Python for Data Analysis, 2e

Python for Data Analysis, 2e

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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
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Product details

  • Paperback | 522 pages
  • 179 x 233 x 28mm | 850g
  • O'Reilly Media, Inc, USA
  • Sebastopol, United States
  • English
  • 2nd ed.
  • 1491957662
  • 9781491957660
  • 6,294

About Wes McKinney

Wes McKinney is the main author of pandas, the popular open sourcePython library for data analysis. Wes is an active speaker andparticipant in the Python and open source communities. He worked as a quantitative analyst at AQR Capital Management and Python consultant before founding DataPad, a data analytics company, in 2013. He graduated from MIT with an S.B. in Mathematics.
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Rating details

890 ratings
4.05 out of 5 stars
5 32% (286)
4 46% (410)
3 18% (161)
2 3% (24)
1 1% (9)
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