Implicit type conversion of lists in to_pandas
MEMBER
I think this behavior comes from PyArrow:
```python
import pyarrow as pa
t = pa.table({"a": [[0]]})
t.to_pandas().a.values[0]
# array([0])
```

I believe this has to do with zero-copy: you can get a pandas DataFrame without copying the buffers from arrow, and therefore end up with numpy arrays.
2022-11-09T13:10:42Z
https://github.com/huggingface/datasets/issues/5220#issuecomment-1308729099
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2022-11-09T13:11:05Z
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CONTRIBUTOR
That's interesting, I guess not much to do here then.
2022-11-10T16:12:26Z
https://github.com/huggingface/datasets/issues/5220#issuecomment-1310535689
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### Describe the bug

```
ds = Dataset.from_list([{'a':[1,2,3]}])
ds.to_pandas().a.values[0]
```
Results in `array([1, 2, 3])`  -- a rather unexpected conversion of types which made downstream tools expecting lists not happy.

### Steps to reproduce the bug

See snippet

### Expected behavior

Keep the original type

### Environment info

datasets 2.6.1
python 3.8.10