Software for Data Analysis Software for Data Analysis
Statistics and Computing

Software for Data Analysis

Programming with R

    • USD 119.99
    • USD 119.99

Descripción editorial

John Chambers has been the principal designer of the S language since its beginning, and in 1999 received the ACM System Software award for S, the only statistical software to receive this award. He is author or coauthor of the landmark books on S.

Now he turns to R, the enormously successful open-source system based on the S language. R's international support and the thousands of packages and other contributions have made it the standard for statistical computing in research and teaching.

This book guides the reader through programming with R, beginning with simple interactive use and progressing by gradual stages, starting with simple functions. More advanced programming techniques can be added as needed, allowing users to grow into software contributors, benefiting their careers and the community. R packages provide a powerful mechanism for contributions to be organized and communicated.

The techniques covered include such modern programming enhancements as classes and methods, namespaces, and interfaces to spreadsheets or data bases, as well as computations for data visualization, numerical methods, and the use of text data.

GÉNERO
Informática e Internet
PUBLICADO
2008
14 de junio
IDIOMA
EN
Inglés
EXTENSIÓN
514
Páginas
EDITORIAL
Springer New York
VENDEDOR
Springer Nature B.V.
TAMAÑO
1.8
MB
A Working Day A Working Day
2022
Connecting the Dots Connecting the Dots
2018
Connecting the Dots Connecting the Dots
2018
The Metaphysical World of Isaac Newton The Metaphysical World of Isaac Newton
2018
The Secret Life of Genius The Secret Life of Genius
2009
Victor Hugo's Conversations with the Spirit World Victor Hugo's Conversations with the Spirit World
2008
Elements of Network Science Elements of Network Science
2025
A First Course in Statistical Learning A First Course in Statistical Learning
2025
Visualization and Imputation of Missing Values Visualization and Imputation of Missing Values
2023
Fundamentals of Supervised Machine Learning Fundamentals of Supervised Machine Learning
2023
Applied Statistical Learning Applied Statistical Learning
2023
An Introduction to Statistics with Python An Introduction to Statistics with Python
2022