我正在尝试从2个不同的目录导入几个文件，每个目录包含~40个txt.files。导入时我想通过公共名称模式合并每个目录中的1个文件。更具体地说，我想使用循环 - 或任何其他方式 - 名称匹配自动完成。最后，我想将连接的文件写入.txt。 有什么办法吗？
到目前为止我得到了什么（主要是通过粘贴不同的东西）：
ls<-list.files("C:/directory1....", pattern=".txt")
ls1<-list.files("C:/directory2....", pattern=".txt")
get<-list()
for(i in 1:length(ls)){
import<-read.table(file=paste("C:/directory1...), ls[i], sep="")
get[[gsub(".txt","",ls[i)]]<-import
}
get2<-list()
for(i in 1:length(ls1)){
import<-read.table(file=paste("C:/directory2...), ls[i], sep="")
get2[[gsub(".txt","",ls[i)]]<-import
}
......基本上就是这样，我不知道如何继续。非常感谢任何帮助。
答案 0 :(得分：0)
这是一个可能适合您的示例。由于问题中没有任何数据，我已经演示了如何使用我的一些本地文件：
path1 <- "./Bolt Exercise/"
path2 <- "./gmad/R/"
all_files <- c(paste(path1, dir(path1, "*.xlsx"), sep = ""),
paste(path2, dir(path2, "*.R"), sep = ""))
common_pattern <- "SLDASM"
read_func <- function(z){
cols <- c("item","qty","per_unit","description","dwg_no","drw","dimension",
"length","material","weight","surface","revision")
return(readxl::read_xlsx(z, skip = 10, col_names = cols))
}
lapply(grep(common_pattern, all_files, val = T),read_func)
<强>输出
> all_files
[1] "./Bolt Exercise/001600211.SLDASM.F Grupo done.xlsx"
[2] "./Bolt Exercise/001600234.SLDASM.F fadhili done.xlsx"
[3] "./Bolt Exercise/001600240.SLDASM.D Gulf done.xlsx"
[4] "./gmad/R/calcCorrProperties.R"
[5] "./gmad/R/getWeatherData.R"
[6] "./gmad/R/getWeatherForecast.R"
[7] "./gmad/R/gmadPlot.R"
[8] "./gmad/R/listMerge.R"
[9] "./gmad/R/listTimeSegments.R"
> grep(common_pattern, all_files, val = T)
[1] "./Bolt Exercise/001600211.SLDASM.F Grupo done.xlsx" "./Bolt Exercise/001600234.SLDASM.F fadhili done.xlsx"
[3] "./Bolt Exercise/001600240.SLDASM.D Gulf done.xlsx"
> lapply(grep(common_pattern, all_files, val = T),read_func)
[[1]]
# A tibble: 6,157 x 12
item qty per_unit description dwg_no drw
<chr> <chr> <chr> <chr> <chr> <chr>
1 Item Qty per unit Description Art./Dwg.No. Drw
2 001 1 1 Pulse Air Intake System SGT6-8000H 100600415 X
3 001.001 8 8 Weather hood upper 121000398 X
4 001.001.001 1 8 Bent plate 950067012 X
5 001.001.002 1 8 Bent plate 950067015 X
6 001.001.003 1 8 Bent plate 950067016 X
7 001.001.100 8 64 Bolt 1701339-04 <NA>
8 001.001.101 8 64 Nut 1701340 <NA>
9 001.001.102 16 128 Washer 1700581 <NA>
10 001.001.103 1 8 Sealing Compound 1001531 <NA>
# ... with 6,147 more rows, and 6 more variables: dimension <chr>, length <chr>, material <chr>, weight <chr>,
# surface <chr>, revision <chr>
[[2]]
# A tibble: 5,100 x 12
item qty per_unit description dwg_no drw dimension length
<chr> <chr> <chr> <chr> <chr> <chr> <chr> <chr>
1 Item Qty per unit Description Art./Dwg.No. Drw Dimension Length
2 001 1 1 Air Intake System SGT6-5000F 100600470 X <NA> <NA>
3 001.001 1 1 Support structure 134600414 X <NA> <NA>
4 001.001.001 1 1 Support structure Top 930603648 X <NA> <NA>
5 001.001.001.001 1 1 Beam 930603660 X <NA> <NA>
6 001.001.001.001.001 1 1 Beam 930603831 X <NA> <NA>
7 001.001.001.001.001.001 1 1 Beam 970023245 <NA> HM500x300A 10304
8 001.001.001.001.001.002 5 5 Plate 970023246 X 16 <NA>
9 001.001.001.001.001.003 1 1 Plate 970023437 X 16 <NA>
10 001.001.001.001.001.004 1 1 Plate 970023286 X 16 <NA>
# ... with 5,090 more rows, and 4 more variables: material <chr>, weight <chr>, surface <chr>, revision <chr>
[[3]]
# A tibble: 2,357 x 12
item qty per_unit description dwg_no drw dimension length material
<chr> <chr> <chr> <chr> <chr> <chr> <chr> <chr> <chr>
1 Item Qty per unit Description Art./Dwg.No. Drw Dimension Length Material
2 001 1 1 Air Intake System 100600492 X <NA> <NA> <NA>
3 001.001 2 2 Weather hood 121600341 X <NA> <NA> <NA>
4 001.001.001 3 6 Bent plate 970025024 X 3 <NA> ASTM A572 Gr 50
5 001.001.002 3 6 Bent plate 970025025 X 3 <NA> ASTM A572 Gr 50
6 001.001.003 1 2 Bent plate 970025022 X 3 <NA> ASTM A572 Gr 50
7 001.001.004 3 6 Bent plate 970025023 X 3 <NA> ASTM A572 Gr 50
8 001.001.005 1 2 Bent plate 970025028 X 3 <NA> ASTM A572 Gr 50
9 001.001.006 1 2 Bent plate 970025029 X 3 <NA> ASTM A572 Gr 50
10 001.001.100 24 48 Bolt 1001477 <NA> M10x20, ISO4017 0 8.8, HDG
# ... with 2,347 more rows, and 3 more variables: weight <chr>, surface <chr>, revision <chr>
如果您想将给定common_pattern的输出合并为一个data.table，则可以将lapply调用括在data.table::rbindlist(lapply(.....), use.names = T, fill = T)中 - 假设您具有相同的结构对于所有文件，如上例所示：
> head(data.table::rbindlist(lapply(grep(common_pattern, all_files, value = T), read_func), use.names = T, fill = T))
item qty per_unit description dwg_no drw dimension length material
1: Item Qty per unit Description Art./Dwg.No. Drw Dimension Length Material
2: 001 1 1 Pulse Air Intake System SGT6-8000H 100600415 X NA NA NA
3: 001.001 8 8 Weather hood upper 121000398 X NA NA Galvanized G90
4: 001.001.001 1 8 Bent plate 950067012 X NA NA Galvanized G90
5: 001.001.002 1 8 Bent plate 950067015 X NA NA Galvanized G90
6: 001.001.003 1 8 Bent plate 950067016 X NA NA Galvanized G90
weight surface revision
1: Weight Surface Revision
2: 244436.3 14125.6 C
3: 51 4.8 A
4: 41 3.8879999999999999 A
5: 4.7 0.45200000000000001 B
6: 4.7 0.45200000000000001 A
对于多个common_patterns，您可以使用嵌套的lapply/sapply语句。