library(shiny)
library(ggplot2)
library(dplyr)
library(tidyr)
library(corrplot)
library(plotly)

# ──────────────────────────────────────────
#  列定義
# ──────────────────────────────────────────
COL_LABELS <- list(
  "整備_実績_売上_（単位：円）"           = "整備_売上",
  "整備_実績_一般車検_（単位：円）"        = "整備_一般車検",
  "整備_実績_整備・板金_（単位：円）"      = "整備_整備・板金",
  "整備_実績_その他_（単位：円）"         = "整備_その他",
  "整備_実績_原価_（単位：円）"           = "整備_原価",
  "整備_実績_粗利_（単位：円）"           = "整備_粗利",
  "整備_実績_販管費_（単位：円）"         = "整備_販管費",
  "整備_実績_営業利益_（単位：円）"        = "整備_営業利益",
  "整備_KPI（一般車検件数）_実績_（単位：台）" = "車検件数",
  "整備_KPI（整備・板金数）_実績_（単位：台）" = "整備・板金数",
  "商品_実績_売上_（単位：円）"           = "商品_売上",
  "商品_実績_原価_（単位：円）"           = "商品_原価",
  "商品_実績_粗利_（単位：円）"           = "商品_粗利",
  "商品_実績_販管費_（単位：円）"         = "商品_販管費",
  "商品_実績_営業利益_（単位：円）"        = "商品_営業利益",
  "運送_実績_売上_（単位：円）"           = "運送_売上",
  "運送_実績_原価_（単位：円）"           = "運送_原価",
  "運送_実績_粗利_（単位：円）"           = "運送_粗利",
  "運送_実績_販管費_（単位：円）"         = "運送_販管費",
  "運送_実績_営業利益_（単位：円）"        = "運送_営業利益",
  "運送_KPI（自社ドライバー数）_実績_（単位：台）" = "自社ドライバー数",
  "運送_KPI（他社ドライバー数）_実績_（単位：台）" = "他社ドライバー数",
  "レンタル_実績_売上_（単位：円）"        = "レンタル_売上",
  "レンタル_実績_原価_（単位：円）"        = "レンタル_原価",
  "レンタル_実績_粗利_（単位：円）"        = "レンタル_粗利",
  "レンタル_実績_販管費_（単位：円）"      = "レンタル_販管費",
  "レンタル_実績_営業利益_（単位：円）"     = "レンタル_営業利益",
  "レンタル_KPI（レンタル台数）_実績_（単位：台）" = "レンタル台数"
)

short_label <- function(col) {
  lbl <- COL_LABELS[[col]]
  if (!is.null(lbl)) lbl else col
}

# ──────────────────────────────────────────
#  データ読み込み
# ──────────────────────────────────────────
load_csv <- function(path) {
  df <- tryCatch({
    # UTF-8 BOM付き・CRLF・2行ヘッダー対応
    # 1行目: date,x1,x2... (コードキー行)
    # 2行目: 年_月,整備_実績_売上... (日本語ヘッダー行)
    # 3行目以降: データ
    raw <- read.csv(path,
                    header    = FALSE,
                    skip      = 0,
                    stringsAsFactors = FALSE,
                    encoding  = "UTF-8",
                    fileEncoding = "UTF-8-BOM",
                    check.names = FALSE)

    # 先頭セルのBOM残骸をさらに除去
    raw[1, 1] <- gsub("^\uFEFF", "", raw[1, 1])
    raw[1, 1] <- gsub("^\\xef\\xbb\\xbf", "", raw[1, 1])

    # 1行目がコードキー行かどうか判定
    first_cell <- as.character(raw[1, 1])
    second_cell <- as.character(raw[1, 2])
    is_code_row <- grepl("^date$", first_cell, ignore.case = TRUE) ||
                   grepl("^x[0-9]+$", second_cell)

    if (is_code_row) {
      # 行1=コードキー, 行2=日本語ヘッダー → 行2をcolnamesに, 行1〜2を削除
      colnames(raw) <- as.character(raw[2, ])
      raw <- raw[-c(1, 2), ]
    } else {
      # 行1=日本語ヘッダー → 行1をcolnamesに, 行1を削除
      colnames(raw) <- as.character(raw[1, ])
      raw <- raw[-1, ]
    }
    raw
  }, error = function(e) {
    message("load_csv error: ", conditionMessage(e))
    NULL
  })

  if (is.null(df) || nrow(df) == 0) return(NULL)

  # 年月列を統一（年_月 → 年月）
  if ("年_月" %in% colnames(df)) {
    df <- df %>% rename(年月 = `年_月`)
  } else if (!("年月" %in% colnames(df))) {
    df <- df %>% mutate(年月 = as.character(df[[1]])) %>% select(年月, everything())
  }

  # 数値列変換
  for (col in setdiff(colnames(df), "年月")) {
    df[[col]] <- suppressWarnings(as.numeric(gsub(",", "", as.character(df[[col]]))))
  }

  # 合計行・空行除外
  df <- df %>% filter(
    !is.na(年月), 年月 != "",
    !grepl("合計|累計|年_月", 年月)
  )
  if (nrow(df) == 0) return(NULL)
  df
}

# デモデータパス
DEMO_PATH <- "DummyData.csv"
DEMO_PATHS <- c(
  "DummyData.csv",
  "SampleData.csv",
  file.path(getwd(), "DummyData.csv"),
  file.path(getwd(), "SampleData.csv"),
  "/srv/shiny-server/DummyData.csv",
  "/srv/shiny-server/SampleData.csv",
  "/mnt/user-data/uploads/DummyData.csv",
  "/mnt/user-data/uploads/SampleData.csv"
)

load_demo <- function() {
  for (p in DEMO_PATHS) {
    if (file.exists(p)) return(load_csv(p))
  }
  NULL
}

fmt_yen <- function(x) {
  if (is.na(x)) return("—")
  if (abs(x) >= 1e8) return(paste0(formatC(x / 1e8, format = "f", digits = 2), "億円"))
  if (abs(x) >= 1e4) return(paste0(format(round(x / 10000), big.mark = ","), "万円"))
  paste0(format(round(x), big.mark = ","), "円")
}

# ──────────────────────────────────────────
#  CSS / Theme
# ──────────────────────────────────────────
dashboard_css <- "
@import url('https://fonts.googleapis.com/css2?family=Noto+Serif+JP:wght@400;600;700&family=IBM+Plex+Mono:wght@400;500;600&family=Noto+Sans+JP:wght@300;400;500;700&display=swap');

/* ── TOKENS (light = default) ── */
:root {
  --bg:      #f0f4f8;
  --bg2:     #ffffff;
  --bg3:     #e8eef5;
  --bg4:     #d8e4f0;
  --border:  #c5d3e4;
  --text:    #0f172a;
  --text2:   #475569;
  --text3:   #94a3b8;
  --accent:  #0284c7;
  --purple:  #7c3aed;
  --gold:    #d97706;
  --success: #059669;
  --danger:  #dc2626;
  --warn:    #d97706;
  --r:       10px;
  --shadow:  0 4px 32px rgba(0,0,0,.12);
  --header-h:56px;
  --bottom-h:60px;
  --sidebar-w:230px;
}
/* ── TOKENS (dark) ── */
body.dark {
  --bg:      #0b0f1a;
  --bg2:     #111827;
  --bg3:     #1a2235;
  --bg4:     #222d42;
  --border:  #2a3550;
  --text:    #e2e8f4;
  --text2:   #7a8db8;
  --text3:   #4a5a7a;
  --accent:  #4fc3f7;
  --purple:  #7c3aed;
  --gold:    #f0b429;
  --success: #34d399;
  --danger:  #f87171;
  --warn:    #fbbf24;
  --shadow:  0 4px 32px rgba(0,0,0,.5);
}

*,*::before,*::after{margin:0;padding:0;box-sizing:border-box;-webkit-tap-highlight-color:transparent;}
/* Shiny用: html/bodyにheight:100%やoverflow:hiddenをつけない */
html{height:100%;}
body{min-height:100%;font-family:'Noto Sans JP',sans-serif;font-size:13px;line-height:1.6;background:var(--bg);color:var(--text);transition:background .25s,color .25s;}
/* Shinyラッパーを透明化 */
.container-fluid,.shiny-bound-output,.tab-content,.tabbable{background:transparent!important;}
button{font-family:inherit;cursor:pointer;}
@keyframes pulse{0%,100%{opacity:1}50%{opacity:.4}}
@keyframes fadein{from{opacity:0;transform:translateY(6px)}to{opacity:1;transform:none}}
@keyframes slideUp{from{transform:translateY(100%);opacity:0}to{transform:none;opacity:1}}

