The definitive guide for statisticians and data scientists who understand the advantages of becoming proficient in both R and Python

The first book of its kind, Python^® for R Users: A Data Science Approach makes it easy for R programmers to code in Python and Python users to program in R. Short on theory and long on actionable analytics, it provides readers with a detailed comparative introduction and overview of both languages and features concise tutorials with command-by-command translations-complete with sample code-of R to Python and Python to R.

Following an introduction to both languages, the author cuts to the chase with step-by-step coverage of the full range of pertinent programming features and functions, including data input, data inspection/data quality, data analysis, and data visualization. Statistical modeling, machine learning, and data mining-including supervised and unsupervised data mining methods-are treated in detail, as are time series forecasting, text mining, and natural language processing.

• Features a quick-learning format with concise tutorials and actionable analytics
• Provides command-by-command translations of R to Python and vice versa
• Incorporates Python and R code throughout to make it easier for readers to compare and contrast features in both languages
• Offers numerous comparative examples and applications in both programming languages
• Designed for use for practitioners and students that know one language and want to learn the other
• Supplies slides useful for teaching and learning either software on a companion website

Python^® for R Users: A Data Science Approach is a valuable working resource for computer scientists and data scientists that know R and would like to learn Python or are familiar with Python and want to learn R. It also functions as textbook for students of computer science and statistics.