R-子集数据框，仅保留所有列上符合多个条件的行

我想要的快速总结如下：

我在同一个文件夹中有数千个.csv文件，其中包含诸如折扣率或折扣现金流之类的短语，主要在第一列，但在前10列中也随机包含

使用一些函数（可能是

grepl（）

，

subset（）

，或

filter（）

），我想提取包含这些短语的行，并将它们与它们各自来自的文件名一起放入新的数据框中

---

我遇到的问题是，我一直在尝试的每个函数一次只允许查看一列或两列。以下是我一直使用的代码：

#Reading in a single .csv file for now:
MyData <- read.csv("c:/____________/.csv", header = TRUE, sep=",")

#Assigning numbers to each column since each file I will be plugging in has different column headings:
colnames(MyData) <- c(1:ncol(MyData))

#Using subset to check the 1st column and 5th column for discount rate 
#(only because I knew these 2 columns contained the phrase "discount rate" ahead of time.)
my.data.frame <- subset(MyData, MyData$`1`=="discount rate" | MyData$`5`=="discount rate")

#现在读取单个.csv文件：
MyData这样的东西行得通吗？您可以使用正则表达式（regex）进行修改
根据您的需要提供“折扣”

#Sample dataframe with 'discount rate', 'discounted rates', or 'discounted cash flow' randomly placed
df <- data.frame(a=c('discount rate', 'nothing', 'discounted cash flow', 'nothing', 'nothing'), b=1:5,
  c=6:10, d=c('nothing', 'discounted rates', 'nothing', 'nothing', 'nothing'), stringsAsFactors = F)
df
                     a b  c                d
1        discount rate 1  6          nothing
2              nothing 2  7 discounted rates
3 discounted cash flow 3  8          nothing
4              nothing 4  9          nothing
5              nothing 5 10          nothing

#Get rows where the word 'discount' occurs in any row
discountRows <- unique(unlist(apply(df, 2, function(x) grep('discount', x))))

#Subset df with only rows where the word 'discount' occurs
df[discountRows,]
                     a b c                d
1        discount rate 1 6          nothing
3 discounted cash flow 3 8          nothing
2              nothing 2 7 discounted rates

#Assign subsetted df to new dataframe with original name in it
assign(paste0(deparse(substitute(df)), '_discountRows'), df[discountRows,])

#随机放置“贴现率”、“贴现率”或“贴现现金流”的示例数据框
df考虑使用
grepl
（在正则表达式匹配中返回
TRUE/FALSE
）放在
apply
中。并将所有内容包装在一个更大的
lappy
中，通过多个csv文件构建一个数据帧列表，其中包含子集行，然后在末尾进行行绑定：

setwd("C:/path/to/my/folder")
myfiles <- list.files(path="C:/path/to/my/folder")

dfList <- lapply(myfiles, function(file){
    df <- read.csv(file, header = TRUE)
    colnames(df) <- c(1:ncol(df))

    # ADD COLUMN FOR FILENAME
    df$filename <- file

    # RETURNS 1 IF ANY COLUMN HAS MATCH
    df$discountfound <- apply(df, 1, function(col) 
                              max(grepl("discount rate|discounted cash flow", col)))

    # SUBSET AND REMOVE discountfound COLUMN
    df <- transform(subset(df, df$discountfound == TRUE), discountfound=NULL)
})

# ASSUMES ALL DATAFRAMES HAVE EQUAL NUMBER OF COLUMNS
finaldf <- do.call(rbind, dfList)

setwd（“C:/path/to/my/folder”）
myfiles你可以试试这个。我希望这就是你想要的

mydata = data.frame(a = c(1:3,"discount rate","discounted rates",2:5),
                    b = c("discount rate","discounted rates",2:8))

row = c()
for (i in 1:nrow(mydata)){
  good_row = grep(paste("discount rate","discounted rates",sep="|"),unlist(mydata[i,]))
  if (length(good_row) != 0){
    row = c(row,i)
  }
}

mydata = mydata[row,]

查看
grep
函数。使用grep，它看起来很复杂，因为您必须指定一个要搜索的列名，但我正在查看的所有文件都没有一致的名称或列数