R/mod_portofoliu.R
In fizic37/RiskManagement: RiskManagement
Defines functions
mod_portofoliu_server
mod_portofoliu_ui
#' portofoliu UI Function
#'
#' @description A shiny Module.
#'
#' @param id,input,output,session Internal parameters for {shiny}.
#'
#' @noRd
#'
#' @importFrom shiny NS tagList
mod_portofoliu_ui <- function(id){
ns <- NS(id)
tagList(shinydashboard::box(title = "Sumar portofoliu",status = "success",collapsible = TRUE,collapsed = FALSE,width = 12,
DT::dataTableOutput(ns("sumar_portofoliu")) %>% shinycssloaders::withSpinner(color = "#77547a"),
br(),
fillRow(flex = c(1, NA), actionButton(inputId = ns("view_sumar_portofoliu"),width = "300px",
label = "Change view - provisions/percentage/brute",my_icon = "toggle-on"),
downloadButton(outputId = ns("down_portof_brut"),label = "Download baza date portofoliu "))),
shinydashboard::box(title = "Monitorizare indicatori provizioane non IFRS",width = 12,
status = "success", collapsible = TRUE,collapsed = TRUE,
selectInput(inputId = ns("select_year_portof"), label = "Selecteaza data raportului",
choices = as.Date("2019-12-31"),
selected = as.Date("2019-12-31"),width = "300px"),
DT::dataTableOutput(ns("rata_cereri_plata")),
br(),
fillRow(flex = c(1,NA),actionButton(inputId = ns("view_rata_cereri"),label = "Change view - percentage/brute",
icon = icon("toggle-on"),width = "300px"),
downloadButton(outputId = ns("down_rata_cereri"), label = "Download baza detaliata")),
br(),
br(),
DT::dataTableOutput(ns("audit_rata_cereri_table"))),
shinydashboard::box(title = "Migrare portofoliu",status = "success",collapsible = TRUE,collapsed = TRUE,width = 12,
fluidPage(
fillRow(flex=c(1,NA),selectInput(inputId = ns("migration_from_nonifrs"), label = "Migration from:",width = "300px",
choices = as.Date("2018-12-31"),
selected = as.Date("2018-12-31")),
selectInput(inputId = ns("migration_to_nonifrs"), label = "Migration to:",
choices = as.Date("2019-12-31"), width="300px",
selected = as.Date("2019-12-31"))),
shinycssloaders::withSpinner(ui_element = DT::dataTableOutput(ns("portfolio_migration"))),
br(),
downloadButton(outputId = ns("down_regularizare_provizioane"),
label = "Download regularizare provizioane")
)))
}
#' portofoliu Server Function
#'
#' @noRd
mod_portofoliu_server <- function(input, output, session){
ns <- session$ns
vals <- reactiveValues()
#observe({if (nrow(vals$portofoliu_database)==0) {portof_database <- readRDS(file = "R/reactivedata/portof_database.rds")}
#else {portof_database <- vals$portofoliu_database}})
portof_database <- readRDS(file = 'R/reactivedata/portof_database.rds')
#vals$portofoliu_database<- portof_database
#observe({vals$portofoliu_database <- portof_database})
#output$diverse_portofoliu <- renderPrint({str(vals$portofoliu_database)})
baza_citita <- portof_database %>% dplyr::filter(anul_de_raportare > as.Date("2009-12-31"))
load('data/cereri_plata.rda')
#cereri_plata <- readRDS(file = 'R/cereri_plata.rds')
ani_raportare_portofoliu <- unique(baza_citita$anul_de_raportare) %>% sort()
choices_data_indicatori_cereri_plata <- ani_raportare_portofoliu[which(ani_raportare_portofoliu<=max(cereri_plata$Data_cerere_plata))]
updateSelectInput(session = session,inputId ='select_year_portof',choices = choices_data_indicatori_cereri_plata,
selected = max(choices_data_indicatori_cereri_plata))
sinteza_portofoliu <- baza_citita %>% dplyr::group_by(anul_de_raportare,categorie_contaminata) %>% dplyr::summarise(expunere=sum(expunere)) %>%
tidyr::pivot_wider(names_from = categorie_contaminata,values_from = expunere) %>% dplyr::ungroup() %>%
dplyr::mutate(Total_sold=rowSums(x = dplyr::select(.,-1),na.rm = TRUE))
sinteza_portofoliu_procentual <- cbind(sinteza_portofoliu[,1],sinteza_portofoliu[,2:6]/sinteza_portofoliu$Total_sold)
sinteza_portofoliu_provizion <- baza_citita %>% dplyr::group_by(anul_de_raportare,categorie_contaminata) %>%
dplyr::summarise(provizion_contabil=sum(provizion_contabil)) %>% tidyr::pivot_wider(names_from = categorie_contaminata,values_from = provizion_contabil) %>%
dplyr::ungroup() %>% dplyr::mutate(Total_Provizion_Contabil=rowSums(x = dplyr::select(.,-1),na.rm = TRUE))
output$sumar_portofoliu <- DT::renderDataTable({
if(is.null(input$view_sumar_portofoliu) || input$view_sumar_portofoliu%%3==0) {
