code: def _pandas_compute_data_heatmap(
      data, missing: bool = False, **kwargs
  ) -> HeatmapWidget:
      """Pre-processes data for the data heatmap.
  
      Values are standardized (removing the mean and scaling to unit variance).
      If `missing` is set to True, the dataframe flags missing records using 1/0.
  
      Args:
          data: The dataframe
          missing (bool): If True, uses missing values instead
          **kwargs: Keyword arguments.
  
      Raises:
          ValueError: Invalid input data type.
  
      Returns:
          HeatmapWidget
      """
      if not _is_dataframe(data):
          raise ValueError("Unsupported input data type")
  
      if missing:
          missing_data = data.isna().astype(int)
          colnames = data.columns.values
          return HeatmapWidget(
              input_data=data,
              colnames=colnames,
              missing=True,
              missing_data=missing_data.transpose(),
          )
      else:
          data = data.select_dtypes(["number"])
          colnames = data.columns.values
          scaler = StandardScaler()
          std_data = pd.DataFrame(
              scaler.fit_transform(data), columns=data.columns
          )
          return HeatmapWidget(
              input_data=data,
              colnames=colnames,
              std_data=std_data.transpose(),
          )
  
imports: from typing import List
  import pandas
  import numpy
  from plotly.offline import init_notebook_mode, iplot
  from matplotlib.figure import Figure
  import seaborn
  import plotly.graph_objs
  from sklearn.preprocessing import StandardScaler
  from data_describe._widget import BaseWidget
  from data_describe.config._config import get_option
  from data_describe.compat import _is_dataframe, _requires, _in_notebook
  from data_describe.backends import _get_viz_backend, _get_compute_backend
label_desc: Use image node_id 2 for calling a global function with example usage: _pandas_compute_data_heatmap(data, missing) and returns: HeatmapWidget, HeatmapWidget