# xarray.CFTimeIndex.to_list

#### CFTimeIndex.to_list()[[source]](https://github.com/pydata/xarray/blob/main/xarray/../.pixi/envs/doc/lib/python3.14/site-packages/pandas/core/base.py#L892-L927)

Return a list of the values.

These are each a scalar type, which is a Python scalar
(for str, int, float) or a pandas scalar
(for Timestamp/Timedelta/Interval/Period)

* **Returns:**
  [`list`](https://docs.python.org/3/builtins/stdtypes.html#list) – List containing the values as Python or pandas scalers.

#### SEE ALSO
[`numpy.ndarray.tolist`](https://numpy.org/doc/stable/reference/generated/numpy.ndarray.tolist.html#numpy.ndarray.tolist)
: Return the array as an a.ndim-levels deep nested list of Python scalars.

### Examples

<div class="try_examples_button_container"><button class="try_examples_button" onclick="window.tryExamplesShowIframe('9b122280-823d-4cfb-8779-6fd0c4f176dc','d8580404-9e2a-4ff9-9ec1-db6c2b7b9110','57ed0420-e413-4e7a-a6d9-bf10c24dee74','../lite/tree/../notebooks/index.html?path=49a33898_22d9_4398_b592_49f52ac5e325.ipynb','None')">Try it in your browser!</button></div>

For Series

```pycon
>>> s = pd.Series([1, 2, 3])
>>> s.to_list()
[1, 2, 3]
```

For Index:

```pycon
>>> idx = pd.Index([1, 2, 3])
>>> idx
Index([1, 2, 3], dtype='int64')
```

```pycon
>>> idx.to_list()
[1, 2, 3]
```

<div id="57ed0420-e413-4e7a-a6d9-bf10c24dee74" class="try_examples_outer_iframe  hidden"><div class="try_examples_button_container"><button class="try_examples_button" onclick="window.tryExamplesHideIframe('9b122280-823d-4cfb-8779-6fd0c4f176dc','57ed0420-e413-4e7a-a6d9-bf10c24dee74')">Go Back</button><button class="try_examples_button" onclick="window.openInNewTab('9b122280-823d-4cfb-8779-6fd0c4f176dc','57ed0420-e413-4e7a-a6d9-bf10c24dee74')">Open In Tab</button></div><div id="d8580404-9e2a-4ff9-9ec1-db6c2b7b9110" class="jupyterlite_sphinx_iframe_container"></div></div><script>document.addEventListener("DOMContentLoaded", function() {window.loadTryExamplesConfig("../try_examples.json");});</script>
