Python For Data Analysis: Data Wrangling With Pandas, Numpy, And Ipython

deWes McKinney

|anglais
31 octobre 2017|
Python For Data Analysis: Data Wrangling With Pandas, Numpy, And Ipython de Wes McKinney
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description

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
Wes 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...
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Titre :Python For Data Analysis: Data Wrangling With Pandas, Numpy, And Ipython
Format :Couverture souple
Dimensions de l'article :550 pages, 9.19 X 7 X 0.68 po
Dimensions à l'expédition :550 pages, 9.19 X 7 X 0.68 po
Publié le :31 octobre 2017
Publié par :O'Reilly Media
Langue :anglais
Convient aux âges :Tous les âges
ISBN - 13 :9781491957660

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