xarray.Dataset.reset_coords#

Dataset.reset_coords(names=None, drop=False)[source]#

Given names of coordinates, reset them to become variables

Parameters:

  • names (str, Iterable of Hashable or None, optional) – Name(s) of non-index coordinates in this dataset to reset into variables. By default, all non-index coordinates are reset.

  • drop (bool, default: False) – If True, remove coordinates instead of converting them into variables.

Examples

>>> dataset = xr.Dataset(
...     {
...         "temperature": (
...             ["time", "lat", "lon"],
...             [[[25, 26], [27, 28]], [[29, 30], [31, 32]]],
...         ),
...         "precipitation": (
...             ["time", "lat", "lon"],
...             [[[0.5, 0.8], [0.2, 0.4]], [[0.3, 0.6], [0.7, 0.9]]],
...         ),
...     },
...     coords={
...         "time": pd.date_range(start="2023-01-01", periods=2),
...         "lat": [40, 41],
...         "lon": [-80, -79],
...         "altitude": 1000,
...     },
... )

# Dataset before resetting coordinates

>>> dataset
<xarray.Dataset>
Dimensions:        (time: 2, lat: 2, lon: 2)
Coordinates:
  * time           (time) datetime64[ns] 2023-01-01 2023-01-02
  * lat            (lat) int64 40 41
  * lon            (lon) int64 -80 -79
    altitude       int64 1000
Data variables:
    temperature    (time, lat, lon) int64 25 26 27 28 29 30 31 32
    precipitation  (time, lat, lon) float64 0.5 0.8 0.2 0.4 0.3 0.6 0.7 0.9

# Reset the ‘altitude’ coordinate

>>> dataset_reset = dataset.reset_coords("altitude")

# Dataset after resetting coordinates

>>> dataset_reset
<xarray.Dataset>
Dimensions:        (time: 2, lat: 2, lon: 2)
Coordinates:
  * time           (time) datetime64[ns] 2023-01-01 2023-01-02
  * lat            (lat) int64 40 41
  * lon            (lon) int64 -80 -79
Data variables:
    temperature    (time, lat, lon) int64 25 26 27 28 29 30 31 32
    precipitation  (time, lat, lon) float64 0.5 0.8 0.2 0.4 0.3 0.6 0.7 0.9
    altitude       int64 1000
Returns:

Dataset

See also

Dataset.set_coords