Assign range of dates for each unique row in the dataframe.

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Providing reprex is always advisable if you want to get input on your problem as fast as possible. There is more info about how to do one here:

Your problem can be solved with a join and unnest from tidyr:

suppressPackageStartupMessages(library(tidyverse))

years <- tibble::tribble(
  ~year, ~dates,
  "2018",  seq(from = as.Date("2018-01-01"), to = as.Date("2018-12-31"), by = "1 day"),
  "2017",  seq(from = as.Date("2017-01-01"), to = as.Date("2017-12-31"), by = "1 day")
)

df <- tibble::tribble(
  ~gpi_year, ~gpi_country, ~gpi_score,
  "2018",      "Iceland",      1.096,
  "2018",      "South Sudan",  3.508,
  "2017",      "Iceland",      2,
  "2017",      "South Sudan",  1
)

options(pillar.sigfig = 4)

df %>%
  dplyr::left_join(years, by = c("gpi_year" = "year")) %>%
  tidyr::unnest(dates)
#> # A tibble: 1,460 x 4
#>    gpi_year gpi_country gpi_score dates     
#>    <chr>    <chr>           <dbl> <date>    
#>  1 2018     Iceland         1.096 2018-01-01
#>  2 2018     Iceland         1.096 2018-01-02
#>  3 2018     Iceland         1.096 2018-01-03
#>  4 2018     Iceland         1.096 2018-01-04
#>  5 2018     Iceland         1.096 2018-01-05
#>  6 2018     Iceland         1.096 2018-01-06
#>  7 2018     Iceland         1.096 2018-01-07
#>  8 2018     Iceland         1.096 2018-01-08
#>  9 2018     Iceland         1.096 2018-01-09
#> 10 2018     Iceland         1.096 2018-01-10
#> # ... with 1,450 more rows

Created on 2018-11-03 by the reprex package (v0.2.1)

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