race. You can refer the same here

Get preliminary apple crop production estimates, by variety of apple, for Ontario from 2012 to 2014.

Statistical data are compiled to serve as a source of agriculture and food statistics for the province of Ontario. Data are prepared primarily by Statistics and Economics staff of the Ministry of Agriculture, Food and Agribusiness, in co-operation with the Agriculture Division of Statistics Canada and various government departments and farm marketing boards.

This dataset provides a detailed breakdown of Apple’s greenhouse gas (GHG) emissions from 2015 to 2022, as the company works toward its goal of achieving net zero emissions by 2030. It includes: • All sources of emissions from corporate operations and the product life cycle • The carbon footprint of Apple’s baseline iPhone during the same period • Normalization factors such as sales, market capitalization, and number of employees

Recommended Analyses • How much has Apple reduced its emissions from 2015 to 2022? • How does this trend compare to Apple’s revenue and market cap trends over the same period? • Which areas have seen the most improvement? Which the least? • Is Apple on track to meet its 2030 net zero goal?

Context

Technology companies have become a dominant driver in recent years of economic growth, consumer tastes and the financial markets. The biggest tech stocks as a group, for example, have dramatically outpaced the broader market in the past decade.

That's because technology has reshaped in a major way how people communicate, consume information, shop, socialize, and work.

Broadly speaking, companies in the technology sector engage in the research, development, and manufacture of technologically based goods and services. They create software, and design and manufacture computers, mobile devices, and home appliances. They also provide products and services related to information technology.

Content

This dataset contains 3 files with the daily stock price and volume of the three companies: Google, Apple, and Facebook from 07/09/2017 to 07/09/2022. Source: Yahoo! Finance

Profile

Apple

Apple Inc. (AAPL) One Apple Park Way Cupertino, CA 95014 United States 408 996 1010 https://www.apple.com

Sector(s): Technology Industry: Consumer Electronics Full Time Employees: 154,000

Total Revenue (2021): $365,817,000
Net Income (2021):$94,680,000
Exchange: Nasdaq

Google

Alphabet Inc. (GOOG) 1600 Amphitheatre Parkway Mountain View, CA 94043 United States 650 253 0000 https://www.abc.xyz

Sector(s): Communication Services Industry: Internet Content & Information Full Time Employees: 174,014

Total Revenue (2021): $257,637,000 Net Income (2021):$76,033,000 Exchange: Nasdaq

Facebook

Meta Platforms, Inc. (META) 1601 Willow Road Menlo Park, CA 94025 United States 650 543 4800 https://investor.fb.com

Sector(s): Communication Services Industry: Internet Content & Information Full Time Employees: 83,553

Total Revenue (2021): $117,929,000 Net Income (2021):$39,370,000 Exchange: Nasdaq

Acknowledgements

Yahoo! Finance Investopedia Nasdaq

Start A New Notebook!

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 Creek. The dataset can be utilized to gain insights into gender-based income distribution within the Apple Creek population, aiding in data analysis and decision-making..

Key observations

• Employment patterns: Within Apple Creek, among individuals aged 15 years and older with income, there were 354 men and 343 women in the workforce. Among them, 227 men were engaged in full-time, year-round employment, while 155 women were in full-time, year-round roles.
• Annual income under $24,999: Of the male population working full-time, 1.32% fell within the income range of under $24,999, while 21.94% of the female population working full-time was represented in the same income bracket.
• Annual income above $100,000: 16.30% of men in full-time roles earned incomes exceeding $100,000, while 10.32% 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 Creek median household income by race. You can refer the same here

Get statistical data on harvested area, marketed production, average price, farm value and average yield for apple production in Ontario.

Statistical data are compiled to serve as a source of agriculture and food statistics for the province of Ontario. Data are prepared primarily by Statistics and Economics staff of the Ministry of Agriculture, Food and Agribusiness, in co-operation with the Agriculture Division of Statistics Canada and various government departments and farm marketing boards.

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

Get statistical data on marketed apple production, transaction price, grower price and average marketing costs by marketing channel such as: processing into juice, processing into non-juice, fresh market from 1994-2012.

