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Python Bokeh – Plotting Ellipses on a Graph
  • Last Updated : 03 Jul, 2020

Bokeh is a Python interactive data visualization. It renders its plots using HTML and JavaScript. It targets modern web browsers for presentation providing elegant, concise construction of novel graphics with high-performance interactivity.

Bokeh can be used to plot ellipses on a graph. Plotting ellipses on a graph can be done using the ellipse() method of the plotting module.

plotting.figure.ellipse()

Syntax : ellipse(parameters)

Parameters :

  • x : x-coordinates of the center of the ellipse
  • y : y-coordinates of the center of the ellipse
  • width : width of each ellipse
  • height : height of each ellipse
  • angle : angle of rotation of the ellipse, default is 0
  • angle_units : unit of the angle, default is rad
  • fill_alpha : fill alpha value of the ellipse
  • fill_color : fill color value of the ellipse
  • height_units : unit of the height, default isdata
  • line_alpha : percentage value of line alpha, default is 1
  • line_cap : value of line cap for the line, default is butt
  • line_color : color of the line, default is black
  • line_dash : value of line dash such as :
    • solid
    • dashed
    • dotted
    • dotdash
    • dashdot

    default is solid

  • line_dash_offset : value of line dash offset, default is 0
  • line_join : value of line join, default in bevel
  • line_width : value of the width of the line, default is 1
  • name : user-supplied name for the model
  • tags : user-supplied values for the model

Other Parameters :



  • alpha : sets all alpha keyword arguments at once
  • color : sets all color keyword arguments at once
  • legend_field : name of a column in the data source that should be used
  • legend_group : name of a column in the data source that should be used
  • legend_label : labels the legend entry
  • muted : determines whether the glyph should be rendered as muted or not, default is False
  • name : optional user-supplied name to attach to the renderer
  • source : user-supplied data source
  • view : view for filtering the data source
  • visible : determines whether the glyph should be rendered or not, default is True
  • x_range_name : name of an extra range to use for mapping x-coordinates
  • y_range_name : name of an extra range to use for mapping y-coordinates
  • level : specifies the render level order for this glyph

Returns : an object of class GlyphRenderer

Example 1 :In this example we will be using the default values for plotting the graph.




# importing the modules
from bokeh.plotting import figure, output_file, show
      
# file to save the model
output_file("gfg.html")
      
# instantiating the figure object
graph = figure(title = "Bokeh Ellipse Graph",
               match_aspect = True)
    
# the points to be plotted
x = 0
y = 0
  
# width of the ellipse
width = 60
  
# height of the ellipse
height = 20
  
# plotting the graph
graph.ellipse(x, y,
              width = width,
              height = height)
   
# displaying the model
show(graph)

Output :

Example 2 :In this example we will be plotting multiple ellipses with different parameters.




# importing the modules
from bokeh.plotting import figure, output_file, show
      
# file to save the model
output_file("gfg.html")
      
# instantiating the figure object
graph = figure(title = "Bokeh Ellipse Graph")
  
# name of the x-axis
graph.xaxis.axis_label = "x-axis"
     
# name of the y-axis
graph.yaxis.axis_label = "y-axis"
    
# the points to be plotted
x = [0, 30, 0]
y = [0, 30, -30]
  
# width of the ellipse
width = [60, 20, 40]
  
# height of the ellipse
height = [20, 180, 80]
  
# angle of the ellipse
angle = [0, 150, 20]
  
# fill alpha values
fill_alpha = 0.3
  
# fill color values
fill_color = ["red", "yellow", "blue"]
  
# line color value
line_color = "black"
  
# plotting the graph
graph.ellipse(x, y,
              width = width,
              height = height,
              angle = angle,
              fill_alpha = fill_alpha,
              fill_color = fill_color,
              line_color = line_color)
   
# displaying the model
show(graph)

Output :

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