R Cookbook

1. Viewing the List of Installed Packages
   
2. 
   
3. Problem
   
4. You want to know what packages are installed on your machine.
   
5. 
   
6. Solution
   
7. Use the library function with no arguments for a basic list. Use installed.packages to see more detailed information about the packages.

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1. Reading Fixed-Width Records
   
2. 
   
3. Problem
   
4. You are reading data from a file of fixed-width records: records whose data items occur at fixed boundaries.
   
5. 
   
6. Solution
   
7. Read the file using the read.fwf function. The main arguments are the file name and the widths of the fields:
   
8. 
   
9. > records <- read.fwf("filename", widths=c(w1, w2, ..., wn
   
10. ))

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1. Reading Tabular Data Files
   
2. 
   
3. Problem
   
4. You want to read a text file that contains a table of data.
   
5. 
   
6. Solution
   
7. Use the read.table function, which returns a data frame:
   
8. 
   
9. > dfrm <- read.table("filename")

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1. Reading from CSV Files
   
2. 
   
3. Problem
   
4. You want to read data from a comma-separated values (CSV) file.
   
5. 
   
6. Solution
   
7. The read.csv function can read CSV files. If your CSV file has a header line, use this:
   
8. 
   
9. > tbl <- read.csv("filename")
   
10. If your CSV file does not contain a header line, set the header option to FALSE:
    
11. 
    
12. > tbl <- read.csv("filename", header=FALSE)

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1. Writing to CSV Files
   
2. 
   
3. Problem
   
4. You want to save a matrix or data frame in a file using the comma-separated values format.
   
5. 
   
6. Solution
   
7. The write.csv function can write a CSV file:
   
8. 
   
9. > write.csv(x, file="filename", row.names=FALSE)

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1. Reading Tabular or CSV Data from the Web
   
2. 
   
3. Problem
   
4. You want to read data directly from the Web into your R workspace.
   
5. 
   
6. Solution
   
7. Use the read.csv, read.table, and scan functions, but substitute a URL for a file name. The functions will read directly from the remote server:
   
8. 
   
9. > tbl <- read.csv("http://www.example.com/download/data.csv")
   
10. You can also open a connection using the URL and then read from the connection, which may be preferable for complicated files.

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1. Reading Data from HTML Tables
   
2. 
   
3. Problem
   
4. You want to read data from an HTML table on the Web.
   
5. 
   
6. Solution
   
7. Use the readHTMLTable function in the XML package. To read all tables on the page, simply give the URL:
   
8. 
   
9. > library(XML)
   
10. > url <- 'http://www.example.com/data/table.html'
    
11. > tbls <- readHTMLTable(url)
    
12. To read only specific tables, use the which parameter. This example reads the third table on the page:
    
13. 
    
14. > tbl <- readHTMLTable(url, which=3)

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1. Reading Files with a Complex Structure
   
2. 
   
3. Problem
   
4. You are reading data from a file that has a complex or irregular structure.
   
5. 
   
6. Solution
   
7. Use the readLines function to read individual lines; then process them as strings to extract data items.
   
8. 
   
9. Alternatively, use the scan function to read individual tokens and use the argument what to describe the stream of tokens in your file. The function can convert tokens into data and then assemble the data into records.

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1. Reading from MySQL Databases
   
2. 
   
3. Problem
   
4. You want access to data stored in a MySQL database.
   
5. 
   
6. Solution
   
7. Install the RMySQL package on your computer.
   
8. 
   
9. Open a database connection using the dbConnect function.
   
10. 
    
11. Use dbGetQuery to initiate a SELECT and return the result sets.
    
12. 
    
13. Use dbDisconnect to terminate the database connection when you are done.
    
14. 
    
15. Discussion
    
16. This recipe requires that the RMySQL package be installed on your computer. That package requires, in turn, the MySQL client software. If the MySQL client software is not already installed and configured, consult the MySQL documentation or your system administrator.
    
17. 
    
18. Use the dbConnect function to establish a connection to the MySQL database. It returns a connection object which is used in subsequent calls to RMySQL functions:
    
19. 
    
20. library(RMySQL)
    
21. con <- dbConnect(MySQL(), user="userid", password="pswd",
    
22.                  host="hostname", client.flag=CLIENT_MULTI_RESULTS)

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1. Appending Data to a Vector
   
2. 
   
3. Problem
   
4. You want to append additional data items to a vector.
   
5. 
   
6. Solution
   
7. Use the vector constructor (c) to construct a vector with the additional data items:
   
8. 
   
9. > v <- c(v,newItems)
   
10. For a single item, you can also assign the new item to the next vector element. R will automatically extend the vector:
    
11. 
    
12. > v[length(v)+1] <- newItem

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