Statistical data are compiled to serve as a source of agriculture and food statistics for the province of Ontario. Data are prepared primarily by Statistics and Economics staff of the Ministry of Agriculture, Food and Agribusiness, in co-operation with the Agriculture Division of Statistics Canada and various government departments and farm marketing boards.

Google 2020-2025 Stock Price

Alphabet Inc. is an American multinational technology conglomerate holding company headquartered in Mountain View, California. Alphabet is the world's second-largest technology company by revenue, after Apple, and one of the world's most valuable companies. It was created through a restructuring of Google on October 2, 2015, and became the parent holding company of Google and several former Google subsidiaries. It is considered one of the Big Five American information technology companies, alongside Amazon, Apple, Meta, and Microsoft.

The establishment of Alphabet Inc. was prompted by a desire to make the core Google business "cleaner and more accountable" while allowing greater autonomy to group companies that operate in businesses other than Internet services. Founders Larry Page and Sergey Brin announced their resignation from their executive posts in December 2019, with the CEO role to be filled by Sundar Pichai, who is also the CEO of Google. Page and Brin remain employees, board members, and controlling shareholders of Alphabet Inc.

Source: https://en.wikipedia.org/wiki/Alphabet_Inc.

Information about this dataset

This dataset provides historical data of GOOG. stock (Google). The data is available at a daily level. Currency is USD.

These terms are key indicators in stock market trading and analysis, providing information about a stock's price movements and trading activity over a specific period (e.g., a day, week, or month):

Close Price:

The final price at which a stock trades during a specific trading session (e.g., at the end of the day). This price is often used as a reference point for comparing daily price movements.

Open Price:

The first price at which a stock trades when the market opens for the day. It can be influenced by after-hours trading, news, or economic events.

High Price:

The highest price at which a stock trades during a specific trading session. It shows the maximum value reached by the stock in that period.

Low Price:

The lowest price at which a stock trades during a specific trading session. It represents the minimum value reached by the stock in that period.

Volume:

The total number of shares traded during a specific period. It indicates the level of interest or activity in a stock, with higher volumes often reflecting greater market interest or volatility.

Codling moth (Cydia pomonella) is the primary insect pest of apple and pear trees in Montana and can destroy an entire crop if uncontrolled. Understanding the moth's life cycle is important for determining management methods and timing of treatments. The purpose of this study was to compare trap-based biofix (first consistent moth capture in the spring) to two temperature based trap-free models for fixed biofix developed in other apple producing regions. Trap-free models determine a date for fixed biofix using temperature accumulation data (growing degree days) from nearby weather stations. Trap-free models compared in the present study were developed and are used in Washington state and Utah state; compared to Montana, Washington is similar latitude but lower elevation, and Utah is similar to higher elevation, but lower latitude. Results presented here suggest that the Washington state model for fixed biofix more closely aligns with Montana trap-based biofix in the 3 years of the study. Generally, trap-based biofix in Montana occured after the Washington state model fixed biofix growing degree date; we surmise that low evening temperatures and frequent high winds in some parts of the state and certain years could influence trap catch.

Methods Data were collected in 2018, 2019, 2020 by a combination of Montana State University (MSU) staff, fruit growers, or volunteers. Data collected by paid staff are indicated in the dataset. We would like to thank all staff, fruit growers, and volunteers who assisted with this study.

Trap-based biofix dates were established by hanging Trece Pherocon III Orange Delta traps equipped with a 1-month Trece codling moth lure in apple trees in participating orchards around 100 growing degree days (GDD) after January 1 (50 degrees Fahrenheit base threshold, 88 degrees Fahrenheit maximum, single sine calculation method, horizontal cutoff); GDD for the orchard were determined using the nearest weather station with GDD data available through USPest.org. Personnel collecting data were instructed to check traps daily for adult male codling moth until biofix was established.

Fixed biofix dates were determined using a USPest.org GDD accumulation (as described above) from the weatherstation nearest to the orchard combined with fixed biofix GDD per the Washington state method (175 GDD) and the elevation and latitude specific Utah state fixed biofix GDD calculated per this equation:

GDD in Fahrenheit = (1755.559-(66.777*latitude)+(0.676*(latitude^2))-(0.0347*elevation in m))*1.8

Differences between trap-based biofix and fixed biofix dates for the two models are compared in the dataset.

