diff --git a/DESCRIPTION b/DESCRIPTION index 3ed9a2ab901682dfeaa03c7a9768569775e52a57..e479dd1eef10af67222bfbda30822200fabfdcef 100644 --- a/DESCRIPTION +++ b/DESCRIPTION @@ -8,7 +8,7 @@ Description: Application shiny de valorisation des mesures de présence de nitrates dans les cours d'eau et les nappes des Pays de la Loire. License: MIT + file LICENSE Depends: - R (>= 2.10) + R (>= 3.5) Imports: config (>= 0.3.2), dplyr, diff --git a/NAMESPACE b/NAMESPACE index 65aa63e2a456deb46c8b1797b93edd3953fdff75..37036e8c1ec1b625e56c62454844c4783269f376 100644 --- a/NAMESPACE +++ b/NAMESPACE @@ -46,7 +46,6 @@ export(prepa_masse_eau_bassin_versant_PDL_fct) export(prepa_nitrates_P90_fct) export(prepa_nitrates_P90_telecharger_fct) export(prepa_nitrates_bassin_versant_fct) -export(prepa_nitrates_fct) export(prepa_nitrates_maxP90_bassin_versant_fct) export(prepa_nitrates_maxP90_bassin_versant_telecharger_fct) export(prepa_nitrates_moyP90_bassin_versant_fct) @@ -86,7 +85,6 @@ importFrom(dplyr,do) importFrom(dplyr,filter) importFrom(dplyr,first) importFrom(dplyr,group_by) -importFrom(dplyr,inner_join) importFrom(dplyr,lag) importFrom(dplyr,left_join) importFrom(dplyr,mutate) diff --git a/R/data_doc-bassin_versant_col_pa.R b/R/data_doc-bassin_versant_col_pa.R index aaf1dc40de4119b940896dc0c8b9004d33e5c523..c7b9602b6a8f66a3018f1c244a279dbdfd3f1339 100644 --- a/R/data_doc-bassin_versant_col_pa.R +++ b/R/data_doc-bassin_versant_col_pa.R @@ -2,7 +2,7 @@ #' #' pression azotée (minérale, organique) par bassin versant par campagne culturale. #' -#' @format A data frame with 4616 rows and 5 variables: +#' @format A data frame with 5538 rows and 5 variables: #' \describe{ #' \item{ code_bassin_versant }{ character } #' \item{ nom_bassin_versant }{ character } diff --git a/R/data_doc-bassin_versant_pa_telecharger.R b/R/data_doc-bassin_versant_pa_telecharger.R index 0ff35df82377d09c7d2fe888dedf255d00b20e20..f7f4dd4f1ca519b35f60ce5bfae39943e011d858 100644 --- a/R/data_doc-bassin_versant_pa_telecharger.R +++ b/R/data_doc-bassin_versant_pa_telecharger.R @@ -2,7 +2,7 @@ #' #' données des bassins versants pour la page Pression azotée à télécharger. #' -#' @format A data frame with 2308 rows and 7 variables: +#' @format A data frame with 2769 rows and 7 variables: #' \describe{ #' \item{ code_bassin_versant }{ character } #' \item{ nom_bassin_versant }{ character } diff --git a/R/data_doc-choix_couleur_P90.R b/R/data_doc-choix_couleur_P90.R index 5cc5f96b71c9e4d59168363f7fe0c192c89eec8d..6063c3b56d4fd038fac9bdc1dee04e85cb67611a 100644 --- a/R/data_doc-choix_couleur_P90.R +++ b/R/data_doc-choix_couleur_P90.R @@ -2,7 +2,7 @@ #' #' définition de la couleur afférente à chacune des classes de percentiles 90. #' -#' @format A data frame with 8 rows and 2 variables: +#' @format A data frame with 7 rows and 2 variables: #' \describe{ #' \item{ classe }{ character } #' \item{ couleur }{ character } diff --git a/R/data_doc-correspondance_sage_bassin_versant.R b/R/data_doc-correspondance_sage_bassin_versant.R index b3b72af0bfdd4cf6e2458adfd634e79cdd86b4c4..4f778fd5efe873f31b1fd631e59031fcf093db24 100644 --- a/R/data_doc-correspondance_sage_bassin_versant.R +++ b/R/data_doc-correspondance_sage_bassin_versant.R @@ -2,11 +2,11 @@ #' #' correspondance entre les SAGE et les bassins versants qui y sont inclus en totalité ou en partie pour la région des Pays de la Loire. #' -#' @format A data frame with 457 rows and 4 variables: +#' @format A data frame with 463 rows and 4 variables: #' \describe{ #' \item{ code_sage }{ character } - #' \item{ code_bassin_versant }{ character } #' \item{ nom_sage }{ character } + #' \item{ code_bassin_versant }{ character } #' \item{ nom_bassin_versant }{ character } #' } #' @source DREAL diff --git a/R/data_doc-departement_col_pa.R b/R/data_doc-departement_col_pa.R index 21b740f5937640bd96d06938bf8b2be626079854..42c4b0884456ad74728ff5569190b65fc85b6e0c 100644 --- a/R/data_doc-departement_col_pa.R +++ b/R/data_doc-departement_col_pa.R @@ -2,7 +2,7 @@ #' #' pression azotée (globale, minérale, organique) par département et région par campagne culturale. #' -#' @format A data frame with 60 rows and 5 variables: +#' @format A data frame with 72 rows and 5 variables: #' \describe{ #' \item{ annee_declaration }{ character } #' \item{ Nom }{ character } diff --git a/R/data_doc-departement_pa_telecharger.R b/R/data_doc-departement_pa_telecharger.R index 17b65adb3406bda71e7209e2e32217e4091e34ca..79fc7731c4288dc91b470d3e6e92cbeacbfcb1a1 100644 --- a/R/data_doc-departement_pa_telecharger.R +++ b/R/data_doc-departement_pa_telecharger.R @@ -2,7 +2,7 @@ #' #' données des départements et de la région pour la page Pression azotée à télécharger. #' -#' @format A data frame with 30 rows and 5 variables: +#' @format A data frame with 36 rows and 5 variables: #' \describe{ #' \item{ Nom }{ character } #' \item{ annee_declaration }{ character } diff --git a/R/data_doc-depassement_seuil_eso.R b/R/data_doc-depassement_seuil_eso.R index 8fbd00b348f5c50262a4ad4725fa2912647d5f27..694cb6c0829d922ffaef22dcc6a7934c84a20b8e 100644 --- a/R/data_doc-depassement_seuil_eso.R +++ b/R/data_doc-depassement_seuil_eso.R @@ -2,7 +2,7 @@ #' #' pourcentage des mesures nitrates des eaux souterraines dépassant le seuil de 50 mg/l au niveau régional ou par SAGE ou par bassin versant, par année. #' -#' @format A data frame with 867 rows and 5 variables: +#' @format A data frame with 921 rows and 5 variables: #' \describe{ #' \item{ annee }{ factor } #' \item{ depassement }{ numeric } diff --git a/R/data_doc-depassement_seuil_esu.R b/R/data_doc-depassement_seuil_esu.R index ee2bf53c465965a79651f871eb8e27f2d24e8db4..df24fa3cb0b45a0fc8c135045744f57335f20778 100644 --- a/R/data_doc-depassement_seuil_esu.R +++ b/R/data_doc-depassement_seuil_esu.R @@ -2,7 +2,7 @@ #' #' pourcentage des mesures nitrates des eaux superficielles dépassant le seuil de 18 mg/l au niveau régional ou par SAGE ou par bassin versant, par année. #' -#' @format A data frame with 3444 rows and 5 variables: +#' @format A data frame with 3694 rows and 5 variables: #' \describe{ #' \item{ annee }{ factor } #' \item{ depassement }{ numeric } diff --git a/R/data_doc-masse_eau_bassin_versant_PDL.R b/R/data_doc-masse_eau_bassin_versant_PDL.R index 5081d872d9ce3f5b8eab9e39df0acd4ef797260c..19a681855b08eb2bc2c4fb95f0e66f8e67a41281 100644 --- a/R/data_doc-masse_eau_bassin_versant_PDL.R +++ b/R/data_doc-masse_eau_bassin_versant_PDL.R @@ -2,7 +2,7 @@ #' #' géodataframe des bassins versants de la région des Pays de la Loire. #' -#' @format A data frame with 457 rows and 3 variables: +#' @format A data frame with 463 rows and 3 variables: #' \describe{ #' \item{ code_bassin_versant }{ character } #' \item{ nom_bassin_versant }{ character } diff --git a/R/data_doc-n_sage_r52.R b/R/data_doc-n_sage_r52.R index 701d6f173a14674cac6add1c5f521575d62c6d8d..a91a2a25fd8fc36868cc332209a538f38a5ed6b1 100644 --- a/R/data_doc-n_sage_r52.R +++ b/R/data_doc-n_sage_r52.R @@ -2,10 +2,9 @@ #' #' géodataframe des SAGE de la région des Pays de la Loire. #' -#' @format A data frame with 24 rows and 16 variables: +#' @format A data frame with 24 rows and 15 variables: #' \describe{ #' \item{ nid }{ character } - #' \item{ vid }{ character } #' \item{ nom_sage }{ character } #' \item{ type }{ character } #' \item{ code_sage }{ character } diff --git a/R/data_doc-nitrates_P90.R b/R/data_doc-nitrates_P90.R index f5cbd086c5ec7126bff184fa9abdee901d0edada..cac24a8fcdedb013cb57312b2a4f83cc05d05959 100644 --- a/R/data_doc-nitrates_P90.R +++ b/R/data_doc-nitrates_P90.R @@ -2,12 +2,15 @@ #' #' percentiles 90 par station par annee. #' -#' @format A data frame with 11972 rows and 9 variables: +#' @format A data frame with 12848 rows and 12 variables: #' \describe{ #' \item{ code_station }{ factor } + #' \item{ code_bss }{ factor } + #' \item{ code_sise_eaux }{ factor } + #' \item{ code_naiades }{ factor } #' \item{ libelle_station }{ factor } - #' \item{ source_station }{ factor } #' \item{ annee }{ numeric } + #' \item{ source_station }{ factor } #' \item{ id_usage }{ factor } #' \item{ P90 }{ numeric } #' \item{ code_nature_eau }{ factor } diff --git a/R/data_doc-nitrates_P90_telecharger.R b/R/data_doc-nitrates_P90_telecharger.R index bdbff40527e60a85135fcd20aa9b3746aa626b62..757ae57afbb531cb337317637515feffb7c0252e 100644 --- a/R/data_doc-nitrates_P90_telecharger.R +++ b/R/data_doc-nitrates_P90_telecharger.R @@ -2,7 +2,7 @@ #' #' données à télécharger des percentiles 90 par station par annee . #' -#' @format A data frame with 7781 rows and 13 variables: +#' @format A data frame with 12848 rows and 13 variables: #' \describe{ #' \item{ annee }{ numeric } #' \item{ code_nature_eau }{ factor } diff --git a/R/data_doc-nitrates_maxP90_bassin_versant.R b/R/data_doc-nitrates_maxP90_bassin_versant.R index 3b24d34003f39eebb6e77bb62b00f02620caa464..1e5b09f09927e3215f27b10f4a18a4e2d8a957f9 100644 --- a/R/data_doc-nitrates_maxP90_bassin_versant.R +++ b/R/data_doc-nitrates_maxP90_bassin_versant.R @@ -2,7 +2,7 @@ #' #' maxima des percentiles 90 par bassin versant par année. #' -#' @format A data frame with 5797 rows and 5 variables: +#' @format A data frame with 6231 rows and 5 variables: #' \describe{ #' \item{ code_bassin_versant }{ character } #' \item{ annee }{ numeric } diff --git a/R/data_doc-nitrates_maxP90_bassin_versant_telecharger.R b/R/data_doc-nitrates_maxP90_bassin_versant_telecharger.R