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: Set numeric axis range based on the input data.
docstr_tok: ["Set","numeric","axis","range","based","on","the","input","data","."]
code: def _set_categorical_axis_default_range(
      self, vertical, data_frame, numeric_column
  ):
      """Set numeric axis range based on the input data."""
      max_value = data_frame[numeric_column].max()
      min_value = data_frame[numeric_column].min()
  
      max_ge_zero = max_value >= 0
      min_ge_zero = min_value >= 0
  
      range_start, range_end = None, None
      if max_ge_zero and min_ge_zero:
          range_start = 0
      elif not max_ge_zero and not min_ge_zero:
          range_end = 0
  
      max_value = max(max_value, 0)
      min_value = min(min_value, 0)
  
      if vertical:
          self._chart.axes.set_yaxis_range(
              start=range_start, end=range_end
          )
          self._chart.axes.set_yaxis_tick_format(
              self._axis_format_precision(max_value, min_value)
          )
      else:
          self._chart.axes.set_xaxis_range(
              start=range_start, end=range_end
          )
          self._chart.axes.set_xaxis_tick_format(
              self._axis_format_precision(max_value, min_value)
          )
  
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 2 for calling the PlotMixedTypeXY obj's underlying member method code with example usage: obj._set_categorical_axis_default_range(vertical, data_frame, numeric_column) without return types