R TIBLE full_连接并有条件地替换NA

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

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
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