Download the fantastic book titled Python for Data Analysis written by Wes McKinney, available in its entirety in both PDF and EPUB formats for online reading. This page includes a concise summary, a preview of the book cover, and detailed information about "Python for Data Analysis", which was released on 25 September 2017. We suggest perusing the summary before initiating your download. This book is a top selection for enthusiasts of the Computers genre.
Summary of Python for Data Analysis by Wes McKinney PDF
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 data 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 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. Use the IPython shell and Jupyter notebook for exploratory computing Learn basic and advanced features in NumPy (Numerical Python) Get started with data analysis tools in the pandas library Use flexible tools to load, clean, transform, merge, and reshape data Create informative visualizations with matplotlib Apply the pandas groupby facility to slice, dice, and summarize datasets Analyze and manipulate regular and irregular time series data Learn how to solve real-world data analysis problems with thorough, detailed examples
Detail About Python for Data Analysis PDF
- Author : Wes McKinney
- Publisher : "O'Reilly Media, Inc."
- Genre : Computers
- Total Pages : 676 pages
- ISBN : 1491957611
- Release Date : 25 September 2017
- PDF File Size : 40,9 Mb
- Language : English
- Rating : 5/5 from 1 reviews
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