code: def make_agg(self, mapping, precomputed, scales):
      grouping_variables = {
          aes_key: mapping[aes_key]
          for aes_key in mapping.keys()
          if should_use_scale_for_grouping(scales[aes_key])
      }
  
      start = (
          self.min_val
          if self.min_val is not None
          else precomputed.min_val
      )
      end = (
          self.max_val
          if self.max_val is not None
          else precomputed.max_val
      )
      if self.bins is None:
          warning(
              f"No number of bins was specfied for geom_histogram, defaulting to {self.DEFAULT_BINS} bins"
          )
          bins = self.DEFAULT_BINS
      else:
          bins = self.bins
      return hl.agg.group_by(
          hl.struct(**grouping_variables),
          hl.agg.hist(mapping["x"], start, end, bins),
      )
  
imports: from typing import List
  import abc
  from pandas import DataFrame
  import pandas
  import hail
  from hail.utils.java import warning
  from .utils import should_use_scale_for_grouping
label_desc: Use image node_id 3 for calling the StatBin obj's underlying member method code with example usage: obj.make_agg(mapping, precomputed, scales) and returns: hl