检查向量中的单词是否出现在数据框不同列的同一行中

Question

我正在尝试对我的数据进行故障排除，并检查某个名称是否出现在同一行的两个不同列中（相同的观察结果）：

df1 <- data.frame(
  text1 = c("John Jay Jakson",
            "John Jay Jakson",
            "John Jay Jakson",
            "John Jack Jakson"), 
  text2 = c("Jerry Jack Jameson", 
            "Jerry Jack Jameson", 
            "Jerry Jack Jameson", 
            "Jerry Jack Jameson"))

df2 <- data.frame(
  names = c("John", "Jay", "Jackson", "Jerry", "Jack", "Jameson"))

我想出的代码如下

data.check = sapply(df2$names, function(x) (grepl(x, df1$text1) & grepl(x, df1$text2))==TRUE)

或者：

which(sapply(df2$names, function(x) (grepl(x, df1$text1) & grepl(x, df1$text2))==TRUE))

但这些并不是筛选数据的最佳方法。相反，我想在 df1 中有一个新列 df1$check，它根据 df1$text1 和 df1$text2 下的每一行是否具有相同的名称来保存 1/0。

我知道将此代码分配给新列是行不通的：

df1$check = sapply(df2$names, function(x) (grepl(x, df1$text1) & grepl(x, df1$text2))==TRUE)

它给了我第 4 行错误，这应该是正确的。

感谢任何帮助，谢谢。

Answer 1

我包括一个 dplyr 方法：

# import required libraries
library(dplyr)
library(stringr)

# create your data (I added two more rows)
df1 <- data.frame(
  text1 = c("John Jay Jakson",
            "John Jay Jakson",
            "John Jay Jakson",
            "John Jack Jakson","Peter","John Snow"),
  text2 = c("Jerry Jack Jameson", 
            "Jerry Jack Jameson", 
            "Jerry Jack Jameson", 
            "Jerry Jack Jameson","Peter", "Clay Snow"))

df2 <- data.frame(
  names = c("John", "Jay", "Jackson", "Jerry", "Jack", "Jameson"))

# optionally convert df2 to vector or list
v2<-as.vector(df2$names)

#use of str_detect() to look for the string
# use of case_when() that works like if/else
# by including the | operator between the different names
# create a new column called check to store 1s and 0s  

df1<-df1%>%
  mutate(check=case_when(str_detect(text1,paste(v2, collapse = "|"))==TRUE & str_detect(text2,paste(v2, collapse = "|"))==TRUE ~"1",
                         TRUE~"0"))

Answer 2

OP 代码中 sapply 的输出 return 是一个逻辑 matrix。

> sapply(df2$names, function(x) (grepl(x, df1$text1) & grepl(x, df1$text2)))
      John   Jay Jackson Jerry  Jack Jameson
[1,] FALSE FALSE   FALSE FALSE FALSE   FALSE
[2,] FALSE FALSE   FALSE FALSE FALSE   FALSE
[3,] FALSE FALSE   FALSE FALSE FALSE   FALSE
[4,] FALSE FALSE   FALSE FALSE  TRUE   FALSE

matrix 的每一列都应该收敛到一个逻辑值以创建一个向量。我们可以用 rowSums 包裹逻辑矩阵，然后将行式总和转换为逻辑向量 (> 0) 并将其强制转换回二进制 (+ - TRUE -> 1, FALSE -> 0)

df1$check <- +(rowSums(sapply(df2$names, function(x) 
     (grepl(x, df1$text1) & grepl(x, df1$text2)))) > 0)
df1$check
[1] 0 0 0 1

或者另一种选择是使用 lapply、return 循环 list 并使用 Reduce 和 | 到 return 向量

df1$check <- +(Reduce(`|`, lapply(df2$names, function(x)
      (grepl(x, df1$text1) & grepl(x, df1$text2)))))

检查向量中的单词是否出现在数据框不同列的同一行中

checking whether a word from a vector appears in the same row in different columns of a data frame

r

dataframe

sapply

grepl