/* ── HEADER ── */
.app-header{
  height:var(--header-h);
  background:linear-gradient(135deg,var(--bg2),var(--bg3));
  border-bottom:1px solid var(--border);
  display:flex;align-items:center;justify-content:space-between;
  padding:0 16px;position:sticky;top:0;left:0;right:0;z-index:200;
  box-shadow:0 2px 20px rgba(0,0,0,.25);
  transition:background .25s,border-color .25s;
}
.hdr-brand{display:flex;align-items:center;gap:10px;min-width:0;}
.hdr-logo{
  flex-shrink:0;width:32px;height:32px;
  background:linear-gradient(135deg,var(--accent),#0284c7);
  border-radius:7px;display:flex;align-items:center;justify-content:center;
  font-size:13px;font-weight:700;color:#fff;
  box-shadow:0 0 14px rgba(79,195,247,.3);
}
.hdr-titles{min-width:0;}
.hdr-title{font-family:'Noto Serif JP',serif;font-size:14px;font-weight:700;letter-spacing:.05em;white-space:nowrap;overflow:hidden;text-overflow:ellipsis;}
.hdr-sub{font-size:9px;color:var(--text2);margin-top:1px;display:none;}
.hdr-right{display:flex;align-items:center;gap:8px;flex-shrink:0;}
.ym-badge{font-family:'IBM Plex Mono',monospace;font-size:10px;color:var(--text2);background:var(--bg3);border:1px solid var(--border);padding:3px 10px;border-radius:5px;white-space:nowrap;}
.status-pill{display:flex;align-items:center;gap:5px;background:rgba(52,211,153,.1);border:1px solid rgba(52,211,153,.3);border-radius:20px;padding:3px 10px;font-size:10px;color:var(--success);white-space:nowrap;}
.status-pill.loading{background:rgba(251,191,36,.1);border-color:rgba(251,191,36,.3);color:var(--warn);}
.status-pill.idle{background:rgba(100,116,139,.1);border-color:rgba(100,116,139,.3);color:var(--text3);}
.s-dot{width:6px;height:6px;border-radius:50%;background:var(--success);box-shadow:0 0 5px var(--success);animation:pulse 2s infinite;flex-shrink:0;}
.status-pill.loading .s-dot,.status-pill.idle .s-dot{background:var(--text3);box-shadow:none;animation:none;}
/* theme toggle */
.theme-btn{background:var(--bg3);border:1px solid var(--border);color:var(--text2);border-radius:6px;padding:4px 10px;font-size:15px;transition:.15s;}
.theme-btn:hover{color:var(--text);border-color:var(--accent);}
/* hamburger */
.hbg{display:none;flex-direction:column;gap:5px;background:none;border:none;padding:6px;}
.hbg span{display:block;width:20px;height:2px;background:var(--text2);border-radius:2px;transition:.2s;}
.hbg.open span:nth-child(1){transform:rotate(45deg) translate(5px,5px);}
.hbg.open span:nth-child(2){opacity:0;}
.hbg.open span:nth-child(3){transform:rotate(-45deg) translate(5px,-5px);}

/* ── LAYOUT ── */
/* Shiny用: fixed layoutは使わず min-heightベースで展開 */
.app-body{display:grid;grid-template-columns:var(--sidebar-w) 1fr;min-height:calc(100vh - var(--header-h));}

/* ── SIDEBAR ── */
.sidebar{background:var(--bg2);border-right:1px solid var(--border);padding:16px 0;overflow-y:auto;min-height:calc(100vh - var(--header-h));transition:background .25s,border-color .25s;}
.sb-section{margin-bottom:6px;}
.sb-label{padding:4px 16px 2px;font-size:9px;font-weight:700;color:var(--text3);text-transform:uppercase;letter-spacing:.12em;}
.sb-item{display:flex;align-items:center;gap:9px;padding:8px 16px;cursor:pointer;border-left:2px solid transparent;transition:.15s;font-size:12px;color:var(--text2);user-select:none;}
.sb-item:hover{background:rgba(79,195,247,.04);color:var(--text);}
.sb-item.active{background:rgba(79,195,247,.08);border-left-color:var(--accent);color:var(--text);}
.sb-icon{font-size:14px;width:18px;text-align:center;}
.sb-divider{height:1px;background:var(--border);margin:8px 16px;}
.upload-zone{margin:8px 12px;border:1.5px dashed var(--border);border-radius:8px;padding:14px 8px;text-align:center;cursor:pointer;transition:.2s;color:var(--text3);font-size:11px;line-height:1.9;}
.upload-zone:hover,.upload-zone.drag{border-color:var(--accent);color:var(--accent);background:rgba(79,195,247,.04);}
.demo-info{padding:6px 16px;font-size:10px;color:var(--text3);line-height:1.8;}

/* ── MAIN ── */
.main{padding:24px 20px 60px;}
.page{display:none;}
.page.active{display:block;animation:fadein .2s ease;}

/* ── SECTION HEADER ── */
.sec-hdr{display:flex;align-items:center;justify-content:space-between;margin-bottom:18px;flex-wrap:wrap;gap:8px;}
.sec-title{font-family:'Noto Serif JP',serif;font-size:17px;font-weight:700;display:flex;align-items:center;gap:8px;}
.sec-badge{font-size:10px;font-weight:600;padding:2px 8px;border-radius:4px;background:rgba(79,195,247,.15);color:var(--accent);border:1px solid rgba(79,195,247,.3);letter-spacing:.04em;}
.sec-badge.demo{background:rgba(124,58,237,.15);color:#a78bfa;border-color:rgba(124,58,237,.3);}

/* ── KPI GRID ── */
.kgrid{display:grid;gap:12px;margin-bottom:18px;}
.g4{grid-template-columns:repeat(4,1fr);}
.g3{grid-template-columns:repeat(3,1fr);}
.g2{grid-template-columns:repeat(2,1fr);}
.kpi{background:var(--bg2);border:1px solid var(--border);border-radius:var(--r);padding:14px 16px;position:relative;overflow:hidden;transition:transform .15s,box-shadow .15s;}
.kpi:hover{transform:translateY(-2px);box-shadow:var(--shadow);}
.kpi::before{content:'';position:absolute;top:0;left:0;right:0;height:2px;}
.k-accent::before{background:var(--accent);}
.k-success::before{background:var(--success);}
.k-gold::before{background:var(--gold);}
.k-warn::before{background:var(--warn);}
.k-danger::before{background:var(--danger);}
.k-purple::before{background:var(--purple);}
.kpi-icon{font-size:18px;margin-bottom:5px;}
.kpi-lbl{font-size:9px;color:var(--text2);text-transform:uppercase;letter-spacing:.08em;margin-bottom:3px;}
.kpi-val{font-family:'IBM Plex Mono',monospace;font-size:20px;font-weight:600;letter-spacing:-.5px;line-height:1.2;}
.kpi-sub{font-size:10px;color:var(--text2);margin-top:3px;}

/* ── TOTAL STRIP ── */
.total-strip{background:linear-gradient(135deg,rgba(79,195,247,.08),rgba(124,58,237,.08));border:1px solid rgba(79,195,247,.2);border-radius:var(--r);padding:18px 22px;display:flex;align-items:center;justify-content:space-between;margin-bottom:18px;gap:12px;flex-wrap:wrap;}
.ts-lbl{font-family:'Noto Serif JP',serif;font-size:13px;font-weight:700;color:var(--text2);}
.ts-ann{font-size:11px;color:var(--text3);margin-top:2px;}
.ts-right{display:flex;align-items:baseline;gap:4px;}
.ts-val{font-family:'IBM Plex Mono',monospace;font-size:34px;font-weight:600;color:var(--accent);letter-spacing:-1px;}
.ts-unit{font-size:13px;color:var(--text2);}

/* ── CARD ── */
.card{background:var(--bg2);border:1px solid var(--border);border-radius:var(--r);padding:18px;margin-bottom:16px;box-shadow:0 2px 10px rgba(0,0,0,.15);}
.card-title{font-family:'Noto Serif JP',serif;font-size:12px;font-weight:700;color:var(--text2);margin-bottom:14px;padding-bottom:10px;border-bottom:1px solid var(--border);display:flex;align-items:center;gap:7px;}
.grid-2{display:grid;grid-template-columns:1fr 1fr;gap:16px;}

/* ── TABLE ── */
.tbl-wrap{overflow-x:auto;}
table{width:100%;border-collapse:collapse;font-size:12px;}
th{background:var(--bg3);padding:8px 12px;text-align:right;font-weight:600;color:var(--text2);font-size:10px;border-bottom:1px solid var(--border);white-space:nowrap;letter-spacing:.03em;}
th:first-child{text-align:left;}
td{padding:7px 12px;border-bottom:1px solid rgba(42,53,80,.5);text-align:right;font-family:'IBM Plex Mono',monospace;font-size:12px;}
td.lc{text-align:left;font-family:'Noto Sans JP',sans-serif;color:var(--text2);}
tr:hover td{background:rgba(255,255,255,.015);}
.pos{color:var(--success);}
.neg{color:var(--danger);}
.gld{color:var(--gold);}
.b{font-weight:700;}

