219 lines
8.6 KiB
Python
219 lines
8.6 KiB
Python
#!/usr/bin/env python3
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"""
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图表 v2：L1付费用户 = 仅L1 + L1+L2，L2付费用户 = 仅L2 + L1+L2
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"""
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import psycopg2
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from collections import defaultdict
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from datetime import datetime, timedelta, date
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import matplotlib
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matplotlib.use('Agg')
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import matplotlib.pyplot as plt
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import matplotlib.dates as mdates
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import matplotlib.font_manager as fm
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import numpy as np
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fm.fontManager.addfont('/usr/share/fonts/opentype/noto/NotoSansCJK-Regular.ttc')
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plt.rcParams['font.family'] = fm.FontProperties(fname='/usr/share/fonts/opentype/noto/NotoSansCJK-Regular.ttc').get_name()
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plt.rcParams['axes.unicode_minus'] = False
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conn = psycopg2.connect(
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host="bj-postgres-16pob4sg.sql.tencentcdb.com",
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port=28591, user="ai_member",
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password="LdfjdjL83h3h3^$&**YGG*", dbname="vala_bi"
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)
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cur = conn.cursor()
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u0_chapters = {55, 56, 57, 58, 59, 343, 344, 345, 346, 348}
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overall_start = date(2025, 9, 1)
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overall_end = date(2026, 5, 11)
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weeks = []
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d = overall_start
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while d < overall_end:
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ws = d
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we = d + timedelta(days=6 - d.weekday())
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if we >= overall_end: we = overall_end - timedelta(days=1)
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weeks.append((ws, we))
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d = we + timedelta(days=1)
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print("分类付费用户...")
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cur.execute("""
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SELECT o.account_id, o.trade_no, o.order_status, o.pay_success_date,
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CASE WHEN o.goods_id IN (57, 60, 63) THEN 'L1'
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WHEN o.goods_id = 61 THEN 'L1+L2'
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WHEN o.goods_id IN (31, 32, 33, 54) THEN 'L2'
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ELSE '其他' END as level_type
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FROM bi_vala_order o
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INNER JOIN bi_vala_app_account a ON o.account_id = a.id
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WHERE a.status = 1 AND a.deleted_at IS NULL AND o.pay_success_date IS NOT NULL
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""")
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orders = cur.fetchall()
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cur.execute("SELECT trade_no FROM bi_refund_order WHERE status = 3")
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refund_trades = set(r[0] for r in cur.fetchall())
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user_levels = defaultdict(set)
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user_orders = defaultdict(list)
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for aid, trade_no, order_status, pay_date, lt in orders:
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is_refunded = (order_status == 4 and trade_no in refund_trades)
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user_levels[aid].add(lt)
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user_orders[aid].append((pay_date.date(), is_refunded))
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def is_paid(aid, as_of):
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return sum(1 for pd, ref in user_orders[aid] if pd <= as_of and not ref) > 0
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# 分组：L1群 = 仅L1 + L1+L2；L2群 = 仅L2 + L1+L2
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l1_group = set() # 买了L1的所有用户
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l2_group = set() # 买了L2的所有用户
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for aid, levels in user_levels.items():
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has_l1 = 'L1' in levels or 'L1+L2' in levels
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has_l2 = 'L2' in levels or 'L1+L2' in levels
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if has_l1: l1_group.add(aid)
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if has_l2: l2_group.add(aid)
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print(f"L1付费群: {len(l1_group)}人, L2付费群: {len(l2_group)}人, 重叠(L1+L2): {len(l1_group & l2_group)}人")
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print("查询课消...")
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cons_map = {}
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for ti in range(8):
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tbl = f"bi_user_chapter_play_record_{ti}"
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cur.execute(f"""SELECT user_id, chapter_id, updated_at FROM {tbl}
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WHERE play_status = 1 AND updated_at >= '2025-09-01' AND updated_at < '2026-05-11'""")
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for uid, cid, ua in cur.fetchall():
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if cid in u0_chapters: continue
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key = (uid, cid)
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d = ua.date() if hasattr(ua, 'date') else datetime.strptime(str(ua)[:10], '%Y-%m-%d').date()
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if key not in cons_map or d < cons_map[key]:
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cons_map[key] = d
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print("角色映射...")
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all_uids = list(set(k[0] for k in cons_map))
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char2acct = {}
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for i in range(0, len(all_uids), 500):
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batch = all_uids[i:i+500]
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ph = ','.join(['%s'] * len(batch))
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cur.execute(f"SELECT id, account_id FROM bi_vala_app_character WHERE id IN ({ph})", batch)
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for cid, aid in cur.fetchall(): char2acct[cid] = aid
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print("按周汇总...")
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results = []
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for ws, we in weeks:
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# 截至 we 的付费用户
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l1_paid = {aid for aid in l1_group if is_paid(aid, we)}
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l2_paid = {aid for aid in l2_group if is_paid(aid, we)}
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l1_cons, l1_cons_users = 0, set()
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l2_cons, l2_cons_users = 0, set()
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for (uid, ch_id), cons_date in cons_map.items():
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if ws <= cons_date <= we:
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aid = char2acct.get(uid)
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if not aid: continue
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if aid in l1_paid:
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l1_cons += 1
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l1_cons_users.add(aid)
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if aid in l2_paid:
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l2_cons += 1
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l2_cons_users.add(aid)
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results.append({
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'ws': ws, 'we': we,
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'L1_paid': len(l1_paid), 'L1_cons': l1_cons, 'L1_cons_users': len(l1_cons_users),
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'L1_no_cons': len(l1_paid) - len(l1_cons_users),
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'L1_avg_all': round(l1_cons / len(l1_paid), 2) if l1_paid else 0,
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'L1_avg_cons': round(l1_cons / len(l1_cons_users), 2) if l1_cons_users else 0,
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'L2_paid': len(l2_paid), 'L2_cons': l2_cons, 'L2_cons_users': len(l2_cons_users),
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'L2_no_cons': len(l2_paid) - len(l2_cons_users),
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'L2_avg_all': round(l2_cons / len(l2_paid), 2) if l2_paid else 0,
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'L2_avg_cons': round(l2_cons / len(l2_cons_users), 2) if l2_cons_users else 0,
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})
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cur.close()
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conn.close()
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# ===== 生成图表 =====
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print("\n生成图表...")
