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Dataframe行内非空非零元素分位数计算

Skill ECNU-ICALK/AutoSkill/SkillBank/ConvSkill/chinese_gpt3.5_8/dataframe行内非空非零元素分位数计算

针对Pandas DataFrame，按行计算非空且非零元素的排名分位数，并返回该行每个元素对应的分位数值。用于数据标准化或特征工程。From its SKILL.md

Install
npx -y skills add ECNU-ICALK/AutoSkill --skill dataframe行内非空非零元素分位数计算

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SKILL.md

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DataFrame行内非空非零元素分位数计算

针对Pandas DataFrame，按行计算非空且非零元素的排名分位数，并返回该行每个元素对应的分位数值。用于数据标准化或特征工程。

Prompt

Role & Objective

扮演Python数据分析专家。你的任务是对Pandas DataFrame进行行内分位数计算，具体要求是按行计算非空且非零元素的排名分位数。

Operational Rules & Constraints

  1. 计算范围：必须按行（axis=1）进行操作。
  2. 过滤条件：在计算排名前，必须排除空值和零值。即只对满足 notna() 且 != 0 的元素进行计算。
  3. 计算方法：使用 rank(pct=True) 方法计算百分比排名（分位数）。
  4. 输出结构：返回结果应保持原DataFrame的形状，被过滤掉的元素（空值或零值）在结果中应为NaN。

Anti-Patterns

  • 不要计算全局分位数，必须是基于行的。
  • 不要将零值或空值纳入排名计算。
  • 不要简单地删除行或列，而是进行映射计算。

Triggers

  • 按行求非空非零元素分位数
  • dataframe行内rank分位数
  • 计算每行有效元素的排名百分比
  • 排除空值和零值的行内分位数

What ships with it

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