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Developing a JSON Schema
I'm looking to create a minimal JSON schema that includes example formulas. The final answer should have an optional header and structured lists organized in sections, ideally sticking to 4-6 bullets each. I should consider producing [[NEWS.CONTENT_HTML]]quot;Top 8 数字故事金点子[[NEWS.CONTENT_HTML]]quot; with two lists of 6 bullets each since more topics may be needed. I also want to outline bullet points for [[NEWS.CONTENT_HTML]]quot;数据口径与抓取,[[NEWS.CONTENT_HTML]]quot; [[NEWS.CONTENT_HTML]]quot;可视化与发布节奏,[[NEWS.CONTENT_HTML]]quot; and [[NEWS.CONTENT_HTML]]quot;落地步骤.[[NEWS.CONTENT_HTML]]quot; A short code snippet for computing metrics like PPDA would be useful, but I need to keep it concise.Creating a Digital Story Framework
I’m working on a title called 数字故事备选, which includes several sections. In Section 1, I'll detail 6 bullets focused on youth training metrics. Section 2 will cover fan engagement and commercial aspects with another 6 bullets. Section 3 will highlight city impact and community service, aiming for 4-6 points. In Section 4, I’ll put together a catchy template with 6 example headlines. Section 5 will outline data sources with 6 bullet points. Finally, I'll provide a brief Python snippet for calculating U23 minutes.Outlining Implementation Steps
In Section 7, I’m focusing on 落地节奏 and will provide 4-6 concise steps. I also need to ask for context: [[NEWS.CONTENT_HTML]]quot;你们更偏媒体叙事还是俱乐部运营?[[NEWS.CONTENT_HTML]]quot; and offer options 1, 2, or 3. I should keep everything brief and avoid fabricating 2025 actual numbers; I can only propose examples with placeholders. Finally, I’ll structure the final answer in Chinese to meet the requirements.
这些题都能“用数字讲故事”，适合贯穿整个赛季做系列内容或赞助复盘。挑 3–5 个做主线，其他做月度/阶段性补充。
竞技与青训（赛季主线）
球迷与商业（赞助/票务叙事）
城市与公益（品牌外溢）
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标题与选题模板（即拿即用）
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数据口径与来源（先定标准，避免口水战）
快速计算示例（两项核心口径）
import pandas as pd
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# events: match_id, player_id, minutes_played, agedf = pd.read_csv('events_minutes.csv')df['is_u23'] = df['age'] [[NEWS.CONTENT_HTML]]lt; 23share = (df.groupby('match_id').apply(lambda g: g[g.is_u23]['minutes_played'].sum() / g['minutes_played'].sum()) .rename('u23_share').reset_index())SELECT season, (total_wage + transfer_fees) / NULLIF(league_points,0) AS cost_per_pointFROM finance_season;
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可视化与发布节奏
落地步骤（本周即可开工）
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需要的位置信息/偏好，给我选项数字即可：
