code: def _call_series(self, a, inputs):
      if isinstance(self._q, TENSOR_TYPE):
          q_val = self._q
          index_val = pd.Index([], dtype=q_val.dtype)
          store_index_value = False
      else:
          q_val = np.asanyarray(self._q)
          index_val = pd.Index(q_val)
          store_index_value = True
  
      # get dtype by tensor
      a_t = astensor(a)
      self._dtype = dtype = tensor_quantile(
          a_t,
          self._q,
          interpolation=self._interpolation,
          handle_non_numeric=not self._numeric_only,
      ).dtype
  
      if q_val.ndim == 0:
          return self.new_scalar(inputs, dtype=dtype)
      else:
          return self.new_series(
              inputs,
              shape=q_val.shape,
              dtype=dtype,
              index_value=parse_index(
                  index_val,
                  a,
                  q_val,
                  self._interpolation,
                  type(self).__name__,
                  store_data=store_index_value,
              ),
              name=a.name,
          )
  
imports: from collections import OrderedDict
  import numpy
  import pandas
  from ...None import opcodes
  from ...core import ENTITY_TYPE, recursive_tile
  from ...serialization.serializables import KeyField, AnyField, StringField, DataTypeField, BoolField, Int32Field
  from ...tensor.core import TENSOR_TYPE, TENSOR_CHUNK_TYPE
  from ...tensor.datasource import empty, tensor, from_series, from_dataframe
  from ...tensor.statistics.quantile import quantile
  from ..operands import DataFrameOperand, DataFrameOperandMixin
  from ..core import DATAFRAME_TYPE
  from ..datasource.from_tensor import series_from_tensor, dataframe_from_tensor
  from ..initializer import DataFrame
  from ..utils import parse_index, build_empty_df, find_common_type, validate_axis
label_desc: Use image node_id 10 for calling the DataFrameQuantile obj's underlying member method code with example usage: obj._call_series(a, inputs) and returns: self, self