Update app.R

app.R

@@ -1,58 +1,187 @@
+# install.packages("shinyWidgets")
+# install.packages("shinycssloaders")
+# install.packages("bslib")
+# install.packages("plotly")
+
 library(shiny)
 library(bslib)
-library(dplyr)
-library(ggplot2)
+library(tidyverse)
+library(DT)
+library(plotly)
+library(shinyWidgets)
+library(shinycssloaders)
 
-df <- readr::read_csv("penguins.csv")
-# Find subset of columns that are suitable for scatter plot
-df_num <- df |> select(where(is.numeric), -Year)
+# --- カスタムCSS（LINE風の配色とカードデザイン） ---
+custom_css <- "
+  .main-title { color: #06C755; font-weight: bold; margin-bottom: 20px; }
+  .card { border-radius: 15px; border: none; box-shadow: 0 4px 6px rgba(0,0,0,0.1); }
+  .btn-primary { background-color: #06C755; border: none; }
+  .btn-primary:hover { background-color: #05a346; }
+  .nav-tabs .nav-link.active { border-bottom: 3px solid #06C755 !important; color: #06C755 !important; }
+"
 
-ui <- page_sidebar(
-  theme = bs_theme(bootswatch = "minty"),
-  title = "Penguins explorer",
+# --- UI ---
+ui <- page_navbar(
+  title = span("Quali Fit トーク履歴解析", class = "main-title"),
+  theme = bs_theme(version = 5, bootswatch = "flatly", primary = "#06C755"),
+  header = tags$head(tags$style(custom_css)),
+  
+  # サイドバー（設定・アップロード）
   sidebar = sidebar(
-    varSelectInput("xvar", "X variable", df_num, selected = "Bill Length (mm)"),
-    varSelectInput("yvar", "Y variable", df_num, selected = "Bill Depth (mm)"),
-    checkboxGroupInput("species", "Filter by species",
-      choices = unique(df$Species), selected = unique(df$Species)
-    ),
-    hr(), # Add a horizontal rule
-    checkboxInput("by_species", "Show species", TRUE),
-    checkboxInput("show_margins", "Show marginal plots", TRUE),
-    checkboxInput("smooth", "Add smoother"),
+    title = "操作パネル",
+    fileInput("file1", "履歴ファイルをアップロード", accept = c(".csv", ".txt")),
+    hr(),
+    uiOutput("filter_ui"),
+    hr(),
+    downloadButton("downloadData", "CSVでエクスポート", class = "btn-primary w-100")
+  ),
+  
+  # メインパネル（タブ構成）
+  nav_panel("📊 ダッシュボード",
+            layout_column_wrap(
+              width = 1/3,
+              value_box(
+                title = "総メッセージ数",
+                value = textOutput("total_msg"),
+                showcase = icon("comment-dots")
+              ),
+              value_box(
+                title = "アクティブ人数",
+                value = textOutput("total_members"),
+                showcase = icon("users")
+              ),
+              value_box(
+                title = "最多発言者",
+                value = textOutput("top_sender"),
+                showcase = icon("award")
+              )
+            ),
+            layout_column_wrap(
+              width = 1/2,
+              card(card_header("発言者別の割合"), withSpinner(plotlyOutput("piePlot"))),
+              card(card_header("時系列のアクティビティ"), withSpinner(plotlyOutput("timePlot")))
+            )
+  ),
+  
+  nav_panel("💬 トーク閲覧",
+            card(
+              full_screen = TRUE,
+              card_header("メッセージ履歴"),
+              DTOutput("table")
+            )
   ),
-  plotOutput("scatter")
+  
+  nav_panel("ℹ️ 使い方",
+            card(
+              markdown("
+      ### Quali Fit 履歴解析ツール
+      1. 左側のサイドバーから、LINEから書き出した`.txt`または`.csv`ファイルをアップロードしてください。
+      2. **ダッシュボード**タブで、コミュニケーションの統計を確認できます。
+      3. **トーク閲覧**タブで、特定のキーワードや人物で検索が可能です。
+      4. フィルタリング後のデータは、CSVとして保存できます。
+      ")
+            )
+  )
 )
 