dt_generate_function(df=sinteza_portofoliu,round_col = 2:6,caption = "Sinteza baza date portofoliu, expuneri:")}
else if (input$view_sumar_portofoliu%%2==0) {dt_generate_function(sinteza_portofoliu_provizion,
round_col = 2:6,caption = "Sinteza baza date portofoliu, provizioane:") }
else {dt_generate_function(sinteza_portofoliu_procentual,round_col = NULL,perc_col = 2:6,
caption = "Sinteza baza date portofoliu, pondere expuneri:")} })
cereri_plata <- cereri_plata %>% dplyr::mutate(an_cerere_plata = lubridate::year(Data_cerere_plata)) %>%
dplyr::select(DocumentId,`Cod Partener`,Cerere_Plata,Data_cerere_plata,an_cerere_plata,
plata_aprobata, dplyr::matches("litigiu|poprire|somatie")) %>%
dplyr::mutate(coef_final = apply(dplyr::select(.data = ., dplyr::contains("coef")), 1, function(x) (ifelse(is.na(x) %>% all(),0,max(x,na.rm = TRUE)))),
litigiu_final = apply(dplyr::select(.data = ., poprire_neplatita, suma_litigiu, valoare_somatie),1,max, na.rm = TRUE)) %>%
dplyr::mutate(Plata_litigii = ifelse(is.infinite(coef_final) | coef_final <= 0.25, plata_aprobata, plata_aprobata + litigiu_final))
rata_transf_plati <- cereri_plata %>% dplyr::filter(Data_cerere_plata >=as.Date("2011-01-01") & Data_cerere_plata<=as.Date("2019-09-30")) %>%
dplyr::summarise(Cereri_plata_primite=sum(Cerere_Plata),Plati_aprobate=sum(plata_aprobata),
Plati_si_litiii_necastigate=sum(Plata_litigii))
observeEvent(input$select_year_portof,{
# I produce my rata_trans_plati table
vals$cereri_plata_filtrata <- cereri_plata %>% dplyr::filter(Data_cerere_plata > input$select_year_portof) %>%
dplyr::group_by(`Cod Partener`,an_cerere_plata) %>%
dplyr::summarise(Cerere_Plata=sum(Cerere_Plata)) %>%
dplyr::mutate(Cerere_Plata_cumulata=cumsum(Cerere_Plata)) %>% dplyr::ungroup()
vals$cereri_plata_splitata <- split(vals$cereri_plata_filtrata,vals$cereri_plata_filtrata$an_cerere_plata)
# I rename columns in cereri_plata_splitata. Rename_col function is to be found in mod_portofoliu_utils
vals$cereri_plata_splitata_prel <- purrr::map(vals$cereri_plata_splitata,~rename_col(df=.x))
# I get my filtered dataframe for future processing grupped by CUI
vals$baza_selectata <- baza_citita[baza_citita$anul_de_raportare==input$select_year_portof,] %>%
dplyr::group_by(`Cod Partener`,categorie_contaminata) %>% dplyr::summarise(expunere=sum(expunere))
# I process my filtered dataframe in order to obtain cumulated cerere_Plata according to year.
# I will not obtain final filtered process because, for example, if a CUI has cereri_plata during years 2015 and 2016
# below code will produce cumulated cereri_plata in 2015 and 2016 but will only show 0 for 2017 and subsequent years
vals$baza_selectata_procesata <- purrr::map_df(.x = vals$cereri_plata_splitata_prel,
.f = ~ dplyr::left_join(x = vals$baza_selectata, y = dplyr::select(.data = .x, `Cod Partener`,
dplyr::contains("Cerere_Plata_cumulata")), by = "Cod Partener" )) %>%
dplyr::select(`Cod Partener`, categorie_contaminata, dplyr::contains("Cerere_Plata_cumulata")) %>%
dplyr::group_by(`Cod Partener`, categorie_contaminata) %>%
dplyr::summarise_at(dplyr::vars(-dplyr::group_cols()), sum, na.rm = T) %>% dplyr::ungroup() %>%
#I add back expunere
dplyr::left_join(y = vals$baza_selectata[, c("Cod Partener", "expunere")], by = "Cod Partener")
# I get my final dataframe with cumulated Cerere_plata_cumulata
vals$baza_selectata_final <- cbind(dplyr::select(vals$baza_selectata_procesata,`Cod Partener`,categorie_contaminata,expunere),
max_col(dplyr::select(vals$baza_selectata_procesata,dplyr::contains("Cerere_plata_cumulata")))) # This cumulates Cere_plata_cumulata
vals$tabel_rata_cerere_plata <- vals$baza_selectata_final %>% dplyr::select(-`Cod Partener`) %>%
dplyr::filter(categorie_contaminata!="cerere_plata") %>% dplyr::group_by(categorie_contaminata) %>%
dplyr::summarise_at(.vars = dplyr::vars(-dplyr::group_cols()),sum) %>% dplyr::ungroup()
output$rata_cereri_plata <- DT::renderDataTable({
if (is.null(input$view_rata_cereri) || input$view_rata_cereri %% 2 == 0) {
dt_generate_function(df = vals$tabel_rata_cerere_plata, round_col = 2:(ncol(vals$baza_selectata_final)-1),
caption = paste0("Evolutie rata de transformare in cereri plata a garantiilor in sold la data de ",
as.character(input$select_year_portof))) }
else {dt_generate_function(df = cbind(vals$tabel_rata_cerere_plata[,1:2],
