def length(cls, dataset):
from holoviews.core.data import PandasInterface
length = sum([geom_length(g) for g in dataset.data.geometry])
geom_type = dataset.data.geom_type.iloc[0]
if geom_type != 'Point':
length += (PandasInterface.length(dataset)-1)
return length
def sort(cls, dataset, by=[], reverse=False):
geo_dims = cls.geom_dims(dataset)
if any(d in geo_dims for d in by):
raise DataError(
"SpatialPandasInterface does not allow sorting "
"by geometry dimension.", cls)
return PandasInterface.sort(dataset, by, reverse)
def groupby(cls, dataset, dimensions, container_type, group_type, **kwargs):
geo_dims = cls.geom_dims(dataset)
if any(d in geo_dims for d in dimensions):
raise DataError("GeoPandasInterface does not allow grouping "
"by geometry dimension.", cls)
return PandasInterface.groupby(dataset, dimensions, container_type, group_type, **kwargs)
def redim(cls, dataset, dimensions):
return PandasInterface.redim(dataset, dimensions)
def select(cls, dataset, selection_mask=None, **selection):
from holoviews.core.data import PandasInterface
return PandasInterface.select(dataset, selection_mask, **selection)
def redim(cls, dataset, dimensions):
from holoviews.core.data import PandasInterface
return PandasInterface.redim(dataset, dimensions)
def shape(cls, dataset):
from holoviews.core.data import PandasInterface
return PandasInterface.shape(dataset)
def groupby(cls, columns, dimensions, container_type, group_type, **kwargs):
from holoviews.core.data import PandasInterface
return PandasInterface.groupby(columns, dimensions, container_type, group_type, **kwargs)