code: def _get_table_row_data(
      n_samples,
      annotation_ratio,
      categorical_metadata,
      numerical_metadata,
      categorical_properties,
      numerical_properties,
      max_values_to_show: int = 5,
  ):
      info_cell = [n_samples, annotation_ratio]
  
      if categorical_metadata is None or len(categorical_metadata) == 0:
          info_cell.append("No categorical metadata")
      else:
          info_cell.append(
              ", ".join(categorical_metadata)
              if len(categorical_metadata) <= max_values_to_show
              else f"{len(categorical_metadata)} metadata columns"
          )
  
      if numerical_metadata is None or len(numerical_metadata) == 0:
          info_cell.append("No numerical metadata")
      else:
          info_cell.append(
              ", ".join(numerical_metadata)
              if len(numerical_metadata) <= max_values_to_show
              else f"{len(numerical_metadata)} metadata columns"
          )
  
      if (
          categorical_properties is None
          or len(categorical_properties) == 0
      ):
          info_cell.append("No categorical properties")
      else:
          info_cell.append(
              ", ".join(categorical_properties)
              if len(categorical_properties) <= max_values_to_show
              else f"{len(categorical_properties)} properties"
          )
  
      if numerical_properties is None or len(numerical_properties) == 0:
          info_cell.append("No numerical properties")
      else:
          info_cell.append(
              ", ".join(numerical_properties)
              if len(numerical_properties) <= max_values_to_show
              else f"{len(numerical_properties)} properties"
          )
  
      return info_cell
  
file_path: deepchecks/deepchecks/nlp/utils/text_data_plot.py
imports: from typing import List, Optional
  import numpy
  import pandas
  import plotly.graph_objs
  from plotly.subplots import make_subplots
  from deepchecks.nlp.task_type import TaskType, TTextLabel
  from deepchecks.nlp.utils.text import break_to_lines_and_trim
  from deepchecks.nlp.utils.text_properties import TEXT_PROPERTIES_DESCRIPTION
  from deepchecks.utils.dataframes import un_numpy
  from deepchecks.utils.distribution.plot import get_density
  from deepchecks.utils.plot import feature_distribution_colors
  from deepchecks.utils.strings import format_percent, get_docs_link
label_desc: Use image node_id 2 for calling a global function with example usage: _get_table_row_data(n_samples, annotation_ratio, categorical_metadata, numerical_metadata, categorical_properties, numerical_properties, max_values_to_show) and returns: info_cell