vals$tabel_rata_cerere_plata[,3:ncol(vals$tabel_rata_cerere_plata)]/vals$tabel_rata_cerere_plata$expunere),
round_col = 2,perc_col = 3:ncol(vals$tabel_rata_cerere_plata),
caption = paste0("Rata de trasformare in cerere de plata a garantiilor in sold la ",as.character(input$select_year_portof))) }
})
output$down_rata_cereri <- downloadHandler(filename = function(){"baza_rata_cereri_plata.csv"},content = function(file){
readr::write_csv(x = vals$baza_selectata_final,path = file) })
})
### Migration table
# I have to group baza citita to every CUI
portof_database_CUI_grouped <- baza_citita %>% dplyr::group_by(`Cod Partener`,anul_de_raportare,categorie_contaminata) %>%
dplyr::summarise(expunere = sum(expunere),provizion_contabil=sum(provizion_contabil)) %>% dplyr::ungroup()
lista_provizion_non_ifrs <- split(portof_database_CUI_grouped,portof_database_CUI_grouped$anul_de_raportare) %>%
purrr::map(~rename_col_nonifrs(df=.x))
updateSelectInput(session = session,inputId ='migration_from_nonifrs',choices = ani_raportare_portofoliu,
selected = ani_raportare_portofoliu[(length(ani_raportare_portofoliu)-1)])
updateSelectInput(session = session,inputId ='migration_to_nonifrs',choices = ani_raportare_portofoliu,
selected = max(ani_raportare_portofoliu))
observe({
vals$portofoliu_perioada_curenta <- lista_provizion_non_ifrs[which(names(lista_provizion_non_ifrs) ==
as.character(input$migration_to_nonifrs))][[1]]
vals$portofoliu_perioada_anterioara <- lista_provizion_non_ifrs[which(names(lista_provizion_non_ifrs) ==
as.character(input$migration_from_nonifrs))][[1]] %>%
dplyr::left_join(y= dplyr::select(vals$portofoliu_perioada_curenta,
dplyr::matches("Expunere|Cod Partener|categorie_contaminata|provizion_contabil")), by = "Cod Partener")
# I need to define below column names because they are reactive due to rename_col function applied to the list of dataframes
# I will need to process with dplyr these column names
vals$categorie_anterioara <- paste0("categorie_contaminata_",input$migration_from_nonifrs)
vals$categorie_curenta <- paste0("categorie_contaminata_",input$migration_to_nonifrs)
vals$expunere_anterioara <- paste0("Expunere_",input$migration_from_nonifrs)
vals$expunere_curenta <- paste0("Expunere_",input$migration_to_nonifrs)
vals$provizion_anterior <- paste0("Provizion_contabil_", input$migration_from_nonifrs)
vals$provizion_curent <- paste0("Provizion_contabil_",input$migration_to_nonifrs)
# I calculate my main indicators here of exposure migration
vals$tabel_brut_migration_expunere <- vals$portofoliu_perioada_anterioara %>% dplyr::group_by(!!rlang::sym(vals$categorie_anterioara),
!!rlang::sym(vals$categorie_curenta)) %>%
dplyr::summarise("vals$expunere_anterioara" = sum(!!rlang::sym(vals$expunere_anterioara)),
'vals$expunere_curenta'=sum(!!rlang::sym(vals$expunere_curenta))) %>% dplyr::ungroup() %>%
dplyr::rename_at(.vars = 3:4,.funs = ~c(vals$expunere_anterioara,vals$expunere_curenta)) %>%
dplyr::mutate(Derecunoscute_rambursate = ifelse(is.na(.[[2]]),-.[[3]],.[[4]] - .[[3]]),
Transferuri_cerere_plata = ifelse(.[[2]] == 'cerere_plata' & .[[1]] != 'cerere_plata', .[[4]], 0),
Transferuri_from_cerere_plata = ifelse(.[[2]] == 'cerere_plata' & .[[1]] != 'cerere_plata', -.[[4]], 0),
Transferuri_insolventa = ifelse(.[[2]] == 'insolventa' & .[[1]] != 'insolventa', .[[4]], 0),
Transferuri_from_insolventa = ifelse(.[[2]] == 'insolventa' & .[[1]] != 'insolventa', -.[[4]], 0),
Transferuri_instiintare = ifelse(.[[2]] == 'instiintare_neplata' & .[[1]] != 'instiintare_neplata', .[[4]], 0),
Transferuri_from_instiintare = ifelse(.[[2]] == 'instiintare_neplata' & .[[1]] != 'instiintare_neplata', -.[[4]], 0 ),
Transferuri_standard = ifelse(.[[2]] == 'standard' & .[[1]] != 'standard', .[[4]], 0),
Transferuri_from_standard = ifelse(.[[2]] == 'standard' & .[[1]] != 'standard', -.[[4]], 0 ))
# I get my transfers to a category (from another one)
vals$tabel1_migration <- vals$tabel_brut_migration_expunere %>% dplyr::group_by(!!rlang::sym(vals$categorie_anterioara)) %>%
dplyr::summarise(Sold_initial = sum(!!rlang::sym(vals$expunere_anterioara)),Derecunoscute_rambursate=sum(Derecunoscute_rambursate),
Transfers_cerere_plata = sum(Transferuri_from_cerere_plata,na.rm=T), Transfers_insolventa=sum(Transferuri_from_insolventa,na.rm=T),
