class_docstr: Plot functions for mixed type x & y axes:
  
  Methods:
      - bar
      - bar_stacked
      - lollipop
      - parallel
class_docstr_tok: ["Plot","functions","for","mixed","type","x","&","y","axes",":","Methods",":","-","bar","-","bar_stacked","-","lollipop","-","parallel"]
docstr: Parallel coordinate plot.
  
  Args:
      data_frame (pandas.DataFrame): Data source for the plot.
      categorical_columns (str or list): Column name to plot on
          the categorical axis.
      numeric_column (str): Column name to plot on the numerical axis.
      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 color sort.
      categorical_order_by (str or array-like, optional):
          Dimension for ordering the categorical axis. Default 'values'.
          - 'values': Order categorical axis by the numerical axis values.
          - 'labels': Order categorical axis by the categorical labels.
          - array-like object (list, tuple, np.array): New labels
              to conform the categorical axis to.
      categorical_order_ascending (bool, optional):
          Sort order of the categorical axis. Default False.
      line_dash (str, optional): Dash style for the line. One of:
          - 'solid'
          - 'dashed'
          - 'dotted'
          - 'dotdash'
          - 'dashdot'
      line_width (int, optional): Width of the line
      alpha (float): Alpha value
docstr_tok: ["Parallel","coordinate","plot",".","Args",":","data_frame","(","pandas.DataFrame",")",":","Data","source","for","the","plot",".","categorical_columns","(","str","or","list",")",":","Column","name","to","plot","on","the","categorical","axis",".","numeric_column","(","str",")",":","Column","name","to","plot","on","the","numerical","axis",".","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","color","sort",".","categorical_order_by","(","str","or","array-like",",","optional",")",":","Dimension","for","ordering","the","categorical","axis",".","Default","'values","'",".","-","'values","'",":","Order","categorical","axis","by","the","numerical","axis","values",".","-","'labels","'",":","Order","categorical","axis","by","the","categorical","labels",".","-","array-like","object","(","list",",","tuple",",","np.array",")",":","New","labels","to","conform","the","categorical","axis","to",".","categorical_order_ascending","(","bool",",","optional",")",":","Sort","order","of","the","categorical","axis",".","Default","False",".","line_dash","(","str",",","optional",")",":","Dash","style","for","the","line",".","One","of",":","-","'solid'","-","'dashed'","-","'dotted'","-","'dotdash'","-","'dashdot'","line_width","(","int",",","optional",")",":","Width","of","the","line","alpha","(","float",")",":","Alpha","value"]
code: def parallel(
      self,
      data_frame,
      categorical_columns,
      numeric_column,
      color_column=None,
      color_order=None,
      categorical_order_by="values",
      categorical_order_ascending=False,
      line_dash="solid",
      line_width=4,
      alpha=1.0,
  ):
      """Parallel coordinate plot.
  
      Args:
          data_frame (pandas.DataFrame): Data source for the plot.
          categorical_columns (str or list): Column name to plot on
              the categorical axis.
          numeric_column (str): Column name to plot on the numerical axis.
          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 color sort.
          categorical_order_by (str or array-like, optional):
              Dimension for ordering the categorical axis. Default 'values'.
              - 'values': Order categorical axis by the numerical axis values.
              - 'labels': Order categorical axis by the categorical labels.
              - array-like object (list, tuple, np.array): New labels
                  to conform the categorical axis to.
          categorical_order_ascending (bool, optional):
              Sort order of the categorical axis. Default False.
          line_dash (str, optional): Dash style for the line. One of:
              - 'solid'
              - 'dashed'
              - 'dotted'
              - 'dotdash'
              - 'dashdot'
          line_width (int, optional): Width of the line
          alpha (float): Alpha value
      """
      settings = self._chart.style._get_settings("line_plot")
      line_cap = settings["line_cap"]
      line_join = settings["line_join"]
  
      vertical = self._chart.axes._vertical
  
      source, factors, _ = self._construct_source(
          data_frame,
          categorical_columns,
          numeric_column,
          # Each color has its own stack for parallel plots.
          # This causes each color to appear as its own column.
          stack_column=color_column,
          categorical_order_by=categorical_order_by,
          categorical_order_ascending=categorical_order_ascending,
      )
  
      colors, color_values = self._get_color_and_order(
          data_frame, color_column, color_order
      )
  
      self._set_categorical_axis_default_factors(vertical, factors)
      self._set_numeric_axis_default_format(
          data_frame, numeric_column, numeric_column
      )
  
      for color_value, color in zip(color_values, colors):
          if color_column is None:  # Single series
              color_value = numeric_column
              legend = None
          else:
              legend = str(color_value)
  
          if vertical:
              x_value, y_value = "factors", str(color_value)
          else:
              y_value, x_value = "factors", str(color_value)
  
          self._plot_with_legend(
              self._chart.figure.line,
              legend_label=legend,
              x=x_value,
              y=y_value,
              source=source,
              line_width=line_width,
              color=color,
              line_join=line_join,
              line_cap=line_cap,
              line_dash=line_dash,
              alpha=alpha,
          )
  
      # Set legend defaults if there are multiple series.
      if color_column is not None:
          self._chart.style._apply_settings("legend")
  
imports: import bokeh
  import pandas
  import numpy
  from chartify._core.colors import Color, color_palettes
  from chartify._core.axes import NumericalYMixin, NumericalXMixin
  from scipy.stats import gaussian_kde
label_desc: Use image node_id 14 for calling the PlotMixedTypeXY obj's underlying member method code with example usage: obj.parallel(data_frame, categorical_columns, numeric_column, color_column, color_order, categorical_order_by, categorical_order_ascending, line_dash, line_width, alpha) without return types