/* ── UPLOAD BANNER ── */
.upload-banner{background:var(--bg2);border:1px solid var(--border);border-radius:var(--r);padding:40px 24px;text-align:center;margin-bottom:20px;}
.upload-banner .big-ico{font-size:52px;margin-bottom:14px;}
.upload-banner h2{font-family:'Noto Serif JP',serif;font-size:17px;margin-bottom:8px;}
.upload-banner p{font-size:12px;color:var(--text2);margin-bottom:20px;line-height:1.9;}
.btn-row{display:flex;gap:12px;justify-content:center;flex-wrap:wrap;}
.btn-primary{display:inline-flex;align-items:center;gap:6px;background:linear-gradient(135deg,var(--accent),#0284c7);color:#fff;font-weight:700;font-size:13px;padding:10px 24px;border-radius:8px;border:none;box-shadow:0 4px 14px rgba(79,195,247,.3);transition:opacity .15s,transform .15s;cursor:pointer;}
.btn-primary:hover{opacity:.85;transform:translateY(-1px);}
.btn-demo{display:inline-flex;align-items:center;gap:6px;background:linear-gradient(135deg,#7c3aed,#4c1d95);color:#fff;font-weight:700;font-size:13px;padding:10px 24px;border-radius:8px;border:none;box-shadow:0 4px 14px rgba(124,58,237,.35);transition:opacity .15s,transform .15s;cursor:pointer;}
.btn-demo:hover{opacity:.85;transform:translateY(-1px);}
.btn-demo-sb{display:block;width:calc(100% - 24px);margin:6px 12px 0;background:rgba(124,58,237,.15);border:1px solid rgba(124,58,237,.4);color:#a78bfa;font-size:11px;font-weight:700;padding:8px;border-radius:7px;cursor:pointer;transition:.15s;text-align:center;}
.btn-demo-sb:hover{background:rgba(124,58,237,.25);color:#c4b5fd;}

/* ── CONTROL PANEL ── */
.ctrl-panel{background:var(--bg2);border:1px solid var(--border);border-radius:var(--r);padding:14px 16px;margin-bottom:16px;}
.ctrl-panel label{font-size:11px;color:var(--text2);display:block;margin-bottom:4px;}
.ctrl-panel select,.ctrl-panel input[type=checkbox]{accent-color:var(--accent);}
.ctrl-panel select{background:var(--bg3);color:var(--text);border:1px solid var(--border);border-radius:5px;padding:5px 8px;font-size:12px;width:100%;}
.ctrl-row{display:grid;grid-template-columns:1fr 1fr;gap:12px;align-items:end;}

/* ── REPORT MODAL ── */
.modal-overlay{display:none;position:fixed;inset:0;z-index:500;background:rgba(0,0,0,.7);backdrop-filter:blur(4px);align-items:flex-end;justify-content:center;}
.modal-overlay.open{display:flex;}
.modal{background:var(--bg2);border:1px solid var(--border);border-radius:16px 16px 0 0;width:100%;max-width:680px;max-height:92vh;display:flex;flex-direction:column;animation:slideUp .3s cubic-bezier(.25,.8,.25,1);box-shadow:0 -8px 40px rgba(0,0,0,.6);}
.modal-header{display:flex;align-items:center;justify-content:space-between;padding:16px 20px;border-bottom:1px solid var(--border);}
.modal-title{font-family:'Noto Serif JP',serif;font-size:15px;font-weight:700;}
.modal-close{background:var(--bg3);border:1px solid var(--border);color:var(--text2);border-radius:6px;padding:5px 10px;font-size:18px;line-height:1;cursor:pointer;transition:.15s;}
.modal-close:hover{color:var(--text);}
.modal-body{overflow-y:auto;padding:20px;flex:1;}
.modal-footer{padding:14px 20px;border-top:1px solid var(--border);display:flex;gap:10px;justify-content:flex-end;flex-wrap:wrap;}

/* ── REPORT PREVIEW ── */
.rpt-preview{background:#fff;color:#1a1a2e;border-radius:8px;padding:28px 24px;font-family:'Noto Sans JP',sans-serif;font-size:12px;line-height:1.8;}
.rpt-preview h1{font-family:'Noto Serif JP',serif;font-size:18px;font-weight:700;color:#0f172a;border-bottom:2px solid #1a4480;padding-bottom:8px;margin-bottom:16px;}
.rpt-preview h2{font-family:'Noto Serif JP',serif;font-size:13px;font-weight:700;color:#1a4480;margin:18px 0 8px;padding-left:10px;border-left:3px solid #4fc3f7;}
.rpt-meta{font-size:11px;color:#64748b;margin-bottom:20px;}
.rpt-kpi-row{display:grid;grid-template-columns:repeat(4,1fr);gap:10px;margin:12px 0;}
.rpt-kpi{background:#f8fafc;border:1px solid #e2e8f0;border-radius:6px;padding:10px 12px;text-align:center;}
.rpt-kpi .rk-lbl{font-size:10px;color:#64748b;margin-bottom:3px;}
.rpt-kpi .rk-val{font-family:'IBM Plex Mono',monospace;font-size:13px;font-weight:700;color:#0f172a;}
.rpt-tbl{width:100%;border-collapse:collapse;margin:8px 0 14px;font-size:11px;}
.rpt-tbl th{background:#1a4480;color:#fff;padding:6px 10px;text-align:left;font-size:10px;}
.rpt-tbl th:not(:first-child){text-align:right;}
.rpt-tbl td{padding:5px 10px;border-bottom:1px solid #e2e8f0;}
.rpt-tbl td:not(:first-child){text-align:right;font-family:'IBM Plex Mono',monospace;}
.rpt-tbl tr:nth-child(even) td{background:#f8fafc;}
.rpt-tbl .tot td{font-weight:700;background:#dbeafe!important;}
.rpt-note{background:#f0f9ff;border:1px solid #bae6fd;border-radius:6px;padding:10px 12px;font-size:10px;color:#0369a1;margin-top:10px;line-height:1.8;}
.btn-dl{display:inline-flex;align-items:center;gap:6px;background:linear-gradient(135deg,var(--success),#059669);color:#fff;font-weight:700;font-size:12px;padding:9px 20px;border-radius:8px;border:none;box-shadow:0 3px 10px rgba(52,211,153,.3);cursor:pointer;transition:.15s;}
.btn-dl:hover{opacity:.85;}
.btn-sec{background:var(--bg3);color:var(--text2);border:1px solid var(--border);font-size:12px;padding:9px 16px;border-radius:8px;cursor:pointer;transition:.15s;}
.btn-sec:hover{color:var(--text);}

/* ── BOTTOM NAV (mobile) ── */
.bottom-nav{display:none;position:fixed;bottom:0;left:0;right:0;height:var(--bottom-h);background:var(--bg2);border-top:1px solid var(--border);z-index:199;align-items:stretch;}
.bn-item{flex:1;display:flex;flex-direction:column;align-items:center;justify-content:center;gap:3px;cursor:pointer;color:var(--text3);font-size:9px;transition:.15s;border-top:2px solid transparent;user-select:none;}
.bn-item:hover{color:var(--text2);}
.bn-item.active{color:var(--accent);border-top-color:var(--accent);}
.bn-icon{font-size:18px;line-height:1;}
.drawer-overlay{display:none;position:fixed;inset:0;z-index:150;background:rgba(0,0,0,.6);}
.drawer-overlay.open{display:block;}

/* ── SCATTER CHECKBOXES ── */
.check-grid{display:grid;grid-template-columns:1fr 1fr;gap:4px 12px;padding:4px 0;}
.check-item{display:flex;align-items:center;gap:6px;font-size:11px;color:var(--text2);cursor:pointer;padding:2px 0;}
.check-item input{accent-color:var(--accent);}

/* ── RESPONSIVE ── */
@media (min-width:769px){.hdr-sub{display:block;}}
@media (max-width:768px){
  :root{--header-h:52px;}
  .sidebar{position:fixed;top:var(--header-h);left:0;bottom:0;width:240px;z-index:160;transform:translateX(-100%);transition:transform .25s cubic-bezier(.25,.8,.25,1);height:auto;overflow-y:auto;}
  .sidebar.open{transform:translateX(0);}
  .hbg{display:flex;}
  .ym-badge{display:none;}
  .app-body{grid-template-columns:1fr;min-height:calc(100vh - var(--header-h));}
  .main{padding:16px 14px calc(80px + var(--bottom-h));}
  .bottom-nav{display:flex;}
  .g4,.g3{grid-template-columns:repeat(2,1fr);}
  .grid-2{grid-template-columns:1fr;}
  .g2{grid-template-columns:1fr 1fr;}
  .kpi-val{font-size:17px;}
  .total-strip{flex-direction:column;align-items:flex-start;gap:6px;}
  .ts-val{font-size:26px;}
  .sec-title{font-size:15px;}
  .ctrl-row{grid-template-columns:1fr;}
  .rpt-kpi-row{grid-template-columns:1fr 1fr;}
}
@media (max-width:420px){
  .g4,.g3,.g2{grid-template-columns:1fr;}
  .kpi-val{font-size:20px;}
  .rpt-kpi-row{grid-template-columns:1fr;}
  .modal-footer{flex-direction:column;}
  .btn-dl,.btn-sec{width:100%;justify-content:center;text-align:center;}
  .check-grid{grid-template-columns:1fr;}
}

/* ── Shiny互換オーバーライド ── */
/* Shinyが生成するラッパー要素をリセット */
body > .container-fluid { padding:0 !important; margin:0 !important; }
.shiny-output-error { color:var(--danger); font-size:11px; padding:4px; }
.shiny-output-error-validation { color:var(--text3); font-size:11px; }
/* Shiny tab/panelのデフォルトスタイルを除去 */
.tab-content { background:transparent !important; border:none !important; padding:0 !important; }
.tabbable > .nav, .tabbable > .tab-content { display:none; }
/* ShinyのfluidPageラッパーを透明に */
body > div.container-fluid { background:transparent !important; }
"

