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根据指定的行切片规则和列映射，将源DataFrame（df_sub）的列数据转换为长格式DataFrame，包含sub_id、trial、start_time、end_time等字段。
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| id | 22b837b0-2356-4c5b-aa41-338f994e06d4 |
| name | Python Pandas 实验数据宽表转长表转换 |
| description | 根据指定的行切片规则和列映射，将源DataFrame（df_sub）的列数据转换为长格式DataFrame，包含sub_id、trial、start_time、end_time等字段。 |
| version | 0.1.0 |
| tags | ["python","pandas","dataframe","data-transformation","etl"] |
| triggers | ["df_sub转df","pandas实验数据转换","提取start_time和end_time","宽表变长表","df_sub每一列对应25行"] |
根据指定的行切片规则和列映射，将源DataFrame（df_sub）的列数据转换为长格式DataFrame，包含sub_id、trial、start_time、end_time等字段。
你是一个Python Pandas数据处理专家。你的任务是根据用户定义的特定逻辑，将源DataFrame（df_sub）转换为目标DataFrame（通常命名为point或df）。
sub_id, trial, start_time, end_time, result, error。df_sub 的每一列（索引为 i）。sub_id：值为 i + 1。trial：生成一个从1到25的列表（list(range(1, 26))）。start_time：从 df_sub 中提取，使用切片逻辑 df_sub.iloc[1::2, i].values（即取奇数行，从第2行开始）。end_time：从 df_sub 中提取，使用切片逻辑 df_sub.iloc[2::2, i].values（即取偶数行，从第3行开始）。result 和 error：默认填充为 None。iloc, DataFrame 构造函数）。Manage personal local Agent Skill files as an installable skill manager. Proactively and periodically detect reusable user-specific, team-specific, or broadly reusable skill material during or after meaningful sessions; run non-blocking extraction checks; offer candidate skill titles or accept a user-supplied topic when extraction direction is ambiguous; preserve the appropriate output language; search local and external skill ecosystems for similar skills; score candidates by evidence, recurrence, personal value, and portability; fully draft proposed skills or diffs before asking for approval; then, after explicit user approval, discard, improve, merge, or create `SKILL.md` folders.
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