Function process_xarray

hvplot/util.py:681–765

(
    data, x, y, by, groupby, use_dask, persist, gridded, label, value_label, other_dims, kind=None
)

def process_xarray(
    data, x, y, by, groupby, use_dask, persist, gridded, label, value_label, other_dims, kind=None
):
    import xarray as xr

    if isinstance(data, xr.Dataset):
        dataset = data
    else:
        name = data.name or label or value_label
        dataset = data.to_dataset(name=name)

    all_vars = list(other_dims) if other_dims else []
    for var in [x, y, by, groupby]:
        if isinstance(var, list):
            all_vars.extend(var)
        elif isinstance(var, str):
            all_vars.append(var)

    if not gridded:
        not_found = [
            var for var in all_vars if var not in list(dataset.data_vars) + list(dataset.coords)
        ]
        _, extra_vars, extra_coords = process_derived_datetime_xarray(dataset, not_found)
        dataset = dataset.assign_coords(**{var: dataset[var] for var in extra_coords})
        dataset = dataset.assign(**{var: dataset[var] for var in extra_vars})

    data_vars = list(dataset.data_vars)
    ignore = (by or []) + (groupby or [])
    dims = [c for c in dataset.coords if dataset[c].shape != () and c not in ignore][::-1]
    index_dims = [d for d in dims if d in dataset.indexes]

    if gridded:
        data = dataset
        if len(dims) < 2:
            dims += [dim for dim in list(data.dims)[::-1] if dim not in dims]
        if not (x or y):
            for c in dataset.coords:
                axis = dataset[c].attrs.get('axis', '')
                if axis.lower() == 'x':
                    x = c
                elif axis.lower() == 'y':
                    y = c
        if not (x or y):
            x, y = index_dims[:2] if len(index_dims) > 1 else dims[:2]
        elif x and not y:
            y = [d for d in dims if d != x][0]
        elif y and not x:
            x = [d for d in dims if d != y][0]
        if len(dims) > 2 and kind not in ('table', 'dataset') and not groupby:
            dims = list(data.coords[x].dims) + list(data.coords[y].dims)
            groupby = [
                d for d in index_dims if d not in (x, y) and d not in dims and d not in other_dims
            ]
    else:
        if use_dask:
            data = dataset.to_dask_dataframe()
            data = data.persist() if persist else data
        else: