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Python Bokeh – Plotting Diamond Dots on a Graph

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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 diamond with dots on a graph. Plotting diamond with dots on a graph can be done using the diamond_dot() method of the plotting module.

plotting.figure.diamond_dot()

Syntax : diamond_dot(parameters)

Parameters :

  • x : x-coordinates of the center of the diamond dot markers
  • y : y-coordinates of the center of the diamond dot markers
  • size : diameter of the diamond dot markers, default is 4
  • angle : angle of rotation of the diamond dot markers, default is 0
  • angle_units : unit of the angle, default is rad
  • fill_alpha : fill alpha value of the diamond dot markers
  • fill_color : fill color value of the diamond dot markers
  • 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. We have provided the size and fill_color attributes to make the glyph visible.




# 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 Diamond Dot Graph")
   
# the points to be plotted
x = [-5, -4, -3, -2, -1, 0, 1, 2, 3, 4, 5]
y = [i ** 2 for i in x]
  
# plotting the graph
graph.diamond_dot(x, y, size = 25, fill_color = None)
   
# displaying the model
show(graph)


Output :

Example 2 :In this example we will be plotting the diamond dots where the sizes are in proportion to their values and various other 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 Diamond Dot 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 = [-5, -4, -3, -2, -1, 0, 1, 2, 3, 4, 5]
y = [i ** 2 for i in x]
   
# size of the diamonds
size = [i * 2 for i in y]
   
# angle of the diamonds
angle = 10
  
# fill color value
fill_color = "yellow"
  
# color of the line
line_color = "red"
  
# name of the legend
legend_label = "Sample Dashes"
    
# plotting the graph
graph.diamond_dot(x, y,
                  size = size,
                  angle = angle,
                  fill_color = fill_color,
                  line_color = line_color,
                  legend_label = legend_label)
     
# displaying the model
show(graph)


Output :



Last Updated : 03 Jul, 2020
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