Learn how to manipulate, analyze, clean, and crunch datasets in Python in detail. The second edition of this practical reference, updated for Python 3.6, is jam-packed with real-world case studies that demonstrate how to efficiently tackle a wide range of data analysis challenges. In the process, you'll learn about the most recent iterations of Jupyter, IPython, NumPy, and pandas. Written by the man behind the Python pandas project, Wes McKinney, this book offers a contemporary, hands-on introduction to Python data science tools. It's perfect for Python programmers who are new to data science and scientific computing, as well as for analysts who are new to Python.
