xarray.Dataset.pint.quantify

Dataset.pint.quantify(units=<object object>, unit_registry=None, **unit_kwargs)

Attach units to the variables of the Dataset.

Units can be specified as a pint.Unit or as a string, which will be parsed by the given unit registry. If no units are specified then the units will be parsed from the "units" entry of the Dataset variable’s .attrs. Will raise a ValueError if any of the variables already contain a unit-aware array with a different unit.

Note

Be aware that unless you’re using dask this will load the data into memory. To avoid that, consider converting to dask first (e.g. using chunk).

Note

Also note that datetime units (i.e. ones that match {units} since {date}) in unit attributes will be ignored, to avoid interfering with xarray’s datetime encoding / decoding.

Parameters:

units (mapping of hashable to unit-like, optional) – Physical units to use for particular DataArrays in this Dataset. It should map variable names to units (unit names or pint.Unit objects). If not provided, quantify will try to read them from Dataset[var].attrs['units'] using pint’s parser. The "units" attribute will be removed from all variables except from dimension coordinates.
unit_registry (pint.UnitRegistry, optional) – Unit registry to be used for the units attached to each DataArray in this Dataset. If not given then a default registry will be created.
**unit_kwargs – Keyword argument form of units.

Returns:

quantified – Dataset whose variables will now contain Quantity arrays with units.

Return type:

Dataset

Notes

"none" and None can be used to mark variables that should not be quantified.

Examples

>>> ds = xr.Dataset(
...     {"a": ("x", [0, 3, 2], {"units": "m"}), "b": ("x", [5, -2, 1])},
...     coords={"x": [0, 1, 2], "u": ("x", [-1, 0, 1], {"units": "s"})},
... )

>>> ds.pint.quantify()
<xarray.Dataset> Size: 96B
Dimensions:  (x: 3)
Coordinates:
  * x        (x) int64 24B 0 1 2
    u        (x) int64 24B [s] -1 0 1
Data variables:
    a        (x) int64 24B [m] 0 3 2
    b        (x) int64 24B 5 -2 1
>>> ds.pint.quantify({"b": "dm"})
<xarray.Dataset> Size: 96B
Dimensions:  (x: 3)
Coordinates:
  * x        (x) int64 24B 0 1 2
    u        (x) int64 24B [s] -1 0 1
Data variables:
    a        (x) int64 24B [m] 0 3 2
    b        (x) int64 24B [dm] 5 -2 1

Don’t quantify specific variables:

>>> ds.pint.quantify({"a": None})
<xarray.Dataset> Size: 96B
Dimensions:  (x: 3)
Coordinates:
  * x        (x) int64 24B 0 1 2
    u        (x) int64 24B [s] -1 0 1
Data variables:
    a        (x) int64 24B 0 3 2
    b        (x) int64 24B 5 -2 1

Quantify with the same unit:

>>> q = ds.pint.quantify()
>>> q
<xarray.Dataset> Size: 96B
Dimensions:  (x: 3)
Coordinates:
  * x        (x) int64 24B 0 1 2
    u        (x) int64 24B [s] -1 0 1
Data variables:
    a        (x) int64 24B [m] 0 3 2
    b        (x) int64 24B 5 -2 1
>>> q.pint.quantify({"a": "m"})
<xarray.Dataset> Size: 96B
Dimensions:  (x: 3)
Coordinates:
  * x        (x) int64 24B 0 1 2
    u        (x) int64 24B [s] -1 0 1
Data variables:
    a        (x) int64 24B [m] 0 3 2
    b        (x) int64 24B 5 -2 1