Transfers_instiintare=sum(Transferuri_from_instiintare,na.rm=T),
Transfers_standard = sum(Transferuri_from_standard,na.rm = TRUE)) %>% tidyr::pivot_longer(cols = -1) %>%
tidyr::pivot_wider(names_from = !!rlang::sym(vals$categorie_anterioara),names_prefix = "categorie_contaminata_")
# I get my transfers from a category to another one (the same table as table1_migration but with minus exposures)
vals$tabel2_migration <- vals$tabel_brut_migration_expunere %>% dplyr::filter(!is.na(.[[2]])) %>%
dplyr::group_by(!!rlang::sym(vals$categorie_curenta)) %>%
dplyr::summarise(Transfers_cerere_plata = sum(Transferuri_cerere_plata,na.rm=T), Transfers_insolventa = sum(Transferuri_insolventa,na.rm = T),
Transfers_instiintare=sum(Transferuri_instiintare,na.rm=T),Transfers_standard = sum(Transferuri_standard,na.rm = TRUE)) %>%
tidyr::pivot_longer(cols = -1) %>% tidyr::pivot_wider(names_from = !!rlang::sym(vals$categorie_curenta),
names_prefix = "categorie_contaminata_")
# I get category of my new exposures categories
vals$tabel3_new_exposures_migration <- dplyr::left_join(x = vals$portofoliu_perioada_curenta,
y = dplyr::select(vals$portofoliu_perioada_anterioara,`Cod Partener`,!!rlang::sym(vals$expunere_anterioara),
!!rlang::sym(vals$categorie_anterioara)),by="Cod Partener") %>%
dplyr::filter(is.na(!!rlang::sym(vals$categorie_anterioara))) %>% dplyr::group_by(!!rlang::sym(vals$categorie_curenta)) %>%
dplyr::summarise(Acordate_efectuate_in_timpul_anului=sum(!!rlang::sym(vals$expunere_curenta))) %>%
tidyr::pivot_longer(cols = -1) %>% tidyr::pivot_wider(names_from = !!rlang::sym(vals$categorie_curenta),
names_prefix = "categorie_contaminata_")
# I produce my final migration_table
vals$tabel_migration_final <- dplyr::bind_rows(vals$tabel1_migration,vals$tabel2_migration,vals$tabel3_new_exposures_migration) %>%
dplyr::group_by(name) %>%
dplyr:: summarise_all(.funs = ~sum(.,na.rm=T)) %>% dplyr::slice(c(3,1,2,4:6)) %>% dplyr::mutate(Total=rowSums(.[2:5])) %>%
dplyr::bind_rows(apply(X = dplyr::select(.,-1),MARGIN = 2,FUN=sum)) %>% tidyr::replace_na(replace = list(name="Total")) %>%
dplyr::rename_at(.vars = 1,~'Miscari_in_timpul_Perioadei')
output$portfolio_migration <- DT::renderDataTable({dt_generate_function(df=vals$tabel_migration_final,round_col = 2:6,show_buttons = TRUE,
caption = "Migratia portofoliului de garantii in functie de categoria contaminata a beneficiarului:") })
# This table produces provision migration for all CUI that are in perioada curenta (it does not matter if they are in perioada anterioara or not)
vals$tabel_variatie_provizioane <- dplyr::left_join(x = dplyr::select(vals$portofoliu_perioada_curenta,`Cod Partener`,
!!rlang::sym(vals$categorie_curenta), !!rlang::sym(vals$provizion_curent)),
y = dplyr::select(vals$portofoliu_perioada_anterioara,`Cod Partener`,!!rlang::sym(vals$categorie_anterioara),
!!rlang::sym(vals$provizion_anterior)),by="Cod Partener") %>%
dplyr::mutate_at(.vars = 5,~replace(x = .,list = which(is.na(.)),values = 0)) %>%
dplyr::mutate(variatie_provizion = .[[3]] - .[[5]])
# This table produces provisions for all CUI that are in perioada_anterioara and are not in perioada curenta
vals$tabel_beneficiari_iesiti <- dplyr::left_join(y = dplyr::select(vals$portofoliu_perioada_curenta,`Cod Partener`,
!!rlang::sym(vals$categorie_curenta),!!rlang::sym(vals$provizion_curent)),
x = dplyr::select(vals$portofoliu_perioada_anterioara,`Cod Partener`,
!!rlang::sym(vals$categorie_anterioara), !!rlang::sym(vals$provizion_anterior)),
by = "Cod Partener") %>% dplyr::filter(is.na(!!rlang::sym(vals$categorie_curenta))) %>%
dplyr::mutate(variatie_provizion = .[[3]] * (-1))
# I produce my final regualrisation provisions
vals$regularizare_provizioane_non_ifrs <- dplyr::bind_rows(vals$tabel_beneficiari_iesiti,vals$tabel_variatie_provizioane)
output$down_regularizare_provizioane <- downloadHandler(filename = function(){"regularizare-provizioane.csv"},
content = function(file){
readr::write_csv(x = vals$regularizare_provizioane_non_ifrs,path = file) })
})
}
## To be copied in the UI
# mod_portofoliu_ui("portofoliu_ui_1")
## To be copied in the server
# callModule(mod_portofoliu_server, "portofoliu_ui_1")
fizic37/RiskManagement documentation built on Feb. 12, 2021, 11:05 a.m.
