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Hands-On Data Science with Anaconda

You're reading from   Hands-On Data Science with Anaconda Utilize the right mix of tools to create high-performance data science applications

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Product type Paperback
Published in May 2018
Publisher Packt
ISBN-13 9781788831192
Length 364 pages
Edition 1st Edition
Languages
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Authors (2):
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James Yan James Yan
Author Profile Icon James Yan
James Yan
Yuxing Yan Yuxing Yan
Author Profile Icon Yuxing Yan
Yuxing Yan
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Toc

Table of Contents (15) Chapters Close

Preface 1. Ecosystem of Anaconda FREE CHAPTER 2. Anaconda Installation 3. Data Basics 4. Data Visualization 5. Statistical Modeling in Anaconda 6. Managing Packages 7. Optimization in Anaconda 8. Unsupervised Learning in Anaconda 9. Supervised Learning in Anaconda 10. Predictive Data Analytics – Modeling and Validation 11. Anaconda Cloud 12. Distributed Computing, Parallel Computing, and HPCC 13. References 14. Other Books You May Enjoy

Introduction to the haven and foreign R packages

The R package called haven is for import and export from SPSS, Stata and SAS files. The package is for Labelled Data Utility Functions, which is a collection of many small functions dealing with labelled data, such as reading and writing data between R and other statistical software packages such as SAS, SPSS, or Stata, and working with labelled data.

This includes easy ways to get, set, and change value and variable label attributes, convert labelled vectors into factors or numeric values (and vice versa), and deal with multiple declared missing values. The following example is about writing several specific outputs:

library(haven)
x<-1:100
y<-matrix(x,50,2)
z<-data.frame(y)
colnames(z)<-c("a","b")
write_sas(z,"c:/temp/tt.sas7bdat")
write_spss(z,"c:/temp/tt.sav")
write_stata(z,&quot...
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