Returns a new dataset with the last `n` values of each array for the specified dimension(s). Parameters ---------- indexers : dict or int, default: 5 A dict with keys matching dimensions and integer values `n` or a single integer `n` applied o
(
self,
indexers: Mapping[Any, int] | int | None = None,
**indexers_kwargs: Any,
)
| 3158 | return self.isel(indexers_slices) |
| 3159 | |
| 3160 | def tail( |
| 3161 | self, |
| 3162 | indexers: Mapping[Any, int] | int | None = None, |
| 3163 | **indexers_kwargs: Any, |
| 3164 | ) -> Self: |
| 3165 | """Returns a new dataset with the last `n` values of each array |
| 3166 | for the specified dimension(s). |
| 3167 | |
| 3168 | Parameters |
| 3169 | ---------- |
| 3170 | indexers : dict or int, default: 5 |
| 3171 | A dict with keys matching dimensions and integer values `n` |
| 3172 | or a single integer `n` applied over all dimensions. |
| 3173 | One of indexers or indexers_kwargs must be provided. |
| 3174 | **indexers_kwargs : {dim: n, ...}, optional |
| 3175 | The keyword arguments form of ``indexers``. |
| 3176 | One of indexers or indexers_kwargs must be provided. |
| 3177 | |
| 3178 | Examples |
| 3179 | -------- |
| 3180 | >>> activity_names = ["Walking", "Running", "Cycling", "Swimming", "Yoga"] |
| 3181 | >>> durations = [30, 45, 60, 45, 60] # in minutes |
| 3182 | >>> energies = [150, 300, 250, 400, 100] # in calories |
| 3183 | >>> dataset = xr.Dataset( |
| 3184 | ... { |
| 3185 | ... "duration": (["activity"], durations), |
| 3186 | ... "energy_expenditure": (["activity"], energies), |
| 3187 | ... }, |
| 3188 | ... coords={"activity": activity_names}, |
| 3189 | ... ) |
| 3190 | >>> sorted_dataset = dataset.sortby("energy_expenditure", ascending=False) |
| 3191 | >>> sorted_dataset |
| 3192 | <xarray.Dataset> Size: 240B |
| 3193 | Dimensions: (activity: 5) |
| 3194 | Coordinates: |
| 3195 | * activity (activity) <U8 160B 'Swimming' 'Running' ... 'Yoga' |
| 3196 | Data variables: |
| 3197 | duration (activity) int64 40B 45 45 60 30 60 |
| 3198 | energy_expenditure (activity) int64 40B 400 300 250 150 100 |
| 3199 | |
| 3200 | # Activities with the least energy expenditures using tail() |
| 3201 | |
| 3202 | >>> sorted_dataset.tail(3) |
| 3203 | <xarray.Dataset> Size: 144B |
| 3204 | Dimensions: (activity: 3) |
| 3205 | Coordinates: |
| 3206 | * activity (activity) <U8 96B 'Cycling' 'Walking' 'Yoga' |
| 3207 | Data variables: |
| 3208 | duration (activity) int64 24B 60 30 60 |
| 3209 | energy_expenditure (activity) int64 24B 250 150 100 |
| 3210 | |
| 3211 | >>> sorted_dataset.tail({"activity": 3}) |
| 3212 | <xarray.Dataset> Size: 144B |
| 3213 | Dimensions: (activity: 3) |
| 3214 | Coordinates: |
| 3215 | * activity (activity) <U8 96B 'Cycling' 'Walking' 'Yoga' |
| 3216 | Data variables: |
| 3217 | duration (activity) int64 24B 60 30 60 |