- Python for Data Analysis
- Data Wrangling with Pandas, NumPy, and IPython
- By Wes McKinney
- Publisher: O'Reilly Media
- Final Release Date: October 2012
- Pages: 466
- 4.2Read 24 ReviewsWrite a Review
- Python for Data Analysis 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. This is a book about the parts of the Python language and libraries you’ll need to effectively solve a broad set of data analysis problems. This book is not an exposition on analytical methods using Python as the implementation language.
- Written by Wes McKinney, the main author of the pandas library, this hands-on book is packed with practical cases studies. It’s ideal for analysts new to Python and for Python programmers new to scientific computing.
- 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 groupby 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
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