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图书名称：R Data Analysis Cookbook - More Than 80 Recipes to Help You Deliver Sharp Data Analysis
作者：Viswa Viswanathan, Shanthi Viswanathan
出版社：Packt Publishing
页数：216
出版时间：2015
语言：English
格式：mobi
内容简介：
Key Features
- Analyse data with ready-to-use and customizable recipes
- Discover convenient functions to speed-up your work and data files
- Explore the leading R packages built for expert data analysis
This book empowers you by showing you ways to use R to generate professional analysis reports. It provides examples for various important analysis and machine-learning tasks that you can try out with associated and readily available data. The book also teaches you to quickly adapt the example code for your own needs and save yourself the time needed to construct code from scratch.
What you will learn
- Get data into your R environment and prepare it for analysis
- Perform exploratory data analyses and generate meaningful visualizations of the data
- Apply several machine-learning techniques for classification and regression
- Get your hands around large data sets with the help of reduction techniques
- Extract patterns from time-series data and produce forecasts based on them
- Learn how to extract actionable information from social network data
- Implement geospatial analysis
- Present your analysis convincingly through reports and build an infrastructure to enable others to play with your data
Shanthi Viswanathan is an experienced technologist who has delivered technology management and enterprise architecture consulting to many enterprise customers. She has worked for Infosys Technologies, Oracle Corporation, and Accenture. As a consultant, Shanthi has helped several large organizations, such as Canon, Cisco, Celgene, Amway, Time Warner Cable, and GE among others, in areas such as data architecture and analytics, master data management, service-oriented architecture, business process management, and modeling.
Table of Contents
- Acquire and Prepare the Ingredients Your Data
- What's in There? Exploratory Data Analysis
- Where Does It Belong? Classification
- Give Me a Number Regression
- Can You Simplify That? Data Reduction Techniques
- Lessons from History Time Series Analysis
- It's All about Your Connections Social Network Analysis
- Put Your Best Foot Forward Document and Present Your Analysis
- Work Smarter, Not Harder Efficient and Elegant R Code
- Where in the World? Geospatial Analysis
- Playing Nice Connecting to Other Systems
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