Add an entry to an arrow dataset
That's a great idea! Thank you so much!

When I try that solution, I get the following error when I try to concatenate `datasets` and `modified_dataset`. I have also attached the output I get when I print out those two variables. Am I missing something?

Code:
``` python
combined_dataset = concatenate_datasets([datasets, modified_dataset])
```

Error:
```
AttributeError: 'DatasetDict' object has no attribute 'features'
```

Output:
```
(Pdb) datasets
DatasetDict({
    train: Dataset({
        features: ['attention_mask', 'input_ids', 'special_tokens_mask'],
        num_rows: 493
    })
})
(Pdb) modified_dataset
DatasetDict({
    train: Dataset({
        features: ['attention_mask', 'input_ids', 'special_tokens_mask'],
        num_rows: 493
    })
})
```

The error is stemming from the fact that the attribute `datasets.features` does not exist. Would it not be possible to use `concatenate_datasets` in such a case? Is there an alternate solution?
Is it possible to add an entry to a dataset object?

**Motivation: I want to transform the sentences in the dataset and add them to the original dataset**

For example, say we have the following code:

``` python
from datasets import load_dataset

# Load a dataset and print the first examples in the training set
squad_dataset = load_dataset('squad')
print(squad_dataset['train'][0])
```

Is it possible to add an entry to `squad_dataset`? Something like the following?

``` python
squad_dataset.append({'text': "This is a new sentence"})
```

The motivation for doing this is that I want to transform the sentences in the squad dataset and add them to the original dataset.

If the above doesn't work, is there any other way of achieving the motivation mentioned above? Perhaps by creating a new arrow dataset by using the older one and the transformer sentences?

Add an entry to an arrow dataset 
 Is it possible to add an entry to a dataset object?

**Motivation: I want to transform the sentences in the dataset and add them to the original dataset**

For example, say we have the following code:

``` python
from datasets import load_dataset

# Load a dataset and print the first examples in the training set
squad_dataset = load_dataset('squad')
print(squad_dataset['train'][0])
```

Is it possible to add an entry to `squad_dataset`? Something like the following?

``` python
squad_dataset.append({'text': "This is a new sentence"})
```

The motivation for doing this is that I want to transform the sentences in the squad dataset and add them to the original dataset.

If the above doesn't work, is there any other way of achieving the motivation mentioned above? Perhaps by creating a new arrow dataset by using the older one and the transformer sentences?
 
 That's a great idea! Thank you so much!

When I try that solution, I get the following error when I try to concatenate `datasets` and `modified_dataset`. I have also attached the output I get when I print out those two variables. Am I missing something?

Code:
``` python
combined_dataset = concatenate_datasets([datasets, modified_dataset])
```

Error:
```
AttributeError: 'DatasetDict' object has no attribute 'features'
```

Output:
```
(Pdb) datasets
DatasetDict({
    train: Dataset({
        features: ['attention_mask', 'input_ids', 'special_tokens_mask'],
        num_rows: 493
    })
})
(Pdb) modified_dataset
DatasetDict({
    train: Dataset({
        features: ['attention_mask', 'input_ids', 'special_tokens_mask'],
        num_rows: 493
    })
})
```

The error is stemming from the fact that the attribute `datasets.features` does not exist. Would it not be possible to use `concatenate_datasets` in such a case? Is there an alternate solution?