Upload Fonctions.R

Fonctions.R

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+# Fonctions
+
+# Fonction pour filtrer les données
+filter_data <- function(data, input, return_columns = NULL) {
+  # If no column is selected, return an empty data table
+  if (length(input$column) == 0) {
+    return(data[0])
+  }
+  
+  filtered_data <- data[
+    Annee_unique >= input$date_range[1] &
+      Annee_unique <= input$date_range[2]
+  ]
+  
+  pattern <- input$motcle
+  
+  # Create a logical vector to store matches across columns
+  matches <- rep(FALSE, nrow(filtered_data))
+  
+  # Check each selected column for matches and combine results with "OR" logic
+  for (col in input$column) {
+    if(input$regex){
+      matches <- matches | grepl(pattern, filtered_data[[col]])
+    } else {
+      matches <- matches | grepl(pattern, filtered_data[[col]], fixed = TRUE)
+    }
+  }
+  
+  # Filter the data based on the combined matches
+  filtered_data <- filtered_data[matches, ]
+  
+  # If return_columns is specified, select only those columns
+  if (!is.null(return_columns)) {
+    filtered_data <- filtered_data[, ..return_columns]
+  }
+  
+  return(filtered_data)
+}
+
+plot_histogram <- function(data_frame) {
+  if ("Annee_unique" %in% names(data_frame) && nrow(data_frame) > 0) {
+    min_year <- min(na.omit(data_frame[, Annee_unique]))
+    max_year <- max(na.omit(data_frame[, Annee_unique]))
+    breaks_hist <- seq(min_year, max_year, length.out = input$num_breaks + 1)
+    
+    if (input$dist_type == "raw") {
+      hist(data_frame()[, Annee_unique],
+           main = "Distribution brute des notices",
+           xlab = "Année",
+           ylab = "Nombre",
+           border = "blue",
+           col = "lightblue",
+           breaks = breaks_hist)
+    } else {
+      # Compute relative distribution
+      filtered_counts <- hist(data_frame[, Annee_unique], plot=FALSE, breaks=breaks_hist)$counts
+      total_counts <- hist(data[data$Annee_unique %in% data_frame[, Annee_unique], Annee_unique], plot=FALSE, breaks=breaks_hist)$counts
+      relative_counts <- ifelse(total_counts == 0, 0, filtered_counts / total_counts)
+      
+      # Ensure names.arg matches the length of relative_counts
+      names_for_bars <- round(seq(min_year, max_year, length.out = length(relative_counts)))
+      
+      barplot(relative_counts, 
+              main = "Distribution relative des notices",
+              xlab = "Année",
+              ylab = "Fréquence relative",
+              border = "blue",
+              col = "lightblue",
+              space = 0,
+              names.arg = names_for_bars)
+    }
+  } else {
+    plot.new()
+    title(main = "No data available for the selected criteria")
+  }
+}