code: def build(self, parent):
      if parent.classifier == "D":
          parent.data.loc[:, parent.selected_col] = apply(
              parent.data[parent.selected_col], json_timestamp
          )
      kde_code = []
      if self.target is None:
          return_data, hist_labels = self.build_histogram_data(
              parent.data[parent.selected_col]
          )
          kde, kde_code = build_kde(
              parent.data[parent.selected_col],
              hist_labels,
              parent.selected_col,
          )
          if kde is not None:
              return_data["kde"] = kde
      else:
          bin_vals = pd.cut(
              parent.data[parent.selected_col], bins=self.bins
          )
          labels = ["{}".format(c) for c in bin_vals.dtype.categories]
          parent.data.loc[:, "bin"] = bin_vals.astype("str")
          return_data = {"targets": [], "labels": labels}
          target_dtype = find_dtype(parent.data[self.target])
          target_formatter = find_dtype_formatter(target_dtype)
          for target, target_data in parent.data[
              [self.target, "bin"]
          ].groupby(self.target):
              target_counts = target_data["bin"].value_counts()
              target_counts = [
                  int(tc)
                  for tc in target_counts.reindex(
                      labels, fill_value=0
                  ).values
              ]
              return_data["targets"].append(
                  dict(
                      target=target_formatter(target, as_string=True),
                      data=target_counts,
                  )
              )
  
      desc, desc_code = load_describe(parent.data[parent.selected_col])
      dtype_info = global_state.get_dtype_info(
          parent.data_id, parent.selected_col
      )
      for p in ["skew", "kurt"]:
          if p in dtype_info:
              desc[p] = dtype_info[p]
  
      return_data["desc"] = desc
      return return_data, self._build_code(parent, kde_code, desc_code)
  
imports: import numpy
  import pandas
  import plotly.express
  import plotly.graph_objs
  import pprint
  import scipy.stats
  import time
  import dtale.global_state
  import dtale.pandas_util
  from dtale.code_export import build_code_export, build_final_chart_code
  from dtale.column_builders import clean, clean_code
  from dtale.describe import load_describe
  from dtale.query import build_query, load_filterable_data
  from dtale.utils import apply, classify_type, find_dtype, find_dtype_formatter, find_selected_column, get_bool_arg, get_int_arg, get_str_arg, grid_columns, grid_formatter, json_float, json_timestamp, make_list
label_desc: Use image node_id 3 for calling the HistogramAnalysis obj's underlying member method code with example usage: obj.build(parent) and returns: return_data,  self