How to Remove Duplicate IDs While Keeping Prior Comments with Pandas GroupBy

Introduction

A follower asked how to delete duplicate process numbers while preserving the preceding approval comments, which cannot be solved with a simple set operation.

Implementation

Method 1

Using pandas' groupby function to aggregate comments, then cleaning up commas and empty cells.

Optimized code handling blank cells:

data['审批意见'] = data['审批意见'] + ','

data = data.groupby(['流程状态','流程编号'])['审批意见'].sum().reset_index()

data['审批意见'] = data['审批意见'].str.strip(',').str.replace(',+', ',', regex=True)

Method 2

An alternative approach that does not consider empty cells but offers a useful idea.

Conclusion

The two methods demonstrate how pandas can efficiently batch‑group data, remove duplicate IDs, and retain the original approval comments, deepening understanding of groupby and string manipulation in Python data processing.