References for the fixed-biofix models are:

Washington state method (Model 1): Jones, VP, Doerr, M, Brunner, JF. 2008. Is Biofix Necessary for Predicting Codling Moth (Lepidoptera: Tortricidae) Emergence in Washington State Apple Orchards? J. Econ. Entomol. 101 (5):1651-1657.

Utah TRAPs method (Model 2): Jones, VP et al 2013. Predicting the emergence of the codling moth, Cydia pomonella (Lepidoptera: Tortricidae), on a degree-day scale in North America. Pest Management Sci., 69:1393-1398.

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 Apple Valley. 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 2023

Based on our analysis ACS 2019-2023 5-Year Estimates, we present the following observations: - All workers, aged 15 years and older: In Apple Valley, the median income for all workers aged 15 years and older, regardless of work hours, was $64,365 for males and $42,255 for females.

These income figures highlight a substantial gender-based income gap in Apple Valley. Women, regardless of work hours, earn 66 cents for each dollar earned by men. This significant gender pay gap, approximately 34%, underscores concerning gender-based income inequality in the city of Apple Valley.

- Full-time workers, aged 15 years and older: In Apple Valley, among full-time, year-round workers aged 15 years and older, males earned a median income of $84,698, while females earned $64,567, leading to a 24% gender pay gap among full-time workers. This illustrates that women earn 76 cents for each dollar earned by men in full-time roles. This analysis indicates a widening gender pay gap, showing a substantial income disparity where women, despite working full-time, face a more significant wage discrepancy compared to men in the same roles.

Surprisingly, the gender pay gap percentage was higher across all roles, including non-full-time employment, for women compared to men. This suggests that full-time employment offers a more equitable income scenario for women compared to other employment patterns in Apple Valley.

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.

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 2023
• 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 Apple Valley median household income by race. You can refer the same here

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 Apple River. 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 2023

Based on our analysis ACS 2019-2023 5-Year Estimates, we present the following observations: - All workers, aged 15 years and older: In Apple River, for all workers aged 15 years and older, irrespective of full-time or part-time work, the median income was $37,875 for both males and females.

This indicates income parity between genders in Apple River, where women and men, regardless of their work hours, earn an equal dollar amount for their efforts, reflecting a balanced income distribution across both sexes.

- Full-time workers, aged 15 years and older: In Apple River, for all full-time workers aged 15 years and older, the median income was equal at, $43,438 for both males and females. This indicates a gender income balance in Apple River, where both men and women, in full-time year-round roles, earn an equal income.

Moreover, across all roles (including full-time and others), the median income for both women and men was identical as well. This illustrates a remarkable wage parity across different employment patterns for male and female workers in income distribution for Apple River.

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.

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 2023
• 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 Apple River median household income by race. You can refer the same here

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 Apple Creek. 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 2023

Based on our analysis ACS 2019-2023 5-Year Estimates, we present the following observations: - All workers, aged 15 years and older: In Apple Creek, the median income for all workers aged 15 years and older, regardless of work hours, was $52,500 for males and $27,461 for females.

These income figures highlight a substantial gender-based income gap in Apple Creek. Women, regardless of work hours, earn 52 cents for each dollar earned by men. This significant gender pay gap, approximately 48%, underscores concerning gender-based income inequality in the village of Apple Creek.

- Full-time workers, aged 15 years and older: In Apple Creek, among full-time, year-round workers aged 15 years and older, males earned a median income of $63,250, while females earned $44,375, leading to a 30% gender pay gap among full-time workers. This illustrates that women earn 70 cents for each dollar earned by men in full-time roles. This analysis indicates a widening gender pay gap, showing a substantial income disparity where women, despite working full-time, face a more significant wage discrepancy compared to men in the same roles.

Surprisingly, the gender pay gap percentage was higher across all roles, including non-full-time employment, for women compared to men. This suggests that full-time employment offers a more equitable income scenario for women compared to other employment patterns in Apple Creek.

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.

