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: Text 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.
      text_column (str): Column name to plot as text labels.
      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. Default.
          - '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.
      font_size (str, optional): Size of text.
      x_offset (int, optional): # of pixels for horizontal text offset.
          Can be negative. Default: 0.
      y_offset (int, optional): # of pixels for vertical text offset.
          Can be negative. Default: 0.
      angle (int): Degrees from horizontal for text rotation.
      text_color (str): Color name or hex value.
          See chartify.color_palettes.show() for available color names.
          If omitted, will default to the next color in
          the current color palette.
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code: def text(
      self,
      data_frame,
      categorical_columns,
      numeric_column,
      text_column,
      color_column=None,
      color_order=None,
      categorical_order_by="values",
      categorical_order_ascending=False,
      font_size="1em",
      x_offset=0,
      y_offset=0,
      angle=0,
      text_color=None,
  ):
      """Text 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.
          text_column (str): Column name to plot as text labels.
          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. Default.
              - '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.
          font_size (str, optional): Size of text.
          x_offset (int, optional): # of pixels for horizontal text offset.
              Can be negative. Default: 0.
          y_offset (int, optional): # of pixels for vertical text offset.
              Can be negative. Default: 0.
          angle (int): Degrees from horizontal for text rotation.
          text_color (str): Color name or hex value.
              See chartify.color_palettes.show() for available color names.
              If omitted, will default to the next color in
              the current color palette.
      """
      vertical = self._chart.axes._vertical
      text_font = self._chart.style._get_settings(
          "text_callout_and_plot"
      )["font"]
  
      source, factors, _ = self._construct_source(
          data_frame,
          categorical_columns,
          numeric_column,
          categorical_order_by=categorical_order_by,
          categorical_order_ascending=categorical_order_ascending,
      )
  
      if text_color:
          text_color = Color(text_color).get_hex_l()
          colors, color_values = [text_color], [None]
      else:
          colors, color_values = self._get_color_and_order(
              data_frame, color_column, color_order
          )
  
      self._set_categorical_axis_default_factors(vertical, factors)
  
      if vertical:
          text_align = "center"
          text_baseline = "bottom"
          x_value, y_value = "factors", numeric_column
          y_offset = y_offset - 4
      else:
          y_value, x_value = "factors", numeric_column
          text_align = "left"
          text_baseline = "middle"
          x_offset = x_offset + 10
  
      for color_value, color in zip(color_values, colors):
          if color_column is None:  # Single series
              sliced_data = data_frame
          else:
              sliced_data = data_frame[
                  data_frame[color_column] == color_value
              ]
  
          # Construct a new source based on the sliced data.
          source, _, _ = self._construct_source(
              sliced_data,
              categorical_columns,
              numeric_column,
              categorical_order_by=categorical_order_by,
              categorical_order_ascending=categorical_order_ascending,
          )
          sliced_data = (
              sliced_data.astype(str)
              .set_index(categorical_columns)
              .reindex(source.data["factors"])
              .reset_index()
          )
          # Text column isn't in the source so it needs to be added.
          sliced_data["text_column"] = sliced_data[text_column]
          source.add(sliced_data["text_column"], name="text_column")
  
          self._chart.figure.text(
              text="text_column",
              x=x_value,
              y=y_value,
              text_font_size=font_size,
              source=source,
              text_color=color,
              y_offset=y_offset,
              x_offset=x_offset,
              angle=angle,
              angle_units="deg",
              text_align=text_align,
              text_baseline=text_baseline,
              text_font=text_font,
          )
  
      return self._chart
  
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 8 for calling the PlotMixedTypeXY obj's underlying member method code with example usage: obj.text(data_frame, categorical_columns, numeric_column, text_column, color_column, color_order, categorical_order_by, categorical_order_ascending, font_size, x_offset, y_offset, angle, text_color) and returns: self