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Defines functions mod_portofoliu_server mod_portofoliu_ui
#' portofoliu UI Function
#'
#' @description A shiny Module.
#'
#' @param id,input,output,session Internal parameters for {shiny}.
#'
#' @noRd
#'
#' @importFrom shiny NS tagList
mod_portofoliu_ui <- function(id){
ns <- NS(id)
tagList(shinydashboard::box(title = "Sumar portofoliu",status = "success",collapsible = TRUE,collapsed = FALSE,width = 12,
DT::dataTableOutput(ns("sumar_portofoliu")) %>% shinycssloaders::withSpinner(color = "#77547a"),
br(),
fillRow(flex = c(1, NA), actionButton(inputId = ns("view_sumar_portofoliu"),width = "300px",
label = "Change view - provisions/percentage/brute",my_icon = "toggle-on"),
downloadButton(outputId = ns("down_portof_brut"),label = "Download baza date portofoliu "))),
shinydashboard::box(title = "Monitorizare indicatori provizioane non IFRS",width = 12,
status = "success", collapsible = TRUE,collapsed = TRUE,
selectInput(inputId = ns("select_year_portof"), label = "Selecteaza data raportului",
choices = as.Date("2019-12-31"),
selected = as.Date("2019-12-31"),width = "300px"),
DT::dataTableOutput(ns("rata_cereri_plata")),
br(),
fillRow(flex = c(1,NA),actionButton(inputId = ns("view_rata_cereri"),label = "Change view - percentage/brute",
icon = icon("toggle-on"),width = "300px"),
downloadButton(outputId = ns("down_rata_cereri"), label = "Download baza detaliata")),
br(),
br(),
DT::dataTableOutput(ns("audit_rata_cereri_table"))),
shinydashboard::box(title = "Migrare portofoliu",status = "success",collapsible = TRUE,collapsed = TRUE,width = 12,
fluidPage(
fillRow(flex=c(1,NA),selectInput(inputId = ns("migration_from_nonifrs"), label = "Migration from:",width = "300px",
choices = as.Date("2018-12-31"),
selected = as.Date("2018-12-31")),
selectInput(inputId = ns("migration_to_nonifrs"), label = "Migration to:",
choices = as.Date("2019-12-31"), width="300px",
selected = as.Date("2019-12-31"))),
shinycssloaders::withSpinner(ui_element = DT::dataTableOutput(ns("portfolio_migration"))),
br(),
downloadButton(outputId = ns("down_regularizare_provizioane"),
label = "Download regularizare provizioane")
)))
}
#' portofoliu Server Function
#'
#' @noRd
mod_portofoliu_server <- function(input, output, session){
ns <- session$ns
vals <- reactiveValues()
#observe({if (nrow(vals$portofoliu_database)==0) {portof_database <- readRDS(file = "R/reactivedata/portof_database.rds")}
#else {portof_database <- vals$portofoliu_database}})
portof_database <- readRDS(file = 'R/reactivedata/portof_database.rds')
#vals$portofoliu_database<- portof_database
#observe({vals$portofoliu_database <- portof_database})
#output$diverse_portofoliu <- renderPrint({str(vals$portofoliu_database)})
baza_citita <- portof_database %>% dplyr::filter(anul_de_raportare > as.Date("2009-12-31"))
load('data/cereri_plata.rda')
#cereri_plata <- readRDS(file = 'R/cereri_plata.rds')
ani_raportare_portofoliu <- unique(baza_citita$anul_de_raportare) %>% sort()
choices_data_indicatori_cereri_plata <- ani_raportare_portofoliu[which(ani_raportare_portofoliu<=max(cereri_plata$Data_cerere_plata))]
updateSelectInput(session = session,inputId ='select_year_portof',choices = choices_data_indicatori_cereri_plata,
selected = max(choices_data_indicatori_cereri_plata))
sinteza_portofoliu <- baza_citita %>% dplyr::group_by(anul_de_raportare,categorie_contaminata) %>% dplyr::summarise(expunere=sum(expunere)) %>%
tidyr::pivot_wider(names_from = categorie_contaminata,values_from = expunere) %>% dplyr::ungroup() %>%
dplyr::mutate(Total_sold=rowSums(x = dplyr::select(.,-1),na.rm = TRUE))
sinteza_portofoliu_procentual <- cbind(sinteza_portofoliu[,1],sinteza_portofoliu[,2:6]/sinteza_portofoliu$Total_sold)
sinteza_portofoliu_provizion <- baza_citita %>% dplyr::group_by(anul_de_raportare,categorie_contaminata) %>%
dplyr::summarise(provizion_contabil=sum(provizion_contabil)) %>% tidyr::pivot_wider(names_from = categorie_contaminata,values_from = provizion_contabil) %>%
dplyr::ungroup() %>% dplyr::mutate(Total_Provizion_Contabil=rowSums(x = dplyr::select(.,-1),na.rm = TRUE))
output$sumar_portofoliu <- DT::renderDataTable({
if(is.null(input$view_sumar_portofoliu) || input$view_sumar_portofoliu%%3==0) {
