In 2024, Millennials were the largest generation group in the United States, making up about 21.81 percent of the population. However, Generation Z was not far behind, with Gen Z accounting for around 20.81 percent of the population in that year.

Millennials were the largest generation group in the United States in 2024, with an estimated population of ***** million. Born between 1981 and 1996, Millennials recently surpassed Baby Boomers as the biggest group, and they will continue to be a major part of the population for many years. The rise of Generation Alpha Generation Alpha is the most recent to have been named, and many group members will not be able to remember a time before smartphones and social media. As of 2024, the oldest Generation Alpha members were still only aging into adolescents. However, the group already makes up around ***** percent of the U.S. population, and they are said to be the most racially and ethnically diverse of all the generation groups. Boomers vs. Millennials The number of Baby Boomers, whose generation was defined by the boom in births following the Second World War, has fallen by around ***** million since 2010. However, they remain the second-largest generation group, and aging Boomers are contributing to steady increases in the median age of the population. Meanwhile, the Millennial generation continues to grow, and one reason for this is the increasing number of young immigrants arriving in the United States.

More than ** percent of Gen Z shoppers returned products bought online from April 2024 to March 2025, while only ** percent of Boomers did the same. The most returned product category among Millennial shoppers was clothing, with ** percent of them returning online purchases in this category. Looking to gain valuable insights about customers of online shops across the globe? Check out our reports about consumers of online shops worldwide. These reports offer the readers a comprehensive overview of customers of eCommerce brands: who they are; what they like; what they think; and how to reach them.

⚡ US Electricity Generation & Emissions Dataset

Monthly and yearly electricity data for the United States, available at both national and state levels.
The dataset covers electricity generation (GWh), power generation capacity (MW), emissions from electricity generation (ktCO2e) and carbon intensity of electricity generation (gCO2 per KWh) for all 50 states.

🗂️ Columns

• Country – Country name (United States of America)
• Country code – ISO-3 country code (USA)
• State – U.S. state or territory (e.g., Alabama)
• State code – State abbreviation (e.g., AL)
• State type – Classification (state / territory / federal district)
• Date – Month and year (DD-MM-YYYY)
• Category – Data category (e.g., Electricity generation, Emissions)
• Subcategory – Aggregate grouping (e.g., Aggregate fuel)
• Variable – Energy type or emission type (Clean, Fossil, Renewables, Gas, Hydro, CO₂, etc.)
• Unit – Measurement unit (e.g., %, GWh, tons)
• Value – Recorded value for the variable
• YoY absolute change – Year-on-year absolute change in value
• YoY % change – Year-on-year percentage change in value

📂 Files

• us_monthly_electricity.csv – Full dataset containing monthly and yearly electricity generation and emissions data at both state and national levels.

🚀 Potential Use Cases

• 📊 State-level comparisons of fossil vs renewable energy adoption
• 📈 Trend analysis of electricity generation and emissions over time
• 🌱 Carbon footprint analysis for clean vs fossil energy
• 🤖 Forecasting models for electricity demand and emission reductions
• 🏛️ Policy evaluation of renewable adoption at state and national levels

📜 License

This dataset is released under the CC0 1.0 Universal (Public Domain Dedication) license.

Distribution of Gen X home buyers by race and ethnicity.

nate-rahn/wildchat-category-generation-single dataset hosted on Hugging Face and contributed by the HF Datasets community

aq1048576/wildchat-category-generation-distinct dataset hosted on Hugging Face and contributed by the HF Datasets community

Layer references: Predominant Generations in the United States in 2018-------------------------------------------------------------------------------------------------------------------------------------This layer shows the predominant generations that make up the population of the United States using country to block group geographies. The vintage of the data is 2018. The top 3 predominant generations are Baby Boomers (born 1946-1964), Millennials (born 1981-1998), and Generation Z (born 1999-2016). Of these three, the predominant generation of the United States is Millennials. The popup is configured to show the predominant generation and population counts for each of the six generations. Size represents the total sum of categories (i.e. total population). Web Map: Predominant Generations in the United StatesFor more information, visit the Updated Demographics documentation. For a full list of variables, click the Data tab. Note: This layer will not being continuously updated or maintained.

Average loan size, purchase price, loan-to-value ratio, and conforming loan limit usage for Gen X buyers.

Distribution of Gen Z home buyers by race and ethnicity.

In the first quarter of 2025, 51.4 percent of the total wealth in the United States was owned by members of the baby boomer generation. In comparison, millennials own around 10.3 percent of total wealth in the U.S. In terms of population distribution, there was almost an equal share of millennials and baby boomers in the United States in 2024.

About this Dataset

For sale are domain names with WHO IS information that were registered between Mar 16, 2018 and Mar 31, 2018 by registrants in United States. Domains which obfuscate registrant, administrative, and other WHO IS contact details have been omitted from this dataset. The following information is availble for download in this dataset: - Domain name, Created Date, Updated Date, Expiration Date, Registrar Name- Registrant Company, Name, Address, City, State/Province/Other, Postal Code, Country, Email, Phone #, Fax #- Administrative Company, Name, Address, City, State/Province/Other, Postal Code, Country, Email, Phone #, Fax #- Technical Company, Name, Address, City, State/Province/Other, Postal Code, Country, Email, Phone #, Fax #- Billing Company, Name, Address, City, State/Province/Other, Postal Code, Country, Email, Phone #, Fax #- NameServer1, NameServer2, NameServer3, NameServer4, - DomainStatus1, DomainStatus2, DomainStatus3, DomainStatus4 Still unsure about purchasing this dataset? View and Download a free sample dataset of global domain name registrations in the Lead Generation category Are you interested in a more targeted domain name registration dataset? Select the "Ask Seller a Question" link, send me a message, and I'll get back to you as soon as I can.

Category

Lead Generation

Keywords

usa,united-states,newly-registered-domains,who-is-data

Row Count

220910

Price

$20.00

This graph shows preferred rewards categories in the United States in 2012, by generation. The survey revealed that 83 percent of millennials prefer cash back rewards programs.

ZIP codes with the highest number of Late Baby Boomer home purchases in 2024.

Context

This is a nicely formatted version of the US Energy Information Administration's U.S. Electric System Operating Data.

It's broken out by aggregation level: US, Regions, Balancing authorities and Balancing authority subregion. Then within that it's broken out into either region, balancing authority or individual utility.

Then each csv is includes data on - BA-to-BA interchange (suffix ID.H) - Day-ahead demand forecast (DF.H) - Demand (D.H) - Net generation by energy source (NG.SUN.H, NG.COL.H, NG.NG.H etc) - Net generation (NG.H) - Total interchange (TI.H)

Note: .H in the suffix stands for hourly in UTC time.

You can see the full data dictionary in data_dictionary.csv

Raw data

The raw data comes from the EIA's bulk data download facility. It's downloaded using this notebook. And structured using this notebook.