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目标

导入并绑定 xlsx 文件列表，其中包含不可预测的不相关的第一列。（必须消除它，但您不知道哪个文件包含不相关的第一列。）

# sample : remind that the xlsx file originally don't have any column names

    DT1 = data.table(a = c("TYPE","X","Y","Z"), b = c("MONTH","Jan","Feb","Mar"))
    DT2 = data.table(a = c(NA,NA,NA,"random_irrelevant_vale") ,b = c("TYPE","X","Y","W"), c = c("MONTH","Apr","Feb","May"))

# give "idcol" & col_names = FALSE is a must
    PATH_LIST<- list.files(path = "PATH",
                               pattern = "*.xlsx",full.names = TRUE)
    names(PATH_LIST) <- basename(PATH_LIST)

    rbindlist(lapply(PATH_LIST,import,col_names = FALSE,
                             col_types = "text"),
                      idcol = "source",fill = TRUE) 

    # EXPECTED OUTPUT
    TYPE MONTH
    X    Jan
    Y    Feb
    Z    Mar
    X    Apr
    Y    Feb
    W    May
  • 不能简单地使用 !grepl("random_irrevelevant_value",x) 因为 "random_irrevelevant_value" 是一个随机值。

我如何在导入和 rbind 步骤之间实现这一点？

4

1 回答 1

1

假设相关列在后面，并且有些文件没有不相关的列，您可以尝试以下操作：

DTls <- lapply(list.files(pattern="DT(.*).csv"), fread, header=FALSE)
m <- min(lengths(DTls))
rbindlist(
    lapply(DTls, function(DT) {
        cols <- head(names(DT), length(DT)-m)
        if (length(cols) > 0)
            DT[, (cols) := NULL]
        DT
    })
)

输出：

     V1    V2
1: TYPE MONTH
2:    X   Jan
3:    Y   Feb
4:    Z   Mar
5: TYPE MONTH
6:    X   Apr
7:    Y   Feb
8:    W   May

数据文件：

library(data.table)
DT1 = data.table(a = c("TYPE","X","Y","Z"), b = c("MONTH","Jan","Feb","Mar"))
DT2 = data.table(a = c(NA,NA,NA,"random_irrelevant_vale") ,b = c("TYPE","X","Y","W"), c = c("MONTH","Apr","Feb","May"))
fwrite(DT1, "DT1.csv", col.names=FALSE)
fwrite(DT2, "DT2.csv", col.names=FALSE)
于 2019-10-07T04:45:05.620 回答