# ──────────────────────────────────────────
#  UI
# ──────────────────────────────────────────
ui <- fluidPage(
  title = "経営指標分析ダッシュボード",
  tags$head(
    tags$meta(name="viewport", content="width=device-width, initial-scale=1.0, maximum-scale=1.0"),
    tags$style(HTML(dashboard_css)),
    tags$script(HTML("
      // ── navigation ──
      function nav(page) {
        document.querySelectorAll('.page').forEach(p=>p.classList.remove('active'));
        document.querySelectorAll('.sb-item').forEach(i=>i.classList.remove('active'));
        document.querySelectorAll('.bn-item').forEach(i=>i.classList.remove('active'));
        var el = document.getElementById('page-'+page);
        if(el) el.classList.add('active');
        var sb = document.getElementById('nav-'+page);
        if(sb) sb.classList.add('active');
        var bn = document.getElementById('bn-'+page);
        if(bn) bn.classList.add('active');
        closeSidebar();
        // Shinyに現在ページを通知
        Shiny.setInputValue('current_page', page, {priority:'event'});
        // Plotlyグラフをリサイズ（非表示->表示時の描画崩れを防ぐ）
        setTimeout(function(){
          if(window.Plotly){
            document.querySelectorAll('.js-plotly-plot').forEach(function(g){
              try{ Plotly.Plots.resize(g); }catch(e){}
            });
          }
        }, 80);
      }
      function toggleDrawer() {
        var sb=document.getElementById('sidebar');
        var hbg=document.getElementById('hbg');
        var ov=document.getElementById('d-overlay');
        sb.classList.toggle('open');
        hbg.classList.toggle('open');
        ov.classList.toggle('open');
      }
      function closeSidebar() {
        document.getElementById('sidebar').classList.remove('open');
        document.getElementById('hbg').classList.remove('open');
        document.getElementById('d-overlay').classList.remove('open');
      }
      function openReport() {
        document.getElementById('modal-overlay').classList.add('open');
        Shiny.setInputValue('open_report', Date.now(), {priority:'event'});
        closeSidebar();
      }
      function closeReport() {
        document.getElementById('modal-overlay').classList.remove('open');
      }
      // drag & drop
      function onDragOver(e){e.preventDefault();e.currentTarget.classList.add('drag');}
      function onDragLeave(e){e.currentTarget.classList.remove('drag');}
      function onDrop(e){
        e.preventDefault();e.currentTarget.classList.remove('drag');
        var f=e.dataTransfer.files[0];
        if(f){ injectFile(f); }
      }
      function injectFile(f){
        // Shiny の fileInput (input[type=file]) を探してファイルを注入
        var inp = document.querySelector('input[type=file]');
        if(!inp) inp = document.querySelector('input[type=file]');
        if(!inp) return;
        try {
          var dt = new DataTransfer();
          dt.items.add(f);
          inp.files = dt.files;
          inp.dispatchEvent(new Event('change', {bubbles:true}));
        } catch(err) {
          // DataTransfer非対応ブラウザへのフォールバック
          console.warn('Drag&drop not supported in this browser:', err);
        }
      }
      // theme
      function toggleTheme(){
        document.body.classList.toggle('dark');
        var isDark=document.body.classList.contains('dark');
        document.getElementById('theme-btn').textContent=isDark?'☀':'🌙';
        Shiny.setInputValue('theme_mode', isDark?'dark':'light');
      }
      // status
      function setStatus(txt,cls){
        var pill=document.getElementById('s-pill');
        var stxt=document.getElementById('s-txt');
        pill.className='status-pill '+cls;
        stxt.textContent=txt;
      }
      $(document).on('shiny:value', function(e){
        if(e.name==='status_text'){setStatus(e.value.text,e.value.cls);}
        if(e.name==='header_ym'){
          document.getElementById('hdr-ym').textContent=e.value;
          document.getElementById('sum-ym').textContent=e.value;
        }
      });
      // Shiny custom message handlers
      Shiny.addCustomMessageHandler('statusUpdate', function(d){setStatus(d.text, d.cls);});
      Shiny.addCustomMessageHandler('ymUpdate', function(v){
        var hym=document.getElementById('hdr-ym'); if(hym) hym.textContent=v;
        var sym=document.getElementById('sum-ym'); if(sym) sym.textContent=v;
      });
      // init
      $(function(){ nav('summary'); });
    "))
  ),

  # ── HEADER ──
  tags$header(class="app-header",
    tags$div(class="hdr-brand",
      tags$button(class="hbg", id="hbg", onclick="toggleDrawer()", `aria-label`="メニュー",
        tags$span(), tags$span(), tags$span()
      ),
      tags$div(class="hdr-logo", "KPI"),
      tags$div(class="hdr-titles",
        tags$div(class="hdr-title", "経営指標分析ダッシュボード"),
        tags$div(class="hdr-sub", "CSV アップロード → 自動集計・レポート生成")
      )
    ),
    tags$div(class="hdr-right",
      tags$span(class="ym-badge", id="hdr-ym", "— 未読込"),
      tags$button(class="theme-btn", id="theme-btn", onclick="toggleTheme()", "🌙"),
      tags$div(class="status-pill idle", id="s-pill",
        tags$div(class="s-dot"),
        tags$span(id="s-txt", "待機中")
      )
    )
  ),

  # ── DRAWER OVERLAY ──
  tags$div(class="drawer-overlay", id="d-overlay", onclick="closeSidebar()"),

  # ── APP BODY ──
  tags$div(class="app-body",

    # ── SIDEBAR ──
    tags$aside(class="sidebar", id="sidebar",
      tags$div(class="sb-section",
        tags$div(class="sb-label", "ページ"),
        tags$div(class="sb-item active", id="nav-summary",  onclick="nav('summary')",
          tags$span(class="sb-icon","📊"), "サマリー"),
        tags$div(class="sb-item", id="nav-timeseries", onclick="nav('timeseries')",
          tags$span(class="sb-icon","📈"), "時系列分析"),
        tags$div(class="sb-item", id="nav-correlation", onclick="nav('correlation')",
          tags$span(class="sb-icon","🔗"), "相関分析"),
        tags$div(class="sb-item", id="nav-regression", onclick="nav('regression')",
          tags$span(class="sb-icon","📉"), "回帰分析"),
        tags$div(class="sb-item", id="nav-scatter", onclick="nav('scatter')",
          tags$span(class="sb-icon","🔵"), "詳細散布図"),
        tags$div(class="sb-item", id="nav-stats", onclick="nav('stats')",
          tags$span(class="sb-icon","📋"), "統計サマリー"),
        tags$div(class="sb-item", id="nav-report-btn", onclick="openReport()",
          tags$span(class="sb-icon","📄"), "評価レポート")
      ),
      tags$div(class="sb-divider"),
      tags$div(class="sb-section",
        tags$div(class="sb-label", "データ読込"),
        tags$div(class="upload-zone", id="dz",
          onclick="(function(){var fi=document.querySelector('input[type=file]');if(fi)fi.click();})()",
          ondragover="onDragOver(event)", ondragleave="onDragLeave(event)", ondrop="onDrop(event)",
          tags$div(class="uz-ico", "📂"),
          "CSVをドロップ", tags$br(), "またはクリック"
        ),
        # fileInput を非表示で配置、upload-zone クリックで発火
        tags$div(style="display:none",
          fileInput("csv_file", NULL, accept=".csv")
        ),
        tags$script(HTML("
          // upload-zone クリックで Shiny の fileInput を開く
          document.addEventListener('DOMContentLoaded', function(){
            var dz = document.getElementById('dz');
            if(dz){
              dz.onclick = function(){
                var fi = document.querySelector('#csv_file + div input[type=file], input[id$=-csv_file]');
                if(!fi) fi = document.querySelector('input[type=file]');
                if(fi) fi.click();
              };
            }
          });
        ")),
        tags$button(class="btn-demo-sb",
          onclick="Shiny.setInputValue('load_demo',Math.random(),{priority:'event'})",
          "▶ デモデータで試す")
      ),
      tags$div(class="sb-divider"),
      tags$div(class="sb-section",
        tags$div(class="sb-label", "対応フォーマット"),
        tags$div(class="demo-info",
          "✦ 整備部門 (売上・原価・粗利・販管費・営業利益・KPI)", tags$br(),
          "✦ 商品部門 (売上・原価・粗利・販管費・営業利益)", tags$br(),
          "✦ 運送部門 (売上・原価・粗利・販管費・営業利益・KPI)", tags$br(),
          "✦ レンタル部門 (売上・原価・粗利・販管費・営業利益・KPI)"
        )
      )
    ),

