👀 Views: 33 💬 Answers: 1 📅 Created: 2025-08-22

pandas for-loop dataframe python-3.10 Python

This might be a silly question, but I tried several approaches but none seem to work... I've searched everywhere and can't find a clear answer... I'm working with a pandas DataFrame and trying to apply a custom function to each row using a for loop combined with `.iloc`. However, I've noticed that the loop stops iterating after only a few rows, and I need to figure out why. Here’s a simplified version of my code: ```python import pandas as pd data = { 'A': [1, 2, 3, 4], 'B': [5, 6, 7, 8] } df = pd.DataFrame(data) def custom_func(row): if row['A'] == 3: return 'Found 3' return row['B'] * 2 for index in range(len(df)): result = custom_func(df.iloc[index]) print(f'Index: {index}, Result: {result}') ``` When I run this code, the output is: ``` Index: 0, Result: 10 Index: 1, Result: 12 Index: 2, Result: Found 3 ``` But it doesn't print the result for `Index: 3`. I have confirmed that my DataFrame is properly constructed and contains four rows. I suspect the scenario might be related to how I'm accessing the rows or the behavior of `iloc` with the function call. I've tried switching to `.iterrows()` instead, and the loop works correctly, but I want to understand why my current approach fails. Is there some kind of early exit or exception that I'm missing? Any insights would be greatly appreciated! Is there a better approach? I'm working on a web app that needs to handle this. Any feedback is welcome!