{"product_id":"python-for-data-analysis-data-wrangling-with-pandas-numpy-and-ipython","title":"Python for Data Analysis: Data Wrangling with Pandas, NumPy, and IPython","description":"\u003cp\u003e\u003cstrong\u003eBook info:\u003c\/strong\u003e Python for Data Analysis: Data Wrangling with Pandas, NumPy, and IPython (Paperback, 550 pages) – O'Reilly Media, 2017. Language: English.\u003c\/p\u003e\n \u003cp\u003eGet complete instructions for manipulating, processing, cleaning, and crunching datasets in Python. Updated for Python 3.6, the second 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. You’ll learn the latest versions of pandas, NumPy, IPython, and Jupyter in the process.\u003c\/p\u003e\u003cp\u003eWritten by Wes McKinney, the creator of the Python pandas project, this book is a practical, modern introduction to data science tools in Python. It’s ideal for analysts new to Python and for Python programmers new to data science and scientific computing. Data files and related material are available on GitHub.\u003c\/p\u003e\u003cul\u003e\n\u003cli\u003eUse the IPython shell and Jupyter notebook for exploratory computing\u003c\/li\u003e\n\u003cli\u003eLearn basic and advanced features in NumPy (Numerical Python)\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  \n\n                                         Editorial Reviews                   About the Author   \u003cp\u003eWes McKinney is a New York?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.\u003c\/p\u003e\u003cbr\u003e \u003cbr\u003e \u003cp\u003eWes was later the co-founder 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 2016, he joined Two Sigma Investments in New York City, where he continues working to make data analysis faster and easier through open source software.\u003c\/p\u003e                                           ","brand":"Wes McKinney","offers":[{"title":"Default Title","offer_id":46069622997226,"sku":"9781491957660","price":7.57,"currency_code":"USD","in_stock":true}],"thumbnail_url":"\/\/cdn.shopify.com\/s\/files\/1\/0714\/5301\/6298\/files\/912I2EtdCbL._SL1500.jpg?v=1781213968","url":"https:\/\/textbookme.store\/products\/python-for-data-analysis-data-wrangling-with-pandas-numpy-and-ipython","provider":"TextbookMe","version":"1.0","type":"link"}