# xarray.CFTimeIndex.slice_indexer

#### CFTimeIndex.slice_indexer(start=None, end=None, step=None)[[source]](https://github.com/pydata/xarray/blob/main/xarray/../.pixi/envs/doc/lib/python3.14/site-packages/pandas/core/indexes/base.py#L6753-L6812)

Compute the slice indexer for input labels and step.

Index needs to be ordered and unique.

* **Parameters:**
  * **start** (`label`, *default* [`None`](https://docs.python.org/3/builtins/constants.html#None)) – If None, defaults to the beginning.
  * **end** (`label`, *default* [`None`](https://docs.python.org/3/builtins/constants.html#None)) – If None, defaults to the end.
  * **step** ([`int`](https://docs.python.org/3/builtins/functions.html#int), *default* [`None`](https://docs.python.org/3/builtins/constants.html#None)) – If None, defaults to 1.
* **Returns:**
  [`slice`](https://docs.python.org/3/builtins/functions.html#slice) – A slice object.

:raises KeyError : `If key does not exist`, or `key is not unique` and `index is`: not ordered.

#### SEE ALSO
`Index.slice_locs`
: Computes slice locations for input labels.

`Index.get_slice_bound`
: Retrieves slice bound that corresponds to given label.

### Notes

This function assumes that the data is sorted, so use at your own peril.

### Examples

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This is a method on all index types. For example you can do:

```pycon
>>> idx = pd.Index(list("abcd"))
>>> idx.slice_indexer(start="b", end="c")
slice(1, 3, None)
```

```pycon
>>> idx = pd.MultiIndex.from_arrays([list("abcd"), list("efgh")])
>>> idx.slice_indexer(start="b", end=("c", "g"))
slice(1, 3, None)
```

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