Попробуйте:
merged <- merge(original, fixes, by = c("country", "city"), all = TRUE)
merged
# country city latitude.x longitude.x latitude.y longitude.y
# 1 usa abc wrong wrong correct correct
# 2 usa iff correct correct <NA> <NA>
# 3 usa lax correct correct <NA> <NA>
# 4 usa sfo correct correct <NA> <NA>
# 5 usa xyz wrong wrong correct correct
merged <- transform(merged,
latitude = ifelse(is.na(latitude.y), latitude.x, latitude.y),
longitude = ifelse(is.na(longitude.y), longitude.x, longitude.y)
)[, c("country", "city", "latitude", "longitude")]
merged
# country city latitude longitude
# 1 usa abc correct correct
# 2 usa iff correct correct
# 3 usa lax correct correct
# 4 usa sfo correct correct
# 5 usa xyz correct correct
dplyr
library(dplyr)
original %>%
left_join(fixes, by = c("country", "city")) %>%
mutate(
latitude = if_else(is.na(latitude.y), latitude.x, latitude.y),
longitude = if_else(is.na(longitude.y), longitude.x, longitude.y)
) %>%
select(-contains("."))
# country city latitude longitude
# 1 usa xyz correct correct
# 2 usa abc correct correct
# 3 usa iff correct correct
# 4 usa sfo correct correct
# 5 usa lax correct correct
data.table
library(data.table)
originalDT <- as.data.table(original)
fixesDT <- as.data.table(fixes)
fixesDT[originalDT, on = c("country", "city")][
,c("latitude", "longitude") :=
.(fifelse(is.na(latitude), i.latitude, latitude),
fifelse(is.na(longitude), i.longitude, longitude)) ][
, .(country, city, latitude, longitude) ]
# country city latitude longitude
# 1: usa xyz correct correct
# 2: usa abc correct correct
# 3: usa iff correct correct
# 4: usa sfo correct correct
# 5: usa lax correct correct
или, если вы предпочитаете внешний вид трубы с data.table
, затем
library(magrittr)
fixesDT[originalDT, on = c("country", "city")] %>%
.[, c("latitude", "longitude") :=
.(fifelse(is.na(latitude), i.latitude, latitude),
fifelse(is.na(longitude), i.longitude, longitude)) ] %>%
.[, .(country, city, latitude, longitude) ]