dt_generate_function(df=sinteza_portofoliu,round_col = 2:6,caption = "Sinteza baza date portofoliu, expuneri:")}
else if (input$view_sumar_portofoliu%%2==0) {dt_generate_function(sinteza_portofoliu_provizion,
round_col = 2:6,caption = "Sinteza baza date portofoliu, provizioane:") }
else {dt_generate_function(sinteza_portofoliu_procentual,round_col = NULL,perc_col = 2:6,
caption = "Sinteza baza date portofoliu, pondere expuneri:")} })
cereri_plata <- cereri_plata %>% dplyr::mutate(an_cerere_plata = lubridate::year(Data_cerere_plata)) %>%
dplyr::select(DocumentId,`Cod Partener`,Cerere_Plata,Data_cerere_plata,an_cerere_plata,
plata_aprobata, dplyr::matches("litigiu|poprire|somatie")) %>%
dplyr::mutate(coef_final = apply(dplyr::select(.data = ., dplyr::contains("coef")), 1, function(x) (ifelse(is.na(x) %>% all(),0,max(x,na.rm = TRUE)))),
litigiu_final = apply(dplyr::select(.data = ., poprire_neplatita, suma_litigiu, valoare_somatie),1,max, na.rm = TRUE)) %>%
dplyr::mutate(Plata_litigii = ifelse(is.infinite(coef_final) | coef_final <= 0.25, plata_aprobata, plata_aprobata + litigiu_final))
rata_transf_plati <- cereri_plata %>% dplyr::filter(Data_cerere_plata >=as.Date("2011-01-01") & Data_cerere_plata<=as.Date("2019-09-30")) %>%
dplyr::summarise(Cereri_plata_primite=sum(Cerere_Plata),Plati_aprobate=sum(plata_aprobata),
Plati_si_litiii_necastigate=sum(Plata_litigii))
observeEvent(input$select_year_portof,{
# I produce my rata_trans_plati table
vals$cereri_plata_filtrata <- cereri_plata %>% dplyr::filter(Data_cerere_plata > input$select_year_portof) %>%
dplyr::group_by(`Cod Partener`,an_cerere_plata) %>%
dplyr::summarise(Cerere_Plata=sum(Cerere_Plata)) %>%
dplyr::mutate(Cerere_Plata_cumulata=cumsum(Cerere_Plata)) %>% dplyr::ungroup()
vals$cereri_plata_splitata <- split(vals$cereri_plata_filtrata,vals$cereri_plata_filtrata$an_cerere_plata)
# I rename columns in cereri_plata_splitata. Rename_col function is to be found in mod_portofoliu_utils
vals$cereri_plata_splitata_prel <- purrr::map(vals$cereri_plata_splitata,~rename_col(df=.x))
# I get my filtered dataframe for future processing grupped by CUI
vals$baza_selectata <- baza_citita[baza_citita$anul_de_raportare==input$select_year_portof,] %>%
dplyr::group_by(`Cod Partener`,categorie_contaminata) %>% dplyr::summarise(expunere=sum(expunere))
# I process my filtered dataframe in order to obtain cumulated cerere_Plata according to year.
# I will not obtain final filtered process because, for example, if a CUI has cereri_plata during years 2015 and 2016
# below code will produce cumulated cereri_plata in 2015 and 2016 but will only show 0 for 2017 and subsequent years
vals$baza_selectata_procesata <- purrr::map_df(.x = vals$cereri_plata_splitata_prel,
.f = ~ dplyr::left_join(x = vals$baza_selectata, y = dplyr::select(.data = .x, `Cod Partener`,
dplyr::contains("Cerere_Plata_cumulata")), by = "Cod Partener" )) %>%
dplyr::select(`Cod Partener`, categorie_contaminata, dplyr::contains("Cerere_Plata_cumulata")) %>%
dplyr::group_by(`Cod Partener`, categorie_contaminata) %>%
dplyr::summarise_at(dplyr::vars(-dplyr::group_cols()), sum, na.rm = T) %>% dplyr::ungroup() %>%
#I add back expunere
dplyr::left_join(y = vals$baza_selectata[, c("Cod Partener", "expunere")], by = "Cod Partener")
# I get my final dataframe with cumulated Cerere_plata_cumulata
vals$baza_selectata_final <- cbind(dplyr::select(vals$baza_selectata_procesata,`Cod Partener`,categorie_contaminata,expunere),
max_col(dplyr::select(vals$baza_selectata_procesata,dplyr::contains("Cerere_plata_cumulata")))) # This cumulates Cere_plata_cumulata
vals$tabel_rata_cerere_plata <- vals$baza_selectata_final %>% dplyr::select(-`Cod Partener`) %>%
dplyr::filter(categorie_contaminata!="cerere_plata") %>% dplyr::group_by(categorie_contaminata) %>%
dplyr::summarise_at(.vars = dplyr::vars(-dplyr::group_cols()),sum) %>% dplyr::ungroup()
output$rata_cereri_plata <- DT::renderDataTable({
if (is.null(input$view_rata_cereri) || input$view_rata_cereri %% 2 == 0) {
dt_generate_function(df = vals$tabel_rata_cerere_plata, round_col = 2:(ncol(vals$baza_selectata_final)-1),
caption = paste0("Evolutie rata de transformare in cereri plata a garantiilor in sold la data de ",
as.character(input$select_year_portof))) }