    # ── MAIN ──
    tags$main(class="main", id="main-area",

      # ══ SUMMARY ══
      tags$div(class="page active", id="page-summary",
        uiOutput("summary_ui")
      ),

      # ══ TIME SERIES ══
      tags$div(class="page", id="page-timeseries",
        tags$div(class="sec-hdr",
          tags$div(class="sec-title", "📈 時系列分析", uiOutput("ts_badge")),
          tags$span(class="ym-badge", id="sum-ym", "—")
        ),
        tags$div(class="card",
          tags$div(class="card-title", "💹 各部門 営業利益推移"),
          plotlyOutput("ts_profit", height="280px")
        ),
        tags$div(class="card",
          tags$div(class="card-title", "💰 各部門 売上高推移"),
          plotlyOutput("ts_sales", height="280px")
        ),
        tags$div(class="card",
          tags$div(class="card-title", "📌 KPI推移"),
          plotlyOutput("ts_kpi", height="280px")
        )
      ),

      # ══ CORRELATION ══
      tags$div(class="page", id="page-correlation",
        tags$div(class="sec-hdr",
          tags$div(class="sec-title", "🔗 相関分析", uiOutput("corr_badge"))
        ),
        tags$div(class="grid-2",
          tags$div(class="card",
            tags$div(class="card-title", "🗺 相関係数ヒートマップ"),
            plotOutput("corr_heatmap", height="480px")
          ),
          tags$div(class="card",
            tags$div(class="card-title", "🏆 相関が強い組み合わせ Top10"),
            tags$div(class="tbl-wrap", tableOutput("corr_table"))
          )
        )
      ),

      # ══ REGRESSION ══
      tags$div(class="page", id="page-regression",
        tags$div(class="sec-hdr",
          tags$div(class="sec-title", "📉 回帰分析", uiOutput("reg_badge"))
        ),
        tags$div(class="ctrl-panel",
          tags$div(class="ctrl-row",
            tags$div(
              tags$label("説明変数（X）— KPI系"),
              selectInput("x_var", NULL, choices=c(
                "車検件数"         = "整備_KPI（一般車検件数）_実績_（単位：台）",
                "整備・板金数"     = "整備_KPI（整備・板金数）_実績_（単位：台）",
                "自社ドライバー数" = "運送_KPI（自社ドライバー数）_実績_（単位：台）",
                "他社ドライバー数" = "運送_KPI（他社ドライバー数）_実績_（単位：台）",
                "レンタル台数"     = "レンタル_KPI（レンタル台数）_実績_（単位：台）"
              ), selected="整備_KPI（一般車検件数）_実績_（単位：台）")
            ),
            tags$div(
              tags$label("被説明変数（Y）— 売上・利益系"),
              selectInput("y_var", NULL, choices=c(
                "整備_売上"         = "整備_実績_売上_（単位：円）",
                "整備_営業利益"     = "整備_実績_営業利益_（単位：円）",
                "商品_売上"         = "商品_実績_売上_（単位：円）",
                "商品_営業利益"     = "商品_実績_営業利益_（単位：円）",
                "運送_売上"         = "運送_実績_売上_（単位：円）",
                "運送_営業利益"     = "運送_実績_営業利益_（単位：円）",
                "レンタル_売上"     = "レンタル_実績_売上_（単位：円）",
                "レンタル_営業利益" = "レンタル_実績_営業利益_（単位：円）"
              ), selected="整備_実績_売上_（単位：円）")
            )
          )
        ),
        tags$div(class="grid-2",
          tags$div(class="card",
            tags$div(class="card-title", "📊 散布図・回帰直線"),
            plotlyOutput("reg_scatter", height="300px")
          ),
          tags$div(class="card",
            tags$div(class="card-title", "📋 回帰分析結果"),
            verbatimTextOutput("reg_results")
          )
        )
      ),

      # ══ SCATTER ══
      tags$div(class="page", id="page-scatter",
        tags$div(class="sec-hdr",
          tags$div(class="sec-title", "🔵 詳細散布図行列", uiOutput("scat_badge"))
        ),
        tags$div(class="card",
          tags$div(class="card-title", "変数の選択"),
          uiOutput("scatter_checks")
        ),
        tags$div(class="card",
          tags$div(class="card-title", "🔵 散布図行列"),
          plotOutput("scatter_matrix", height="600px")
        )
      ),

      # ══ STATS ══
      tags$div(class="page", id="page-stats",
        tags$div(class="sec-hdr",
          tags$div(class="sec-title", "📋 統計サマリー", uiOutput("stats_badge"))
        ),
        tags$div(class="grid-2",
          tags$div(class="card",
            tags$div(class="card-title", "🔧 整備部門"),
            verbatimTextOutput("stats_seibitsubi")
          ),
          tags$div(class="card",
            tags$div(class="card-title", "🛒 商品部門"),
            verbatimTextOutput("stats_shohin")
          )
        ),
        tags$div(class="grid-2",
          tags$div(class="card",
            tags$div(class="card-title", "🚚 運送部門"),
            verbatimTextOutput("stats_unsou")
          ),
          tags$div(class="card",
            tags$div(class="card-title", "🚗 レンタル部門"),
            verbatimTextOutput("stats_rental")
          )
        )
      )
    ) # /main
  ), # /app-body

  # ── BOTTOM NAV (mobile) ──
  tags$nav(class="bottom-nav",
    tags$div(class="bn-item active", id="bn-summary", onclick="nav('summary')",
      tags$div(class="bn-icon","📊"), "サマリー"),
    tags$div(class="bn-item", id="bn-timeseries", onclick="nav('timeseries')",
      tags$div(class="bn-icon","📈"), "時系列"),
    tags$div(class="bn-item", id="bn-correlation", onclick="nav('correlation')",
      tags$div(class="bn-icon","🔗"), "相関"),
    tags$div(class="bn-item", id="bn-regression", onclick="nav('regression')",
      tags$div(class="bn-icon","📉"), "回帰"),
    tags$div(class="bn-item", id="bn-report-btn", onclick="openReport()",
      tags$div(class="bn-icon","📄"), "レポート")
  ),

  # ── REPORT MODAL ──
  tags$div(class="modal-overlay", id="modal-overlay",
    tags$div(class="modal",
      tags$div(class="modal-header",
        tags$div(class="modal-title", "📄 経営指標 評価レポート"),
        tags$button(class="modal-close", onclick="closeReport()", "✕")
      ),
      tags$div(class="modal-body",
        uiOutput("report_preview")
      ),
      tags$div(class="modal-footer",
        tags$button(class="btn-dl", onclick="window.print()", "🖨 印刷 / PDF保存"),
        tags$button(class="btn-sec", onclick="closeReport()", "閉じる")
      )
    )
  )
)

# ──────────────────────────────────────────
#  SERVER
# ──────────────────────────────────────────
server <- function(input, output, session) {

  # ── データ ──
  demo_data <- reactive({ load_demo() })

  uploaded_data <- reactive({
    req(input$csv_file)
    load_csv(input$csv_file$datapath)
  })

  # デモ切替フラグ
  use_demo <- reactiveVal(TRUE)
  observeEvent(input$load_demo, { use_demo(TRUE) })
  observeEvent(input$csv_file,  { use_demo(FALSE) })

  df <- reactive({
    if (use_demo()) {
      d <- demo_data()
      if (!is.null(d)) return(d)
    }
    uploaded_data()
  })

  is_demo <- reactive({ use_demo() && !is.null(demo_data()) })

  # ── ページ切替時の再描画トリガー ──
  # current_page が変わるたびに page_trigger をインクリメント
  page_trigger <- reactiveVal(0)
  observeEvent(input$current_page, {
    page_trigger(page_trigger() + 1)
  }, ignoreNULL = TRUE)

  # ── ステータス更新 ──
  observe({
    d <- df()
    if (!is.null(d)) {
      txt <- if (is_demo()) "デモデータ表示中" else "データ読込完了"
      cls <- if (is_demo()) "loading" else ""
      session$sendCustomMessage("statusUpdate", list(text=txt, cls=cls))
      latest_ym <- tail(d$年月, 1)
      session$sendCustomMessage("ymUpdate", latest_ym)
    }
  })

  # ── バッジ ──
  badge_ui <- function() {
    if (is_demo()) tags$span(class="sec-badge demo", "DEMO") else tags$span(class="sec-badge", "LIVE")
  }
  output$ts_badge     <- renderUI(badge_ui())
  output$corr_badge   <- renderUI(badge_ui())
  output$reg_badge    <- renderUI(badge_ui())
  output$scat_badge   <- renderUI(badge_ui())
  output$stats_badge  <- renderUI(badge_ui())

  # ── Helper ──
  get_numeric_cols <- function(d) {
    cols <- colnames(d)[colnames(d) != "年月"]
    cols[sapply(cols, function(c) is.numeric(d[[c]]))]
  }

