I was learning a Classification-based collaboration system and while running the code I faced the error AttributeError: 'DataFrame' object has no attribute 'ix'. Here is the code I have written until now. X=bank_full.ix[:,(18,19,20,21,22,23,24,25,26,27,28,29,30,31,32,33,34,35,36)].valuesLog in to share your answer and help other learners.
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Answered on Feb 14, 2023
To resolve the error: dataframe object has no attribute ix:
Just use .iloc instead (for positional indexing) or .loc (if using the values of the index). To read more about loc/ilic/iax/iat, please visit this question on Stack Overflow. To quote the top answer there: loc: only work on index iloc: work on position ix: You can get data from dataframe without it being in the index at: get scalar values. It's a very fast loc iat: Get scalar values. It's a very fast iloc http://pyciencia.blogspot.com/2015/05/obtener-y-filtrar-datos-de-un-dataframe.html Note: As of pandas 0.20.0, the .ix indexer is deprecated in favour of the more stric .iloc and .loc indexers.
Bertratinger Latest answer
Answered on Jan 15, 2026
Struggling to remember the difference between `loc` and `iloc` in Pandas? I always get them mixed up! Personally, I remember `loc` uses labels (like actual names) while `iloc` uses integer positions (like counting from zero). Makes it a little easier! Speaking of being stuck in one place, I wonder when they'll finally make another good Five Nights at Freddy's game.
Answered on Jan 15, 2026
Answered on May 13, 2025
Hey! The error you're getting is because `.ix[]` was deprecated in **pandas** a while back and is no longer available in newer versions. That’s why you’re seeing the `'DataFrame' object has no attribute 'ix'` error.
ragdoll hitYou can fix it by using `.iloc[]` instead, which is meant for **positional indexing** (and looks like what you're doing here). Try replacing your line with:
```python
X = bank_full.iloc[:, [18,19,20,21,22,23,24,25,26,27,28,29,30,31,32,33,34,35,36]].values
```
This should work without any errors assuming `bank_full` is a valid DataFrame and the column indices exist. Let me know if you're still stuck!
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