## data.load_dataset()


Load a bundled dataset by name.


Usage

``` python
data.load_dataset(
    name,
    *,
    backend=None,
)
```


Greenwood ships several classic survival-analysis datasets from R's [survival](Parametric.md#greenwood.Parametric.survival) package, stored as gzipped CSVs. This function decompresses them on the fly and returns a DataFrame in your preferred backend.


## Parameters


`name: str`  
One of [available_datasets()](available_datasets.md#greenwood.available_datasets) (e.g., `"lung"`, `"veteran"`, `"ovarian"`, `"pbc"`, `"pbcseq"`, `"colon"`, `"mgus2"`).

`backend: str | None = None`  
`"pandas"` or `"polars"`. When left as `None` (the default), Greenwood picks a backend for you: it prefers Polars if it is installed, otherwise uses Pandas, and raises if neither is available.


## Returns


`DataFrame`  
A Polars or Pandas DataFrame with the dataset contents.


## Examples

Load the NCCTG lung cancer dataset as a Polars DataFrame:


``` python
import greenwood as gw

# Load the NCCTG lung cancer dataset as a Polars DataFrame
lung = gw.load_dataset("lung", backend="polars")
lung.head()
```


shape: (5, 10)

| inst | time | status | age | sex | ph.ecog | ph.karno | pat.karno | meal.cal | wt.loss |
|------|------|--------|-----|-----|---------|----------|-----------|----------|---------|
| i64  | i64  | i64    | i64 | i64 | i64     | i64      | i64       | i64      | i64     |
| 3    | 306  | 2      | 74  | 1   | 1       | 90       | 100       | 1175     | null    |
| 3    | 455  | 2      | 68  | 1   | 0       | 90       | 90        | 1225     | 15      |
| 3    | 1010 | 1      | 56  | 1   | 0       | 90       | 90        | null     | 15      |
| 5    | 210  | 2      | 57  | 1   | 1       | 90       | 60        | 1150     | 11      |
| 1    | 883  | 2      | 60  | 1   | 0       | 100      | 90        | null     | 0       |


See all available dataset names:


``` python
# List all available dataset names
gw.available_datasets()
```


    ['colon', 'lung', 'mgus2', 'ovarian', 'pbc', 'pbcseq', 'veteran']