  # ─────────────────────────────────────────
  #  SUMMARY
  # ─────────────────────────────────────────
  output$summary_ui <- renderUI({
    d <- df()
    if (is.null(d)) {
      return(tags$div(class="upload-banner",
        tags$div(class="big-ico","📈"),
        tags$h2("CSVをアップロードしてください"),
        tags$p("経営指標CSVをアップロードすると", tags$br(), "ダッシュボードが自動生成されます"),
        tags$div(class="btn-row",
          tags$button(class="btn-primary",
            onclick="(function(){var fi=document.querySelector('input[type=file]');if(fi)fi.click();})()",
            "📂 CSVを選択"),
          tags$button(class="btn-demo",
            onclick="Shiny.setInputValue('load_demo',Math.random(),{priority:'event'})",
            "▶ デモを見る")
        ),
        tags$div(style="margin-top:14px;font-size:10px;color:var(--text3)",
          "デモモードでサンプルデータを確認できます")
      ))
    }

    latest <- tail(d, 1)
    prev   <- if(nrow(d) >= 2) d[nrow(d)-1,] else latest
    total_sales   <- sum(latest$`整備_実績_売上_（単位：円）`,
                        latest$`商品_実績_売上_（単位：円）`,
                        latest$`運送_実績_売上_（単位：円）`,
                        latest$`レンタル_実績_売上_（単位：円）`, na.rm=TRUE)
    total_profit  <- sum(latest$`整備_実績_営業利益_（単位：円）`,
                        latest$`商品_実績_営業利益_（単位：円）`,
                        latest$`運送_実績_営業利益_（単位：円）`,
                        latest$`レンタル_実績_営業利益_（単位：円）`, na.rm=TRUE)
    prev_sales   <- sum(prev$`整備_実績_売上_（単位：円）`,
                       prev$`商品_実績_売上_（単位：円）`,
                       prev$`運送_実績_売上_（単位：円）`,
                       prev$`レンタル_実績_売上_（単位：円）`, na.rm=TRUE)
    prev_profit  <- sum(prev$`整備_実績_営業利益_（単位：円）`,
                       prev$`商品_実績_営業利益_（単位：円）`,
                       prev$`運送_実績_営業利益_（単位：円）`,
                       prev$`レンタル_実績_営業利益_（単位：円）`, na.rm=TRUE)

    diff_s <- total_sales  - prev_sales
    diff_p <- total_profit - prev_profit
    sign_s <- if(diff_s >= 0) "▲" else "▼"
    sign_p <- if(diff_p >= 0) "▲" else "▼"
    cls_s  <- if(diff_s >= 0) "pos" else "neg"
    cls_p  <- if(diff_p >= 0) "pos" else "neg"

    kpi_row <- function(icon, lbl, val, sub, cls) {
      tags$div(class=paste("kpi", cls),
        tags$div(class="kpi-icon", icon),
        tags$div(class="kpi-lbl", lbl),
        tags$div(class="kpi-val", val),
        tags$div(class="kpi-sub", sub)
      )
    }

    tagList(
      tags$div(class="sec-hdr",
        tags$div(class="sec-title", "📊 経営サマリー", badge_ui()),
        tags$span(class="ym-badge", id="sum-ym", tail(d$年月, 1))
      ),
      tags$div(class="total-strip",
        tags$div(
          tags$div(class="ts-lbl", "直近月 全部門 合計売上"),
          tags$div(class="ts-ann", paste0("前月比: ", sign_s, " ", fmt_yen(abs(diff_s))))
        ),
        tags$div(class="ts-right",
          tags$div(class="ts-val", fmt_yen(total_sales)),
          tags$div(class="ts-unit", "/ 月")
        )
      ),
      tags$div(class="kgrid g4",
        kpi_row("🔧", "整備_売上",
          fmt_yen(latest$`整備_実績_売上_（単位：円）`),
          paste0("営業利益: ", fmt_yen(latest$`整備_実績_営業利益_（単位：円）`)), "k-accent"),
        kpi_row("🛒", "商品_売上",
          fmt_yen(latest$`商品_実績_売上_（単位：円）`),
          paste0("営業利益: ", fmt_yen(latest$`商品_実績_営業利益_（単位：円）`)), "k-success"),
        kpi_row("🚚", "運送_売上",
          fmt_yen(latest$`運送_実績_売上_（単位：円）`),
          paste0("営業利益: ", fmt_yen(latest$`運送_実績_営業利益_（単位：円）`)), "k-gold"),
        kpi_row("🚗", "レンタル_売上",
          fmt_yen(latest$`レンタル_実績_売上_（単位：円）`),
          paste0("営業利益: ", fmt_yen(latest$`レンタル_実績_営業利益_（単位：円）`)), "k-purple")
      ),
      tags$div(class="total-strip",
        tags$div(
          tags$div(class="ts-lbl", "直近月 全部門 合計営業利益"),
          tags$div(class="ts-ann", paste0("前月比: ", sign_p, " ", fmt_yen(abs(diff_p))))
        ),
        tags$div(class="ts-right",
          tags$div(class="ts-val",
            style=if(total_profit < 0) "color:var(--danger)" else "",
            fmt_yen(total_profit)),
          tags$div(class="ts-unit", "/ 月")
        )
      ),
      tags$div(class="kgrid g4",
        kpi_row("📊", "車検件数",
          paste0(latest$`整備_KPI（一般車検件数）_実績_（単位：台）`, " 台"),
          "整備KPI", "k-accent"),
        kpi_row("🔩", "整備・板金数",
          paste0(latest$`整備_KPI（整備・板金数）_実績_（単位：台）`, " 台"),
          "整備KPI", "k-accent"),
        kpi_row("👤", "自社ドライバー数",
          paste0(latest$`運送_KPI（自社ドライバー数）_実績_（単位：台）`, " 名"),
          "運送KPI", "k-gold"),
        kpi_row("🚙", "レンタル台数",
          paste0(latest$`レンタル_KPI（レンタル台数）_実績_（単位：台）`, " 台"),
          "レンタルKPI", "k-purple")
      ),
      tags$div(class="card",
        tags$div(class="card-title", "📋 部門別 直近月 損益サマリー"),
        tags$div(class="tbl-wrap",
          tags$table(
            tags$thead(tags$tr(
              tags$th("部門"), tags$th("売上"), tags$th("原価"), tags$th("粗利"),
              tags$th("販管費"), tags$th("営業利益"), tags$th("粗利率")
            )),
            tags$tbody(
              do.call(tagList, lapply(
                list(
                  list("🔧 整備", "整備_実績_売上_（単位：円）","整備_実績_原価_（単位：円）","整備_実績_粗利_（単位：円）","整備_実績_販管費_（単位：円）","整備_実績_営業利益_（単位：円）"),
                  list("🛒 商品", "商品_実績_売上_（単位：円）","商品_実績_原価_（単位：円）","商品_実績_粗利_（単位：円）","商品_実績_販管費_（単位：円）","商品_実績_営業利益_（単位：円）"),
                  list("🚚 運送", "運送_実績_売上_（単位：円）","運送_実績_原価_（単位：円）","運送_実績_粗利_（単位：円）","運送_実績_販管費_（単位：円）","運送_実績_営業利益_（単位：円）"),
                  list("🚗 レンタル","レンタル_実績_売上_（単位：円）","レンタル_実績_原価_（単位：円）","レンタル_実績_粗利_（単位：円）","レンタル_実績_販管費_（単位：円）","レンタル_実績_営業利益_（単位：円）")
                ),
                function(row) {
                  s  <- as.numeric(latest[[row[[2]]]])
                  co <- as.numeric(latest[[row[[3]]]])
                  g  <- as.numeric(latest[[row[[4]]]])
                  sg <- as.numeric(latest[[row[[5]]]])
                  op <- as.numeric(latest[[row[[6]]]])
                  grate <- if (!is.na(s) && s != 0) paste0(round(g/s*100, 1), "%") else "—"
                  op_cls <- if (!is.na(op) && op < 0) "neg" else "pos"
                  tags$tr(
                    tags$td(class="lc b", row[[1]]),
                    tags$td(fmt_yen(s)),
                    tags$td(fmt_yen(co)),
                    tags$td(fmt_yen(g)),
                    tags$td(fmt_yen(sg)),
                    tags$td(class=op_cls, tags$b(fmt_yen(op))),
                    tags$td(class="gld", grate)
                  )
                }
              ))
            )
          )
        )
      )
    )
  })

  # ─────────────────────────────────────────
  #  TIME SERIES
  # ─────────────────────────────────────────
  ts_plot <- function(d, cols, label_map, title, ylab) {
    if (is.null(d)) return(NULL)
    long <- d %>% select(年月, all_of(cols)) %>%
      pivot_longer(-年月, names_to="部門", values_to="値") %>%
      mutate(部門 = label_map[部門])
    p <- ggplot(long, aes(x=factor(年月, levels=unique(年月)), y=値, color=部門, group=部門)) +
      geom_line(linewidth=1) + geom_point(size=2.5) +
      labs(title=title, x="年月", y=ylab, color="") +
      theme_minimal(base_size=11) +
      theme(axis.text.x=element_text(angle=45, hjust=1, size=9, colour="#475569"),
            axis.text.y=element_text(colour="#475569"),
            axis.title=element_text(colour="#475569"),
            plot.background=element_rect(fill="transparent", colour=NA),
            panel.background=element_rect(fill="transparent", colour=NA),
            legend.background=element_rect(fill="transparent", colour=NA),
            legend.text=element_text(colour="#0f172a"),
            panel.grid.major=element_line(colour="#e2e8f0"),
            panel.grid.minor=element_blank(),
            plot.title=element_text(hjust=.5, size=12, face="bold", colour="#0f172a"))
    ggplotly(p, tooltip=c("x","y","colour")) %>%
      layout(paper_bgcolor="rgba(0,0,0,0)", plot_bgcolor="rgba(0,0,0,0)",
             font=list(color="#475569"),
             legend=list(orientation="h", y=-0.25, font=list(color="#0f172a")))
  }

