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数据清洗自动化 — 脏数据→去重/补全/格式统一/异常检测→干净数据集
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Based on SOC occupation classification
Manage Bitbucket pull requests, repositories, and pipelines and Jira issues from the terminal with the bj CLI. bj mirrors the GitHub gh CLI, so gh pr/issue/repo commands map to bj pr/issue/repo, no MCP server or API wiring needed. Installs the bj CLI automatically if it is missing. Use when working with Bitbucket or Jira, opening or reviewing pull requests, managing Jira issues, running pipelines, or when a git branch name contains a Jira issue key like PROJ-42.
Use when auditing a paid ad account for incremental contribution, wasted spend, or measurement integrity before scaling; runs a typed 20-item ROAS profile with verified vetoes and a SHIP/FIX/BLOCK/UNDECIDED gate on own exported data. Not for campaign structure design — use campaign-architect; not for creative production — use ad-creative-builder. 付费广告账户审计/ROAS评分
Use when the user asks to "write ad copy", "generate RSA headlines", or "build ad creative at volume"; produces ad units — RSA headlines/descriptions, hooks, and an angle matrix — message-matched to the destination landing page. Not for scoring an ad account — use ad-account-auditor; not for the post-click page — use landing-optimizer; not for organic articles — use content-writer. 广告创意/广告文案/RSA标题
Use when the user asks to "design an A/B test", "set up a creative/landing test", "run an incrementality test", or "is this result statistically and practically material?"; produces a hypothesis, variant matrix, sample-size/duration/power plan, and a documented effect/uncertainty read from own exported results. It applies only a precommitted owner-approved action rule; the statistical helper never chooses a business action. Not for producing variants — use ad-creative-builder; not for reading back one shipped change — use paid-measurement-loop. 广告AB测试设计/实验设计/显著性判定/增效测试
Use when platform-reported conversions disagree with GA4/ecommerce, when you suspect Meta and Google are double-counting the same sales, or for a standing (monthly) reconciliation workbook that de-dups stacked credit against an order-ID truth set, normalizes attribution windows and currency, compares attribution models, and reads incrementality from a geo/holdout test. Not for the point-in-time R2 veto or RQS gate — use ad-account-auditor; not for the ROI/ROAS ratio math itself — use roi-calculator; not for organic dark-social share attribution or GA4 direct-traffic decomposition — use dark-social-attributor. 付费广告归因对账/去重/增量
Use when the user asks to "analyze my target audience", "build an audience profile for influencer targeting", "research a niche community", or "deep-dive a subculture before partnering with creators"; in audience mode produces demographic/psychographic profiles, a platform-priority matrix, named personas, and an influencer-selection criteria set, and in niche mode produces a community map, culture decode (language/norms/taboos), key-voice tiers, a Brand Fit Score, and a phased entry strategy. Not for finding specific creators to contract — use influencer-discovery; not for scoring a shortlist on ACE — use fit-scorer. 目标受众画像/人群分析 · 细分社群/亚文化调研
| name | data-cleaning-pipeline |
| version | 1.0.0 |
| description | 数据清洗自动化 — 脏数据→去重/补全/格式统一/异常检测→干净数据集 |
| author | Hermes-Sedimentary |
| tags | ["数据清洗","ETL","数据分析","Python"] |
| price | ¥149 |
价格: ¥149
数据清洗自动化 — 脏数据→去重/补全/格式统一/异常检测→干净数据集
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