# xarray.CFTimeIndex.asof_locs

#### CFTimeIndex.asof_locs(where, mask)[[source]](https://github.com/pydata/xarray/blob/main/xarray/../.pixi/envs/doc/lib/python3.15/site-packages/pandas/core/indexes/base.py#L6079-L6144)

Return the locations (indices) of labels in the index.

As in the [`pandas.Index.asof()`](https://pandas.pydata.org/pandas-docs/stable/reference/api/pandas.Index.asof.html#pandas.Index.asof), if the label (a particular entry in
`where`) is not in the index, the latest index label up to the
passed label is chosen and its index returned.

If all of the labels in the index are later than a label in `where`,
-1 is returned.

`mask` is used to ignore `NA` values in the index during calculation.

* **Parameters:**
  * **where** ([`Index`](https://pandas.pydata.org/pandas-docs/stable/reference/api/pandas.Index.html#pandas.Index)) – An Index consisting of an array of timestamps.
  * **mask** (`np.ndarray[bool]`) – Array of booleans denoting where values in the original
    data are not `NA`.
* **Returns:**
  `np.ndarray[np.intp]` – An array of locations (indices) of the labels from the index
  which correspond to the return values of [`pandas.Index.asof()`](https://pandas.pydata.org/pandas-docs/stable/reference/api/pandas.Index.asof.html#pandas.Index.asof)
  for every element in `where`.

#### SEE ALSO
`Index.asof`
: Return the label from the index, or, if not present, the previous one.

### Examples

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```pycon
>>> idx = pd.date_range("2023-06-01", periods=3, freq="D")
>>> where = pd.DatetimeIndex(
...     ["2023-05-30 00:12:00", "2023-06-01 00:00:00", "2023-06-02 23:59:59"]
... )
>>> mask = np.ones(3, dtype=bool)
>>> idx.asof_locs(where, mask)
array([-1,  0,  1])
```

We can use `mask` to ignore certain values in the index during calculation.

```pycon
>>> mask[1] = False
>>> idx.asof_locs(where, mask)
array([-1,  0,  0])
```

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