Supply raw data to the model This takes an arbitrary array, runs some quick checks, and returns the array if appropriate. Parameters ---------- target : str The eventual target of the raw data array : list, pd.Series, or array
(self, target, array)
| 265 | return summed |
| 266 | |
| 267 | def supply_raw(self, target, array): |
| 268 | """Supply raw data to the model |
| 269 | |
| 270 | This takes an arbitrary array, runs some quick checks, and returns |
| 271 | the array if appropriate. |
| 272 | |
| 273 | Parameters |
| 274 | ---------- |
| 275 | target : str |
| 276 | The eventual target of the raw data |
| 277 | array : list, pd.Series, or array |
| 278 | The raw data being supplied |
| 279 | |
| 280 | Returns |
| 281 | ======= |
| 282 | np.array |
| 283 | The data for the model |
| 284 | |
| 285 | Raises |
| 286 | ------ |
| 287 | pyfair.utility.fair_exception.FairException |
| 288 | Raised if the data has null values |
| 289 | |
| 290 | """ |
| 291 | # Ensure numeric |
| 292 | clean_array = pd.to_numeric(array) |
| 293 | # Coerce to series |
| 294 | if type(array) == pd.Series: |
| 295 | s = pd.Series(clean_array.values) |
| 296 | else: |
| 297 | s = pd.Series(clean_array) |
| 298 | # Check numeric and not null |
| 299 | if s.isnull().any(): |
| 300 | raise FairException('Supplied data contains null values') |
| 301 | # Ensure values are appropriate |
| 302 | if target in self._le_1_targets: |
| 303 | if s.max() > 1 or s.min() < 0: |
| 304 | raise FairException(f'{target} data greater or less than one') |
| 305 | self._supplied_values[target] = {'raw': s.values.tolist()} |
| 306 | return s.values |
| 307 | |
| 308 | def _determine_func(self, **kwargs): |
| 309 | """Checks keywords and returns the appropriate function object.""" |
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