index 4d9354323e47e57e21e0fa62cdecee77b2afad37..80ba9d0fb3345db5a1392a4d83b7f6ed9012d0a0 100644 --- a/R/data_doc-nitrates_maxP90_bassin_versant_telecharger.R +++ b/R/data_doc-nitrates_maxP90_bassin_versant_telecharger.R @@ -2,7 +2,7 @@ #' #' données à télécharger des maxima des percentiles 90 par bassin versant par année. #' -#' @format A data frame with 5937 rows and 8 variables: +#' @format A data frame with 6231 rows and 8 variables: #' \describe{ #' \item{ annee }{ numeric } #' \item{ code_nature_eau }{ factor } diff --git a/R/data_doc-nitrates_moyP90_bassin_versant.R b/R/data_doc-nitrates_moyP90_bassin_versant.R index 9a1a5dc5e204cfdb9704578be2a21fb552939d12..9dd4f38740ac089ca691b555b64ea722cc31915e 100644 --- a/R/data_doc-nitrates_moyP90_bassin_versant.R +++ b/R/data_doc-nitrates_moyP90_bassin_versant.R @@ -2,7 +2,7 @@ #' #' moyennes des percentiles 90 par bassin versant par année. #' -#' @format A data frame with 5797 rows and 5 variables: +#' @format A data frame with 6231 rows and 5 variables: #' \describe{ #' \item{ code_bassin_versant }{ character } #' \item{ annee }{ numeric } diff --git a/R/data_doc-nitrates_moyP90_bassin_versant_telecharger.R b/R/data_doc-nitrates_moyP90_bassin_versant_telecharger.R index c7d9b835c14411688eef8115d58343fbe0c09a2d..631a7fa543e0c69e6a057cae56b88ab8e87755a5 100644 --- a/R/data_doc-nitrates_moyP90_bassin_versant_telecharger.R +++ b/R/data_doc-nitrates_moyP90_bassin_versant_telecharger.R @@ -2,7 +2,7 @@ #' #' données à télécharger des moyennes des percentiles 90 par bassin versant par année. #' -#' @format A data frame with 5937 rows and 8 variables: +#' @format A data frame with 6231 rows and 8 variables: #' \describe{ #' \item{ annee }{ numeric } #' \item{ code_nature_eau }{ factor } diff --git a/R/data_doc-nitrates_telecharger.R b/R/data_doc-nitrates_telecharger.R index 54f0b46bdf04d1451afb424f9c40c060553c83f7..fa0faa867a1c64d2023265bc7078126a7c9ec1b9 100644 --- a/R/data_doc-nitrates_telecharger.R +++ b/R/data_doc-nitrates_telecharger.R @@ -2,7 +2,7 @@ #' #' données à télécharger des mesures de nitrates par station. #' -#' @format A data frame with 63239 rows and 15 variables: +#' @format A data frame with 81525 rows and 15 variables: #' \describe{ #' \item{ annee }{ numeric } #' \item{ mois }{ numeric } @@ -13,9 +13,9 @@ #' \item{ nom_bassin_versant }{ character } #' \item{ code_station }{ character } #' \item{ libelle_station }{ character } - #' \item{ source_prelevement }{ character } + #' \item{ source_prelevement_analyse }{ character } #' \item{ resultat_analyse }{ numeric } - #' \item{ code_remarque }{ integer } + #' \item{ code_remarque }{ numeric } #' \item{ insee_dep }{ factor } #' \item{ code_commune }{ character } #' \item{ captage_prioritaire }{ logical } diff --git a/R/data_doc-nitrates_tendanceP90.R b/R/data_doc-nitrates_tendanceP90.R index 9c671efc4c727c0df058791176d62901d19c316b..266bbd803682bff2472595d0480d3e74c7c0be83 100644 --- a/R/data_doc-nitrates_tendanceP90.R +++ b/R/data_doc-nitrates_tendanceP90.R @@ -2,7 +2,7 @@ #' #' tendances des percentiles 90 par station par période de 10 ans. #' -#' @format A data frame with 8754 rows and 5 variables: +#' @format A data frame with 10135 rows and 5 variables: #' \describe{ #' \item{ code_station }{ factor } #' \item{ libelle_station }{ factor } diff --git a/R/data_doc-nitrates_tendanceP90_telecharger.R b/R/data_doc-nitrates_tendanceP90_telecharger.R index 136423e48128d681d87441651a68aa31fd318a70..de32794aff15c33e5320b4880ead107dd4ab1345 100644 --- a/R/data_doc-nitrates_tendanceP90_telecharger.R +++ b/R/data_doc-nitrates_tendanceP90_telecharger.R @@ -2,7 +2,7 @@ #' #' données à télécharger des tendances des percentiles 90 par station par période de 10 ans. #' -#' @format A data frame with 6311 rows and 12 variables: +#' @format A data frame with 10135 rows and 12 variables: #' \describe{ #' \item{ periode }{ factor } #' \item{ code_nature_eau }{ factor } diff --git a/R/data_doc-periode_nitrates_tendanceP90.R b/R/data_doc-periode_nitrates_tendanceP90.R index 9fa48fb235c251c95e0285bb13256b74bde951c7..80303af825f6dda1e492e8cde81e36c6b15dc30f 100644 --- a/R/data_doc-periode_nitrates_tendanceP90.R +++ b/R/data_doc-periode_nitrates_tendanceP90.R @@ -2,7 +2,7 @@ #' #' affectation d'une période de 10 ans à chaque année. #' -#' @format A data frame with 16 rows and 2 variables: +#' @format A data frame with 17 rows and 2 variables: #' \describe{ #' \item{ annee }{ factor } #' \item{ periode }{ factor } diff --git a/R/data_doc-repartition_P90.R b/R/data_doc-repartition_P90.R index 54d0d29a9d12c6cf978714bd1a6c69adbdb0efff..db89325c5be3fbf1ae68b353e85ef1f532b63179 100644 --- a/R/data_doc-repartition_P90.R +++ b/R/data_doc-repartition_P90.R @@ -2,7 +2,7 @@ #' #' répartition du nombre de stations par classe de percentiles 90 au niveau régional ou par SAGE ou par bassin versant, par annee. #' -#' @format A data frame with 11750 rows and 8 variables: +#' @format A data frame with 11505 rows and 8 variables: #' \describe{ #' \item{ code_nature_eau }{ factor } #' \item{ annee }{ numeric } diff --git a/R/data_doc-repartition_maxBV.R b/R/data_doc-repartition_maxBV.R index 3bb3c894553a39e32724f4fc494720e42bbdc23b..ca6eb2885cd24f35ff1639d65a393f0694820b12 100644 --- a/R/data_doc-repartition_maxBV.R +++ b/R/data_doc-repartition_maxBV.R @@ -2,7 +2,7 @@ #' #' répartition des maxima de percentiles 90 par classes de concentration au niveau régional ou par SAGE, par année. #' -#' @format A data frame with 2854 rows and 7 variables: +#' @format A data frame with 2580 rows and 7 variables: #' \describe{ #' \item{ code_nature_eau }{ factor } #' \item{ annee }{ numeric } diff --git a/R/data_doc-repartition_moyBV.R b/R/data_doc-repartition_moyBV.R index 8ae1e140c762f3ce47cfbfa9f9c0a863ead676c2..e51152364589f506b73d390eab5eb67d182e6f04 100644 --- a/R/data_doc-repartition_moyBV.R +++ b/R/data_doc-repartition_moyBV.R @@ -2,7 +2,7 @@ #' #' répartition des moyennes de percentiles 90 par classes de concentration au niveau régional ou par SAGE, par année. #' -#' @format A data frame with 2733 rows and 7 variables: +#' @format A data frame with 2431 rows and 7 variables: #' \describe{ #' \item{ code_nature_eau }{ factor } #' \item{ annee }{ numeric } diff --git a/R/data_doc-repartition_tendanceP90.R b/R/data_doc-repartition_tendanceP90.R index 75dfc1711fcf73af3d3ae4d23b7cf0cd9199cf80..09f20181fb8e0b1bd4eaee8bec0dcd6fad7bfbb1 100644 --- a/R/data_doc-repartition_tendanceP90.R +++ b/R/data_doc-repartition_tendanceP90.R @@ -2,7 +2,7 @@ #' #' répartition des tendances de percentiles 90 par classes de concentration au niveau régional ou par SAGE ou par bassin versant, par période de 10 ans. #' -#' @format A data frame with 6412 rows and 8 variables: +#' @format A data frame with 7254 rows and 8 variables: #' \describe{ #' \item{ code_nature_eau }{ factor } #' \item{ periode }{ factor } diff --git a/R/data_doc-station_pdl.R b/R/data_doc-station_pdl.R index bde9eb65679f1c09f3d1148fd38731b8c8399638..858c4a09bc83b4740917403719ed15dcc341a360 100644 --- a/R/data_doc-station_pdl.R +++ b/R/data_doc-station_pdl.R @@ -2,21 +2,23 @@ #' #' géodataframe des stations de mesures de la région des Pays de la Loire. #' -#' @format A data frame with 3816 rows and 14 variables: +#' @format A data frame with 3870 rows and 16 variables: #' \describe{ #' \item{ code_station }{ character } + #' \item{ code_bss }{ character } + #' \item{ code_sise_eaux }{ character } + #' \item{ code_naiades }{ character } #' \item{ libelle_station }{ character } + #' \item{ code_nature_eau }{ character } #' \item{ date_creation }{ Date } - #' \item{ source }{ character } + #' \item{ source_station }{ character } #' \item{ code_masse_eau }{ character } - #' \item{ code_eu_masse_eau }{ character } + #' \item{ code_bassin_versant }{ character } #' \item{ code_commune }{ character } #' \item{ code_sage }{ character } - #' \item{ code_bassin_versant }{ character } #' \item{ captage_prioritaire }{ logical } #' \item{ insee_dep }{ factor } #' \item{ test }{ logical } - #' \item{ code_nature_eau }{ character } #' \item{ the_geom }{ sfc_POINT,sfc } #' } #' @source DREAL diff --git a/R/fct_carte_P90.R b/R/fct_carte_P90.R index 661220acde7baa715d99a03d5a7e78de221ae98e..d01a3dc8ae420fcdeca426f8ae197bff97cd2279 100644 --- a/R/fct_carte_P90.R +++ b/R/fct_carte_P90.R @@ -116,7 +116,8 @@ carte_P90_station_fct <- function(selectSage, selectBV, nitrates_P90_carte, sage lapply(htmltools::HTML) factpal_P90_station <- leaflet::colorFactor( # palette = c("#33CCFF","#00CC33","#66FF99","#FFFF00","orange","red","#FF6633","#CC3300"), - palette = c("#33CCFF", "#00CC33", "#66FF99", "#FFFF00", "orange", "red", "#A10684", "#723E64"), + # palette = c("#33CCFF", "#00CC33", "#66FF99", "#FFFF00", "orange", "red", "#A10684", "#723E64"), + palette = c("#33CCFF", "#00CC33", "#FFFF00", "orange", "red", "#A10684", "#723E64"), nitrates_P90$classe ) if(selectSage == "Tous" & selectBV == "Tous")({ diff --git a/R/fct_carte_moymaxP90.R b/R/fct_carte_moymaxP90.R index 8ad8c199dbdf68fa40655ce79da35c5d24a554dc..99114d5be2a74f40b569485e6b457c551c747d14 100644 --- a/R/fct_carte_moymaxP90.R +++ b/R/fct_carte_moymaxP90.R @@ -88,7 +88,8 @@ carte_bassin_versant_fct <- function(modalite, selectSage, nitrates_bassin_versa titre_legende <- paste("Classe<br>", qualification_percentiles, "des P90<br>par bassin versant") factpal_bassin_versant <- leaflet::colorFactor( - palette = c("#33CCFF", "#00CC33", "#66FF99", "#FFFF00", "orange", "red", "#A10684", "#723E64"), + # palette = c("#33CCFF", "#00CC33", "#66FF99", "#FFFF00", "orange", "red", "#A10684", "#723E64"), + palette = c("#33CCFF", "#00CC33", "#FFFF00", "orange", "red", "#A10684", "#723E64"), nitrates_maxP90_bassin_versant$classe ) diff --git a/R/fct_preparation_data.R b/R/fct_preparation_data.R index 559a9cbdb5691e57ab3939b5968035004681c6dd..f48d081f47befcd4abfb16ef2835134586f505d8 100644 --- a/R/fct_preparation_data.R +++ b/R/fct_preparation_data.R @@ -48,38 +48,6 @@ prepa_station_PDL_fct <- function(station){ dplyr::filter(test == FALSE) } -#' prepa_nitrates_fct -#' -#' @description Une fonction pour produire les tables des mesures nitrates en fonction du code_nature_eau (ESU ou ESO) des stations -#' @param station_code_nature_eau choix dans la table des stations selon leur code_nature_eau (ESU ou ESO) -#' -#' @return Un dataframe. -#' -#' @export -#' @importFrom dplyr filter inner_join rename select -#' @importFrom sf st_drop_geometry -prepa_nitrates_fct <- function(station_code_nature_eau){ - nitrates_esu_ou_eso <- nitrates %>% - dplyr::inner_join( - station_pdl %>% dplyr::filter(code_nature_eau == station_code_nature_eau) %>% sf::st_drop_geometry(), - by = c("code_station") - ) %>% - dplyr::rename( - code_intervenant_prelevement = "code_intervenant.x", - code_intervenant_analyse = "code_intervenant.y", - source_prelevement = "source.x", - source_station = "source.y" - ) %>% - dplyr::select( - code_station, libelle_station, source_station, - code_prelevement, source_prelevement, - date_prelevement, heure_prelevement, annee, mois, - id_usage, - code_analyse, date_analyse, - resultat_analyse, code_remarque - ) -} - #' prepa_correspondance_sage_bassin_versant_fct #' #' @description Une fonction pour produire la table de correspondance entre bassin_versant et SAGE @@ -196,6 +164,7 @@ prepa_NatureEau_fct <- function(station_pdl){ #' @importFrom dplyr group_by arrange mutate n filter rename select ungroup case_when mutate_if prepa_nitrates_P90_fct <- function(nitrates){ nitrates_P90 <- nitrates %>% + dplyr::left_join(station_pdl %>% sf::st_drop_geometry()) %>% dplyr::group_by(code_station, annee) %>% dplyr::arrange(code_station, annee, desc(resultat_analyse)) %>% dplyr::mutate( @@ -211,8 +180,9 @@ prepa_nitrates_P90_fct <- function(nitrates){ dplyr::mutate(classe = dplyr::case_when( P90 < 10 ~ "0-10 mg/l", P90 < 18 ~ "10-18 mg/l", - P90 < 30 ~ "18-30 mg/l", - P90 < 40 ~ "30-40 mg/l", + # P90 < 30 ~ "18-30 mg/l", + # P90 < 40 ~ "30-40 mg/l", + P90 < 40 ~ "18-40 mg/l", P90 < 50 ~ "40-50 mg/l", P90 < 60 ~ "50-60 mg/l", P90 < 70 ~ "60-70 mg/l", @@ -220,8 +190,10 @@ prepa_nitrates_P90_fct <- function(nitrates){ ) ) %>% dplyr::select( - -c(code_prelevement, source_prelevement, date_prelevement, heure_prelevement, mois, - code_analyse, date_analyse, code_remarque) + # -c(code_prelevement_analyse, source_prelevement_analyse, date_prelevement, heure_prelevement, mois, + # date_analyse, code_remarque) + c(code_station, code_bss, code_sise_eaux, code_naiades, libelle_station, + annee, source_station, id_usage, P90, code_nature_eau, pos_a_garder, classe) ) %>% dplyr::filter(!is.na(classe)) %>% dplyr::mutate_if(is.character,as.factor) @@ -358,7 +330,9 @@ prepa_nitrates_bassin_versant_fct <- function(nitrates_P90){ nitrates_bassin_versant <- nitrates_P90 %>% dplyr::semi_join(station_pdl) %>% dplyr::left_join( - station_pdl %>% dplyr::select(c(code_station, libelle_station, code_bassin_versant)) %>% sf::st_drop_geometry(), + station_pdl %>% + dplyr::select(c(code_station, libelle_station, code_bassin_versant)) %>% + sf::st_drop_geometry(), by = c("code_station") ) %>% dplyr::group_by(code_bassin_versant, annee, code_nature_eau) %>% @@ -385,12 +359,13 @@ prepa_nitrates_moyP90_bassin_versant_fct <- function(nitrates_bassin_versant){ classe = dplyr::case_when( moyP90 < 10 ~ "0-10 mg/l", moyP90 < 18 ~ "10-18 mg/l", - moyP90 < 30 ~ "18-30 mg/l", - moyP90 < 40 ~ "30-40 mg/l", + # moyP90 < 30 ~ "18-30 mg/l", + # moyP90 < 40 ~ "30-40 mg/l", + moyP90 < 40 ~ "18-40 mg/l", moyP90 < 50 ~ "40-50 mg/l", moyP90 < 60 ~ "50-60 mg/l", moyP90 < 70 ~ "60-70 mg/l", - moyP90 >=70 ~ "70 mg/l et plus" + moyP90 >= 70 ~ "70 mg/l et plus" ) ) } @@ -411,12 +386,13 @@ prepa_nitrates_maxP90_bassin_versant_fct <- function(nitrates_bassin_versant){ classe = dplyr::case_when( maxP90 < 10 ~ "0-10 mg/l", maxP90 < 18 ~ "10-18 mg/l", - maxP90 < 30 ~ "18-30 mg/l", - maxP90 < 40 ~ "30-40 mg/l", + # maxP90 < 30 ~ "18-30 mg/l", + # maxP90 < 40 ~ "30-40 mg/l", + maxP90 < 40 ~ "18-40 mg/l", maxP90 < 50 ~ "40-50 mg/l", maxP90 < 60 ~ "50-60 mg/l", - maxP90 < 70 ~ "60-70 mg/l", - maxP90 >=70 ~ "70 mg/l et plus" + maxP90 < 70 ~ "60-70 mg/l", + maxP90 >= 70 ~ "70 mg/l et plus" ) ) } @@ -435,15 +411,19 @@ prepa_nitrates_maxP90_bassin_versant_fct <- function(nitrates_bassin_versant){ #' @export #' @importFrom dplyr semi_join left_join select group_by summarise n mutate ungroup bind_rows rename #' @importFrom sf st_drop_geometry -prepa_repartition_P90_fct <- function(nitrates_P90, - station_pdl, - n_sage_r52, - masse_eau_bassin_versant_PDL, - correspondance_sage_bassin_versant){ +prepa_repartition_P90_fct <- function( + nitrates_P90, + station_pdl, + n_sage_r52, + masse_eau_bassin_versant_PDL, + correspondance_sage_bassin_versant + ){ repartition_P90_region <- nitrates_P90 %>% dplyr::semi_join(station_pdl) %>% dplyr::left_join( - station_pdl %>% dplyr::select(code_station, code_sage, code_bassin_versant, insee_dep) %>% sf::st_drop_geometry() + station_pdl %>% + dplyr::select(code_station, code_sage, code_bassin_versant, insee_dep) %>% + sf::st_drop_geometry() ) %>% dplyr::group_by(code_nature_eau, annee, classe) %>% dplyr::summarise(n = dplyr::n()) %>% @@ -457,7 +437,9 @@ prepa_repartition_P90_fct <- function(nitrates_P90, repartition_P90_sage <- nitrates_P90 %>% dplyr::semi_join(station_pdl) %>% dplyr::left_join( - station_pdl %>% dplyr::select(code_station, code_sage, code_bassin_versant, insee_dep) %>% sf::st_drop_geometry() + station_pdl %>% + dplyr::select(code_station, code_sage, code_bassin_versant, insee_dep) %>% + sf::st_drop_geometry() ) %>% dplyr::group_by(code_nature_eau, code_sage, annee, classe) %>% dplyr::summarise(n = dplyr::n()) %>% @@ -476,7 +458,9 @@ prepa_repartition_P90_fct <- function(nitrates_P90, repartition_P90_bassin_versant <- nitrates_P90 %>% dplyr::semi_join(station_pdl) %>% dplyr::left_join( - station_pdl %>% dplyr::select(code_station, code_sage, code_bassin_versant, insee_dep) %>% sf::st_drop_geometry() + station_pdl %>% + dplyr::select(code_station, code_sage, code_bassin_versant, insee_dep) %>% + sf::st_drop_geometry() ) %>% dplyr::group_by(code_nature_eau, code_bassin_versant, annee, classe) %>% dplyr::summarise(n = dplyr::n()) %>% @@ -518,11 +502,13 @@ prepa_repartition_P90_fct <- function(nitrates_P90, #' @export #' @importFrom dplyr semi_join group_by summarise n mutate ungroup rename left_join select bind_rows #' @importFrom sf st_drop_geometry -prepa_repartition_tendanceP90_fct <- function(nitrates_tendanceP90, - station_pdl, - n_sage_r52, - masse_eau_bassin_versant_PDL, - correspondance_sage_bassin_versant){ +prepa_repartition_tendanceP90_fct <- function( + nitrates_tendanceP90, + station_pdl, + n_sage_r52, + masse_eau_bassin_versant_PDL, + correspondance_sage_bassin_versant + ){ repartition_tendanceP90_region <- nitrates_tendanceP90 %>% dplyr::semi_join(station_pdl) %>% dplyr::group_by(code_nature_eau, periode, tendance) %>% @@ -541,7 +527,9 @@ prepa_repartition_tendanceP90_fct <- function(nitrates_tendanceP90, repartition_tendanceP90_sage <- nitrates_tendanceP90 %>% dplyr::semi_join(station_pdl) %>% dplyr::left_join( - station_pdl %>% dplyr::select(code_station, code_sage, code_bassin_versant) %>% sf::st_drop_geometry() + station_pdl %>% + dplyr::select(code_station, code_sage, code_bassin_versant) %>% + sf::st_drop_geometry() ) %>% dplyr::group_by(code_nature_eau, code_sage, periode,tendance) %>% dplyr::summarise(n = dplyr::n()) %>% @@ -562,7 +550,9 @@ prepa_repartition_tendanceP90_fct <- function(nitrates_tendanceP90, repartition_tendanceP90_bassin_versant <- nitrates_tendanceP90 %>% dplyr::semi_join(station_pdl) %>% dplyr::left_join( - station_pdl %>% dplyr::select(code_station, code_sage, code_bassin_versant) %>% sf::st_drop_geometry() + station_pdl %>% + dplyr::select(code_station, code_sage, code_bassin_versant) %>% + sf::st_drop_geometry() ) %>% dplyr::group_by(code_nature_eau, code_bassin_versant, periode, tendance) %>% dplyr::summarise(n = dplyr::n()) %>% @@ -603,9 +593,11 @@ prepa_repartition_tendanceP90_fct <- function(nitrates_tendanceP90, #' @export #' @importFrom dplyr group_by summarise n mutate ungroup rename left_join filter select bind_rows #' @importFrom sf st_drop_geometry -prepa_repartition_moymaxBV_fct <- function(nitrates_moymaxP90_bassin_versant, - correspondance_sage_bassin_versant, - n_sage_r52){ +prepa_repartition_moymaxBV_fct <- function( + nitrates_moymaxP90_bassin_versant, + correspondance_sage_bassin_versant, + n_sage_r52 + ){ repartition_region <- nitrates_moymaxP90_bassin_versant %>% dplyr::group_by(code_nature_eau, annee, classe) %>% dplyr::summarise(n = dplyr::n()) %>% @@ -678,11 +670,13 @@ prepa_nitrates_nature_eau_fct <- function(station_pdl, nature_eau){ #' @export #' @importFrom dplyr group_by mutate n ungroup filter select left_join bind_rows mutate_if