Loading CSV exported dataset has unexpected format
COLLABORATOR
Hi! Parquet is the only format that supports complex/nested features such as `Translation`. So, this should work:
```python
test_dataset = load_dataset("opus100", name="en-fr", split="test")

# Save with .to_parquet()
test_parquet_path = "try_testset_save.parquet"
test_dataset.to_parquet(test_parquet_path)

# Load dataset from the Parquet
loaded_dataset = load_dataset("parquet", data_files=test_parquet_path)
print(test_dataset_fromfile[0]["translation"])
print(test_dataset_fromfile[0]["translation"]["en"])
```
2024-01-22T15:24:18Z
https://github.com/huggingface/datasets/issues/6600#issuecomment-1904236853
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Indeed this works great, thank you !
2024-01-23T14:42:31Z
https://github.com/huggingface/datasets/issues/6600#issuecomment-1906198505
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### Describe the bug

I wanted to be able to save a HF dataset for translations and load it again in another script, but I'm a bit confused with the documentation and the result I've got so I'm opening this issue to ask if this behavior is as expected.

### Steps to reproduce the bug

The documentation I've mainly consulted is https://huggingface.co/docs/datasets/v2.16.1/en/package_reference/loading_methods#datasets.load_dataset and https://huggingface.co/docs/datasets/package_reference/main_classes#datasets.Dataset (where I've found `.to_csv()`)

```python
# Load a dataset of translations
test_dataset = load_dataset("opus100", name="en-fr", split="test")

# Save with .to_csv()
test_csv_path = "try_testset_save.csv"
test_dataset.to_csv(test_csv_path)

# Load dataset from the CSV
loaded_dataset = load_dataset("csv", data_files=test_csv_path)
print(test_dataset_fromfile[0]["translation"])
print(test_dataset_fromfile[0]["translation"]["en"])
```
```
Creating CSV from Arrow format: 100%
2/2 [00:00<00:00, 47.99ba/s]
Downloading data files: 100%
1/1 [00:00<00:00, 65.33it/s]
Extracting data files: 100%
1/1 [00:00<00:00, 42.10it/s]
Generating train split:
2000/0 [00:00<00:00, 47486.09 examples/s]

{'en': "She wasn't going to vaccinate her kid against polio,  no way.", 'fr': 'Elle ne vaccinerait pas son enfant contre la polio. Pas question.'}

---------------------------------------------------------------------------
TypeError                                 Traceback (most recent call last)
Cell In[29], line 11
      9 loaded_dataset = load_dataset("csv", data_files=test_csv_path)
     10 print(test_dataset_fromfile[0]["translation"])
---> 11 print(test_dataset_fromfile[0]["translation"]["en"])

TypeError: string indices must be integers, not 'str'
```


### Expected behavior

Each translation was saved as a stringified dict like `"{'en': ""She wasn't going to vaccinate her kid against polio,  no way."", 'fr': 'Elle ne vaccinerait pas son enfant contre la polio. Pas question.'}"` where I would have expected 2 columns (1st with English segments, and 2nd with French segments), and I was expecting `load_dataset` to infer the type of feature automatically as I haven't seen anything about it in the documentation.

Do you have an example of how to effectively save and load datasets of translations ?

### Environment info

- `datasets` version: 2.15.0
- Platform: Linux-3.10.0-1160.36.2.el7.x86_64-x86_64-with-glibc2.17
- Python version: 3.11.5
- `huggingface_hub` version: 0.16.4
- PyArrow version: 14.0.2
- Pandas version: 2.1.4
- `fsspec` version: 2023.10.0