Python for Data Analysis, 2e by Wes Mckinney (Paperback, 2017)

Publisher’s SynopsisGet complete instructions for manipulating, processing, cleaning, and crunching datasets in Python. Updated for Python 3.6, the second edition of this hands-on guide is packed with practical case studies that show you how to solve a broad set of data analysis problems effectively. You’ll learn the latest versions of pandas, NumPy, IPython, and Jupyter in the process.Written by Wes McKinney, the creator of the Python pandas project, this book is a practical, modern introduction to data science tools in Python. It’s ideal for analysts new to Python and for Python programmers new to data science and scientific computing. Data files and related material are available on GitHub.Use the IPython shell and Jupyter notebook for exploratory computingLearn basic and advanced features in NumPy (Numerical Python)Get started with data analysis tools in the pandas libraryUse flexible tools to load, clean, transform, merge, and reshape dataCreate informative visualizations with matplotlibApply the pandas groupby facility to slice, dice, and summarize datasetsAnalyze and manipulate regular and irregular time series dataLearn how to solve real-world data analysis problems with thorough, detailed examples

The Oxford Handbook of Gender in Organizations Hardcover Book

The Oxford Handbook of Gender in Organizations is a comprehensive textbook written by Ruth Simpson, Ronald J. Burke, and Savita Kumra. Published by Oxford University Press in 2014, this hardcover book is an essential resource for students and professionals interested in organizational Sociology and Zoology. The book covers various aspects of gender in organizations, including its impact on business practices, hiring practices, and employee behavior. With a height of 253mm, width of 180mm, and a weight of 1172g, this book is a valuable addition to any library. It contains 572 pages and comes with a dust jacket. The book is written in English and is suitable for adult and further education levels.