class_docstr: This class is intended to build correlation matrix plot.
  
  Examples
  --------
  .. jupyter-execute::
      :linenos:
      :emphasize-lines: 7
  
      import numpy as np
      from lets_plot import *
      from lets_plot.bistro.corr import *
      LetsPlot.setup_html()
      np.random.seed(42)
      data = {var: np.random.poisson(size=10) for var in 'abcdef'}
      corr_plot(data).tiles().build()
  
  |
  
  .. jupyter-execute::
      :linenos:
      :emphasize-lines: 7-9
  
      import numpy as np
      from lets_plot import *
      from lets_plot.bistro.corr import *
      LetsPlot.setup_html()
      np.random.seed(42)
      data = {var: np.random.uniform(size=10) for var in 'abcd'}
      corr_plot(data).tiles(type='upper', diag=True)\
          .labels(type='upper', diag=True, map_size=True, color='black')\
          .palette_RdBu().build()
  
  |
  
  .. jupyter-execute::
      :linenos:
      :emphasize-lines: 7-9
  
      import numpy as np
      from lets_plot import *
      from lets_plot.bistro.corr import *
      LetsPlot.setup_html()
      np.random.seed(42)
      data = {var: np.random.normal(size=10) for var in 'abcdef'}
      corr_plot(data, flip=False, threshold=.4).points().labels()\
          .palette_gradient(low='#d73027', mid='#ffffbf', high='#1a9850')\
          .build()
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code: def _set_labels(
      self, type=None, diag=None, map_size=None, color=None
  ):
      self._labels_params = {
          "type": type,
          "diag": diag,
          "color": color,
          "threshold": self.threshold,
      }
      self._labels_map_size = map_size
      return self
  
imports: from typing import Any
  from lets_plot.plot.util import is_data_frame
  from lets_plot.plot.core import PlotSpec
label_desc: Use image node_id 17 for calling the corr_plot obj's underlying member method code with example usage: obj._set_labels(type, diag, map_size, color) and returns: self