Bases: QualityChecker
Checks if any data are missing. A variable's data are considered missing if they are
set to the variable's _FillValue (if it has a _FillValue) or NaN (NaT for datetime-
like variables).
Methods:
Functions
run
run(
dataset: xr.Dataset, variable_name: str
) -> NDArray[np.bool_]
Source code in tsdat/qc/checkers/check_missing.py
| def run(self, dataset: xr.Dataset, variable_name: str) -> NDArray[np.bool_]:
results: NDArray[np.bool_] = dataset[variable_name].isnull().data
if "_FillValue" in dataset[variable_name].attrs:
fill_value = dataset[variable_name].attrs["_FillValue"]
results |= dataset[variable_name].data == fill_value
elif np.issubdtype(dataset[variable_name].data.dtype, str): # type: ignore
fill_value = ""
results |= dataset[variable_name].data == fill_value
return results
|