  profit_map <- c(
    "整備_実績_営業利益_（単位：円）"  = "整備",
    "商品_実績_営業利益_（単位：円）"  = "商品",
    "運送_実績_営業利益_（単位：円）"  = "運送",
    "レンタル_実績_営業利益_（単位：円）" = "レンタル"
  )
  sales_map <- c(
    "整備_実績_売上_（単位：円）"  = "整備",
    "商品_実績_売上_（単位：円）"  = "商品",
    "運送_実績_売上_（単位：円）"  = "運送",
    "レンタル_実績_売上_（単位：円）" = "レンタル"
  )
  kpi_map <- c(
    "整備_KPI（一般車検件数）_実績_（単位：台）" = "車検件数",
    "整備_KPI（整備・板金数）_実績_（単位：台）" = "整備・板金数",
    "運送_KPI（自社ドライバー数）_実績_（単位：台）" = "自社ドライバー数",
    "運送_KPI（他社ドライバー数）_実績_（単位：台）" = "他社ドライバー数",
    "レンタル_KPI（レンタル台数）_実績_（単位：台）" = "レンタル台数"
  )

  output$ts_profit <- renderPlotly({
    page_trigger()  # ページ切替時に再描画
    ts_plot(df(), names(profit_map), profit_map, "各部門 営業利益推移", "営業利益（円）")
  })
  output$ts_sales <- renderPlotly({
    page_trigger()
    ts_plot(df(), names(sales_map), sales_map, "各部門 売上高推移", "売上（円）")
  })
  output$ts_kpi <- renderPlotly({
    page_trigger()
    ts_plot(df(), names(kpi_map), kpi_map, "KPI推移", "件数 / 台数")
  })

  # ─────────────────────────────────────────
  #  CORRELATION
  # ─────────────────────────────────────────
  output$corr_heatmap <- renderPlot({
    page_trigger()
    d <- df()
    req(d)
    nd <- d %>% select(-年月) %>% select(where(is.numeric))
    nd <- nd[complete.cases(nd), ]
    req(nrow(nd) >= 3)
    cm <- cor(nd, use="complete.obs")
    cm[is.na(cm)] <- 0
    colnames(cm) <- rownames(cm) <- sapply(colnames(cm), short_label)
    par(bg="white", col.axis="#475569", col.lab="#475569", col.main="#0f172a")
    corrplot(cm, method="color", type="full",
             tl.cex=0.65, tl.col="#0f172a",
             addCoef.col="#0f172a", number.cex=0.5,
             col=colorRampPalette(c("#dc2626","#f8fafc","#059669"))(100),
             bg="white",
             title="相関係数ヒートマップ", mar=c(0,0,2,0))
  }, bg="white")

  output$corr_table <- renderTable({
    d <- df()
    req(d)
    nd <- d %>% select(-年月) %>% select(where(is.numeric))
    nd <- nd[complete.cases(nd), ]
    req(nrow(nd) >= 3)
    cm <- cor(nd, use="complete.obs")
    cm[is.na(cm)] <- 0
    ut <- upper.tri(cm)
    pairs <- data.frame(
      変数1 = sapply(rownames(cm)[row(cm)[ut]], short_label),
      変数2 = sapply(colnames(cm)[col(cm)[ut]], short_label),
      相関係数 = round(cm[ut], 3)
    ) %>% arrange(desc(abs(相関係数))) %>% head(10)
    pairs
  }, striped=TRUE, hover=TRUE, spacing="s")

  # ─────────────────────────────────────────
  #  REGRESSION
  # ─────────────────────────────────────────
  # x_var / y_var は静的selectInput → renderUI不要
  reg_data <- reactive({
    d <- df()
    req(d, input$x_var, input$y_var)
    xv <- input$x_var
    yv <- input$y_var
    if (!(xv %in% colnames(d)) || !(yv %in% colnames(d))) return(NULL)
    d %>%
      select(年月, X=all_of(xv), Y=all_of(yv)) %>%
      filter(!is.na(X), !is.na(Y), is.finite(X), is.finite(Y))
  })

  output$reg_scatter <- renderPlotly({
    page_trigger()
    rd <- reg_data()
    req(!is.null(rd), nrow(rd) >= 3)
    model <- lm(Y ~ X, data=rd)
    xl <- short_label(input$x_var)
    yl <- short_label(input$y_var)
    p <- ggplot(rd, aes(x=X, y=Y, text=paste0("年月: ", 年月))) +
      geom_point(size=3, color="#4fc3f7", alpha=.7) +
      geom_smooth(method="lm", se=TRUE, color="#f87171", fill="#f87171", alpha=.15) +
      labs(title=paste(yl, "vs", xl), x=xl, y=yl) +
      theme_minimal(base_size=11) +
      theme(plot.background=element_rect(fill="transparent", colour=NA),
            panel.background=element_rect(fill="transparent", colour=NA),
            axis.text=element_text(colour="#475569"),
            axis.title=element_text(colour="#475569"),
            plot.title=element_text(hjust=.5, size=12, face="bold", colour="#0f172a"),
            panel.grid.major=element_line(colour="#e2e8f0"),
            panel.grid.minor=element_blank())
    ggplotly(p, tooltip=c("text","x","y")) %>%
      layout(paper_bgcolor="rgba(0,0,0,0)", plot_bgcolor="rgba(0,0,0,0)",
             font=list(color="#475569"))
  })

  output$reg_results <- renderPrint({
    rd <- reg_data()
    req(!is.null(rd), nrow(rd) >= 3)
    model <- lm(Y ~ X, data=rd)
    xl <- short_label(input$x_var)
    yl <- short_label(input$y_var)
    cat(sprintf("回帰分析: %s ~ %s\n\n", yl, xl))
    s <- summary(model)
    cat(sprintf("切片 (β₀):     %s\n", format(coef(model)[1], big.mark=",", digits=6)))
    cat(sprintf("傾き (β₁):     %s\n", format(coef(model)[2], big.mark=",", digits=6)))
    cat(sprintf("決定係数 (R²): %.4f\n", s$r.squared))
    cat(sprintf("相関係数 (r):  %.4f\n", cor(rd$X, rd$Y)))
    cat(sprintf("p値:           %.4f\n", summary(model)$coefficients[2,4]))
    cat(sprintf("観測数:        %d\n", nrow(rd)))
    cat("\n── 詳細 ──\n")
    print(s)
  })

  # ─────────────────────────────────────────
  #  SCATTER
  # ─────────────────────────────────────────
  output$scatter_checks <- renderUI({
    d <- df()
    req(d)
    money_cols <- grep("売上|粗利|営業利益", colnames(d), value=TRUE)
    default_sel <- money_cols[seq_len(min(6, length(money_cols)))]
    choices <- setNames(money_cols, sapply(money_cols, short_label))
    tagList(
      tags$div(class="check-grid",
        checkboxGroupInput("scatter_sel", NULL,
          choices  = choices,
          selected = default_sel,
          inline   = FALSE
        )
      )
    )
  })

  scatter_selected <- reactive({
    req(input$scatter_sel)
    input$scatter_sel
  })

  output$scatter_matrix <- renderPlot({
    page_trigger()
    d <- df()
    req(d)
    sel <- tryCatch(scatter_selected(), error=function(e) NULL)
    if (is.null(sel) || length(sel) < 2) {
      par(bg="white", col.main="#0f172a")
      plot(1,1,type="n",xlab="",ylab="",main="2つ以上の変数を選択してください",
           col.main="#0f172a")
      return()
    }
    sd <- d %>% select(all_of(sel)) %>% select(where(is.numeric))
    sd <- sd[complete.cases(sd), ]
    req(nrow(sd) >= 3)
    colnames(sd) <- sapply(colnames(sd), short_label)
    par(bg="white", col.main="#0f172a", col.axis="#475569", col.lab="#475569")
    pairs(sd,
          col.axis = "#475569",
          panel=function(x, y, ...) {
            points(x, y, col="#4fc3f7", cex=.7, pch=16)
            abline(lm(y~x), col="#f87171", lty=2, lwd=1.5)
          },
          diag.panel=function(x, ...) {
            usr <- par("usr"); on.exit(par(usr))
            par(usr=c(usr[1:2], 0, 1.5))
            h <- hist(x, plot=FALSE)
            breaks <- h$breaks
            nB <- length(breaks)
            y <- h$counts; y <- y/max(y)
            rect(breaks[-nB], 0, breaks[-1], y, col="#34d399", border=NA)
          },
          main="散布図行列", col.main="#0f172a")
  }, bg="white")

