88 lines
4.4 KiB
Python
88 lines
4.4 KiB
Python
#!/usr/bin/env python3
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"""图表 v4: L1只看L1课程, L2只看L2课程"""
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import json, os
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from datetime import date, timedelta
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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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with open('/root/.openclaw/workspace/output/course_data_v4.json') as f:
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data = json.load(f)
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results = data['results']
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out = '/root/.openclaw/workspace/output'
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configs = {
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'L1': {'prefix': 'L1', 'color': '#4A90D9', 'light': '#A8CFF1', 'label': 'L1'},
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'L2': {'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']; color = cfg['color']; light = cfg['light']; 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_sub = results[first:]
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dates = [date.fromisoformat(r['ws']) for r in data_sub]
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xs = [d + timedelta(days=3) for d in dates]
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paid = [r[f'{pfx}_paid'] for r in data_sub]
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cons_users = [r[f'{pfx}_cons_users'] for r in data_sub]
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no_cons = [r[f'{pfx}_no_cons'] for r in data_sub]
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avg_all = [r[f'{pfx}_avg_all'] for r in data_sub]
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avg_cons = [r[f'{pfx}_avg_cons'] for r in data_sub]
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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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ax.bar(x_idx, cons_users, 0.65, color=light, label='有课消用户', zorder=3)
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ax.bar(x_idx, no_cons, 0.65, bottom=cons_users, color='#D0D0D0', label='无课消用户', zorder=3)
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step = max(1, len(data_sub)//10)
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for i in range(0, len(data_sub), 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_sub), 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（只看{label}课程，剔除U0）', 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}%',
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transform=ax.transAxes, 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}/{pfx}_users_stack_v4.png', dpi=150, bbox_inches='tight', facecolor='white')
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plt.close()
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print(f' ✅ {pfx}_users_stack_v4.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, 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, 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_sub), max(1, len(data_sub)//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（只看{label}课程，剔除U0）', 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}/{pfx}_avg_trend_v4.png', dpi=150, bbox_inches='tight', facecolor='white')
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plt.close()
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print(f' ✅ {pfx}_avg_trend_v4.png')
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print('\n✅ 4张v4图表已生成')
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