arrange #' @importFrom sf st_drop_geometry -prepa_depassement_seuil_nature_eau_fct <- function(nitrates_nature_eau, - seuil, - station_pdl, - n_sage_r52, - masse_eau_bassin_versant_PDL){ +prepa_depassement_seuil_nature_eau_fct <- function( + nitrates_nature_eau, + seuil, + station_pdl, + n_sage_r52, + masse_eau_bassin_versant_PDL + ){ depassement_seuil_region <- nitrates_nature_eau %>% dplyr::group_by(annee) %>% unique() %>% @@ -701,10 +695,6 @@ prepa_depassement_seuil_nature_eau_fct <- function(nitrates_nature_eau, dplyr::mutate(nom_sage = "Tous", nom_bassin_versant = "Tous") depassement_seuil_sage <- nitrates_nature_eau %>% - dplyr::left_join( - station_pdl %>% dplyr::select(code_station, code_sage) %>% sf::st_drop_geometry(), - by = "code_station" - ) %>% dplyr::group_by(code_sage, annee) %>% unique() %>% dplyr::mutate(nbre_mesure = dplyr::n()) %>% @@ -728,10 +718,6 @@ prepa_depassement_seuil_nature_eau_fct <- function(nitrates_nature_eau, dplyr::select(-c(code_sage)) depassement_seuil_bassin_versant <- nitrates_nature_eau %>% - dplyr::left_join( - station_pdl %>% dplyr::select(code_station, code_sage, code_bassin_versant) %>% sf::st_drop_geometry(), - by = "code_station" - ) %>% dplyr::group_by(code_bassin_versant, code_sage, annee) %>% unique() %>% dplyr::mutate(nbre_mesure = dplyr::n()) %>% @@ -779,9 +765,11 @@ prepa_depassement_seuil_nature_eau_fct <- function(nitrates_nature_eau, #' @export #' @importFrom dplyr semi_join select left_join arrange #' @importFrom sf st_drop_geometry -prepa_nitrates_telecharger_fct <- function(nitrates, - station_pdl, - correspondance_sage_bassin_versant){ +prepa_nitrates_telecharger_fct <- function( + nitrates, + station_pdl, + correspondance_sage_bassin_versant + ){ nitrates_telecharger <- nitrates %>% dplyr::semi_join(station_pdl, by = c("code_station")) %>% dplyr::select( @@ -792,10 +780,11 @@ prepa_nitrates_telecharger_fct <- function(nitrates, libelle_station, resultat_analyse, code_remarque, - source_prelevement + source_prelevement_analyse ) %>% dplyr::left_join( - station_pdl %>% sf::st_drop_geometry() %>% + station_pdl %>% + sf::st_drop_geometry() %>% dplyr::select( code_station, code_sage, @@ -812,7 +801,7 @@ prepa_nitrates_telecharger_fct <- function(nitrates, code_sage, nom_sage, code_bassin_versant, nom_bassin_versant, code_station, libelle_station, - source_prelevement, resultat_analyse, code_remarque, + source_prelevement_analyse, resultat_analyse, code_remarque, insee_dep, code_commune, captage_prioritaire ) %>% @@ -831,9 +820,11 @@ prepa_nitrates_telecharger_fct <- function(nitrates, #' @export #' @importFrom dplyr semi_join select left_join arrange #' @importFrom sf st_drop_geometry -prepa_nitrates_P90_telecharger_fct <- function(nitrates_P90, - station_pdl, - correspondance_sage_bassin_versant){ +prepa_nitrates_P90_telecharger_fct <- function( + nitrates_P90, + station_pdl, + correspondance_sage_bassin_versant + ){ nitrates_P90_telecharger <- nitrates_P90 %>% dplyr::semi_join(station_pdl, by = c("code_station")) %>% dplyr::select( @@ -845,7 +836,8 @@ prepa_nitrates_P90_telecharger_fct <- function(nitrates_P90, classe ) %>% dplyr::left_join( - station_pdl %>% sf::st_drop_geometry() %>% + station_pdl %>% + sf::st_drop_geometry() %>% dplyr::select( code_station, code_sage, @@ -881,13 +873,16 @@ prepa_nitrates_P90_telecharger_fct <- function(nitrates_P90, #' @export #' @importFrom dplyr semi_join select left_join arrange #' @importFrom sf st_drop_geometry -prepa_nitrates_tendanceP90_telecharger_fct <- function(nitrates_tendanceP90, - station_pdl, - correspondance_sage_bassin_versant){ +prepa_nitrates_tendanceP90_telecharger_fct <- function( + nitrates_tendanceP90, + station_pdl, + correspondance_sage_bassin_versant + ){ nitrates_tendanceP90_telecharger <- nitrates_tendanceP90 %>% dplyr::semi_join(station_pdl, by = c("code_station")) %>% dplyr::left_join( - station_pdl %>% sf::st_drop_geometry() %>% + station_pdl %>% + sf::st_drop_geometry() %>% dplyr::select( code_station, code_sage, @@ -921,8 +916,10 @@ prepa_nitrates_tendanceP90_telecharger_fct <- function(nitrates_tendanceP90, #' #' @export #' @importFrom dplyr left_join select arrange -prepa_nitrates_moyP90_bassin_versant_telecharger_fct <- function(nitrates_moyP90_bassin_versant, - correspondance_sage_bassin_versant){ +prepa_nitrates_moyP90_bassin_versant_telecharger_fct <- function( + nitrates_moyP90_bassin_versant, + correspondance_sage_bassin_versant + ){ nitrates_moyP90_bassin_versant_telecharger <- nitrates_moyP90_bassin_versant %>% dplyr::left_join(correspondance_sage_bassin_versant) %>% dplyr::select( @@ -946,8 +943,10 @@ prepa_nitrates_moyP90_bassin_versant_telecharger_fct <- function(nitrates_moyP90 #' #' @export #' @importFrom dplyr left_join select arrange -prepa_nitrates_maxP90_bassin_versant_telecharger_fct <- function(nitrates_maxP90_bassin_versant, - correspondance_sage_bassin_versant){ +prepa_nitrates_maxP90_bassin_versant_telecharger_fct <- function( + nitrates_maxP90_bassin_versant, + correspondance_sage_bassin_versant + ){ nitrates_maxP90_bassin_versant_telecharger <- nitrates_maxP90_bassin_versant %>% dplyr::left_join(correspondance_sage_bassin_versant) %>% dplyr::select( diff --git a/R/globals.R b/R/globals.R index 9dd8d4b0fc624d28abe79f55ec4e64973be1cab7..6465efa0c343704f816e0ff1657ad47fa0ff3c34 100644 --- a/R/globals.R +++ b/R/globals.R @@ -40,7 +40,8 @@ utils::globalVariables( "bassin_versant_pa_telecharger", "departement_pa_telecharger", "depassement", "nbre_depassement", "non_depassement", - "captage_prioritaire" - + "captage_prioritaire", + "code_prelevement_analyse", "source_prelevement_analyse", + "code_bss", "code_naiades", "code_sise_eaux" ) ) diff --git a/data-raw/explo_prepa_data.R b/data-raw/explo_prepa_data.R index c08024727a6c448f41b29df89d2b8c828a635d4d..f78fcf333d9f990e1eee20f5731b63205608c92a 100644 --- a/data-raw/explo_prepa_data.R +++ b/data-raw/explo_prepa_data.R @@ -6,7 +6,7 @@ rm(list=ls()) nitrate_prelevement_analyse <- datalibaba::importer_data( db = "si_eau", schema = "nitrates", - table = "nitrate_prelevement_analyse_v0_20" + table = "nitrate_prelevement_analyse_v0_21" ) # 83882 obs # names(nitrate_prelevement_analyse) # [1] "code_prelevement_analyse" "code_intervenant" "source" "code_reseau" @@ -77,29 +77,27 @@ nitrates_station <- nitrates_station %>% ) %>% dplyr::select(code_station, tidyr::everything()) # 81721 obs -# dplyr::filter(nitrates_station, captage_prioritaire == "TRUE") %>% -# dplyr::pull(code_station) %>% -# unique() -# [1] "035000242" "BSS000TRNA" "BSS000VVKA" "BSS000VXRH" "BSS000VXSR" "BSS000XWUM" "BSS000XWVU" "BSS000XWVX" "BSS000XXAR" -# [10] "BSS000XXLZ" "BSS000XXXJ" "BSS000XYQY" "BSS000ZRMP" "BSS000ZRWX" "BSS000ZSMH" "BSS000ZSMK" "BSS000ZSZS" "BSS000ZTAB" -# [19] "BSS000ZTJM" "BSS000ZTKU" "BSS000ZWLX" "BSS001BNWY" "BSS001DMXF" "BSS001EUDY" "BSS001EUMJ" "BSS001EYVU" "BSS001FDCD" -# [28] "BSS001HKWP" "BSS001HLXD" "BSS001HMKY" "BSS001JPLC" "BSS001JZRT" "BSS001LFKF" "BSS001NLEZ" "BSS001NLXS" "044000102" -# [37] "044000449" "049000024" "049000388" "049000402" "053000091" "053000106" "085000047" "085000094" "085000410" -# [46] "085000446" +dplyr::filter(nitrates_station, captage_prioritaire == "TRUE") %>% + dplyr::pull(code_station) %>% + unique() +# [1] "035000242" "BSS000TRNA" "BSS000VVKA" "BSS000VXRH" "BSS000VXSR" "BSS000XWUM" "BSS000XWVU" "BSS000XWVX" "BSS000XXAR" "BSS000XXLZ" "BSS000XXXJ" +# [12] "BSS000XYQY" "BSS000ZRMP" "BSS000ZRWX" "BSS000ZSMH" "BSS000ZSMK" "BSS000ZSZS" "BSS000ZTAB" "BSS000ZTJM" "BSS000ZTKU" "BSS000ZWLX" "BSS001BNWY" +# [23] "BSS001DLVY" "BSS001DMXF" "BSS001EUDY" "BSS001EUMJ" "BSS001EYVU" "BSS001FDCD" "BSS001HKWP" "BSS001HLXD" "BSS001HMKY" "BSS001JPLC" "BSS001JZRT" +# [34] "BSS001LFKF" "BSS001NLEZ" "BSS001NLXS" "044000102" "044000449" "049000024" "049000388" "049000402" "053000091" "053000106" "085000047" +# [45] "085000094" "085000410" "085000446" -# dplyr::filter(station_mesure, captage_prioritaire == "TRUE") %>% -# dplyr::mutate( -# code_station = dplyr::case_when( -# nature_eau == "ESU" ~ code_sise_eaux, -# nature_eau == "ESO" & is.na(code_bss) | code_bss == "00000X0000" | code_bss == "XXX" ~ code_sise_eaux, -# nature_eau == "ESO" & !is.na(code_bss) ~ code_bss -# ) -# ) %>% -# dplyr::pull(code_station) %>% -# unique() -# [1] "BSS001JPLC" "BSS001EUMJ" "044000449" "BSS001EUDY" "044000102" "BSS001DMXF" "BSS001HLXD" "BSS001FDCD" "BSS001LFKF" -# [10] "049000388" "BSS001HMKY" "BSS001EYVU" "BSS001JZRT" "BSS001HKWP" "049000402" "049000024" "BSS000ZSZS" "BSS000ZSMH" -# [19] "BSS001BNWY" "BSS000TRNA" "053000091" "053000106" "035000242" "BSS000ZRWX" "BSS000VVKA" "BSS000ZRMP" "BSS000XWUM" -# [28] "BSS000XWVX" "BSS000ZTAB" "BSS000XXAR" "BSS000ZSMK" "BSS000XXXJ" "BSS000ZTKU" "BSS000XXLZ" "BSS000XWVU" "BSS000VXRH" -# [37] "BSS000XYQY" "BSS000ZTJM" "BSS000VXSR" "BSS000ZWLX" "085000047" "085000410" "085000446" "085000094" "BSS001NLEZ" -# [46] "BSS001NLXS" +dplyr::filter(station_mesure, captage_prioritaire == "TRUE") %>% + dplyr::mutate( + code_station = dplyr::case_when( + nature_eau == "ESU" ~ code_sise_eaux, + nature_eau == "ESO" & is.na(code_bss) | code_bss == "00000X0000" | code_bss == "XXX" ~ code_sise_eaux, + nature_eau == "ESO" & !is.na(code_bss) ~ code_bss + ) + ) %>% + dplyr::pull(code_station) %>% + unique() +# [1] "BSS001JPLC" "BSS001EUMJ" "044000449" "BSS001EUDY" "044000102" "BSS001DMXF" "BSS001HLXD" "BSS001FDCD" "BSS001LFKF" "049000388" "BSS001HMKY" +# [12] "BSS001EYVU" "BSS001JZRT" "BSS001HKWP" "049000402" "049000024" "BSS000ZSZS" "BSS000ZSMH" "BSS001BNWY" "053000091" "053000106" "BSS000ZRWX" +# [23] "BSS000VVKA" "BSS000ZRMP" "BSS000XWUM" "BSS000XWVX" "BSS000ZTAB" "BSS000XXAR" "BSS000ZSMK" "BSS000XXXJ" "BSS000ZTKU" "BSS000XXLZ" "BSS000XWVU" +# [34] "BSS000VXRH" "BSS000XYQY" "BSS000ZTJM" "BSS000VXSR" "BSS000ZWLX" "085000047" "085000410" "085000446" "085000094" "BSS001NLEZ" "BSS001NLXS" +# [45] "BSS000TRNA" "035000242" "BSS001DLVY" diff --git a/data-raw/prepa_data.R b/data-raw/prepa_data.R index 20deabb764967d42ca9e16c2f2778f05df4fdc12..aeb4a5da533f5ad71117761a85cdeaa377db29a6 100644 --- a/data-raw/prepa_data.R +++ b/data-raw/prepa_data.R @@ -5,88 +5,83 @@ rm(list=ls()) # chargement des données ------------ -nitrate_analyse <- datalibaba::importer_data( +nitrate_prelevement_analyse <- datalibaba::importer_data( db = "si_eau", schema = "nitrates", - table = "nitrate_analyse_v0_17" - ) # 82725 obs -# names(nitrate_analyse) -# [1] "code_analyse" "code_intervenant" "code_prelevement" "code_parametre" "code_fraction_analysee" -# [6] "date_analyse" "resultat_analyse" "code_remarque" "limite_detection" "limite_quantification" - -nitrate_prelevement <- datalibaba::importer_data( - db = "si_eau", - schema = "nitrates", - table = "nitrate_prelevement_v0_17" - ) # 82343 obs -# names(nitrate_prelevement) -# 1] "code_prelevement" "code_intervenant" "source" "code_reseau" "code_station" "date_prelevement" -# [7] "heure_prelevement" "code_support" "id_usage" "id_prelevement_motif" "commentaire" + table = "nitrate_prelevement_analyse_v0_21" +) # 83882 obs +# names(nitrate_prelevement_analyse) +# [1] "code_prelevement_analyse" "code_intervenant" "source" "code_reseau" +# [5] "code_station" "date_prelevement" "heure_prelevement" "code_support" +# [9] "nature_eau" "id_usage" "id_prelevement_motif" "date_analyse" +# [13] "resultat_analyse" "code_parametre" "code_fraction_analysee" "code_remarque" +# [17] "limite_detection" "limite_quantification" + +nitrate_prelevement_analyse <- dplyr::rename( + nitrate_prelevement_analyse, + source_prelevement_analyse = source + ) # création de la table nitrates --------- -nitrates <- dplyr::inner_join( - nitrate_prelevement, - nitrate_analyse, - by = c("code_prelevement") -) %>% - dplyr::mutate( - annee = lubridate::year(date_prelevement), - mois = lubridate::month(date_prelevement) - ) # 82693 obs - -nitrates_esu <- prepa_nitrates_fct(station_code_nature_eau = "ESU") # 58610 obs -nitrates_eso <- prepa_nitrates_fct(station_code_nature_eau = "ESO") # 21010 obs - -nitrates <- dplyr::bind_rows( - nitrates_esu %>% dplyr::mutate(code_nature_eau = "ESU"), - nitrates_eso %>% dplyr::mutate(code_nature_eau = "ESO") -) # 79620 obs - -# unique(nitrates$annee) -# [1] 2007 2008 2009 2010 2011 2012 2013 2014 2015 2016 2017 2018 2019 2020 2021 2022 2023 - -# un peu de ménage intermédiaire --------- -rm( - nitrate_analyse, - nitrate_prelevement, - nitrates_esu, - nitrates_eso - ) +nitrates <- nitrate_prelevement_analyse %>% + dplyr::mutate( + annee = lubridate::year(date_prelevement), + mois = lubridate::month(date_prelevement) + ) %>% + dplyr::rename(code_nature_eau = nature_eau) + +nitrates_code_bss <- station_pdl %>% + sf::st_drop_geometry() %>% + dplyr::inner_join( + nitrates, + by = c("code_bss" = "code_station", "code_nature_eau") + ) # 4771 obs + +nitrates_code_sise_eaux <- station_pdl %>% + sf::st_drop_geometry() %>% + dplyr::inner_join( + nitrates, + by = c("code_sise_eaux" = "code_station", "code_nature_eau") + ) # 76397 obs + +nitrates_code_naiades <- station_pdl %>% + sf::st_drop_geometry() %>% + dplyr::inner_join( + nitrates, + by = c("code_naiades" = "code_station", "code_nature_eau") + ) # 357 obs + +nitrates_station <- dplyr::bind_rows( + nitrates_code_bss, + nitrates_code_sise_eaux, + nitrates_code_naiades + ) %>% # 81525 obs + dplyr::group_by( + code_bss, code_sise_eaux, code_naiades, libelle_station, code_nature_eau, source_station, + code_masse_eau, code_bassin_versant, code_commune, code_sage, + captage_prioritaire, + source_prelevement_analyse, code_prelevement_analyse, code_intervenant, date_analyse, resultat_analyse + ) %>% + dplyr::slice(1) %>% + dplyr::ungroup() # 81525 obs + +nitrates <- nitrates_station + +# unique(nitrates$annee) %>% sort() +# [1] 2007 2008 2009 2010 2011 2012 2013 2014 2015 2016 2017 2018 2019 2020 2021 2022 2023 # calcul P90 ---------------- nitrates_P90 <- prepa_nitrates_P90_fct(nitrates) -# 12766 obs dont 6104 esu et 6662 eso +# 12848 obs dont 6101 esu et 6747 eso # calcul de la tendance P90 ----------------------------- nitrates_tendanceP90 <- purrr::map(c(2016:2023), ~prepa_creer_tendanceP90(.x)) %>% dplyr::bind_rows() -# 10078 obs dont 5268 esu et 4810 eso - -# Warning messages: -# 1: There was 1 warning in `dplyr::mutate()`. -# ℹ In argument: `determination = as.numeric(summary(Mods)[8])`. -# ℹ In row 435. -# Caused by warning in `summary.lm()`: -# ! ajustement pratiquement parfait : le résumé n’est peut-être pas fiable -# 2: There was 1 warning in `dplyr::mutate()`. -# ℹ In argument: `determination = as.numeric(summary(Mods)[8])`. -# ℹ In row 439. -# Caused by warning in `summary.lm()`: -# ! ajustement pratiquement parfait : le résumé n’est peut-être pas fiable -# 3: There was 1 warning in `dplyr::mutate()`. -# ℹ In argument: `determination = as.numeric(summary(Mods)[8])`. -# ℹ In row 453. -# Caused by warning in `summary.lm()`: -# ! ajustement pratiquement parfait : le résumé n’est peut-être pas fiable -# 4: There was 1 warning in `dplyr::mutate()`. -# ℹ In argument: `determination = as.numeric(summary(Mods)[8])`. -# ℹ In row 490. -# Caused by warning in `summary.lm()`: -# ! ajustement pratiquement parfait : le résumé n’est peut-être pas fiable +# 23450 obs dont 12686 esu et 10764 eso nitrates_tendanceP90 <- nitrates_tendanceP90 %>% dplyr::select(code_station, libelle_station, code_nature_eau, tendance, periode) %>% @@ -100,24 +95,13 @@ periode_nitrates_tendanceP90 <- prepa_periode_nitrates_tendanceP90_fct(2023) # calcul de la moyenne et du maximum des P90 sur un bassin versant ---------- nitrates_bassin_versant <- prepa_nitrates_bassin_versant_fct(nitrates_P90) %>% dplyr::filter(!is.na(code_bassin_versant)) -# 6202 obs dont 3749 obs esu et 2453 eso - -# 0 station dont le code_bassin_versant n'est pas renseigné -# nitrates_P90 %>% -# dplyr::semi_join(station_pdl) %>% -# dplyr::left_join( -# station_pdl %>% dplyr::select(c(code_station, libelle_station, code_bassin_versant)) %>% sf::st_drop_geometry(), -# by = c("code_station", "libelle_station") -# ) %>% -# dplyr::filter(is.na(code_bassin_versant)) %>% -# dplyr::pull(code_station) %>% -# unique() -# character(0) +# 6231 obs dont 3765 obs esu et 2466 eso nitrates_moyP90_bassin_versant <- prepa_nitrates_moyP90_bassin_versant_fct(nitrates_bassin_versant) -# 6202 obs +# 6231 obs + nitrates_maxP90_bassin_versant <- prepa_nitrates_maxP90_bassin_versant_fct(nitrates_bassin_versant) -# 6202 obs +# 6231 obs # répartition P90 ------------ @@ -127,7 +111,7 @@ repartition_P90 <- prepa_repartition_P90_fct( n_sage_r52, masse_eau_bassin_versant_PDL, correspondance_sage_bassin_versant - ) # 12259 obs + ) # 11505 obs # répartition tendance P90 ----------- @@ -137,7 +121,7 @@ repartition_tendanceP90 <- prepa_repartition_tendanceP90_fct( n_sage_r52, masse_eau_bassin_versant_PDL, correspondance_sage_bassin_versant - ) # 7224 obs + ) # 7254 obs # répartition moyenne et maximum BV -------- @@ -145,20 +129,21 @@ repartition_moyBV <- prepa_repartition_moymaxBV_fct( nitrates_moyP90_bassin_versant, correspondance_sage_bassin_versant, n_sage_r52 - ) # 2829 obs + ) # 2431 obs repartition_maxBV <- prepa_repartition_moymaxBV_fct( nitrates_maxP90_bassin_versant, correspondance_sage_bassin_versant, n_sage_r52 - ) # 2963 obs + ) # 2580 obs # concentration ----------------- nitrates_esu <- prepa_nitrates_nature_eau_fct(station_pdl, "ESU") -# 58610 obs +# 59645 obs + nitrates_eso <- prepa_nitrates_nature_eau_fct(station_pdl, "ESO") -# 21010 obs +# 21880 obs depassement_seuil_esu <- prepa_depassement_seuil_nature_eau_fct( nitrates_esu, @@ -167,7 +152,7 @@ depassement_seuil_esu <- prepa_depassement_seuil_nature_eau_fct( n_sage_r52, masse_eau_bassin_versant_PDL ) -# 3662 obs +# 3694 obs depassement_seuil_eso <- prepa_depassement_seuil_nature_eau_fct( nitrates_eso, @@ -176,11 +161,12 @@ depassement_seuil_eso <- prepa_depassement_seuil_nature_eau_fct( n_sage_r52, masse_eau_bassin_versant_PDL ) -# 920 obs +# 921 obs # choix des couleurs ----------- -couleur <- c("#33CCFF", "#00CC33", "#66FF99", "#FFFF00", "orange", "red", "#A10684", "#723E64") +# couleur <- c("#33CCFF", "#00CC33", "#66FF99", "#FFFF00", "orange", "red", "#A10684", "#723E64") +couleur <- c("#33CCFF", "#00CC33", "#FFFF00", "orange", "red", "#A10684", "#723E64") facteur <- nitrates_P90 %>% dplyr::arrange(classe) %>% dplyr::pull(classe) %>% @@ -208,20 +194,24 @@ nitrates_telecharger <- prepa_nitrates_telecharger_fct( station_pdl, correspondance_sage_bassin_versant ) + nitrates_P90_telecharger <- prepa_nitrates_P90_telecharger_fct( nitrates_P90, station_pdl, correspondance_sage_bassin_versant ) + nitrates_tendanceP90_telecharger <- prepa_nitrates_tendanceP90_telecharger_fct( nitrates_tendanceP90, station_pdl, correspondance_sage_bassin_versant ) + nitrates_moyP90_bassin_versant_telecharger <- prepa_nitrates_moyP90_bassin_versant_telecharger_fct( nitrates_moyP90_bassin_versant, correspondance_sage_bassin_versant ) + nitrates_maxP90_bassin_versant_telecharger <- prepa_nitrates_maxP90_bassin_versant_telecharger_fct( nitrates_maxP90_bassin_versant, correspondance_sage_bassin_versant @@ -277,22 +267,24 @@ usethis::use_data( # # versement sur le sgbd/datamart/nitrates ------ + datalibaba::poster_data( data = nitrates_P90, db = "datamart", schema = "nitrates", - table = "nitrates_p90_v0_17", + table = "nitrates_p90_v0_21", pk = c("code_station", "libelle_station", "annee"), post_row_name = FALSE, overwrite = TRUE, droits_schema = TRUE, user = "does" ) + datalibaba::commenter_table( comment = "calcul du P90 par station", db = "datamart", schema = "nitrates", - table = "nitrates_p90_v0_17", + table = "nitrates_p90_v0_21", user = "does" ) @@ -300,18 +292,19 @@ datalibaba::poster_data( data = nitrates_tendanceP90, db = "datamart", schema = "nitrates", - table = "nitrates_tendancep90_v0_17", + table = "nitrates_tendancep90_v0_21", pk = c("code_station", "libelle_station", "periode"), post_row_name = FALSE, overwrite = TRUE, droits_schema = TRUE, user = "does" ) + datalibaba::commenter_table( comment = "calcul de la tendance P90 par station", db = "datamart", schema = "nitrates", - table = "nitrates_tendancep90_v0_17", + table = "nitrates_tendancep90_v0_21", user = "does" ) @@ -319,7 +312,7 @@ datalibaba::poster_data( data = nitrates_moyP90_bassin_versant, db = "datamart", schema = "nitrates", - table = "nitrates_moyp90_bassin_versant_v0_17", + table = "nitrates_moyp90_bassin_versant_v0_21", pk = c("code_bassin_versant", "annee", "code_nature_eau"), post_row_name = FALSE, overwrite = TRUE, @@ -330,7 +323,7 @@ datalibaba::commenter_table( comment = "calcul de la moyenne P90 par bassin versant", db = "datamart", schema = "nitrates", - table = "nitrates_moyp90_bassin_versant_v0_17", + table = "nitrates_moyp90_bassin_versant_v0_21", user = "does" ) @@ -338,18 +331,19 @@ datalibaba::poster_data( data = nitrates_maxP90_bassin_versant, db = "datamart", schema = "nitrates", - table = "nitrates_maxp90_bassin_versant_v0_17", + table = "nitrates_maxp90_bassin_versant_v0_21", pk = c("code_bassin_versant", "annee", "code_nature_eau"), post_row_name = FALSE, overwrite = TRUE, droits_schema = TRUE, user = "does" ) + datalibaba::commenter_table( comment = "calcul du maximum P90 par bassin versant", db = "datamart", schema = "nitrates", - table = "nitrates_maxp90_bassin_versant_v0_17", + table = "nitrates_maxp90_bassin_versant_v0_21", user = "does" ) diff --git a/data-raw/prepa_pression_azotee.R b/data-raw/prepa_pression_azotee.R index fe0b210dc4748d9897d97b0e6936ae31b3377528..0044db74ebadb089a703524ab3e5e73e97c1233f 100644 --- a/data-raw/prepa_pression_azotee.R +++ b/data-raw/prepa_pression_azotee.R @@ -4,13 +4,28 @@ library(nitrates.pdl) rm(list=ls()) -# importation des données de la DRAAF -------- +# importation des données de la DRAAF 2023 pm -------- # Departement_2023 <- utils::read.csv2("inst/extdata/Departement_2023.csv") # names(Departement_2023) # [1] "ANNEE_DECLARATION" "Nom" "Code" "SAU_recensee" "QTE_ORG_MIN" # [6] "QTE_N_MIN_EPAN" "ORG_EPAN_THEORIQ" "Comptage" "pression_azote_globale" "pression_azote_mineral" # [11] "pression_azote_orga" +# ME_2023 <- utils::read.csv2("inst/extdata/ME_2023.csv") +# names(ME_2023) +# [1] "ANNEE_DECLARATION" "Nom" "Code" "SAU_recensee" "QTE_ORG_MIN" +# [6] "QTE_N_MIN_EPAN" "ORG_EPAN_THEORIQ" "Comptage" "pression_azote_globale" "pression_azote_mineral" +# [11] "pression_azote_orga" + +# SAGE_2023 <- utils::read.csv2("inst/extdata/SAGE_2023.csv") %>% +# dplyr::mutate(Code = as.character(Code)) +# names(SAGE_2023) +# [1] "ANNEE_DECLARATION" "Nom" "Code" "SAU_recensee" "QTE_ORG_MIN" +# [6] "QTE_N_MIN_EPAN" "ORG_EPAN_THEORIQ" "Comptage" "pression_azote_globale" "pression_azote_mineral" +# [11] "pression_azote_orga" + + +# importation des données de la DRAAF 2024 -------- Departement_2024 <- utils::read.csv2("inst/extdata/Departement_2024.csv") # names(Departement_2024) # [1] "ANNEE_DECLARATION" "DEPARTEMENT" "Code" "SAU_recensee" @@ -18,12 +33,6 @@ Departement_2024 <- utils::read.csv2("inst/extdata/Departement_2024.csv") # [9] "nb_occurences" "pression_azote_globale" "pression_azote_mineral" "pression_azote_orga" # [13] "pression_azote_orga_non_maitri" -# ME_2023 <- utils::read.csv2("inst/extdata/ME_2023.csv") -# names(ME_2023) -# [1] "ANNEE_DECLARATION" "Nom" "Code" "SAU_recensee" "QTE_ORG_MIN" -# [6] "QTE_N_MIN_EPAN" "ORG_EPAN_THEORIQ" "Comptage" "pression_azote_globale" "pression_azote_mineral" -# [11] "pression_azote_orga" - ME_2024 <- utils::read.csv2("inst/extdata/ME_2024.csv") # names(ME_2024) # [1] "ANNEE_DECLARATION" "CODE_ME" "Nom" "SAU_recensee" @@ -31,13 +40,6 @@ ME_2024 <- utils::read.csv2("inst/extdata/ME_2024.csv") # [9] "Comptage" "pression_azote_globale" "pression_azote_mineral" "pression_azote_orga" # [13] "pression_azote_orga_non_maitri" -# SAGE_2023 <- utils::read.csv2("inst/extdata/SAGE_2023.csv") %>% - dplyr::mutate(Code = as.character(Code)) -# names(SAGE_2023) -# [1] "ANNEE_DECLARATION" "Nom" "Code" "SAU_recensee" "QTE_ORG_MIN" -# [6] "QTE_N_MIN_EPAN" "ORG_EPAN_THEORIQ" "Comptage" "pression_azote_globale" "pression_azote_mineral" -# [11] "pression_azote_orga" - SAGE_2024 <- utils::read.csv2("inst/extdata/SAGE_2024.csv") %>% dplyr::mutate(Code = as.character(Code)) # names(SAGE_2024) @@ -158,10 +160,15 @@ palette_pa <- gouvdown::gouv_colors("q0", "o0", "o1", "o2", "n2", "l2") bassin_versant_col_pa <- bassin_versant_carte_pa %>% sf::st_drop_geometry() %>% dplyr::select(-pression_azote_globale, -classe) %>% + dplyr::rename( + minerale = pression_azote_mineral, + organique = pression_azote_orga + ) %>% tidyr::gather( key = "pression", value = "valeur", - pression_azote_mineral, pression_azote_orga + # pression_azote_mineral, pression_azote_orga + minerale, organique ) %>% dplyr::mutate(valeur = round(valeur, digits = 0)) %>% dplyr::arrange( @@ -169,17 +176,21 @@ bassin_versant_col_pa <- bassin_versant_carte_pa %>% nom_bassin_versant, annee_declaration ) -usethis::use_data(bassin_versant_col_pa, choix_couleur_col_pa, overwrite = TRUE) + +usethis::use_data(bassin_versant_col_pa, overwrite = TRUE) # utilitaires.ju::use_data_doc( # "bassin_versant_col_pa", # description = "pression azotée (minérale, organique) par bassin versant par campagne culturale", source = "DREAL" # ) choix_couleur_col_pa <- data.frame( - pression = c("pression_azote_mineral", "pression_azote_orga"), + # pression = c("pression_azote_mineral", "pression_azote_orga"), + pression = c("minerale", "organique"), couleur = c(gouvdown::gouv_colors("o0"), gouvdown::gouv_colors("l1")) ) %>% dplyr::pull(couleur) + +usethis::use_data(choix_couleur_col_pa, overwrite = TRUE) # utilitaires.ju::use_data_doc( # "choix_couleur_col_pa", # description = "choix des couleurs pour diagramme des pressions azotées (minérale, organique) par bassin versant par campagne culturale", @@ -187,8 +198,8 @@ choix_couleur_col_pa <- data.frame( # ) # exemple pour voir -plot_bv <- plot_bv_col_pa_fct(nom = "Baie de Bourgneuf") -plot_bv +# plot_bv <- plot_bv_col_pa_fct(nom = "Baie de Bourgneuf") +# plot_bv # diagramme colonnes départements -------------- @@ -199,14 +210,15 @@ departement_col_pa <- Departement %>% annee_declaration = ANNEE_DECLARATION, Nom = DEPARTEMENT, Code, - pression_azote_mineral, - pression_azote_orga - ) %>% + minerale = pression_azote_mineral, + organique = pression_azote_orga + ) %>% tidyr::gather( key = "pression", value = "valeur", - pression_azote_mineral, pression_azote_orga - ) %>% + # pression_azote_mineral, pression_azote_orga + minerale, organique + ) %>% dplyr::mutate(valeur = round(valeur, digits = 0)) %>% dplyr::mutate(Code = ifelse(Code == 303, 90, Code)) %>% dplyr::arrange( diff --git a/data-raw/prepa_referentiel.R b/data-raw/prepa_referentiel.R index 9316f5808a68bc5e30aa63e6cbd6a1c79d633b1e..1de598b9ffd33ff72334d5b640e4725e7ad188f2 100644 --- a/data-raw/prepa_referentiel.R +++ b/data-raw/prepa_referentiel.R @@ -179,37 +179,50 @@ bv_hors_correspondance_2 <- dplyr::anti_join( # stations de mesure ----------- -station_esu <- datalibaba::importer_data( +station_mesure <- datalibaba::importer_data( db = "si_eau", schema = "stations", - table = "station_esu" - ) # 3675 obs + table = "r_station_mesure_p_2024_r52" +) # 7047 obs +# names(station_mesure) +# [1] "id_station" "code_bss" "code_sise_eaux" "code_naiades" "libelle_station" +# [6] "nature_eau" "date_creation" "source" "code_masse_eau" "code_bassin_versant" +# [11] "code_commune" "code_sage" "captage_prioritaire" "the_geom" -station_eso <- datalibaba::importer_data( - db = "si_eau", - schema = "stations", - table = "station_eso" - ) # 2034 obs +station_mesure <- dplyr::rename(station_mesure, source_station = source) + +station_esu <- dplyr::filter(station_mesure, nature_eau == "ESU") # 3673 obs +station_eso <- dplyr::filter(station_mesure, nature_eau == "ESO") # 3374 obs # mention du département, et restriction au périmètre régional et aux géométries définies -station_esu_PDL <- prepa_station_PDL_fct(station_esu) # 1835 obs -station_eso_PDL <- prepa_station_PDL_fct(station_eso) # 2027 obs +station_esu_PDL <- prepa_station_PDL_fct(station_esu) # 1833 obs +station_eso_PDL <- prepa_station_PDL_fct(station_eso) # 2049 obs station <- dplyr::bind_rows( station_esu, - station_eso %>% dplyr::select(-code_sise_eaux) - ) # 5709 obs + station_eso + ) # 7047 obs