Python for Data Analysis: Data Wrangling with Pandas, NumPy, and IPython

The "Python Data Science Handbook" is a comprehensive guide to manipulating, processing, cleaning, and crunching datasets in Python.

With updated content for Python 3.6, this second edition provides practical case studies that show you how to solve a broad set of data analysis problems effectively.

Written by Wes McKinney, the creator of the Python pandas project, this book is ideal for analysts new to Python and for Python programmers new to data science and scientific computing.

You'll learn the latest versions of pandas, NumPy, IPython, and Jupiter in the process.

The book includes data files and related material on GitHub, allowing you to practice your skills with real-world examples.

Whether you're a beginner or an experienced analyst, this hands-on guide will help you become proficient in data science tools in Python.