R TIBLE full_连接并有条件地替换NA
对不起,我没有更好的主题。我不能百分之百确定正确的条款。给定下面的R TIBLE full_连接并有条件地替换NA,r,tidyverse,R,Tidyverse,对不起,我没有更好的主题。我不能百分之百确定正确的条款。给定下面的foo和bar,我想通过full\u join(我想)生成bam foo在full\u加入后您可以通过ID library(dplyr) library(tidyr) full_join(foo,bar,by=c("ID","value","variable")) %>% group_by(ID) %>% fill(everything(), .di
foo
和bar
,我想通过full\u join
(我想)生成bam
foo在full\u加入后
您可以通过ID
library(dplyr)
library(tidyr)
full_join(foo,bar,by=c("ID","value","variable")) %>%
group_by(ID) %>%
fill(everything(), .direction = 'updown')
# ID Longitude Latitude value variable Elev
# <int> <dbl> <dbl> <dbl> <chr> <dbl>
#1 1 -118 47 2 A 100
#2 2 -117 46 5 B 200
#3 1 -118 47 4 A 100
#4 2 -117 46 1 B 200
#5 1 -118 47 19 D 100
#6 2 -117 46 20 E 200
#7 1 -118 47 32 D 100
#8 2 -117 46 18 E 200
库(dplyr)
图书馆(tidyr)
完全联接(foo,bar,by=c(“ID”,“value”,“variable”))%>%
分组依据(ID)%>%
填充(所有内容(),.direction='updown')
#ID经纬度值变量Elev
#
#1 1-118 47 2 A 100
#2 2-117 46 5 B 200
#3 1-118 47 4 A 100
#4 2-117 46 1 B 200
#5 1-118 47 19 D 100
#6 2-117 46 20 E 200
#7 1-118 47 32 D 100
#8 2-117 46 18 E 200
library(dplyr)
library(tidyr)
full_join(foo,bar,by=c("ID","value","variable")) %>%
group_by(ID) %>%
fill(everything(), .direction = 'updown')
# ID Longitude Latitude value variable Elev
# <int> <dbl> <dbl> <dbl> <chr> <dbl>
#1 1 -118 47 2 A 100
#2 2 -117 46 5 B 200
#3 1 -118 47 4 A 100
#4 2 -117 46 1 B 200
#5 1 -118 47 19 D 100
#6 2 -117 46 20 E 200
#7 1 -118 47 32 D 100
#8 2 -117 46 18 E 200