1.R數據的保存與加載
可通過save()函數保存為.Rdata文件，通過load()函數將數據加載到R中。
- > a <- 1:10
- > save(a,file='d://data//dumData.Rdata')
- > rm(a) #將對象a從R中刪除
- > load('d://data//dumData.Rdata')
- > print(a)
- [1] 1 2 3 4 5 6 7 8 9 10
2.CSV文件的導入與導出
下面創建df1的數據框，通過函數write.csv()保存為一個.csv文件，然后通過read.csv()將df1加載到數據框df2中。
- > var1 <- 1:5
- > var2 <- (1:5)/10
- > var3 <- c("R and","Data Mining","Examples","Case","Studies")
- > df1 <- data.frame(var1,var2,var3)
- > names(df1) <- c("VariableInt","VariableReal","VariableChar")
- > write.csv(df1,"d://data//dummmyData.csv",row.names = FALSE)
- > df2 <- read.csv("d://data//dummmyData.csv")
- > print(df2)
- VariableInt VariableReal VariableChar
- 1 1 0.1 R and
- 2 2 0.2 Data Mining
- 3 3 0.3 Examples
- 4 4 0.4 Case
- 5 5 0.5 Studies
3.通過ODBC導入與導出數據
RODBC提供了ODBC數據庫的連接。
3.1從數據庫中讀取數據
odbcConnect()建立一個數據庫連接，sqlQuery()向數據庫發送一個SQL查詢，odbcClose()關閉數據庫連接。
- library(RODBC)
- connection <- odbcConnect(dsn="servername",uid="userid",pwd="******")
- query <- "SELECT * FROM lib.table WHERE ..."
- # or read query from file
- # query <- readChar("data/myQuery.sql", nchars=99999)
- myData <- sqlQuery(connection, query, errors = TRUE)
- odbcClose(connection)
sqlSave()和sqlUpdate()用於寫入或更新一個ODBC數據庫表。
R語言數據儲存與讀取
1 首先用getwd() 獲得當前目錄，用setwd("C:/data")設定當前目錄
2 數據保存
創建數據框d
>d <- data.frame(obs = c(1, 2, 3), treat = c("A", "B", "A"), weight = c(2.3, NA, 9))
2.1 保存為簡單文本
>write.table(d, file = "c:/data/foo.txt", row.names = F, quote = F) # 空格分隔
>write.table(d, file = "c:/data/foo.txt", row.names = F, quote = F, sep="\t") # tab 分隔的文件
2.2 保存為逗號分割文本
>write.csv(d, file = "c:/data/foo.csv", row.names = F, quote = F)
2.3 保存為R格式文件
>save(d, file = "c:/data/foo.Rdata")
2.4 保存工作空間鏡像
>save.image( ) = save(list =ls(all=TRUE), file=".RData")
3 數據讀取
讀取函數主要有：read.table( ), scan( ) ，read.fwf( )，readLines().
3.1 用 read.table( ) 讀 "c:\data” 下houses.dat
>setwd("C:/data"); HousePrice <- read.table(file="houses.dat")
如果明確數據第一行做表頭，則使用header選項
>HousePrice <- read.table("houses.dat", header=TRUE)
read.table( ) 變形有： read.csv( ),read.csv2( ), read.delim( ), read.delim2( ).前兩讀取逗號分割數據，后兩個讀取其他分割符數據。
3.2 用scan( ) 比read.table( ) 更靈活。
但要指定 變量類型：如：C:\data\data.dat:
M 65 168
M 70 172
F 54 156
F 58 163
>mydata <- scan("data.dat", what = list("", 0, 0))
>mydata <- scan("data.dat", what = list(Sex="", Weight=0, Height=0))
3.3 用read.fwf( )讀取文件中一些固定寬度數據
如：C:\data\data.txt:
A1.501.2
A1.551.3
B1.601.4
>mydata <- read.fwf("data.txt", widths=c(1, 4, 3), col.names=c("X","Y","Z"))
4 excel格式數據讀取
4.1 利用剪切板
選擇excel數據，再用(CTRL+C)復制。在R中鍵入命令：
>mydata <- read.delim("clipboard")
4.2 使用程序包 RODBC.
如： c:\data\body.xls
Sex Weight Height
M 65 168
M 70 172
F 54 156
F 58 163
> library(RODBC)
> z <- odbcConnectExcel("c:/data/body.xls")
> foo <- sqlFetch(z, "Sheet1")
> close(z)
To an Excel Spreadsheet 保存為Excel文件：
library(xlsx) # 注意： 軟件包需要安裝
write.xlsx(mydata, "c:/mydata.xlsx") # 參考： https://danganothererror.wordpress.com/2012/02/12/write-data-frame-to-excel-file/
The WriteXLS function from the WriteXLS package (link: http://cran.r-project.org/web/packages/WriteXLS/index.html) can write data to Excel.
Alternatively, write.xlsx from the xlsx package (link: http://cran.r-project.org/web/packages/xlsx/) will also work.
注意：
1 writeLines 會在最后一行/或者每行末尾加一個換行符
# fileConn<-file(output_fasta)
# writeLines(mystr, fileConn)
# close(fileConn)
2 另外一個寫文件的方法是sink，不會在行末加換行符
sink(output_fasta)
cat(mystr)
sink()
write is a wrapper for cat, which gives further details on the format used.
save for writing any R objects, write.table for data frames, and scan for reading data.