diff --git a/DESCRIPTION b/DESCRIPTION
index abdf852..559f8c2 100644
--- a/DESCRIPTION
+++ b/DESCRIPTION
@@ -1,6 +1,6 @@
 Package: melodi
 Title: Retrieve Data from the Insee Melodi APIs
-Version: 1.0.0
+Version: 1.0.1
 Authors@R: c(
     person("Cédric", "Bobinec", email = "cedric.bobinec@insee.fr", role = c("aut", "cre")),
     person("Christophe", "Goudeau", role = "aut", email = "christophe.goudeau@insee.fr"),
@@ -30,7 +30,8 @@ Imports:
     zip,
     labelled,
     tibble,
-    stats
+    stats,
+    purrr
 VignetteBuilder: knitr
 URL: https://InseeFrLab.github.io/melodi/, https://github.com/InseeFrLab/melodi
 BugReports: https://github.com/InseeFrLab/melodi/issues
diff --git a/NEWS.md b/NEWS.md
index 9bbf3c2..498fae5 100644
--- a/NEWS.md
+++ b/NEWS.md
@@ -1,3 +1,6 @@
+# melodi 1.0.1
+- #12 : `get_range_geo` : ajout GEO_OBJECT_LABEL + remplacement des boucles par purrr
+
 # melodi 1.0.0
 - Relèvement du seuil de `get_data` à **100 000** lignes (amélioration de l'API Melodi)
 - Centralisation en **options** des paramètres techniques d'appel à l'API, plutôt qu'en paramètre (ou caché) dans les fonctions
diff --git a/R/get_range_geo.R b/R/get_range_geo.R
index 3ce1074..3765256 100644
--- a/R/get_range_geo.R
+++ b/R/get_range_geo.R
@@ -27,59 +27,30 @@ get_range_geo <- function(
   message("Request dataset range : ", url)
 
   dataset <- httr2::request(url) |>
-    httr2::req_user_agent(getOption("rmelodi.req_user_agent")) |>
     httr2::req_perform() |>
     httr2::resp_body_json(simplifyVector = FALSE)
 
-  range <- dataset[["range"]]
-
   # Keep GEO only
-  range <- Filter(function(x) {
-    x[["concept"]][["code"]] == "GEO"
-  }, range)
+  range_geo <- dataset$range |>
+    purrr::keep(\(x) x$concept$code == "GEO") |>
+    purrr::pluck(1, "values")
 
-  if (length(range) == 0) {
+  if (is.null(range_geo) || length(range_geo) == 0) {
     stop("Error: 'GEO' dimension is not present in the dataset.")
   }
 
-  # for null cases (English GEO labels...)
-  safe_extract <- function(x) {
-    if (is.null(x)) NA else x
-  }
-
-  codebook_list <- list()
-
-  for (i in seq_along(range)) {
-    # concepts returned by the API are effectively dimensions of the dataset
-    dimension <- range[[i]][["concept"]][["code"]] |> safe_extract()
-    dimension_label <- range[[i]][["concept"]][["label"]][[lang]] |> safe_extract()
-
-    values <- range[[i]][["values"]] |> safe_extract()
-
-    for (j in seq_along(values)) {
-      value <- values[[j]][["code"]] |> safe_extract()
-      value_label <- values[[j]][["label"]][[lang]] |> safe_extract()
-      value_id <- values[[j]][["id"]] |> safe_extract()
-
-      # Créer la liste sans geo_object si dimension_geo est FALSE
-      codebook_list[[length(codebook_list) + 1]] <- list(
-        dimension = dimension,
-        dimension_label = dimension_label,
-        value = value,
-        value_label = value_label,
-        value_id = value_id
-      )
-    }
-  }
-
-  codebook_df <- do.call(rbind, lapply(codebook_list, as.data.frame))
-  rownames(codebook_df) <- NULL
-
-  codebook_df <- codebook_df |>
-    dplyr::arrange(dimension, value) |>
-    tidyr::separate(value_id, into = c("GEO_REF", "GEO_OBJECT", "GEO"), sep = "-") |>
-    dplyr::mutate(GEO_LABEL = value_label) |>
-    dplyr::select(GEO_REF, GEO_OBJECT, GEO, GEO_LABEL) |>
+  # Unfold
+  codebook_df <- tibble::tibble(
+    GEO_LABEL        = purrr::map_chr(range_geo, ~ .x$label[[lang]] %||% NA_character_),
+    GEO_OBJECT_LABEL = purrr::map_chr(range_geo, ~ .x$type[[lang]]  %||% NA_character_),
+    value_id         = purrr::map_chr(range_geo, "id", .default = NA_character_)
+  ) |>
+    tidyr::separate_wider_delim(
+      value_id,
+      delim = "-",
+      names = c("GEO_REF", "GEO_OBJECT", "GEO"),
+    ) |>
+    dplyr::select(GEO_REF, GEO_OBJECT, GEO_OBJECT_LABEL, GEO, GEO_LABEL) |>
     dplyr::arrange(GEO_OBJECT, GEO)
 
   return(codebook_df)
diff --git a/R/globals.R b/R/globals.R
index 270a242..075b423 100644
--- a/R/globals.R
+++ b/R/globals.R
@@ -11,6 +11,6 @@ globalVariables(
     # get_data
     "value", "GEO",
     # get_range_geo
-    "GEO_REF", "GEO_OBJECT", "GEO_LABEL"
+    "GEO_REF", "GEO_OBJECT", "GEO_LABEL", "GEO_OBJECT_LABEL", "value_id"
   )
 )
diff --git a/tests/testthat/test-get_range_geo.R b/tests/testthat/test-get_range_geo.R
index 05aee76..b3b887a 100644
--- a/tests/testthat/test-get_range_geo.R
+++ b/tests/testthat/test-get_range_geo.R
@@ -5,7 +5,7 @@ vcr::use_cassette("get_range_geo_ec_deces", {
     expect_s3_class(range_geo, "data.frame")
     expect_true(
       all(
-        c("GEO_REF", "GEO_OBJECT", "GEO", "GEO_LABEL") %in%
+        c("GEO_REF", "GEO_OBJECT", "GEO_OBJECT_LABEL", "GEO", "GEO_LABEL") %in%
           colnames(range_geo)
       )
       )
@@ -20,13 +20,21 @@ vcr::use_cassette("get_range_geo_ec_deces", {
       object = unique(range_geo$GEO_OBJECT),
       expected = c("DEP", "FRANCE", "OTHER", "REG")
     )
-    # Check one label is OK
+    # Check one GEO label is OK
     expect_equal(
       object = range_geo %>%
         dplyr::filter(GEO == "44" & GEO_OBJECT == "DEP") %>%
         dplyr::pull(GEO_LABEL),
       expected = "Loire-Atlantique"
     )
+    # Check one GEO_OBJECT label is OK
+    expect_equal(
+      object = range_geo %>%
+        dplyr::filter(GEO_OBJECT == "DEP") %>%
+        dplyr::pull(GEO_OBJECT_LABEL) %>%
+        unique(),
+      expected = "Département"
+    )
   })
 })