def process_derived_datetime_xarray(data, not_found):
from pandas.api.types import is_datetime64_any_dtype as isdate
extra_vars = []
extra_coords = []
for var in not_found:
if '.' in var:
derived_from = var.split('.')[0]
if isdate(data[derived_from]):
if derived_from in data.coords:
extra_coords.append(var)
else:
extra_vars.append(var)
not_found = [var for var in not_found if var not in extra_vars + extra_coords]
return not_found, extra_vars, extra_coords
def process_derived_datetime_pandas(data, not_found, indexes=None):
from pandas.api.types import is_datetime64_any_dtype as isdate
indexes = indexes or []
extra_cols = {}
for var in not_found:
if '.' in var:
parts = var.split('.')
base_col = parts[0]
dt_str = parts[-1]
if base_col in data.columns:
if isdate(data[base_col]):
extra_cols[var] = getattr(data[base_col].dt, dt_str)
elif base_col == 'index':
if isdate(data.index):
extra_cols[var] = getattr(data.index, dt_str)
elif base_col in indexes:
index = data.axes[indexes.index(base_col)]
if isdate(index):
extra_cols[var] = getattr(index, dt_str)
data = data.assign(**extra_cols)
not_found = [var for var in not_found if var not in extra_cols.keys()]
return not_found, data