Python for R Users

Book Description

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.

A. Ohri is the founder of Decisionstats.com and currently works as a senior data scientist. He has advised multiple startups in analytics off-shoring, analytics services, and analytics education, as well as using social media to enhance buzz for analytics products. Mr. Ohri’s research interests include spreading open source analytics, analyzing social media manipulation with mechanism design, simpler interfaces for cloud computing, investigating climate change and knowledge flows. His other books include R for Business Analytics and R for Cloud Computing.

Table of Contents

Chapter 1 Introduction To Python R And Data Science
Chapter 2 Data Input
Chapter 3 Data Inspection And Data Quality
Chapter 4 Exploratory Data Analysis
Chapter 5 Statistical Modeling
Chapter 6 Data Visualization
Chapter 7 Machine Learning Made Easier
Chapter 8 Conclusion And Summary

中文：

书名：适用于R用户的Python

了解精通R和Python的优势的统计学家和数据科学家的权威指南

它的第一本书，《面向R用户的Python：数据科学方法》使R程序员可以轻松地使用Python语言编写代码，而Python用户使用R语言进行编程。该书简要介绍理论，详细介绍可操作的分析，为读者提供两种语言的详细比较介绍和概述，并提供简明的教程，以及从R到Python和从Python到R的逐个命令翻译–包括样例代码。

在介绍了这两种语言之后，作者开始逐步介绍所有相关的编程特性和功能，包括数据输入、数据检查/数据质量、数据分析和数据可视化。统计建模、机器学习和数据挖掘-包括监督和非监督数据挖掘方法-以及时间序列预测、文本挖掘和自然语言处理都将详细讨论。

• 具有简明教程和可操作分析的快速学习格式
• 提供从R到Python的逐个命令转换，反之亦然
• 在整个过程中整合了Python和R代码，便于读者比较和对比两种语言的功能
• 提供了大量两种编程语言的比较示例和应用程序
• 专为通晓一门语言并想学习另一门语言的从业者和学生而设计
• 在配套网站上提供对任一软件的教学和学习有用的幻灯片

面向R用户的Python：数据科学方法是计算机科学家和数据科学家的宝贵工作资源，他们了解R并希望学习Python，或熟悉Python并希望学习R。它还可用作计算机科学和统计学学生的教科书。

啊。 是Decisionstats.com的创始人，目前是一名高级数据科学家。他曾为多家初创公司提供分析外包、分析服务和分析教育方面的咨询，并利用社交媒体为分析产品提升知名度。奥里先生的研究兴趣包括传播开源分析、通过机制设计分析社交媒体操纵、简化云计算界面、调查气候变化和知识流动。他的其他著作包括商业分析的R和云计算的R。

目录表

第1章：PythonR和数据科学简介
Chapter 2 Data Input
Chapter 3 Data Inspection And Data Quality
第四章探索性数据分析
第五章统计建模
第六章数据可视化
第7章机器学习变得更容易
第八章结论与总结