После группировки по 'стране', mutate
, чтобы получить соответствующий 'tfp.level' для значения 'год' 1980
library(dplyr)
df1 %>%
group_by(country) %>%
mutate(tfllevel1980 = `tfp level`[year == 1980])
# A tibble: 10 x 5
# Groups: country [2]
# country ISO year `tfp level` tfllevel1980
# <chr> <chr> <int> <dbl> <dbl>
# 1 Australia AUS 1980 0.797 0.797
# 2 Australia AUS 1981 0.809 0.797
# 3 Australia AUS 1982 0.791 0.797
# 4 Australia AUS 1983 0.818 0.797
# 5 Australia AUS 1984 0.828 0.797
# 6 Australia AUS 1985 0.825 0.797
# 7 Costa Rica CRI 1980 1.08 1.08
# 8 Costa Rica CRI 1981 1.03 1.08
# 9 Costa Rica CRI 1982 0.934 1.08
#10 Costa Rica CRI 1983 0.921 1.08
Или используя base R
df1$tfplevel1980 <- with(df1, ave(`tfp level` * (year == 1980),
country, FUN = function(x) x[x!= 0]))
Данные
df1 <- structure(list(country = c("Australia", "Australia", "Australia",
"Australia", "Australia", "Australia", "Costa Rica", "Costa Rica",
"Costa Rica", "Costa Rica"), ISO = c("AUS", "AUS", "AUS", "AUS",
"AUS", "AUS", "CRI", "CRI", "CRI", "CRI"), year = c(1980L, 1981L,
1982L, 1983L, 1984L, 1985L, 1980L, 1981L, 1982L, 1983L),
`tfp level` = c(0.796980202,
0.808527768, 0.790943801, 0.818122745, 0.827925146, 0.825170755,
1.082085967, 1.033975005, 0.934024811, 0.920588791)),
class = "data.frame", row.names = c(NA,
-10L))