Return the coordinate label of the minimum value along a dimension. Returns a new `Dataset` named after the dimension with the values of the coordinate labels along that dimension corresponding to minimum values along that dimension. In comparison to :py:meth:`~Data
(
self,
dim: Hashable | None = None,
*,
skipna: bool | None = None,
fill_value: Any = xrdtypes.NA,
keep_attrs: bool | None = None,
)
| 9196 | return self._replace_with_new_dims(variables, indexes=indexes, attrs=attrs) |
| 9197 | |
| 9198 | def idxmin( |
| 9199 | self, |
| 9200 | dim: Hashable | None = None, |
| 9201 | *, |
| 9202 | skipna: bool | None = None, |
| 9203 | fill_value: Any = xrdtypes.NA, |
| 9204 | keep_attrs: bool | None = None, |
| 9205 | ) -> Self: |
| 9206 | """Return the coordinate label of the minimum value along a dimension. |
| 9207 | |
| 9208 | Returns a new `Dataset` named after the dimension with the values of |
| 9209 | the coordinate labels along that dimension corresponding to minimum |
| 9210 | values along that dimension. |
| 9211 | |
| 9212 | In comparison to :py:meth:`~Dataset.argmin`, this returns the |
| 9213 | coordinate label while :py:meth:`~Dataset.argmin` returns the index. |
| 9214 | |
| 9215 | Parameters |
| 9216 | ---------- |
| 9217 | dim : Hashable, optional |
| 9218 | Dimension over which to apply `idxmin`. This is optional for 1D |
| 9219 | variables, but required for variables with 2 or more dimensions. |
| 9220 | skipna : bool or None, optional |
| 9221 | If True, skip missing values (as marked by NaN). By default, only |
| 9222 | skips missing values for ``float``, ``complex``, and ``object`` |
| 9223 | dtypes; other dtypes either do not have a sentinel missing value |
| 9224 | (``int``) or ``skipna=True`` has not been implemented |
| 9225 | (``datetime64`` or ``timedelta64``). |
| 9226 | fill_value : Any, default: NaN |
| 9227 | Value to be filled in case all of the values along a dimension are |
| 9228 | null. By default this is NaN. The fill value and result are |
| 9229 | automatically converted to a compatible dtype if possible. |
| 9230 | Ignored if ``skipna`` is False. |
| 9231 | keep_attrs : bool or None, optional |
| 9232 | If True, the attributes (``attrs``) will be copied from the |
| 9233 | original object to the new one. If False, the new object |
| 9234 | will be returned without attributes. |
| 9235 | |
| 9236 | Returns |
| 9237 | ------- |
| 9238 | reduced : Dataset |
| 9239 | New `Dataset` object with `idxmin` applied to its data and the |
| 9240 | indicated dimension removed. |
| 9241 | |
| 9242 | See Also |
| 9243 | -------- |
| 9244 | DataArray.idxmin, Dataset.idxmax, Dataset.min, Dataset.argmin |
| 9245 | |
| 9246 | Examples |
| 9247 | -------- |
| 9248 | >>> array1 = xr.DataArray( |
| 9249 | ... [0, 2, 1, 0, -2], dims="x", coords={"x": ["a", "b", "c", "d", "e"]} |
| 9250 | ... ) |
| 9251 | >>> array2 = xr.DataArray( |
| 9252 | ... [ |
| 9253 | ... [2.0, 1.0, 2.0, 0.0, -2.0], |
| 9254 | ... [-4.0, np.nan, 2.0, np.nan, -2.0], |
| 9255 | ... [np.nan, np.nan, 1.0, np.nan, np.nan], |