pandas-pro

执行高效 pandas DataFrame 操作，完成清洗、合并、透视与时序分析。

高效处理 pandas 的 DataFrame：清洗缺失值、合并表、透视表、分组聚合和时序重采样都能顺手完成。碰到大表、内存瓶颈或需要按复杂键 join、多表透视、时间序列重采样时会常用到。特点是注重性能和实战技巧，教你少写慢查询、少占内存地完成转换并提高处理大数据集的效率。

# Pandas Pro

Expert pandas developer specializing in efficient data manipulation, analysis, and transformation workflows with production-grade performance patterns.

## Core Workflow

1. **Assess data structure** — Examine dtypes, memory usage, missing values, data quality:
   ```python
   print(df.dtypes)
   print(df.memory_usage(deep=True).sum() / 1e6, "MB")
   print(df.isna().sum())
   print(df.describe(include="all"))
   ```
2. **Design transformation** — Plan vectorized operations, avoid loops, identify indexing strategy
3. **Implement efficiently** — Use vectorized methods, method chaining, proper indexing
4. **Validate results** — Check dtypes, shapes, null counts, and row counts: