R 将2个数据帧与其中一个数据帧中用逗号分隔的值合并

我有两个这样的数据帧

df1 <- data.frame(Colors = c("Yellow","Pink","Green","Blue","White","Red"
                            ,"Cyan","Brown","Violet","Orange","Gray"))

df2 <- data.frame(Colors = c("Yellow,Pink","Green","Gold","White","Red,Cyan,Brown",
                             "Violet","Magenta","Gray"))

---

如果我在每个拆分项目上使用

pmatch

进行

df基本
R
解决方案：

split_list <- strsplit(as.character(df2$Colors),",")
keep_lgl   <- sapply(split_list,function(x) !anyNA(pmatch(x,df1$Colors)))
df2[keep_lgl,,drop=FALSE]

#           Colors
# 1    Yellow,Pink
# 2          Green
# 4          White
# 5 Red,Cyan,Brown
# 6         Violet
# 8           Gray

您可以使用
fuzzyjoin
包中的
regex\u internal\u join
来加入
df1
和
df2
。最后，从
df2
列中选择唯一的行

library(dplyr)
library(fuzzyjoin)

regex_inner_join(df2, df1, by=c(Colors = "Colors")) %>%
  select(Colors = Colors.x) %>% distinct()

#           Colors
# 1    Yellow,Pink
# 2          Green
# 3          White
# 4 Red,Cyan,Brown
# 5         Violet
# 6           Gray

# Just to demonstrate, result of joined tables using regex_inner_join. One,
# can work-out to convert data in desired format afterwards.

regex_inner_join(df2, df1, by=c(Colors = "Colors")) 
#         Colors.x Colors.y
# 1    Yellow,Pink   Yellow
# 2    Yellow,Pink     Pink
# 3          Green    Green
# 4          White    White
# 5 Red,Cyan,Brown      Red
# 6 Red,Cyan,Brown     Cyan
# 7 Red,Cyan,Brown    Brown
# 8         Violet   Violet
# 9           Gray     Gray

“黄色、粉色”与“黄色”、“粉色”不同，因此不会返回。红色、青色、棕色也一样。本质上，您正试图在这两个位置上连接两个不同的字符串。联接通过匹配完全相同的ID进行操作
library(tidyverse)
df2 %>% mutate(keep=Colors) %>%
  separate_rows(Colors) %>%
  add_count(keep) %>%
  inner_join(df1) %>%
  add_count(keep) %>% # doesn't do anything here but important in general
  filter(n==nn)   %>% # same
  distinct(keep)  %>%
  rename(Colors=keep)

# # A tibble: 6 x 1
# Colors
# <fctr>
# 1    Yellow,Pink
# 2          Green
# 3          White
# 4 Red,Cyan,Brown
# 5         Violet
# 6           Gray

df2 %>% mutate(keep=Colors) %>%
  separate_rows(Colors) %>%
  left_join(df1 %>% mutate(Colors2=Colors,.)) %>%
  group_by(keep) %>%
  summarize(filt=anyNA(Colors2)) %>%
  filter(!filt) %>%
  select(-2)

# # A tibble: 6 x 1
#             keep
#           <fctr>
# 1           Gray
# 2          Green
# 3 Red,Cyan,Brown
# 4         Violet
# 5          White
# 6    Yellow,Pink

library(dplyr)
library(fuzzyjoin)

regex_inner_join(df2, df1, by=c(Colors = "Colors")) %>%
  select(Colors = Colors.x) %>% distinct()

#           Colors
# 1    Yellow,Pink
# 2          Green
# 3          White
# 4 Red,Cyan,Brown
# 5         Violet
# 6           Gray

# Just to demonstrate, result of joined tables using regex_inner_join. One,
# can work-out to convert data in desired format afterwards.

regex_inner_join(df2, df1, by=c(Colors = "Colors")) 
#         Colors.x Colors.y
# 1    Yellow,Pink   Yellow
# 2    Yellow,Pink     Pink
# 3          Green    Green
# 4          White    White
# 5 Red,Cyan,Brown      Red
# 6 Red,Cyan,Brown     Cyan
# 7 Red,Cyan,Brown    Brown
# 8         Violet   Violet
# 9           Gray     Gray