class_docstr: Container for data heatmap calculation and visualization.
  
  This class (object) is returned from the ``data_heatmap`` function. The
  attributes documented below can be accessed or extracted.
  
  
  Attributes:
      input_data: The input data.
      colnames: Names of numeric columns.
      std_data: The transposed, standardized data after scaling.
      missing: If True, the heatmap shows missing values as indicators
          instead of standardized values.
      missing_data: The missing value indicator data.
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docstr: Data heatmap.
  
  Args:
      input_data: The input data.
      colnames: Names of numeric columns.
      std_data: The transposed, standardized data after scaling.
      missing (bool): If True, the heatmap shows missing values as indicators
          instead of standardized values.
      missing_data: The missing value indicator data.
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code: def __init__(
      self,
      input_data=None,
      colnames=None,
      std_data=None,
      missing=False,
      missing_data=None,
      **kwargs,
  ):
      """Data heatmap.
  
      Args:
          input_data: The input data.
          colnames: Names of numeric columns.
          std_data: The transposed, standardized data after scaling.
          missing (bool): If True, the heatmap shows missing values as indicators
              instead of standardized values.
          missing_data: The missing value indicator data.
      """
      super(HeatmapWidget, self).__init__(**kwargs)
      self.input_data = input_data
      self.colnames = colnames
      self.std_data = std_data
      self.missing = missing
      self.missing_data = missing_data
      self.viz_data = missing_data if missing else std_data
  
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 1 to create a new HeatmapWidget object from inherited base classes: BaseWidget with example: obj = HeatmapWidget(input_data, colnames, std_data, missing, missing_data)