else {dt_generate_function(df = cbind(vals$tabel_rata_cerere_plata[,1:2],
vals$tabel_rata_cerere_plata[,3:ncol(vals$tabel_rata_cerere_plata)]/vals$tabel_rata_cerere_plata$expunere),
round_col = 2,perc_col = 3:ncol(vals$tabel_rata_cerere_plata),
caption = paste0("Rata de trasformare in cerere de plata a garantiilor in sold la ",as.character(input$select_year_portof))) }
})
output$down_rata_cereri <- downloadHandler(filename = function(){"baza_rata_cereri_plata.csv"},content = function(file){
readr::write_csv(x = vals$baza_selectata_final,path = file) })
})
### Migration table
# I have to group baza citita to every CUI
portof_database_CUI_grouped <- baza_citita %>% dplyr::group_by(`Cod Partener`,anul_de_raportare,categorie_contaminata) %>%
dplyr::summarise(expunere = sum(expunere),provizion_contabil=sum(provizion_contabil)) %>% dplyr::ungroup()
lista_provizion_non_ifrs <- split(portof_database_CUI_grouped,portof_database_CUI_grouped$anul_de_raportare) %>%
purrr::map(~rename_col_nonifrs(df=.x))
updateSelectInput(session = session,inputId ='migration_from_nonifrs',choices = ani_raportare_portofoliu,
selected = ani_raportare_portofoliu[(length(ani_raportare_portofoliu)-1)])
updateSelectInput(session = session,inputId ='migration_to_nonifrs',choices = ani_raportare_portofoliu,
selected = max(ani_raportare_portofoliu))
observe({
vals$portofoliu_perioada_curenta <- lista_provizion_non_ifrs[which(names(lista_provizion_non_ifrs) ==
as.character(input$migration_to_nonifrs))][[1]]
vals$portofoliu_perioada_anterioara <- lista_provizion_non_ifrs[which(names(lista_provizion_non_ifrs) ==
as.character(input$migration_from_nonifrs))][[1]] %>%
dplyr::left_join(y= dplyr::select(vals$portofoliu_perioada_curenta,
dplyr::matches("Expunere|Cod Partener|categorie_contaminata|provizion_contabil")), by = "Cod Partener")
# I need to define below column names because they are reactive due to rename_col function applied to the list of dataframes
# I will need to process with dplyr these column names
vals$categorie_anterioara <- paste0("categorie_contaminata_",input$migration_from_nonifrs)
vals$categorie_curenta <- paste0("categorie_contaminata_",input$migration_to_nonifrs)
vals$expunere_anterioara <- paste0("Expunere_",input$migration_from_nonifrs)
vals$expunere_curenta <- paste0("Expunere_",input$migration_to_nonifrs)
vals$provizion_anterior <- paste0("Provizion_contabil_", input$migration_from_nonifrs)
vals$provizion_curent <- paste0("Provizion_contabil_",input$migration_to_nonifrs)
# I calculate my main indicators here of exposure migration
vals$tabel_brut_migration_expunere <- vals$portofoliu_perioada_anterioara %>% dplyr::group_by(!!rlang::sym(vals$categorie_anterioara),
!!rlang::sym(vals$categorie_curenta)) %>%
dplyr::summarise("vals$expunere_anterioara" = sum(!!rlang::sym(vals$expunere_anterioara)),
'vals$expunere_curenta'=sum(!!rlang::sym(vals$expunere_curenta))) %>% dplyr::ungroup() %>%
dplyr::rename_at(.vars = 3:4,.funs = ~c(vals$expunere_anterioara,vals$expunere_curenta)) %>%
dplyr::mutate(Derecunoscute_rambursate = ifelse(is.na(.[[2]]),-.[[3]],.[[4]] - .[[3]]),
Transferuri_cerere_plata = ifelse(.[[2]] == 'cerere_plata' & .[[1]] != 'cerere_plata', .[[4]], 0),
Transferuri_from_cerere_plata = ifelse(.[[2]] == 'cerere_plata' & .[[1]] != 'cerere_plata', -.[[4]], 0),
Transferuri_insolventa = ifelse(.[[2]] == 'insolventa' & .[[1]] != 'insolventa', .[[4]], 0),
Transferuri_from_insolventa = ifelse(.[[2]] == 'insolventa' & .[[1]] != 'insolventa', -.[[4]], 0),
Transferuri_instiintare = ifelse(.[[2]] == 'instiintare_neplata' & .[[1]] != 'instiintare_neplata', .[[4]], 0),
Transferuri_from_instiintare = ifelse(.[[2]] == 'instiintare_neplata' & .[[1]] != 'instiintare_neplata', -.[[4]], 0 ),
Transferuri_standard = ifelse(.[[2]] == 'standard' & .[[1]] != 'standard', .[[4]], 0),
Transferuri_from_standard = ifelse(.[[2]] == 'standard' & .[[1]] != 'standard', -.[[4]], 0 ))
# I get my transfers to a category (from another one)
vals$tabel1_migration <- vals$tabel_brut_migration_expunere %>% dplyr::group_by(!!rlang::sym(vals$categorie_anterioara)) %>%
dplyr::summarise(Sold_initial = sum(!!rlang::sym(vals$expunere_anterioara)),Derecunoscute_rambursate=sum(Derecunoscute_rambursate),
Transfers_cerere_plata = sum(Transferuri_from_cerere_plata,na.rm=T), Transfers_insolventa=sum(Transferuri_from_insolventa,na.rm=T),
