根据另一个数据框中的列值从 R 中的数据框中删除行

Question

我有两个数据框如下：

df1 <- data.frame(fruit=c("apple", "blackberry", "orange", "pear", "grape"), 
color=c("black", "purple", "blue", "green", "red"), 
quantity1=c(1120, 7600, 21409, 120498, 25345), 
quantity2=c(1200, 7898, 21500, 140985, 27098), 
taste=c("sweet", "bitter", "sour", "salty", "spicy"))

df2 <- data.frame(fruit=c("apple", "orange", "pear"), 
color=c("black", "yellow", "green"), 
quantity=c(1145, 65094, 120500))

我想根据 df2 中的行删除 df1 中的行，它们必须匹配所有 3 个条件：

1. 水果名称必须匹配
2. 颜色必须匹配
3. df2 中的数量必须是 df1 中两个数量之间的值

我的示例中的 output 应如下所示：

df3 <- data.frame(fruit=c("blackberry", "orange", "grape"), 
color=c("purple", "blue", "red"), 
quantity1=c(7600, 21409, 25345), 
quantity2=c(21500, 7898, 27098), 
taste=c("bitter", "sour", "spicy"))

Answer 1

我想知道是否也可以使用tidyverse ：

library(tidyverse)
df1 %>%
  left_join(df2, by = c("fruit", "color")) %>%
  filter(is.na(quantity) | quantity <= quantity1 | quantity >= quantity2)
  
#>        fruit  color quantity1 quantity2  taste quantity
#> 1 blackberry purple      7600      7898 bitter       NA
#> 2     orange   blue     21409     21500   sour       NA
#> 3      grape    red     25345     27098  spicy       NA

Answer 2

使用data.table ，我们可以使用非等连接

library(data.table)
setDT(df1)[!df2, on = .(fruit, color, quantity1 <= quantity,
           quantity2 >= quantity)]
#        fruit  color quantity1 quantity2  taste
#1: blackberry purple      7600      7898 bitter
#2:     orange   blue     21409     21500   sour
#3:      grape    red     25345     27098  spicy

---

或者使用与fuzzy_anti_join相同的方法，如本文所示

Answer 3

您可以使用来自fuzzy_anti_join fuzzyjoin的fuzzy_anti_join：

fuzzyjoin::fuzzy_anti_join(df1, df2, 
     by = c('fruit', 'color','quantity1' = 'quantity', 'quantity2' = 'quantity'), 
     match_fun = list(`==`, `==`, `<=`, `>=`))

# A tibble: 3 x 5
#  fruit      color  quantity1 quantity2 taste 
#  <chr>      <chr>      <dbl>     <dbl> <chr> 
#1 blackberry purple      7600      7898 bitter
#2 orange     blue       21409     21500 sour  
#3 grape      red        25345     27098 spicy