station_pdl <- dplyr::bind_rows( station_esu_PDL %>% - dplyr::mutate(code_nature_eau = "ESU") %>% + dplyr::rename(code_nature_eau = nature_eau) %>% dplyr::mutate( etoile = ifelse(startsWith(libelle_station,"* A"), "oui", "non") ) %>% dplyr::filter(etoile == "non") %>% # élimination de stations qui ne se rattachent à aucun prélèvement dplyr::select(-etoile), - station_eso_PDL %>% dplyr::mutate(code_nature_eau = "ESO") %>% dplyr::select(-code_sise_eaux) - ) # 3850 obs + station_eso_PDL %>% + dplyr::rename(code_nature_eau = nature_eau) + ) %>% + dplyr::mutate( + code_station = dplyr::case_when( + code_nature_eau == "ESU" ~ code_sise_eaux, + code_nature_eau == "ESO" & is.na(code_bss) | code_bss == "00000X0000" | code_bss == "XXX" ~ code_sise_eaux, + code_nature_eau == "ESO" & !is.na(code_bss) ~ code_bss + ) + ) %>% + dplyr::select(-id_station) %>% + dplyr::select(code_station, tidyr::everything()) # 3870 obs # un peu de ménage --------- @@ -228,6 +241,9 @@ NatureEau <- prepa_NatureEau_fct(station_pdl) # sauvegarde et documentation ---------- + +# remotes::install_gitlab('dreal-pdl/csd/utilitaires.ju', host = "gitlab-forge.din.developpement-durable.gouv.fr") + usethis::use_data( Sage, BassinVersant, diff --git a/data/BassinVersant.rda b/data/BassinVersant.rda index 195b7222a5dc3b1f2c0cfa658ed35db3ea044266..e579fdee0202ec9ab66712f54a4d79557ea3d5d7 100644 Binary files a/data/BassinVersant.rda and b/data/BassinVersant.rda differ diff --git a/data/BassinVersant_pa.rda b/data/BassinVersant_pa.rda index 9c7dc3c93d8869e04d17cdb5a6897c8e7c8861bb..cad8743df8f4001120dca847f8b1bc82f4469d4b 100644 Binary files a/data/BassinVersant_pa.rda and b/data/BassinVersant_pa.rda differ diff --git a/data/Campagne_pa.rda b/data/Campagne_pa.rda index 3045e16748d4218e814646ec11f4a92533aba0bc..2d69dbf683e539bf96cb12b262882c2d705656e2 100644 Binary files a/data/Campagne_pa.rda and b/data/Campagne_pa.rda differ diff --git a/data/NatureEau.rda b/data/NatureEau.rda index bf5c0e24c6b5b669f6512dfc657f278e496e68f5..6020740990a15102ba066f8ea37f36765cc0f574 100644 Binary files a/data/NatureEau.rda and b/data/NatureEau.rda differ diff --git a/data/Sage.rda b/data/Sage.rda index ad69d8c28d0f8c444106fb8a4ad28b4196e4d375..24424e02a00709478632b5411ef5e18b45cad328 100644 Binary files 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b/data/repartition_P90.rda differ diff --git a/data/repartition_maxBV.rda b/data/repartition_maxBV.rda index 2dc22e4438eebc11aec0e25c215eecc92b4823e3..7efbf2f2e80347037e2fee9e4eb60df4843c0b37 100644 Binary files a/data/repartition_maxBV.rda and b/data/repartition_maxBV.rda differ diff --git a/data/repartition_moyBV.rda b/data/repartition_moyBV.rda index 35c99fc6c0b01b041444887e28050102bae57033..6e9f80dcc75a9cbadd1f0054be5f4e5d41c7e24f 100644 Binary files a/data/repartition_moyBV.rda and b/data/repartition_moyBV.rda differ diff --git a/data/repartition_tendanceP90.rda b/data/repartition_tendanceP90.rda index ee7357feb7a9800240d0dd61cd1d1bc076188ff2..5b50aa075dc2d6c8db1adcc14b442406955a9179 100644 Binary files a/data/repartition_tendanceP90.rda and b/data/repartition_tendanceP90.rda differ diff --git a/data/station_pdl.rda b/data/station_pdl.rda index c3570015ead41c385fe952cb758ca2c942c9d88c..6a2fae8de5cc7804346b6c83e57fe362b1a3f8d3 100644 Binary files a/data/station_pdl.rda and b/data/station_pdl.rda differ diff --git a/inst/app/www/News.md b/inst/app/www/News.md index 7cff532015fcc0b2a4bc78c13fcdd4170ae3e98a..d8156d8855e4c23854c288386c47e85ec2d73014 100644 --- a/inst/app/www/News.md +++ b/inst/app/www/News.md @@ -2,9 +2,9 @@ Annonce des évolutions de l'application et des données qu'elle valorise. -### Nitrates v3_1 +### Nitrates v3.1 -Publiée le xx septembre 2024 +Publiée le xx avril 2025 ##### Evolution des données diff --git a/man/bassin_versant_col_pa.Rd b/man/bassin_versant_col_pa.Rd index 264a3160fa8dc13ec2fb12ff329a20ff5a15a1c5..cf07153852d64df4fb0bc47c5fc28805e6e201f5 100644 --- a/man/bassin_versant_col_pa.Rd +++ b/man/bassin_versant_col_pa.Rd @@ -5,7 +5,7 @@ \alias{bassin_versant_col_pa} \title{bassin_versant_col_pa} \format{ -A data frame with 4616 rows and 5 variables: +A data frame with 5538 rows and 5 variables: \describe{ \item{ code_bassin_versant }{ character } \item{ nom_bassin_versant }{ character } diff --git a/man/bassin_versant_pa_telecharger.Rd b/man/bassin_versant_pa_telecharger.Rd index ea9cc5d08cd21e25a727c13e3bfc06facfcc2c92..a35e386dba1942d092c8f653a2a606c31f0ac18b 100644 --- a/man/bassin_versant_pa_telecharger.Rd +++ b/man/bassin_versant_pa_telecharger.Rd @@ -5,7 +5,7 @@ \alias{bassin_versant_pa_telecharger} \title{bassin_versant_pa_telecharger} \format{ -A data frame with 2308 rows and 7 variables: +A data frame with 2769 rows and 7 variables: \describe{ \item{ code_bassin_versant }{ character } \item{ nom_bassin_versant }{ character } diff --git a/man/choix_couleur_P90.Rd b/man/choix_couleur_P90.Rd index 92724f9b99958bda5809cd52a82fd867e116bf08..a423e676412397ffb7c89c77c94843809e45587a 100644 --- a/man/choix_couleur_P90.Rd +++ b/man/choix_couleur_P90.Rd @@ -5,7 +5,7 @@ \alias{choix_couleur_P90} \title{choix_couleur_P90} \format{ -A data frame with 8 rows and 2 variables: +A data frame with 7 rows and 2 variables: \describe{ \item{ classe }{ character } \item{ couleur }{ character } diff --git a/man/correspondance_sage_bassin_versant.Rd b/man/correspondance_sage_bassin_versant.Rd index 5c193f80fcc943789f2f483622f8fabed91a0dc8..61144b3d4b4e471e920e1cff35c9af2dd76d44ef 100644 --- a/man/correspondance_sage_bassin_versant.Rd +++ b/man/correspondance_sage_bassin_versant.Rd @@ -5,11 +5,11 @@ \alias{correspondance_sage_bassin_versant} \title{correspondance_sage_bassin_versant} \format{ -A data frame with 457 rows and 4 variables: +A data frame with 463 rows and 4 variables: \describe{ \item{ code_sage }{ character } - \item{ code_bassin_versant }{ character } \item{ nom_sage }{ character } + \item{ code_bassin_versant }{ character } \item{ nom_bassin_versant }{ character } } } diff --git a/man/departement_col_pa.Rd b/man/departement_col_pa.Rd index 6d3e4d03be8a61178d190c993432aaee83bf44ad..5feb31245ab3b0b05b90041b6e73c88cc7a4270c 100644 --- a/man/departement_col_pa.Rd +++ b/man/departement_col_pa.Rd @@ -5,7 +5,7 @@ \alias{departement_col_pa} \title{departement_col_pa} \format{ -A data frame with 60 rows and 5 variables: +A data frame with 72 rows and 5 variables: \describe{ \item{ annee_declaration }{ character } \item{ Nom }{ character } diff --git a/man/departement_pa_telecharger.Rd b/man/departement_pa_telecharger.Rd index 6c9a71d5597f3864179252bf6d946cc75666a9c1..b097ef7ea008d1d8c0bf8dac5952c68872795494 100644 --- a/man/departement_pa_telecharger.Rd +++ b/man/departement_pa_telecharger.Rd @@ -5,7 +5,7 @@ \alias{departement_pa_telecharger} \title{departement_pa_telecharger} \format{ -A data frame with 30 rows and 5 variables: +A data frame with 36 rows and 5 variables: \describe{ \item{ Nom }{ character } \item{ annee_declaration }{ character } diff --git a/man/depassement_seuil_eso.Rd b/man/depassement_seuil_eso.Rd index b619c005b6da8302773c9afd4884a2cfa4a02d56..6834cb9e34da20bf402b21a27443aed216af8574 100644 --- a/man/depassement_seuil_eso.Rd +++ b/man/depassement_seuil_eso.Rd @@ -5,7 +5,7 @@ \alias{depassement_seuil_eso} \title{depassement_seuil_eso} \format{ -A data frame with 867 rows and 5 variables: +A data frame with 921 rows and 5 variables: \describe{ \item{ annee }{ factor } \item{ depassement }{ numeric } diff --git a/man/depassement_seuil_esu.Rd b/man/depassement_seuil_esu.Rd index fa01ef81c701125e499f5f79d5f469c4dca19fbd..375ae9b71e1f54294d646d3e095042f879275af2 100644 --- a/man/depassement_seuil_esu.Rd +++ b/man/depassement_seuil_esu.Rd @@ -5,7 +5,7 @@ \alias{depassement_seuil_esu} \title{depassement_seuil_esu} \format{ -A data frame with 3444 rows and 5 variables: +A data frame with 3694 rows and 5 variables: \describe{ \item{ annee }{ factor } \item{ depassement }{ numeric } diff --git a/man/masse_eau_bassin_versant_PDL.Rd b/man/masse_eau_bassin_versant_PDL.Rd index 3736391e39ee954115157a91e954a9345193b960..b9f16edd24d827dee77ce57e9881e147db246e33 100644 --- a/man/masse_eau_bassin_versant_PDL.Rd +++ b/man/masse_eau_bassin_versant_PDL.Rd @@ -5,7 +5,7 @@ \alias{masse_eau_bassin_versant_PDL} \title{masse_eau_bassin_versant_PDL} \format{ -A data frame with 457 rows and 3 variables: +A data frame with 463 rows and 3 variables: \describe{ \item{ code_bassin_versant }{ character } \item{ nom_bassin_versant }{ character } diff --git a/man/n_sage_r52.Rd b/man/n_sage_r52.Rd index dabe9416c86a8b1f6161bada0bd3e51d141083e2..a5bc6a8f3c4e84fb23b1abefca7097aa865347cf 100644 --- a/man/n_sage_r52.Rd +++ b/man/n_sage_r52.Rd @@ -5,10 +5,9 @@ \alias{n_sage_r52} \title{n_sage_r52} \format{ -A data frame with 24 rows and 16 variables: +A data frame with 24 rows and 15 variables: \describe{ \item{ nid }{ character } - \item{ vid }{ character } \item{ nom_sage }{ character } \item{ type }{ character } \item{ code_sage }{ character } diff --git a/man/nitrates_P90.Rd b/man/nitrates_P90.Rd index 88ae4adb5f9c5fc65a9868ed7d3c6d45a30e60eb..676edd85d5d05a6d7f79809d2dbdf0c1c86ec375 100644 --- a/man/nitrates_P90.Rd +++ b/man/nitrates_P90.Rd @@ -5,12 +5,15 @@ \alias{nitrates_P90} \title{nitrates_P90} \format{ -A data frame with 11972 rows and 9 variables: +A data frame with 12848 rows and 12 variables: \describe{ \item{ code_station }{ factor } + \item{ code_bss }{ factor } + \item{ code_sise_eaux }{ factor } + \item{ code_naiades }{ factor } \item{ libelle_station }{ factor } - \item{ source_station }{ factor } \item{ annee }{ numeric } + \item{ source_station }{ factor } \item{ id_usage }{ factor } \item{ P90 }{ numeric } \item{ code_nature_eau }{ factor } diff --git a/man/nitrates_P90_telecharger.Rd b/man/nitrates_P90_telecharger.Rd index 3d1135c91341feea10cdaa51221c2e04b9b6c9a1..da4e500a93e2a16e42582ac42fb45cfd572eebab 100644 --- a/man/nitrates_P90_telecharger.Rd +++ b/man/nitrates_P90_telecharger.Rd @@ -5,7 +5,7 @@ \alias{nitrates_P90_telecharger} \title{nitrates_P90_telecharger} \format{ -A data frame with 7781 rows and 13 variables: +A data frame with 12848 rows and 13 variables: \describe{ \item{ annee }{ numeric } \item{ code_nature_eau }{ factor } diff --git a/man/nitrates_maxP90_bassin_versant.Rd b/man/nitrates_maxP90_bassin_versant.Rd index 8547d95eec9daa2419ac7351e990b53d27b243db..2a7e36a06a5cfb22ee85341b8609e81d2aa6e99d 100644 --- a/man/nitrates_maxP90_bassin_versant.Rd +++ b/man/nitrates_maxP90_bassin_versant.Rd @@ -5,7 +5,7 @@ \alias{nitrates_maxP90_bassin_versant} \title{nitrates_maxP90_bassin_versant} \format{ -A data frame with 5797 rows and 5 variables: +A data frame with 6231 rows and 5 variables: \describe{ \item{ code_bassin_versant }{ character } \item{ annee }{ numeric } diff --git a/man/nitrates_maxP90_bassin_versant_telecharger.Rd b/man/nitrates_maxP90_bassin_versant_telecharger.Rd index 89ba636b5494e2852696efddd00c324d7027ca0d..4483db83f9d972ba0c0243be6159b8f9b59da301 100644 --- a/man/nitrates_maxP90_bassin_versant_telecharger.Rd +++ b/man/nitrates_maxP90_bassin_versant_telecharger.Rd @@ -6,7 +6,7 @@ \alias{nitrates_maxP90_bassin_versant_telecharger} \title{nitrates_maxP90_bassin_versant_telecharger} \format{ -A data frame with 5937 rows and 8 variables: +A data frame with 6231 rows and 8 variables: \describe{ \item{ annee }{ numeric } \item{ code_nature_eau }{ factor } diff --git a/man/nitrates_moyP90_bassin_versant.Rd b/man/nitrates_moyP90_bassin_versant.Rd index 1dfd5330e3b9ed8269b01854fd7a515dc1a771fc..9d6d4abfafd850a6e460def7c3acd0879096e536 100644 --- a/man/nitrates_moyP90_bassin_versant.Rd +++ b/man/nitrates_moyP90_bassin_versant.Rd @@ -5,7 +5,7 @@ \alias{nitrates_moyP90_bassin_versant} \title{nitrates_moyP90_bassin_versant} \format{ -A data frame with 5797 rows and 5 variables: +A data frame with 6231 rows and 5 variables: \describe{ \item{ code_bassin_versant }{ character } \item{ annee }{ numeric } diff --git a/man/nitrates_moyP90_bassin_versant_telecharger.Rd b/man/nitrates_moyP90_bassin_versant_telecharger.Rd index 79ed6fb357eac04ee296d8824424123f8715267a..25231eff94e3ee414eb27d7259d76b054e712a24 100644 --- a/man/nitrates_moyP90_bassin_versant_telecharger.Rd +++ b/man/nitrates_moyP90_bassin_versant_telecharger.Rd @@ -6,7 +6,7 @@ \alias{nitrates_moyP90_bassin_versant_telecharger} \title{nitrates_moyP90_bassin_versant_telecharger} \format{ -A data frame with 5937 rows and 8 variables: +A data frame with 6231 rows and 8 variables: \describe{ \item{ annee }{ numeric } \item{ code_nature_eau }{ factor } diff --git a/man/nitrates_telecharger.Rd b/man/nitrates_telecharger.Rd index 0a521800315eb5d5d13c97db0a163484f43ab899..4b4baa0ba324c5990d9774ef5d614a3814b079da 100644 --- a/man/nitrates_telecharger.Rd +++ b/man/nitrates_telecharger.Rd @@ -5,7 +5,7 @@ \alias{nitrates_telecharger} \title{nitrates_telecharger} \format{ -A data frame with 63239 rows and 15 variables: +A data frame with 81525 rows and 15 variables: \describe{ \item{ annee }{ numeric } \item{ mois }{ numeric } @@ -16,9 +16,9 @@ A data frame with 63239 rows and 15 variables: \item{ nom_bassin_versant }{ character } \item{ code_station }{ character } \item{ libelle_station }{ character } - \item{ source_prelevement }{ character } + \item{ source_prelevement_analyse }{ character } \item{ resultat_analyse }{ numeric } - \item{ code_remarque }{ integer } + \item{ code_remarque }{ numeric } \item{ insee_dep }{ factor } \item{ code_commune }{ character } \item{ captage_prioritaire }{ logical } diff --git a/man/nitrates_tendanceP90.Rd b/man/nitrates_tendanceP90.Rd index d4cd7868654eb6607fdd3a373777afd8d7d2ec63..847283ef3b68b5abc4a1635892d542742a91e784 100644 --- a/man/nitrates_tendanceP90.Rd +++ b/man/nitrates_tendanceP90.Rd @@ -5,7 +5,7 @@ \alias{nitrates_tendanceP90} \title{nitrates_tendanceP90} \format{ -A data frame with 8754 rows and 5 variables: +A data frame with 10135 rows and 5 variables: \describe{ \item{ code_station }{ factor } \item{ libelle_station }{ factor } diff --git a/man/nitrates_tendanceP90_telecharger.Rd b/man/nitrates_tendanceP90_telecharger.Rd index 07a4ad921b10d8dbd65b7ced1cac47b18bf47bd1..6d3e52bffee82f0ea8af2a0722228f462adc91c4 100644 --- a/man/nitrates_tendanceP90_telecharger.Rd +++ b/man/nitrates_tendanceP90_telecharger.Rd @@ -5,7 +5,7 @@ \alias{nitrates_tendanceP90_telecharger} \title{nitrates_tendanceP90_telecharger} \format{ -A data frame with 6311 rows and 12 variables: +A data frame with 10135 rows and 12 variables: \describe{ \item{ periode }{ factor } \item{ code_nature_eau }{ factor } diff --git a/man/periode_nitrates_tendanceP90.Rd b/man/periode_nitrates_tendanceP90.Rd index aefe4b242ebe65cae6c4d7e099537d40eda4f3b1..61d7b381d3c159e63c0eb915c6435a96fc22a615 100644 --- a/man/periode_nitrates_tendanceP90.Rd +++ b/man/periode_nitrates_tendanceP90.Rd @@ -5,7 +5,7 @@ \alias{periode_nitrates_tendanceP90} \title{periode_nitrates_tendanceP90} \format{ -A data frame with 16 rows and 2 variables: +A data frame with 17 rows and 2 variables: \describe{ \item{ annee }{ factor } \item{ periode }{ factor } diff --git a/man/prepa_nitrates_fct.Rd b/man/prepa_nitrates_fct.Rd deleted file mode 100644 index 21d21d5ccffe631d982c39ca410f84b11d952e50..0000000000000000000000000000000000000000 --- a/man/prepa_nitrates_fct.Rd +++ /dev/null @@ -1,17 +0,0 @@ -% Generated by roxygen2: do not edit by hand -% Please edit documentation in R/fct_preparation_data.R -\name{prepa_nitrates_fct} -\alias{prepa_nitrates_fct} -\title{prepa_nitrates_fct} -\usage{ -prepa_nitrates_fct(station_code_nature_eau) -} -\arguments{ -\item{station_code_nature_eau}{choix dans la table des stations selon leur code_nature_eau (ESU ou ESO)} -} -\value{ -Un dataframe. -} -\description{ -Une fonction pour produire les tables des mesures nitrates en fonction du code_nature_eau (ESU ou ESO) des stations -} diff --git a/man/repartition_P90.Rd b/man/repartition_P90.Rd index 7e892cc6024cbe2059bd2724fdb26dc46d91ae07..d1c213698177f8fc7b80b3ba88f19fcd485fd470 100644 --- a/man/repartition_P90.Rd +++ b/man/repartition_P90.Rd @@ -5,7 +5,7 @@ \alias{repartition_P90} \title{repartition_P90} \format{ -A data frame with 11750 rows and 8 variables: +A data frame with 11505 rows and 8 variables: \describe{ \item{ code_nature_eau }{ factor } \item{ annee }{ numeric } diff --git a/man/repartition_maxBV.Rd b/man/repartition_maxBV.Rd index 416d16791e6b036438c3911cf9c4d2bfc8206d96..5f7cb95d5b5b9881ee85dc234c3009595bfcd2fc 100644 --- a/man/repartition_maxBV.Rd +++ b/man/repartition_maxBV.Rd @@ -5,7 +5,7 @@ \alias{repartition_maxBV} \title{repartition_maxBV} \format{ -A data frame with 2854 rows and 7 variables: +A data frame with 2580 rows and 7 variables: \describe{ \item{ code_nature_eau }{ factor } \item{ annee }{ numeric } diff --git a/man/repartition_moyBV.Rd b/man/repartition_moyBV.Rd index 66867170b46faff0f7bb99c2ec9cc0864ded808f..d99b285ac883ca3c4b64c9fde155ba0552cba478 100644 --- a/man/repartition_moyBV.Rd +++ b/man/repartition_moyBV.Rd @@ -5,7 +5,7 @@ \alias{repartition_moyBV} \title{repartition_moyBV} \format{ -A data frame with 2733 rows and 7 variables: +A data frame with 2431 rows and 7 variables: \describe{ \item{ code_nature_eau }{ factor } \item{ annee }{ numeric } diff --git a/man/repartition_tendanceP90.Rd b/man/repartition_tendanceP90.Rd index 380ec564e54119e1128484f579abeacefaf6ded8..9bfd9fb9340386cd1d8ec7137d1eff3b8fde9447 100644 --- a/man/repartition_tendanceP90.Rd +++ b/man/repartition_tendanceP90.Rd @@ -5,7 +5,7 @@ \alias{repartition_tendanceP90} \title{repartition_tendanceP90} \format{ -A data frame with 6412 rows and 8 variables: +A data frame with 7254 rows and 8 variables: \describe{ \item{ code_nature_eau }{ factor } \item{ periode }{ factor } diff --git a/man/station_pdl.Rd b/man/station_pdl.Rd index 6aeeaba2dff3b4f10b5c68220c189984649b3b01..011f551102fe196a05ecb71177b405c80a36a431 100644 --- a/man/station_pdl.Rd +++ b/man/station_pdl.Rd @@ -5,21 +5,23 @@ \alias{station_pdl} \title{station_pdl} \format{ -A data frame with 3816 rows and 14 variables: +A data frame with 3870 rows and 16 variables: \describe{ \item{ code_station }{ character } + \item{ code_bss }{ character } + \item{ code_sise_eaux }{ character } + \item{ code_naiades }{ character } \item{ libelle_station }{ character } + \item{ code_nature_eau }{ character } \item{ date_creation }{ Date } - \item{ source }{ character } + \item{ source_station }{ character } \item{ code_masse_eau }{ character } - \item{ code_eu_masse_eau }{ character } + \item{ code_bassin_versant }{ character } \item{ code_commune }{ character } \item{ code_sage }{ character } - \item{ code_bassin_versant }{ character } \item{ captage_prioritaire }{ logical } \item{ insee_dep }{ factor } \item{ test }{ logical } - \item{ code_nature_eau }{ character } \item{ the_geom }{ sfc_POINT,sfc } } }