src/data.py

# data.py
import pandas as pd

# --- 1. 群組去識別化 (僅保留 K13R - Cyber，其餘改為抽象代號) ---
GROUPS = [
    'K13R - Cyber', 
    'Team Alpha', 'Team Beta', 'Hub-04 (Ops)', 
    'Hub-09 (Tech)', 'Project Nexus', 'Division X', 
    'Core Node', 'Aura Analytics', 'Echo Admin'
]

DIFFICULTY_LABELS = {
    'L1': 'L1 - 基礎支援', 'L2': 'L2 - 專業技能', 
    'L3': 'L3 - 高專業顧問', 'L4': 'L4 - 關鍵專案支援'
}

# --- 2. 使用者去識別化 (主角設定為 TonTon Huang) ---
current_user = {
    "id": "u1", 
    "name": "TonTon Huang", 
    "group": "K13R - Cyber", 
    "title": "Senior Manager",
    "skills": ["Cybersecurity", "Risk Management", "Project Governance", "ISO 27001"],
    "points": 3500, "activeTasks": 2, "completedTasks": 42, "monthlyCollabs": 10, 
    "role": "MANAGER", "avatar": None
}

mock_users = [
    {"id": "u2", "name": "Alex C.", "group": "Echo Admin", "title": "Coordinator", "matchRate": 95, "avatar": None},
    {"id": "u3", "name": "Morgan D.", "group": "Project Nexus", "title": "Level 3 Lead", "matchRate": 93, "avatar": None},
    {"id": "u4", "name": "Taylor S.", "group": "Hub-09 (Tech)", "title": "Specialist", "matchRate": 84, "avatar": None},
    {"id": "u5", "name": "Jordan L.", "group": "Aura Analytics", "title": "Level 2 Expert", "matchRate": 78, "avatar": None}
]

# --- 3. 任務資料去識別化 ---
mock_tasks = [
    {"id": "t1", "title": "春酒活動攝影支援", "publisherGroup": "Echo Admin", "type": "INTERNAL", "difficulty": "L1", "skillsRequired": ["Photography", "Event Shooting", "Photo Editing"], "points": 50, "status": "PUBLISHED", "applicantsCount": 3, "aiTags": ["#攝影愛好者", "#活動紀錄"], "description": "公司春酒活動希望邀請對攝影有興趣的同仁共同參與活動紀錄..."},
    {"id": "t2", "title": "內部風險小教室講師支援", "publisherGroup": "Division X", "type": "INTERNAL", "difficulty": "L2", "skillsRequired": ["Risk Awareness", "Public Speaking", "Compliance"], "points": 80, "status": "PUBLISHED", "applicantsCount": 1, "aiTags": ["#知識共享", "#風險管理"], "description": "各組 Leader 可發起內部小教室分享..."},
    {"id": "t3", "title": "ISO 27001 & ISO27701 稽核專案支援", "publisherGroup": "K13R - Cyber", "type": "EXTERNAL", "difficulty": "L4", "skillsRequired": ["ISO 27001", "ISO 27701", "資安稽核"], "points": 300, "status": "PUBLISHED", "applicantsCount": 0, "aiTags": ["#資安專家", "#關鍵專案"], "description": "高難度資安稽核專案，需支援多場次稽核..."},
    {"id": "t4", "title": "海外市場調查分析專案", "publisherGroup": "Project Nexus", "type": "EXTERNAL", "difficulty": "L3", "skillsRequired": ["海外市場研究", "產業資料蒐集", "簡報整理"], "points": 180, "status": "PUBLISHED", "applicantsCount": 2, "aiTags": ["#市場研究", "#海外專案"], "description": "針對新興市場進行深度產業分析..."},
    {"id": "t5", "title": "跨國企業併購專案支援", "publisherGroup": "Team Alpha", "type": "EXTERNAL", "difficulty": "L4", "skillsRequired": ["跨國企業研究", "交易案例蒐集", "外語閱讀"], "points": 500, "status": "PUBLISHED", "applicantsCount": 5, "aiTags": ["#併購研究", "#外語能力"], "description": "大型跨國併購專案支援..."},
    {"id": "t6", "title": "永續指標 Dashboard 製作", "publisherGroup": "Aura Analytics", "type": "EXTERNAL", "difficulty": "L2", "skillsRequired": ["Power BI", "資料視覺化", "數據整理"], "points": 150, "status": "PUBLISHED", "applicantsCount": 4, "aiTags": ["#資料視覺化", "#永續數據"], "description": "將指標轉化為直觀的視覺化圖表..."}
]

# --- 4. Dashboard & Analytics 圖表資料去識別化 ---
dashboard_trend_data = pd.DataFrame({
    "月份": ["1月", "2月", "3月", "4月", "5月"],
    "協作次數": [2, 5, 3, 8, 4]
}).set_index("月份")

group_collab_data = pd.DataFrame({
    "組別": ['K13R', 'Nexus', 'Hub-09', 'Alpha', 'Aura', 'Beta'],
    "內部協作": [400, 300, 200, 278, 189, 239],
    "支援他組": [240, 139, 980, 390, 480, 380]
}).set_index("組別")