小白的数据分析学习R

R语言的文件读取小技能

2019-05-24  本文已影响75人  村野孤云

使用R软件,解锁数据读取新姿势。

1.批量读取文件夹里面某类文件

library(data.table)

file_names<- list.files(pattern = ".csv")
for (i in 1:length(file_names)) { 
  name<-gsub(".csv","",file_names[i])
  assign(name,fread(file_names[i])
}

2.批量将文件夹某类文件读取进来并合并成一个数据框,要求数据规整

file <- list.files(pattern = ".csv")#正则表达式匹配文件后缀
names(file) <- files
data <- lapply(file, fread)
data0 <- do.call(rbind,data)

3.批量读取Excel中多个Sheet工作表合并到一个数据框里,同样要求数据规整。

install.packages("openxlsx")  
library(openxlsx)
aa <-NA
pb <- txtProgressBar(min = 0, max =2, style = 3)
for (i in 1:2){ 
mydata<-read.xlsx("###.xlsx", sheet = i, startRow = 1, colNames = T,
                  rowNames = FALSE, detectDates = FALSE, skipEmptyRows = TRUE,
                  skipEmptyCols = TRUE, rows = NULL, cols = NULL, check.names = FALSE,
                  namedRegion = NULL, na.strings = "NA", fillMergedCells = FALSE)   
aa <- rbind(aa,mydata)  
setTxtProgressBar(pb,i)
}

4.批量写出全局环境中的数据

for (i in 1:length(ls()))
 {write.csv(eval(parse(text = ls(pattern = " ")[i])),
                  paste0(),na="",row.names=F)# paste0()定义文件名  
}

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