diff --git a/R/creer_graphe_5_2.R b/R/creer_graphe_5_2.R
index e4a64c34bef58fe737c033feb5f3d36db3125bea..1bdffb0d1a7a84b83ff79888d9e007f77b299fee 100644
--- a/R/creer_graphe_5_2.R
+++ b/R/creer_graphe_5_2.R
@@ -24,20 +24,22 @@ creer_graphe_5_2 <- function(millesime_obs_artif,code_reg) {
     code_reg = as.character(code_reg)
   }
 
+  datemax <- lubridate::ymd(paste0(millesime_obs_artif,'0101'))
+
+  datemin <- datemax - lubridate::years(9)
+  datefin <- datemax + lubridate::years(10)
+  # datefin <- as.Date("2031-01-01")
+  millesime_fin <- millesime_obs_artif + 9
+  pas <- millesime_obs_artif - lubridate::year(datemin)
+
   data <- observatoire_artificialisation %>%
     COGiter::filtrer_cog(reg = code_reg) %>%
     dplyr::filter(.data$TypeZone %in% c("R\u00e9gions","D\u00e9partements")) %>%
     dplyr::select(.data$TypeZone,.data$Zone,.data$date,.data$flux_naf_artificialisation_total) %>%
     dplyr::arrange(.data$TypeZone,.data$Zone,.data$date) %>%
     dplyr::mutate(simul=FALSE,
-                  flux_naf_artificialisation_total = .data$flux_naf_artificialisation_total / 10000)
-
-  datemax <- lubridate::ymd(paste0(millesime_obs_artif,'0101'))
-  datemin <- min(data$date)
-  datefin <- datemax + lubridate::years(10)
-  # datefin <- as.Date("2031-01-01")
-  millesime_fin <- millesime_obs_artif + 9
-  pas <- millesime_obs_artif - lubridate::year(datemin)
+                  flux_naf_artificialisation_total = .data$flux_naf_artificialisation_total / 10000) %>%
+    dplyr::filter(.data$date >= datemin)
 
   simul <- data %>%
     dplyr::filter(.data$date %in% c(datemin,datemax)) %>%