+# --- Server ---
 server <- function(input, output, session) {
-  subsetted <- reactive({
-    req(input$species)
-    df |> filter(Species %in% input$species)
-  })
-
-  output$scatter <- renderPlot(
-    {
-      p <- ggplot(subsetted(), aes(!!input$xvar, !!input$yvar)) +
-        theme_light() +
-        list(
-          theme(legend.position = "bottom"),
-          if (input$by_species) aes(color = Species),
-          geom_point(),
-          if (input$smooth) geom_smooth()
-        )
-
-      if (input$show_margins) {
-        margin_type <- if (input$by_species) "density" else "histogram"
-        p <- p |> ggExtra::ggMarginal(
-          type = margin_type, margins = "both",
-          size = 8, groupColour = input$by_species, groupFill = input$by_species
-        )
+  
+  # 解析ロジック
+  parsed_df <- reactive({
+    req(input$file1)
+    lines <- readLines(input$file1$datapath, warn = FALSE, encoding = "UTF-8")
+    
+    chat_list <- list()
+    current_date <- NA
+    current_thread <- "不明"
+    
+    for (line in lines) {
+      if (grepl("\\[LINE\\] (.*?)とのトーク履歴", line)) {
+        current_thread <- sub("\\[LINE\\] (.*?)とのトーク履歴.*", "\\1", line)
+        next
       }
-
-      p
-    },
-    res = 100
+      if (grepl("^\\d{4}/\\d{2}/\\d{2}", line)) {
+        current_date <- sub("^(\\d{4}/\\d{2}/\\d{2}).*", "\\1", line)
+        next
+      }
+      if (grepl("^\"?\\d{2}:\\d{2}\t", line)) {
+        clean_line <- gsub("^\"", "", line)
+        parts <- strsplit(clean_line, "\t")[[1]]
+        if (length(parts) >= 3) {
+          chat_list[[length(chat_list) + 1]] <- data.frame(
+            Thread = current_thread,
+            Date = as.Date(current_date, format="%Y/%m/%d"),
+            Time = parts[1],
+            Sender = parts[2],
+            Message = gsub("\"$", "", parts[3]),
+            stringsAsFactors = FALSE
+          )
+        }
+      } else if (length(chat_list) > 0 && !is.na(current_date)) {
+        last_idx <- length(chat_list)
+        chat_list[[last_idx]]$Message <- paste(chat_list[[last_idx]]$Message, line)
+      }
+    }
+    bind_rows(chat_list)
+  })
+  
+  # 動的フィルター
+  output$filter_ui <- renderUI({
+    df <- parsed_df()
+    tagList(
+      pickerInput("thread_sel", "スレッド選択:", choices = unique(df$Thread), multiple = TRUE, selected = unique(df$Thread), options = list(`actions-box` = TRUE)),
+      pickerInput("sender_sel", "送信者選択:", choices = unique(df$Sender), multiple = TRUE, selected = unique(df$Sender), options = list(`actions-box` = TRUE)),
+      # 修正点: btnDel を btnReset に変更
+      searchInput("keyword", "本文検索:", placeholder = "キーワード入力...", btnSearch = icon("search"), btnReset = icon("times"))
+    )
+  })
+  
+  # フィルタリング後のデータ
+  filtered_df <- reactive({
+    df <- parsed_df()
+    if (!is.null(input$thread_sel)) df <- df %>% filter(Thread %in% input$thread_sel)
+    if (!is.null(input$sender_sel)) df <- df %>% filter(Sender %in% input$sender_sel)
+    if (!is.null(input$keyword) && input$keyword != "") {
+      df <- df %>% filter(grepl(input$keyword, Message, ignore.case = TRUE))
+    }
+    df
+  })
+  
+  # --- メトリクス ---
+  output$total_msg <- renderText({ nrow(filtered_df()) })
+  output$total_members <- renderText({ n_distinct(filtered_df()$Sender) })
+  output$top_sender <- renderText({ 
+    res <- filtered_df() %>% count(Sender) %>% slice_max(n, n = 1) %>% pull(Sender)
+    if(length(res) > 0) res[1] else "なし"
+  })
+  
+  # --- グラフ作成 ---
+  output$piePlot <- renderPlotly({
+    plot_ly(filtered_df() %>% count(Sender), labels = ~Sender, values = ~n, type = 'pie', hole = 0.4) %>%
+      layout(showlegend = TRUE)
+  })
+  
+  output$timePlot <- renderPlotly({
+    p <- filtered_df() %>% count(Date) %>%
+      ggplot(aes(x = Date, y = n)) +
+      # 修正点: size を linewidth に変更
+      geom_line(color = "#06C755", linewidth = 1) + 
+      geom_point(color = "#06C755") +
+      theme_minimal() + labs(x = "", y = "投稿数")
+    ggplotly(p)
+  })
+  
+  # --- テーブル ---
+  output$table <- renderDT({
+    datatable(filtered_df(), options = list(pageLength = 15, autoWidth = TRUE), rownames = FALSE)
+  })
+  
+  # --- エクスポート ---
+  output$downloadData <- downloadHandler(
+    filename = function() { paste0("Struct_Chat_", Sys.Date(), ".csv") },
+    content = function(file) { write.csv(filtered_df(), file, row.names = FALSE, fileEncoding = "CP932") }
   )
 }
 
-shinyApp(ui, server)
+shinyApp(ui, server)