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out = '/root/.openclaw/workspace/output'
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configs = {
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'L1_all': {'prefix': 'L1', 'color': '#4A90D9', 'light': '#A8CFF1', 'label': 'L1'},
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'L2_all': {'prefix': 'L2', 'color': '#E85D47', 'light': '#F4A9A0', 'label': 'L2'},
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}
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for key, cfg in configs.items():
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pfx = cfg['prefix']
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color = cfg['color']
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light = cfg['light']
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label = cfg['label']
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first = next(i for i, r in enumerate(results) if r[f'{pfx}_paid'] > 0)
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data = results[first:]
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xs = [r['ws'] + timedelta(days=3) for r in data]
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dates = [r['ws'] for r in data]
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paid = [r[f'{pfx}_paid'] for r in data]
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cons_users = [r[f'{pfx}_cons_users'] for r in data]
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no_cons = [r[f'{pfx}_no_cons'] for r in data]
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avg_all = [r[f'{pfx}_avg_all'] for r in data]
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avg_cons = [r[f'{pfx}_avg_cons'] for r in data]
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# 图1: 堆叠柱状
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fig, ax = plt.subplots(figsize=(18, 8))
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x_idx = np.arange(len(xs))
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bar_w = 0.65
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ax.bar(x_idx, cons_users, bar_w, color=light, label='有课消用户', zorder=3)
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ax.bar(x_idx, no_cons, bar_w, bottom=cons_users, color='#D0D0D0', label='无课消用户', zorder=3)
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step = max(1, len(data)//10)
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for i in range(0, len(data), step):
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ax.annotate(str(paid[i]), (i, paid[i]), textcoords='offset points', xytext=(0, 5),
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fontsize=7.5, ha='center', color='#333333', fontweight='bold')
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ax.set_xticks(x_idx[::step])
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ax.set_xticklabels([dates[i].strftime('%m/%d') for i in range(0, len(data), step)], fontsize=8.5, rotation=45)
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ax.set_ylabel('用户数', fontsize=13)
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ax.set_title(f'{label}付费用户周课消分布（剔除U0序章）', fontsize=16, fontweight='bold')
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ax.legend(fontsize=12, loc='upper left')
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ax.grid(axis='y', alpha=0.3, zorder=0)
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ax.set_xlim(-0.5, len(x_idx) - 0.5)
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no_rate = no_cons[-1] / paid[-1] * 100 if paid[-1] else 0
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ax.text(0.97, 0.95, f'付费{paid[-1]}人 | 无课消率{no_rate:.0f}%', transform=ax.transAxes,
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fontsize=11, ha='right', va='top', color='#666666', fontstyle='italic')
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plt.tight_layout()
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plt.savefig(f'{out}/{key}_users_stack.png', dpi=150, bbox_inches='tight', facecolor='white')
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plt.close()
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print(f' ✅ {key}_users_stack.png')
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# 图2: 折线
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fig, ax = plt.subplots(figsize=(18, 8))
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ax.plot(xs, avg_all, 'o-', color='#999999', linewidth=2.2, markersize=5,
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label='人均课消（全部付费用户）', markerfacecolor='white')
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ax.plot(xs, avg_cons, 's-', color=color, linewidth=2.8, markersize=5,
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label='人均课消（有课消用户）', markerfacecolor='white')
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ax.fill_between(xs, avg_all, avg_cons, alpha=0.08, color=color)
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for i in range(0, len(data), max(1, len(data)//8)):
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ax.annotate(f'{avg_all[i]:.1f}', (xs[i], avg_all[i]), textcoords='offset points',
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xytext=(0, -15), fontsize=7.5, color='#999999', ha='center')
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ax.annotate(f'{avg_cons[i]:.1f}', (xs[i], avg_cons[i]), textcoords='offset points',
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xytext=(0, 7), fontsize=7.5, color=color, ha='center', fontweight='bold')
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ax.xaxis.set_major_formatter(mdates.DateFormatter('%m/%d'))
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ax.xaxis.set_major_locator(mdates.MonthLocator())
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plt.setp(ax.xaxis.get_majorticklabels(), rotation=45, fontsize=9)
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ax.set_ylabel('课消数（节/周）', fontsize=13)
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ax.set_title(f'{label}付费用户周人均课消趋势（剔除U0序章）', fontsize=16, fontweight='bold')
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ax.legend(fontsize=12, loc='upper left')
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ax.grid(True, alpha=0.3)
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ax.set_xlim(date(2025, 8, 30), date(2026, 5, 12))
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plt.tight_layout()
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plt.savefig(f'{out}/{key}_avg_trend.png', dpi=150, bbox_inches='tight', facecolor='white')
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plt.close()
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print(f' ✅ {key}_avg_trend.png')
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print('\n✅ 4张图表已生成')
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