我想將（left_join）一個tibble（df2）連接到另一個（df1），僅當df1中col2的值為NA時。我目前使用的代碼不是很優雅。任何關于如何縮短代碼的建議將不勝感激！
library(tidyverse)
# df1 contains NAs that need to be replaced by values from df2, for relevant col1 values
df1 <- tibble(col1 = c("a", "b", "c", "d"), col2 = c(1, 2, NA, NA), col3 = c(10, 20, 30, 40))
df2 <- tibble(col1 = c("a", "b", "c", "d"), col2 = c(5, 6, 7, 8), col3 = c(50, 60, 70, 80))
# my current approach
df3 <- df1 %>%
filter(!is.na(col2))
df4 <- df1 %>%
filter(is.na(col2)) %>%
select(col1)%>%
left_join(df2)
# output tibble that is expected
df_final <- df3 %>%
bind_rows(df4)
uj5u.com熱心網友回復：
這是一個dplyr對我有用的小答案，盡管如果您有大量行，它可能會變慢：
df1 %>%
filter(is.na(col2)) %>%
select(col1) %>%
left_join(df2, by = "col1") %>%
bind_rows(df1, .) %>%
filter(!is.na(col2))
uj5u.com熱心網友回復：
我們可以使用data.table方法
library(data.table)
setDT(df1)[setDT(df2), col2 := fcoalesce(col2, i.col2), on = .(col1)]
-輸出
> df1
col1 col2 col3
1: a 1 10
2: b 2 20
3: c 7 30
4: d 8 40
或者一個選項 tidyverse
library(dplyr)
library(stringr)
df1 %>%
left_join(df2, by = c("col1")) %>%
transmute(col1, across(ends_with(".x"),
~ coalesce(., get(str_replace(cur_column(), ".x", ".y"))),
.names = "{str_remove(.col, '.x')}"))
-輸出
# A tibble: 4 x 3
col1 col2 col3
<chr> <dbl> <dbl>
1 a 1 10
2 b 2 20
3 c 7 30
4 d 8 40
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