code: def _clustering_params_to_dataframe(
      threshold,
      cluster_threshold,
      min_distance,
      height_control,
      alpha,
  ):
      """Create a Pandas DataFrame from the supplied arguments.
  
      For use as part of the Cluster Table.
  
      Parameters
      ----------
      threshold : float
          Cluster forming threshold in same scale as `stat_img` (either a
          p-value or z-scale value).
  
      cluster_threshold : int or None
          Cluster size threshold, in voxels.
  
      min_distance : float, default=8
          For display purposes only.
          Minimum distance between subpeaks in mm.
  
      height_control : string or None
          False positive control meaning of cluster forming
          threshold: 'fpr' (default) or 'fdr' or 'bonferroni' or None
  
      alpha : float
          Number controlling the thresholding (either a p-value or q-value).
          Its actual meaning depends on the height_control parameter.
          This function translates alpha to a z-scale threshold.
  
      Returns
      -------
      table_details : Pandas.DataFrame
          Dataframe with clustering parameters.
  
      """
      table_details = OrderedDict()
      threshold = np.around(threshold, 3)
      if height_control:
          table_details.update({"Height control": height_control})
          """
          HTMLDocument.get_iframe() invoked in Python2 Jupyter Notebooks
          mishandles certain unicode characters
          & raises error due to greek alpha symbol.
          This is simpler than overloading the class using inheritance,
          especially given limited Python2 use at time of release.
          """
          if os.sys.version_info.major == 2:
              table_details.update({"alpha": alpha})
          else:
              table_details.update({"\u03B1": alpha})
          table_details.update({"Threshold (computed)": threshold})
      else:
          table_details.update({"Height control": "None"})
          table_details.update({"Threshold Z": threshold})
      table_details.update(
          {"Cluster size threshold (voxels)": cluster_threshold}
      )
      table_details.update({"Minimum distance (mm)": min_distance})
      table_details = pd.DataFrame.from_dict(
          table_details,
          orient="index",
      )
      return table_details
  
imports: import os
  import string
  import warnings
  from collections import OrderedDict
  from collections.abc import Iterable
  from html import escape
  import numpy
  import pandas
  from matplotlib import pyplot
  from nilearn.plotting import plot_glass_brain, plot_roi, plot_stat_map
  from nilearn.plotting.img_plotting import MNI152TEMPLATE
  from nilearn.plotting.matrix_plotting import plot_contrast_matrix, plot_design_matrix
  from nilearn.reporting.html_report import HTMLReport
  from .._utils import fill_doc
  from nilearn._utils import check_niimg
  from nilearn.maskers import NiftiMasker
  from nilearn.reporting.get_clusters_table import get_clusters_table
  from nilearn.reporting.utils import figure_to_svg_quoted
label_desc: Use image node_id 13 for calling a global function with example usage: _clustering_params_to_dataframe(threshold, cluster_threshold, min_distance, height_control, alpha) and returns: table_details