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Learning R : A Step-By-Step Function Guide to Data Analysis by Richard Cotton...
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Libro en perfecto estado y poco leído. La tapa no tiene desperfectos y si procede, con sobrecubierta para las tapas duras. Incluye todas las páginas sin arrugas ni roturas. El texto no está subrayado ni resaltado de forma alguna, y no hay anotaciones en los márgenes. Puede presentar marcas de identificación mínimas en la contraportada o las guardas. Muy poco usado. Consulta el anuncio del vendedor para obtener más información y la descripción de cualquier posible imperfección.
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N.º de artículo de eBay:156796783752
Características del artículo
- Estado
- ISBN
- 9781449357108
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Product Identifiers
Publisher
O'reilly Media, Incorporated
ISBN-10
1449357105
ISBN-13
9781449357108
eBay Product ID (ePID)
159814161
Product Key Features
Number of Pages
400 Pages
Publication Name
Learning R : a Step-By-Step Function Guide to Data Analysis
Language
English
Publication Year
2013
Subject
Programming Languages / General, Data Modeling & Design, Mathematical & Statistical Software, Probability & Statistics / General, Data Processing
Type
Textbook
Subject Area
Mathematics, Computers
Format
Trade Paperback
Dimensions
Item Height
0.9 in
Item Weight
23.8 Oz
Item Length
9.1 in
Item Width
6.9 in
Additional Product Features
Intended Audience
Scholarly & Professional
LCCN
2016-416293
Illustrated
Yes
Table Of Content
Preface The R Language Chapter 1: Introduction Chapter 2: A Scientific Calculator Chapter 3: Inspecting Variables and Your Workspace Chapter 4: Vectors, Matrices, and Arrays Chapter 5: Lists and Data Frames Chapter 6: Environments and Functions Chapter 7: Strings and Factors Chapter 8: Flow Control and Loops Chapter 9: Advanced Looping Chapter 10: Packages Chapter 11: Dates and Times The Data Analysis Workflow Chapter 12: Getting Data Chapter 13: Cleaning and Transforming Chapter 14: Exploring and Visualizing Chapter 15: Distributions and Modeling Chapter 16: Programming Chapter 17: Making Packages Appendixes Bibliography Index Colophon
Synopsis
If you do any kind of data analysis, you need R in your toolkit. This book teaches you how to be productive with this important programming language for statistics by covering everything about R you need to know, including data gathering, transformation, visualization, modelling, and publishing., Learn how to perform data analysis with the R language and software environment, even if you have little or no programming experience. With the tutorials in this hands-on guide, you'??ll learn how to use the essential R tools you need to know to analyze data, including data types and programming concepts. The second half of Learning R shows you real data analysis in action by covering everything from importing data to publishing your results. Each chapter in the book includes a quiz on what you'??ve learned, and concludes with exercises, most of which involve writing R code. Write a simple R program, and discover what the language can do Use data types such as vectors, arrays, lists, data frames, and strings Execute code conditionally or repeatedly with branches and loops Apply R add-on packages, and package your own work for others Learn how to clean data you import from a variety of sources Understand data through visualization and summary statistics Use statistical models to pass quantitative judgments about data and make predictions Learn what to do when things go wrong while writing data analysis code, Learn how to perform data analysis with the R language and software environment, even if you have little or no programming experience. With the tutorials in this hands-on guide, you'll learn how to use the essential R tools you need to know to analyze data, including data types and programming concepts. The second half of Learning R shows you real data analysis in action by covering everything from importing data to publishing your results. Each chapter in the book includes a quiz on what you've learned, and concludes with exercises, most of which involve writing R code. Write a simple R program, and discover what the language can do Use data types such as vectors, arrays, lists, data frames, and strings Execute code conditionally or repeatedly with branches and loops Apply R add-on packages, and package your own work for others Learn how to clean data you import from a variety of sources Understand data through visualization and summary statistics Use statistical models to pass quantitative judgments about data and make predictions Learn what to do when things go wrong while writing data analysis code, If you have basic programming skills and do any kind of data analysis, you need R in your toolkit. This book teaches you how to be productive with this important programming language for statistics by covering everything about R you need to know, including: Data gathering from different sources such as web scraping and databases Data transformation/manipulation that can save you hours Visualization that provides a great way of showing insights into datasets Modelling that shows just how many different analyses can be done in R
LC Classification Number
QA276.45.R3
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