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 2023
• 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 Apple Creek median household income by race. You can refer the same here

About this dataset

Context

The dataset tabulates the Apple Valley 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 Apple Valley 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 Apple Valley was 55,336, a 0.15% decrease year-by-year from 2022. Previously, in 2022, Apple Valley population was 55,417, a decline of 0.79% compared to a population of 55,859 in 2021. Over the last 20 plus years, between 2000 and 2023, population of Apple Valley increased by 9,441. In this period, the peak population was 56,271 in the year 2020. 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 Apple Valley is shown in this column.
• Year on Year Change: This column displays the change in Apple Valley 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 Apple Valley Population by Year. You can refer the same here

About this dataset

Context

The dataset tabulates the Apple Valley household income by gender. The dataset can be utilized to understand the gender-based income distribution of Apple Valley income.

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, CA annual median income by work experience and sex dataset : Aged 15+, 2010-2022 (in 2022 inflation-adjusted dollars)
• Apple Valley, CA annual income distribution by work experience and gender dataset (Number of individuals ages 15+ with income, 2022)

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 income distribution by gender. You can refer the same here

About this dataset

Context

The dataset tabulates the data for the Apple Valley, MN population pyramid, which represents the Apple Valley population distribution across age and gender, using estimates from the U.S. Census Bureau American Community Survey (ACS) 2018-2022 5-Year Estimates. It lists the male and female population for each age group, along with the total population for those age groups. Higher numbers at the bottom of the table suggest population growth, whereas higher numbers at the top indicate declining birth rates. Furthermore, the dataset can be utilized to understand the youth dependency ratio, old-age dependency ratio, total dependency ratio, and potential support ratio.

Key observations

• Youth dependency ratio, which is the number of children aged 0-14 per 100 persons aged 15-64, for Apple Valley, MN, is 34.7.
• Old-age dependency ratio, which is the number of persons aged 65 or over per 100 persons aged 15-64, for Apple Valley, MN, is 24.9.
• Total dependency ratio for Apple Valley, MN is 59.7.
• Potential support ratio, which is the number of youth (working age population) per elderly, for Apple Valley, MN is 4.0.

Content

When available, the data consists of estimates from the U.S. Census Bureau American Community Survey (ACS) 2018-2022 5-Year Estimates.

Age groups:

• Under 5 years
• 5 to 9 years
• 10 to 14 years
• 15 to 19 years
• 20 to 24 years
• 25 to 29 years
• 30 to 34 years
• 35 to 39 years
• 40 to 44 years
• 45 to 49 years
• 50 to 54 years
• 55 to 59 years
• 60 to 64 years
• 65 to 69 years
• 70 to 74 years
• 75 to 79 years
• 80 to 84 years
• 85 years and over

Variables / Data Columns

• Age Group: This column displays the age group for the Apple Valley population analysis. Total expected values are 18 and are define above in the age groups section.
• Population (Male): The male population in the Apple Valley for the selected age group is shown in the following column.
• Population (Female): The female population in the Apple Valley for the selected age group is shown in the following column.
• Total Population: The total population of the Apple Valley for the selected age group is shown in the following column.

Good to know

Margin of Error

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

Custom data

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

Inspiration

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

Recommended for further research

This dataset is a part of the main dataset for Apple Valley Population by Age. You can refer the same here

About this dataset

Context

The dataset tabulates the Apple Valley median household income by race. The dataset can be utilized to understand the racial distribution of Apple Valley income.

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 breakdown by race betwen 2011 and 2021
• Median Household Income by Racial Categories in Apple Valley, MN (2021, 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 by race. You can refer the same here

About this dataset

Context

The dataset tabulates the Apple Valley 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 Apple Valley. The dataset can be utilized to understand the population distribution of Apple Valley by age. For example, using this dataset, we can identify the largest age group in Apple Valley.

Key observations

The largest age group in Apple Valley, MN was for the group of age 10-14 years with a population of 4,572 (8.28%), according to the 2021 American Community Survey. At the same time, the smallest age group in Apple Valley, MN was the 85+ years with a population of 613 (1.11%). 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 Apple Valley is shown in this column.
• % of Total Population: This column displays the population of each age group as a proportion of Apple Valley 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 Apple Valley Population by Age. 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