code: def aggregate(cls, dataset, dimensions, function, **kwargs):
      data = dataset.data
      cols = [d.name for d in dataset.kdims if d in dimensions]
      vdims = dataset.dimensions("value", label="name")
      reindexed = data[cols + vdims]
      if function in [np.std, np.var]:
          # Fix for consistency with other backend
          # pandas uses ddof=1 for std and var
          fn = lambda x: function(x, ddof=0)
      else:
          fn = util._PANDAS_FUNC_LOOKUP.get(function, function)
      if len(dimensions):
          # The reason to use `numeric_cols` is to prepare for when pandas will not
          # automatically drop columns that are not numerical for numerical
          # functions, e.g., `np.mean`.
          # pandas started warning about this in v1.5.0
          if function in [np.size]:
              # np.size actually works with non-numerical columns
              numeric_cols = [
                  c for c in reindexed.columns if c not in cols
              ]
          else:
              numeric_cols = [
                  c
                  for c, d in zip(reindexed.columns, reindexed.dtypes)
                  if is_numeric_dtype(d) and c not in cols
              ]
          grouped = reindexed.groupby(cols, sort=False)
          df = (
              grouped[numeric_cols]
              .aggregate(fn, **kwargs)
              .reset_index()
          )
      else:
          agg = reindexed.apply(fn, **kwargs)
          data = {col: [v] for col, v in zip(agg.index, agg.values)}
          df = pd.DataFrame(data, columns=list(agg.index))
  
      dropped = []
      for vd in vdims:
          if vd not in df.columns:
              dropped.append(vd)
      return df, dropped
  
imports: import numpy
  import pandas
  from packaging.version import Version
  from pandas.api.types import is_numeric_dtype
  from ..None import util
  from ..dimension import Dimension, dimension_name
  from ..element import Element
  from ..ndmapping import NdMapping, item_check, sorted_context
  from .interface import DataError, Interface
  from .util import finite_range
label_desc: Use image node_id 9 for calling the PandasInterface obj's underlying member method code with example usage: obj.aggregate(cls, dataset, dimensions, function) and returns: df,  dropped