我在多列数据框中有一列，让我们称之为df1，它由一些文本组成，下面是一些示例行：
"896 European ancestry cases, 2,455 European ancestry controls"
"591 European individuals, 687 European males"
"1,968 African American cases, 3,928 African American controls"
然后我在另一个数据帧中有两列，让我们称之为df2，如下所示：
"European ancestry cases", "European"
"European ancestry controls", "European"
"European individuals", "European"
"European males", "European"
"African American cases", "African"
"African American controls", "African"
引号实际上不存在，我只是用它们来阐明列的数量。
我想在df1中用df2的第二列替换df2的第一列的所有实例。换句话说，我只想更改df1，但使用df2中的信息，这将返回以下结果：
"896 European, 2,455 European"
"591 European, 687 European"
"1,968 African, 3,928 African"
关于如何在R中实现这一点有什么想法吗？
（PS.实际数据对于df1和df2都有数千行，还有更多的变化，这些示例行简化了问题）
你可以试试
# 1
gsub("(European|African)([^,]+)", "\\1", df1$txt)
# 2
gsub("(?<=European|African)[^,]+", "", df1$txt, perl = TRUE)
# [1] "896 European, 2,455 European"
# [2] "591 European, 687 European"
# [3] "1,968 African, 3,928 African"
您还可以使用stringr中的str_replace_all（）来执行多个替换，方法是向其传递一个命名向量（c（模式1=替换1））。
library(tidyverse)
df1 %>%
mutate(txt = str_replace_all(txt, deframe(df2)))
# txt
# 1 896 European, 2,455 European
# 2 591 European, 687 European
# 3 1,968 African, 3,928 African
df1 <- data.frame(txt = c("896 European ancestry cases, 2,455 European ancestry controls",
"591 European individuals, 687 European males",
"1,968 African American cases, 3,928 African American controls"))
df2 <- structure(list(
V1 = c("European ancestry cases", "European ancestry controls", "European individuals", "European males", "African American cases", "African American controls"),
V2 = c("European", "European", "European", "European", "African", "African")),
class = "data.frame", row.names = c(NA, -6L))
这里还有一个：
#library(dplyr)
#library(stringr)
#library(tidyr)
#library(readr)
library(tidyverse)
df1 %>%
mutate(id = row_number()) %>%
separate_rows(col1, sep = "\\, ") %>%
mutate(col1 = str_c(parse_number(col1),
str_extract(col1, str_c(unique(df2$col2), collapse = "|")), sep = " ")) %>%
group_by(id) %>%
mutate(col1 = toString(col1)) %>%
slice(1) %>%
ungroup() %>%
select(-id)
col1
<chr>
1 896 European, 2455 European
2 591 European, 687 European
3 1968 African, 3928 African
数据：
> dput(df1)
structure(list(col1 = c("896 European ancestry cases, 2,455 European ancestry controls",
"591 European individuals, 687 European males", "1,968 African American cases, 3,928 African American controls"
)), class = "data.frame", row.names = c(NA, -3L))
> dput(df2)
structure(list(col1 = c("European ancestry cases", "European ancestry controls",
"European individuals", "European males", "African American cases",
"African American controls"), col2 = c("European", "European",
"European", "European", "African", "African")), class = "data.frame", row.names = c(NA,
-6L))
