docstr: Area plot.
  
  Args:
      data_frame (pandas.DataFrame): Data source for the plot.
      radius_column (str): Column name containing radius values.
      color_column (str, optional): Column name to group by on
          the color dimension.
      color_order (list, optional): List of values within the
          'color_column' for specific sorting of the colors.
      alpha (float): Alpha value.
docstr_tok: ["Area","plot",".","Args",":","data_frame","(","pandas.DataFrame",")",":","Data","source","for","the","plot",".","radius_column","(","str",")",":","Column","name","containing","radius","values",".","color_column","(","str",",","optional",")",":","Column","name","to","group","by","on","the","color","dimension",".","color_order","(","list",",","optional",")",":","List","of","values","within","the","'color_column","'","for","specific","sorting","of","the","colors",".","alpha","(","float",")",":","Alpha","value","."]
code: def area(
      self,
      data_frame,
      radius_column,
      color_column=None,
      color_order=None,
      alpha=0.2,
  ):
      """Area plot.
  
      Args:
          data_frame (pandas.DataFrame): Data source for the plot.
          radius_column (str): Column name containing radius values.
          color_column (str, optional): Column name to group by on
              the color dimension.
          color_order (list, optional): List of values within the
              'color_column' for specific sorting of the colors.
          alpha (float): Alpha value.
      """
      colors, color_values = self._get_color_and_order(
          data_frame, color_column, color_order
      )
  
      self._set_numeric_axis_default_format(
          data_frame, radius_column, radius_column
      )
  
      for color_value, color in zip(color_values, colors):
          if color_column is None:  # Single line
              sliced_data = data_frame
          else:
              sliced_data = data_frame[
                  data_frame[color_column] == color_value
              ]
  
          coord_df = sliced_data[[radius_column]].copy()
          coord_df[self._THETA_COLUMN] = self._get_thetas(len(coord_df))
          coord_df[
              [self._X_COLUMN, self._Y_COLUMN]
          ] = self._to_xy_coords(
              coord_df, radius_column, self._THETA_COLUMN
          )
          # Add endpoint
          coord_df = pd.concat(
              [coord_df, pd.DataFrame([coord_df.iloc[0]])]
          )
  
          source = self._named_column_data_source(
              coord_df, series_name=color_value
          )
  
          color_value = (
              str(color_value)
              if color_value is not None
              else color_value
          )
  
          self._plot_with_legend(
              self._chart.figure.patch,
              legend_label=color_value,
              x=self._X_COLUMN,
              y=self._Y_COLUMN,
              source=source,
              color=color,
              line_width=0,
              alpha=alpha,
              y_range_name=self._y_range_name,
          )
  
      # Set legend defaults if there are multiple series.
      if color_column is not None:
          self._chart.style._apply_settings("legend")
  
      return self._chart
  
imports: from chartify._core.colors import Color
  from chartify._core.chart import Chart
  from chartify._core.style import Style
  from chartify._core.axes import BaseAxes
  from chartify._core.plot import BasePlot
  from chartify._core.callout import Callout
  from chartify._core.options import options
  import numpy
  import pandas
label_desc: Use image node_id 5 for calling the PlotRadar obj's underlying member method code with example usage: obj.area(data_frame, radius_column, color_column, color_order, alpha) and returns: self