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Sebastopol, CA—Python for Data Analysis ($39.99, O'Reilly Media) is concerned with the nuts and bolts of manipulating, processing, cleaning, and crunching data in Python. It is also a practical, modern introduction to scientific computing in Python, tailored for data-intensive applications.
"Many new Python users have struggled due to the lack of comprehensive learning resources for the central tools in the stack," says author Wes McKinney (@wesmckinn), citing NumPy, IPython, pandas, matplotlib, and others. "This book is an approachable introduction for new users but holds value for experienced Python programmers, too."
In other words, it's ideal for analysts new to Python and for Python programmers new to scientific computing. With Python for Data Analysis, you will:
- Use the IPython interactive shell as your primary development environment
- Learn basic and advanced NumPy (Numerical Python) features
- Get started with data analysis tools in the pandas library
- Use high-performance tools to load, clean, transform, merge, and reshape data
- Create scatter plots and static or interactive visualizations with matplotlib
- Apply the pandas group-by facility to slice, dice, and summarize datasets
- Measure data by points in time, whether it's specific instances, fixed periods, or intervals
- Learn how to solve problems in web analytics, social sciences, finance, and economics, through detailed examples
For a review copy or more information please email reviews@oreilly.com. Please include your delivery address and contact information.
Additional Resources
For more information about the book, including table of contents, author bios, and cover graphic, see: http://shop.oreilly.com/product/0636920023784.do
About O’Reilly
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