Load a bundled dataset by name.
data.load_dataset(
name,
*,
backend=None,
)
Greenwood ships several classic survival-analysis datasets from R’s 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() (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:
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:
# List all available dataset names
gw.available_datasets()
['colon', 'lung', 'mgus2', 'ovarian', 'pbc', 'pbcseq', 'veteran']