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

Introduction

Hello, I am a Python enthusiast. A fan asked how to delete duplicate workflow IDs while preserving the preceding approval comments. Simple set operations cannot handle this because we need to keep the original comments.

Implementation Process

Two solutions are provided.

Method 1

This approach uses pandas groupby to aggregate comments, handling empty cells first.

Because the original data contains blank cells, we replace them before grouping:

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

This alternative, suggested by another expert, also uses groupby but does not address blank cells.

Conclusion

The two methods demonstrate how pandas.groupby() can be leveraged to batch‑process data, remove duplicate IDs, and retain important approval comments, deepening understanding of this powerful function.