Transfers_instiintare=sum(Transferuri_from_instiintare,na.rm=T),
Transfers_standard = sum(Transferuri_from_standard,na.rm = TRUE)) %>% tidyr::pivot_longer(cols = -1) %>%
tidyr::pivot_wider(names_from = !!rlang::sym(vals$categorie_anterioara),names_prefix = "categorie_contaminata_")
# I get my transfers from a category to another one (the same table as table1_migration but with minus exposures)
vals$tabel2_migration <- vals$tabel_brut_migration_expunere %>% dplyr::filter(!is.na(.[[2]])) %>%
dplyr::group_by(!!rlang::sym(vals$categorie_curenta)) %>%
dplyr::summarise(Transfers_cerere_plata = sum(Transferuri_cerere_plata,na.rm=T), Transfers_insolventa = sum(Transferuri_insolventa,na.rm = T),
Transfers_instiintare=sum(Transferuri_instiintare,na.rm=T),Transfers_standard = sum(Transferuri_standard,na.rm = TRUE)) %>%
tidyr::pivot_longer(cols = -1) %>% tidyr::pivot_wider(names_from = !!rlang::sym(vals$categorie_curenta),
names_prefix = "categorie_contaminata_")
# I get category of my new exposures categories
vals$tabel3_new_exposures_migration <- dplyr::left_join(x = vals$portofoliu_perioada_curenta,
y = dplyr::select(vals$portofoliu_perioada_anterioara,`Cod Partener`,!!rlang::sym(vals$expunere_anterioara),
!!rlang::sym(vals$categorie_anterioara)),by="Cod Partener") %>%
dplyr::filter(is.na(!!rlang::sym(vals$categorie_anterioara))) %>% dplyr::group_by(!!rlang::sym(vals$categorie_curenta)) %>%
dplyr::summarise(Acordate_efectuate_in_timpul_anului=sum(!!rlang::sym(vals$expunere_curenta))) %>%
tidyr::pivot_longer(cols = -1) %>% tidyr::pivot_wider(names_from = !!rlang::sym(vals$categorie_curenta),
names_prefix = "categorie_contaminata_")
# I produce my final migration_table
vals$tabel_migration_final <- dplyr::bind_rows(vals$tabel1_migration,vals$tabel2_migration,vals$tabel3_new_exposures_migration) %>%
dplyr::group_by(name) %>%
dplyr:: summarise_all(.funs = ~sum(.,na.rm=T)) %>% dplyr::slice(c(3,1,2,4:6)) %>% dplyr::mutate(Total=rowSums(.[2:5])) %>%
dplyr::bind_rows(apply(X = dplyr::select(.,-1),MARGIN = 2,FUN=sum)) %>% tidyr::replace_na(replace = list(name="Total")) %>%
dplyr::rename_at(.vars = 1,~'Miscari_in_timpul_Perioadei')
output$portfolio_migration <- DT::renderDataTable({dt_generate_function(df=vals$tabel_migration_final,round_col = 2:6,show_buttons = TRUE,
caption = "Migratia portofoliului de garantii in functie de categoria contaminata a beneficiarului:") })
# This table produces provision migration for all CUI that are in perioada curenta (it does not matter if they are in perioada anterioara or not)
vals$tabel_variatie_provizioane <- dplyr::left_join(x = dplyr::select(vals$portofoliu_perioada_curenta,`Cod Partener`,
!!rlang::sym(vals$categorie_curenta), !!rlang::sym(vals$provizion_curent)),
y = dplyr::select(vals$portofoliu_perioada_anterioara,`Cod Partener`,!!rlang::sym(vals$categorie_anterioara),
!!rlang::sym(vals$provizion_anterior)),by="Cod Partener") %>%
dplyr::mutate_at(.vars = 5,~replace(x = .,list = which(is.na(.)),values = 0)) %>%
dplyr::mutate(variatie_provizion = .[[3]] - .[[5]])
# This table produces provisions for all CUI that are in perioada_anterioara and are not in perioada curenta
vals$tabel_beneficiari_iesiti <- dplyr::left_join(y = dplyr::select(vals$portofoliu_perioada_curenta,`Cod Partener`,
!!rlang::sym(vals$categorie_curenta),!!rlang::sym(vals$provizion_curent)),
x = dplyr::select(vals$portofoliu_perioada_anterioara,`Cod Partener`,
!!rlang::sym(vals$categorie_anterioara), !!rlang::sym(vals$provizion_anterior)),
by = "Cod Partener") %>% dplyr::filter(is.na(!!rlang::sym(vals$categorie_curenta))) %>%
dplyr::mutate(variatie_provizion = .[[3]] * (-1))
# I produce my final regualrisation provisions
vals$regularizare_provizioane_non_ifrs <- dplyr::bind_rows(vals$tabel_beneficiari_iesiti,vals$tabel_variatie_provizioane)
output$down_regularizare_provizioane <- downloadHandler(filename = function(){"regularizare-provizioane.csv"},
content = function(file){
readr::write_csv(x = vals$regularizare_provizioane_non_ifrs,path = file) })
})
}
## To be copied in the UI
# mod_portofoliu_ui("portofoliu_ui_1")
## To be copied in the server
# callModule(mod_portofoliu_server, "portofoliu_ui_1")
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