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Python Bokeh – Plotting Dashes 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 dashes on a graph. Plotting dashes on a graph can be done using the dash() method of the plotting module.

plotting.figure.dash()

Syntax : dash(parameters)

Parameters :

  • x : x-coordinates of the center of the dash markers
  • y : y-coordinates of the center of the dash markers
  • size : diameter of the dash markers, default is 4
  • angle : angle of rotation of the dash markers, default is 0
  • angle_units : unit of the angle, default is rad
  • fill_alpha : fill alpha value of the dash markers
  • fill_color : fill color value of the dash 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.




# 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 Dash Graph")
   
# the points to be plotted
x = [-5, -4, -3, -2, -1, 0, 1, 2, 3, 4, 5]
y = [25, 16, 9, 4, 1, 0, 1, 4, 9, 16, 25]
    
# plotting the dashes
graph.dash(x, y)
    
# displaying the model
show(graph)


Output :

Example 2 :In this example we will be plotting the dashes with dotted lines alongside 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 Dash 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 = [25, 16, 9, 4, 1, 0, 1, 4, 9, 16, 25]
  
# size of the dashes
size = 20
  
# angle of the dashes
angle = 10
  
# color of the line
line_color = "red"
   
# type of line
line_dash = "dotted"
   
# offset of line dash
line_dash_offset = 1
  
# width of the dashes
line_width = 10
  
# name of the legend
legend_label = "Sample Dashes"
   
# plotting the line graph for AAPL
graph.dash(x, y,
           size = size,
           angle = angle,
           line_color = line_color,
           line_dash = line_dash,
           line_dash_offset = line_dash_offset,
           line_width = line_width,
           legend_label = legend_label)
    
# plotting the dashes
graph.dash(x, y)
    
# displaying the model
show(graph)


Output :



Last Updated : 03 Jul, 2020
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