根据R中的另一个数据帧更新列值 [英] updating column values based on another data frame in R

问题描述

我到处都是stackoverflow，找不到我想要的东西，因此，如果这是重复的帖子，对不起，非常感谢您的链接！

I've looked around stackoverflow and couldn't find what i was looking for, so if this is a duplicate post, sorry AND I'd greatly appreciate the link!

我有两个数据框：CarDF和重复的CarDF

I have two data frames: CarDF and duplicateCarDF

ID <- c(1,2,3,4,5,6,7,8)
car <- c("acura", "audi", "benz", "benz", "bmw", "toyota", "toyota", "jeep")
year <- c(2001, 2002, '2004', '2016','1999', '2017', '2017',2005)

CarDF <- data.frame(ID, car, year)

ID2 <-c(4,7)
car2 <- c("benz2", "toyota2")
year2 <- c(2016, 2017)

duplicateCarDF <- data.frame(ID = ID2, car = car2, year = year2)

我的目标是使用基于ID的重复CarDF中的更新名称来更新CarDF中的汽车。

My goal is to update the cars in CarDF with the updated names in duplicateCarDF based on the IDs.

我尝试了以下操作...

I've tried the following...

CarDF$car <- ifelse(duplicateCarDF$ID %in% CarDF$ID, duplicateCarDF$car, CarDF$car )

但它将汽车名称交替更改为benz2和Toyota2。我只想更新ID 4和7的汽车。

but it changes the car names to benz2 and toyota2 alternating. I just want to update the car for ID 4 and 7.

任何帮助将不胜感激！

推荐答案

使用 dplyr 动词，我们可以通过 ID left_join 然后有条件地替换 car 根据新值是否丢失。

Using dplyr verbs we can left_join by ID and then conditionally replace car based on whether or not the new value is missing.

library(dplyr)

CarDF %>%
  left_join(
    duplicateCarDF %>%           # note: the year column doesn't add any
      select(ID, new_car = car), # value here unless you have duplicated ID values
    by = "ID"
  ) %>%
  mutate(
    car = if_else(
      is.na(new_car),
      as.character(car),    # note: I'm coercing these to character because
      as.character(new_car) # we've joined two df with different levels
    )
  ) %>%
  select(-new_car)

#   ID     car year
# 1  1   acura 2001
# 2  2    audi 2002
# 3  3    benz 2004
# 4  4   benz2 2016
# 5  5     bmw 1999
# 6  6  toyota 2017
# 7  7 toyota2 2017
# 8  8    jeep 2005

这篇关于根据R中的另一个数据帧更新列值的文章就介绍到这了，希望我们推荐的答案对大家有所帮助，也希望大家多多支持IT屋！