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Title: Python for Analysis Data: Wrangling with Pandas Data, NumPy, and IPython Volume: Author(s): Wes McKinney Year: 2017 Edition: 2 Language: English Pages (biblio/tech): 544\541 Molting RESULT SPECIFICATION Reproduction Black WHITE Paper B5 BOOKPAPER (STRONG CUIDER), LIGHT MATERIALS Clear PRINTING (NICE) Hardcover VolULUME Get 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 analysis problems effectively. You'll learn the latest versions of pandas, NumPy, IPython, and Jupyter in the process. Written by Wes McKinney, the creator of the Python pandas project, this book is a practical, modern introduction to science tools in Python data. It's ideal for analysts new to Python and for Python programmers new to science and scientific computing data. File and relative data are available on GitHub material. Use the IPython shell and Jupyter notebook for exploratory computingLearn basic and advanced features in NumPy (Numerical Python)Get start with analysis data tools in the pandas libraryUse flexible tools to load, clean, merge, and reshape dataCreate Visualizations informative with matplotlibApply the pandas groupby facility to slice, dice, and summarize datasetsAnalyze and manipulate regular and irregular time series dataLearn how to solve real-world data analysis problems with thorough, detailed examples