R in a Nutshell 2nd Edition

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R in a Nutshell 2nd Edition By Joseph Adler

Publisher: O'Reilly Media
Final Release Date: September 2012
Pages: 724

If you’re considering R for statistical computing and data visualization, this book provides a quick and practical guide to just about everything you can do with the open source R language and software environment. You’ll learn how to write R functions and use R packages to help you prepare, visualize, and analyze data. Author Joseph Adler illustrates each process with a wealth of examples from medicine, business, and sports.

Updated for R 2.14 and 2.15, this second edition includes new and expanded chapters on R performance, the ggplot2 data visualization package, and parallel R computing with Hadoop.

• Get started quickly with an R tutorial and hundreds of examples
• Explore R syntax, objects, and other language details
• Find thousands of user-contributed R packages online, including Bioconductor
• Learn how to use R to prepare data for analysis
• Visualize your data with R’s graphics, lattice, and ggplot2 packages
• Use R to calculate statistical fests, fit models, and compute probability distributions
• Speed up intensive computations by writing parallel R programs for Hadoop
• Get a complete desktop reference to R
  

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关键词：nutshell Edition editio dition Shell everything computing practical software provides

1. Pasting Together Data Structures
   
2. 
   
3. R provides several functions that allow you to paste together multiple data structures into a single structure.
   
4. 
   
5. Paste
   
6. 
   
7. The simplest of these functions is paste. The paste function allows you to concatenate multiple character vectors into a single vector. (If you concatenate a vector of another type, it will be coerced to a character vector first.)
   
8. 
   
9. > x <- c("a", "b", "c", "d", "e")
   
10. > y <- c("A", "B", "C", "D", "E")
    
11. > paste(x,y)
    
12. [1] "a A" "b B" "c C" "d D" "e E"
    
13. By default, values are separated by a space; you can specify another separator (or none at all) with the sep argument:
    
14. 
    
15. > paste(x, y, sep="-")
    
16. [1] "a-A" "b-B" "c-C" "d-D" "e-E"
    
17. If you would like all of values in the returned vector to be concatenated with one another (to return just a single value), then specify a value for the collapse argument. The value of collapse will be used as the separator in this value:
    
18. 
    
19. > paste(x, y, sep="-", collapse="#")
    
20. [1] "a-A#b-B#c-C#d-D#e-E"

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1. rbind and cbind
   
2. 
   
3. Sometimes, you would like to bind together multiple data frames or matrices. You can do this with the rbind and cbind functions. The cbind function will combine objects by adding columns. You can picture this as combining two tables horizontally. As an example, let’s start with the data frame for the top five salaries in the NFL in 2008:[33]
   
4. 
   
5. > top.5.salaries
   
6.   name.last name.first     team position   salary
   
7. 1   Manning     Peyton    Colts       QB 18700000
   
8. 2     Brady        Tom Patriots       QB 14626720
   
9. 3    Pepper     Julius Panthers       DE 14137500
   
10. 4    Palmer     Carson  Bengals       QB 13980000
    
11. 5   Manning        Eli   Giants       QB 12916666
    
12. Now let’s create a new data frame with two more columns (a year and a rank):
    
13. 
    
14. > year <- c(2008, 2008, 2008, 2008, 2008)
    
15. > rank <- c(1, 2, 3, 4, 5)
    
16. > more.cols <- data.frame(year, rank)
    
17. > more.cols
    
18.   year rank
    
19. 1 2008    1
    
20. 2 2008    2
    
21. 3 2008    3
    
22. 4 2008    4
    
23. 5 2008    5
    
24. Finally, let’s put together these two data frames:
    
25. 
    
26. > cbind(top.5.salaries, more.cols)
    
27.   name.last name.first     team position   salary year rank
    
28. 1   Manning     Peyton    Colts       QB 18700000 2008    1
    
29. 2     Brady        Tom Patriots       QB 14626720 2008    2
    
30. 3    Pepper     Julius Panthers       DE 14137500 2008    3
    
31. 4    Palmer     Carson  Bengals       QB 13980000 2008    4
    
32. 5   Manning        Eli   Giants       QB 12916666 2008    5
    
33. The rbind function will combine objects by adding rows. You can picture this as combining two tables vertically.
    
34. 
    
35. As an example, suppose that you had a data frame with the top five salaries (as shown above) and a second data frame with the next three salaries:

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SleepyTom 发表于 2016-5-8 00:30
R in a Nutshell 2nd Edition By Joseph Adler

Publisher: O'Reilly Media

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