  # ─────────────────────────────────────────
  #  STATS
  # ─────────────────────────────────────────
  make_stats <- function(dept_name, cols) {
    renderPrint({
      d <- df()
      req(d)
      cat(dept_name, "の基本統計量\n")
      cat(paste(rep("─", 30), collapse=""), "\n\n")
      for (col in cols) {
        if (col %in% colnames(d)) {
          cat(short_label(col), ":\n")
          print(summary(d[[col]]))
          cat("\n")
        }
      }
    })
  }

  output$stats_seibitsubi <- make_stats("整備部門", c(
    "整備_実績_売上_（単位：円）","整備_実績_原価_（単位：円）",
    "整備_実績_粗利_（単位：円）","整備_実績_営業利益_（単位：円）",
    "整備_KPI（一般車検件数）_実績_（単位：台）","整備_KPI（整備・板金数）_実績_（単位：台）"
  ))
  output$stats_shohin <- make_stats("商品部門", c(
    "商品_実績_売上_（単位：円）","商品_実績_原価_（単位：円）",
    "商品_実績_粗利_（単位：円）","商品_実績_営業利益_（単位：円）"
  ))
  output$stats_unsou <- make_stats("運送部門", c(
    "運送_実績_売上_（単位：円）","運送_実績_原価_（単位：円）",
    "運送_実績_粗利_（単位：円）","運送_実績_営業利益_（単位：円）",
    "運送_KPI（自社ドライバー数）_実績_（単位：台）","運送_KPI（他社ドライバー数）_実績_（単位：台）"
  ))
  output$stats_rental <- make_stats("レンタル部門", c(
    "レンタル_実績_売上_（単位：円）","レンタル_実績_原価_（単位：円）",
    "レンタル_実績_粗利_（単位：円）","レンタル_実績_営業利益_（単位：円）",
    "レンタル_KPI（レンタル台数）_実績_（単位：台）"
  ))

  # ─────────────────────────────────────────
  #  REPORT
  # ─────────────────────────────────────────
  output$report_preview <- renderUI({
    d <- df()
    if (is.null(d)) {
      return(tags$div(style="text-align:center;padding:40px;color:var(--text2)",
        "📊 データを読み込むとレポートが生成されます"))
    }

    latest  <- tail(d, 1)
    period  <- paste0(head(d$年月, 1), " 〜 ", tail(d$年月, 1))
    months  <- nrow(d)

    dept_rows <- list(
      list("整備",   "整備_実績_売上_（単位：円）","整備_実績_粗利_（単位：円）","整備_実績_販管費_（単位：円）","整備_実績_営業利益_（単位：円）"),
      list("商品",   "商品_実績_売上_（単位：円）","商品_実績_粗利_（単位：円）","商品_実績_販管費_（単位：円）","商品_実績_営業利益_（単位：円）"),
      list("運送",   "運送_実績_売上_（単位：円）","運送_実績_粗利_（単位：円）","運送_実績_販管費_（単位：円）","運送_実績_営業利益_（単位：円）"),
      list("レンタル","レンタル_実績_売上_（単位：円）","レンタル_実績_粗利_（単位：円）","レンタル_実績_販管費_（単位：円）","レンタル_実績_営業利益_（単位：円）")
    )

    total_s  <- sum(sapply(dept_rows, function(r) as.numeric(latest[[r[[2]]]]) ), na.rm=TRUE)
    total_op <- sum(sapply(dept_rows, function(r) as.numeric(latest[[r[[5]]]]) ), na.rm=TRUE)
    op_margin <- if (!is.na(total_s) && total_s != 0) round(total_op/total_s*100, 1) else NA

    # avg profit trend
    avg_profit_cols <- sapply(dept_rows, function(r) r[[5]])
    avg_profits <- sapply(avg_profit_cols, function(col) mean(d[[col]], na.rm=TRUE))
    best_dept <- names(which.max(avg_profits))
    best_dept_lbl <- gsub("_実績_営業利益.*","",best_dept)

    rpt_tbl_rows <- do.call(tagList, lapply(dept_rows, function(r) {
      s  <- as.numeric(latest[[r[[2]]]])
      g  <- as.numeric(latest[[r[[3]]]])
      sg <- as.numeric(latest[[r[[4]]]])
      op <- as.numeric(latest[[r[[5]]]])
      op_cls <- if (!is.na(op) && op < 0) "style='color:#dc2626'" else "style='color:#059669'"
      tags$tr(
        tags$td(r[[1]]),
        tags$td(fmt_yen(s)),
        tags$td(fmt_yen(g)),
        tags$td(fmt_yen(sg)),
        tags$td(HTML(paste0("<span ", op_cls, "><b>", fmt_yen(op), "</b></span>")))
      )
    }))

    tags$div(class="rpt-preview",
      tags$h1("経営指標 評価レポート"),
      tags$div(class="rpt-meta",
        paste0("対象期間: ", period, "　（", months, "ヶ月）　"),
        tags$br(),
        paste0("出力日時: ", format(Sys.time(), "%Y年%m月%d日 %H:%M")),
        if (is_demo()) tags$span(style="margin-left:8px;background:#fef3c7;color:#d97706;padding:1px 8px;border-radius:4px;font-size:10px;", "DEMO DATA")
      ),
      tags$div(class="rpt-kpi-row",
        tags$div(class="rpt-kpi", tags$div(class="rk-lbl","合計売上"), tags$div(class="rk-val", fmt_yen(total_s))),
        tags$div(class="rpt-kpi", tags$div(class="rk-lbl","合計営業利益"), tags$div(class="rk-val", fmt_yen(total_op))),
        tags$div(class="rpt-kpi", tags$div(class="rk-lbl","営業利益率"), tags$div(class="rk-val", if(!is.na(op_margin)) paste0(op_margin, "%") else "—")),
        tags$div(class="rpt-kpi", tags$div(class="rk-lbl","分析期間"), tags$div(class="rk-val", paste0(months, " ヶ月")))
      ),
      tags$h2("直近月 部門別損益"),
      tags$table(class="rpt-tbl",
        tags$thead(tags$tr(
          tags$th("部門"), tags$th("売上"), tags$th("粗利"), tags$th("販管費"), tags$th("営業利益")
        )),
        tags$tbody(rpt_tbl_rows,
          tags$tr(class="tot",
            tags$td("合計"),
            tags$td(fmt_yen(total_s)),
            tags$td("—"), tags$td("—"),
            tags$td(fmt_yen(total_op))
          )
        )
      ),
      tags$h2("KPI 直近月"),
      tags$table(class="rpt-tbl",
        tags$thead(tags$tr(tags$th("KPI指標"), tags$th("直近月値"))),
        tags$tbody(
          tags$tr(tags$td("車検件数"), tags$td(paste0(latest$`整備_KPI（一般車検件数）_実績_（単位：台）`, " 台"))),
          tags$tr(tags$td("整備・板金数"), tags$td(paste0(latest$`整備_KPI（整備・板金数）_実績_（単位：台）`, " 台"))),
          tags$tr(tags$td("自社ドライバー数"), tags$td(paste0(latest$`運送_KPI（自社ドライバー数）_実績_（単位：台）`, " 名"))),
          tags$tr(tags$td("他社ドライバー数"), tags$td(paste0(latest$`運送_KPI（他社ドライバー数）_実績_（単位：台）`, " 名"))),
          tags$tr(tags$td("レンタル台数"), tags$td(paste0(latest$`レンタル_KPI（レンタル台数）_実績_（単位：台）`, " 台")))
        )
      ),
      tags$h2("分析コメント"),
      tags$div(class="rpt-note",
        tags$b("■ 売上状況: "),
        paste0("直近月の全部門合計売上は ", fmt_yen(total_s), "。"),
        tags$br(),
        tags$b("■ 収益性: "),
        paste0("全部門合計営業利益は ", fmt_yen(total_op), "（営業利益率: ",
               if(!is.na(op_margin)) paste0(op_margin, "%") else "計算不可", "）。"),
        tags$br(),
        tags$b("■ 部門評価: "),
        paste0("分析期間中、平均営業利益が最も高い部門は ", best_dept_lbl, " 部門。"),
        tags$br(),
        tags$b("■ データ期間: "), paste0(period, "（計 ", months, "ヶ月）のデータを使用。")
      )
    )
  })

  # ─────────────────────────────────────────
  #  非表示ページも常にレンダリング
  #  (display:none のページでも描画を維持)
  # ─────────────────────────────────────────
  outputOptions(output, "ts_profit",      suspendWhenHidden = FALSE)
  outputOptions(output, "ts_sales",       suspendWhenHidden = FALSE)
  outputOptions(output, "ts_kpi",         suspendWhenHidden = FALSE)
  outputOptions(output, "corr_heatmap",   suspendWhenHidden = FALSE)
  outputOptions(output, "corr_table",     suspendWhenHidden = FALSE)
  outputOptions(output, "reg_scatter",    suspendWhenHidden = FALSE)
  outputOptions(output, "reg_results",    suspendWhenHidden = FALSE)
  outputOptions(output, "scatter_matrix", suspendWhenHidden = FALSE)
  outputOptions(output, "scatter_checks", suspendWhenHidden = FALSE)
  outputOptions(output, "stats_seibitsubi", suspendWhenHidden = FALSE)
  outputOptions(output, "stats_shohin",   suspendWhenHidden = FALSE)
  outputOptions(output, "stats_unsou",    suspendWhenHidden = FALSE)
  outputOptions(output, "stats_rental",   suspendWhenHidden = FALSE)
  outputOptions(output, "summary_ui",     suspendWhenHidden = FALSE)
  outputOptions(output, "report_preview", suspendWhenHidden = FALSE)
}

shinyApp(ui = ui, server = server)