How to Auto‑Fill Missing Product Names in Pandas Using ID Fallback

Hello, I am a Python enthusiast.

1. Introduction

A few days ago, a member of a Python community asked how to automatically fill missing product names in a sales data table. The goal is to merge the sales table with a product information table on the product ID, but some rows have an empty product ID, requiring a fallback to match on another identifier.

2. Implementation

The solution is to first perform a left merge on the product ID, then replace missing product names by looking up the product name using the alternative ID column.

df1 = df1.merge(df2[['产品号', '产品名称']], on='产品号', how='left')
df1.loc[df1['产品号'].isnull(), '产品名称'] = df1.loc[df1['产品号'].isnull(), 'ID'].map(
    lambda x: df2[df2['ID'] == x]['产品名称'].values[0]
)

This code successfully resolves the issue for the community member.

3. Conclusion

The article demonstrates a practical Pandas technique for handling missing values by merging tables and applying a conditional fallback lookup, helping readers solve similar data‑processing problems.