Each row in this wide dataset represents the results of 100 simulated participants on three hypothetical experiments, along with their gender and control/treatment group. Parameters ---------- indexed: bool If True, then the index is named "participant". Applica
(indexed=False, return_type="pandas")
| 267 | |
| 268 | |
| 269 | def experiment(indexed=False, return_type="pandas"): |
| 270 | """ |
| 271 | Each row in this wide dataset represents the results of 100 simulated participants |
| 272 | on three hypothetical experiments, along with their gender and control/treatment group. |
| 273 | |
| 274 | Parameters |
| 275 | ---------- |
| 276 | indexed: bool |
| 277 | If True, then the index is named "participant". |
| 278 | Applicable only if `return_type='pandas'` |
| 279 | |
| 280 | return_type: {'pandas', 'polars', 'pyarrow', 'modin', 'cudf'} |
| 281 | Type of the resulting dataframe |
| 282 | |
| 283 | Returns |
| 284 | ------- |
| 285 | Dataframe of `return_type` type |
| 286 | Dataframe with 100 rows and the following columns: |
| 287 | `['experiment_1', 'experiment_2', 'experiment_3', 'gender', 'group']`. |
| 288 | If `indexed` is True, the data frame index is named "participant" |
| 289 | """ |
| 290 | |
| 291 | if indexed and return_type not in BACKENDS_WITH_INDEX_SUPPORT: |
| 292 | msg = f"Backend '{return_type}' does not support setting index" |
| 293 | raise NotImplementedError(msg) |
| 294 | |
| 295 | df = nw.from_native( |
| 296 | _get_dataset("experiment", return_type=return_type), eager_only=True |
| 297 | ) |
| 298 | if indexed: # then it must be pandas |
| 299 | df = df.to_native() |
| 300 | df.index.name = "participant" |
| 301 | return df |
| 302 | return df.to_native() |
| 303 | |
| 304 | |
| 305 | def medals_wide(indexed=False, return_type="pandas"): |
nothing calls this directly
no test coverage detected