{"title":"Computers - Data Science - Data Analytics","description":"\u003cp\u003eExplore our collection of data science books, including the Python Data Science Handbook and data analytics books for beginners. Perfect for anyone looking to dive into data and computer science!\u003c\/p\u003e","products":[{"product_id":"python-for-data-analysis-data-wrangling-with-pandas-numpy-and-jupyter-9781098104030","title":"Python for Data Analysis: Data Wrangling with Pandas, Numpy, and Jupyter","description":"\u003cp\u003eGet the definitive handbook for manipulating, processing, cleaning, and crunching datasets in Python. Updated for Python 3.10 and pandas 1.4, the third edition of this hands-on guide is packed with practical case studies that show you how to solve a broad set of data analysis problems effectively. 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Data files and related material are available on GitHub. \u003c\/p\u003e\u003cul\u003e \u003cli\u003eUse the Jupyter notebook and IPython shell for exploratory computing \u003c\/li\u003e\n\u003cli\u003eLearn basic and advanced features in NumPy \u003c\/li\u003e\n\u003cli\u003eGet started with data analysis tools in the pandas library \u003c\/li\u003e\n\u003cli\u003eUse flexible tools to load, clean, transform, merge, and reshape data \u003c\/li\u003e\n\u003cli\u003eCreate informative visualizations with matplotlib \u003c\/li\u003e\n\u003cli\u003eApply the pandas groupby facility to slice, dice, and summarize datasets \u003c\/li\u003e\n\u003cli\u003eAnalyze and manipulate regular and irregular time series data \u003c\/li\u003e\n\u003cli\u003eLearn how to solve real-world data analysis problems with thorough, detailed examples \u003c\/li\u003e\n\u003c\/ul\u003e\u003cbr\u003e\u003cbr\u003e\u003cb\u003eAuthor:\u003c\/b\u003e Wes McKinney\u003cbr\u003e\u003cb\u003ePublisher:\u003c\/b\u003e O'Reilly Media\u003cbr\u003e\u003cb\u003ePublished:\u003c\/b\u003e 09\/20\/2022\u003cbr\u003e\u003cb\u003ePages:\u003c\/b\u003e 579\u003cbr\u003e\u003cb\u003eBinding Type:\u003c\/b\u003e Paperback\u003cbr\u003e\u003cb\u003eWeight:\u003c\/b\u003e 2.07lbs\u003cbr\u003e\u003cb\u003eSize:\u003c\/b\u003e 6.90h x 9.10w x 1.20d\u003cbr\u003e\u003cb\u003eISBN:\u003c\/b\u003e 9781098104030\u003cbr\u003e\u003cbr\u003e\u003cb\u003eAbout the Author\u003c\/b\u003e\u003cbr\u003e\u003cb\u003e\u003ci\u003eMcKinney, Wes:\u003c\/i\u003e\u003c\/b\u003e - Wes McKinney is a Nashville-based software developer and entrepreneur. After finishing his undergraduate degree in mathematics at MIT in 2007, he went on to do quantitative finance work at AQR Capital Management in Greenwich, CT. Frustrated by cumbersome data analysis tools, he learned Python and started building what would later become the pandas project. He's now an active member of the Python data community and is an advocate for the use of Python in data analysis, finance, and statistical computing applications.\u003cbr\u003e \u003cbr\u003e Wes was later the cofounder and CEO of DataPad, whose technology assets and team were acquired by Cloudera in 2014. He has since become involved in big data technology, joining the Project Management Committees for the Apache Arrow and Apache Parquet projects in the Apache Software Foundation. In 2018, he founded Ursa Labs, a not-for-profit organization focused Apache Arrow development, in partnership with RStudio and Two Sigma Investments. In 2021, he cofounded technology startup Voltron Data, where he currently works as the Chief Technology Officer.","brand":"booksdeli.com","offers":[{"title":"Wes McKinney \/ Paperback \/ English","offer_id":47281973428381,"sku":"9781098104030","price":104.33,"currency_code":"USD","in_stock":true}],"thumbnail_url":"\/\/cdn.shopify.com\/s\/files\/1\/0619\/5648\/9373\/files\/img_daad9f89-494b-49a1-bf54-2b5c9065670c.jpg?v=1759941299"},{"product_id":"fundamentals-of-data-engineering-plan-and-build-robust-data-systems-9781098108304","title":"Fundamentals of Data Engineering: Plan and Build Robust Data Systems","description":"\u003cp\u003eData engineering has grown rapidly in the past decade, leaving many software engineers, data scientists, and analysts looking for a comprehensive view of this practice. 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