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Marriages of Bute and Warren Counties, North Carolina 1764-1868
Bute County was discontinued in 1779. Franklin and Warren counties were formed from the area of Bute County.
Remember the Raisin! Kentucky and Kentuckians in the Battles and Massacre at Frenchtown, Michigan Territory, in the War of 1812
. The Battle on River Raisin, which was fought in and around Frenchtown (now Monroe), Michigan from January 18 to January 23, 1812, was one of the four principal campaigns of the War of 1812 engaged in by Kentucky forces. Following the massacre of American forces at Frenchtown--including as many as sixty Kentucky soldiers-- Kentucky, patriots exhorted one another with shouts of "Remember the Raisin," which gave the new nation the "vengeance-fired impetus" to wage the remaining battles of the War of 1812. The larger of these two works treats all aspects of the Battle on River Raisin and features detailed biographical and genealogical sketches of nearly 100 officers and enlisted men who served on River Raisin and complete rosters of the Kentucky soldiers who saw action there. The smaller companion volume is a miscellaneous listing of Kentucky veterans of the War of 1812 compiled from newspaper files, pension lists, county histories, veterans' publications, and so on.
Football Analytics with Python & R
Baseball is not the only sport to use "moneyball." American football fans, teams, and gamblers are increasingly using data to gain an edge against the competition. Professional and college teams use data to help select players and identify team needs. Fans use data to guide fantasy team picks and strategies. Sports bettors and fantasy football players are using data to help inform decision making. This concise book provides a clear introduction to using statistical models to analyze football data. Whether your goal is to produce a winning team, dominate your fantasy football league, qualify for an entry-level football analyst position, or simply learn R and Python using fun example cases, this book is your starting place. You'll learn how to: Apply basic statistical concepts to football datasets Describe football data with quantitative methods Create efficient workflows that offer reproducible results Use data science skills such as web scraping, manipulating data, and plotting data Implement statistical models for football data Link data summaries and model outputs to create reports or presentations using tools such as R Markdown and R Shiny And more
