Wes McKinney.
Python for Data Analysis: data wrangling with pandas, numpy, and Ipython.
O'Reilly. 2013
Written by Wes McKinney, the main author of the pandas library, Python for Data Analysts also serves as a practical, modern introduction to scientific computing in Python for data-intensive applications. 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
• Work with time series data in many different forms
• Learn how to solve problems in web analytics, social sciences, finance,
and economics, through detailed examples