用R中另一列的值替换一列的多个观测值

我试图用另外两列中的值替换两列中的值。这是一个相当基本的问题，有人问过

python

，但我使用的是R

我有一个类似这样的

df

（只在更大的范围内[>20000]）：

对于63只松鼠，我需要替换它们的

locx

和

locy

值

我通常用以下代码替换值：

library(dplyr)    

df <- df %>%
   mutate(locx = ifelse (squirrel_id=="6391", "12.5", locx),
         locy = ifelse (squirrel_id=="6391", "15.5", locy),
         locx = ifelse (squirrel_id=="8443", "2.5", locx),
         locy = ifelse (squirrel_id=="8443", "80", locy)) #etc for 63 squirrels

但这会产生额外的126行代码，我怀疑有一种更简单的方法可以做到这一点

我确实在一个单独的

df

中有所有新的

locx

和

locy

值，但我不知道如何通过

squirrel\u id

连接这两个

数据帧

df

带有需要替换旧

df

中的值：

squirrel_id    new_locx    new_locy   
6391           12.5        15.5 
8443           2.5         80
6025           -55.0       0.0

---

如何更有效地执行此操作？

您可以

左键连接两个数据帧，然后使用
if\u else
语句获取右键
locx
和
locy
。试用：

library(dplyr)
df %>% left_join(df2, by = "squirrel_id") %>%
        mutate(locx = if_else(is.na(new_locx), locx, new_locx), # as suggested by @echasnovski, we can also use locx = coalesce(new_locx, locx)
               locy = if_else(is.na(new_locy), locy, new_locy)) %>% # or locy = coalesce(new_locy, locy)
        select(-new_locx, -new_locy)
# output
  squirrel_id  locx locy  dist
1        6391  12.5 15.5  50.0
2        6391  12.5 15.5  20.0
3        6391  12.5 15.5  15.5
4        8443   2.5 80.0 800.0
5        6025 -55.0  0.0   0.0
6        5000  18.5 18.5  10.0 # squirrel_id 5000 was created for an example of id 
# present if df but not in df2

数据

df <- structure(list(squirrel_id = c(6391L, 6391L, 6391L, 8443L, 6025L, 
5000L), locx = c(17.5, 17.5, 17.5, 20.5, -5, 18.5), locy = c(10, 
10, 10, 1, -0.5, 12.5), dist = c(50, 20, 15.5, 800, 0, 10)), class = "data.frame", row.names = c(NA, 
-6L))
df2 <- structure(list(squirrel_id = c(6391L, 8443L, 6025L), new_locx = c(12.5, 
2.5, -55), new_locy = c(15.5, 80, 0)), class = "data.frame", row.names = c(NA, 
-3L))

df使用@ANG的数据，这里有一个
data.table
解决方案。它通过引用连接并更新原始的
df

library(data.table)

setDT(df)
setDT(df2)

df[df2, on = c('squirrel_id'), `:=` (locx = new_locx, locy = new_locy) ]

df

   squirrel_id  locx locy  dist
1:        6391  12.5 15.5  50.0
2:        6391  12.5 15.5  20.0
3:        6391  12.5 15.5  15.5
4:        8443   2.5 80.0 800.0
5:        6025 -55.0  0.0   0.0
6:        5000  18.5 12.5  10.0

另见：



请注意，您可以使用
coalesce（x，y）
而不是
if_else（is.na（x），x，y）
。感谢您指出@echasnovski，我将编辑我的帖子
df <- structure(list(squirrel_id = c(6391L, 6391L, 6391L, 8443L, 6025L, 
5000L), locx = c(17.5, 17.5, 17.5, 20.5, -5, 18.5), locy = c(10, 
10, 10, 1, -0.5, 12.5), dist = c(50, 20, 15.5, 800, 0, 10)), class = "data.frame", row.names = c(NA, 
-6L))
df2 <- structure(list(squirrel_id = c(6391L, 8443L, 6025L), new_locx = c(12.5, 
2.5, -55), new_locy = c(15.5, 80, 0)), class = "data.frame", row.names = c(NA, 
-3L))

library(data.table)

setDT(df)
setDT(df2)

df[df2, on = c('squirrel_id'), `:=` (locx = new_locx, locy = new_locy) ]

df

   squirrel_id  locx locy  dist
1:        6391  12.5 15.5  50.0
2:        6391  12.5 15.5  20.0
3:        6391  12.5 15.5  15.5
4:        8443   2.5 80.0 800.0
5:        6025 -55.0  0.0   0.0
6:        5000  18.5 12.5  10.0