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Python Bokeh – Plotting Hexagon Bins on a Graph
  • Last Updated : 10 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 hexagon tiles on a graph. Plotting hexagon tiles on a graph can be done using the hexbin() method of the plotting module.

plotting.figure.hexbin()

Syntax : hexbin(parameters)

Parameters :

  • x : NumPy array of x-coordinates of the hexagon tile bins
  • y : NumPy array of y-coordinates of the hexagon tile bins
  • size : radius of the hexagonal tile bins, default is 1
  • palette : orientation value, default is Viridis256
  • orientation : palette to colormap the bins, default is pointytop
  • line_color : color of the line, default is black
  • fill_color : fill color value of the hexagon tile bin markers
  • aspect_scale : aspect ratio scaling value

Any additional keyword arguments are passed to hex_tile().



Returns : an object of class GlyphRenderer and DataFrame

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

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# importing the modules 
from bokeh.plotting import figure, output_file, show 
import numpy as np
  
# file to save the model 
output_file("gfg.html"
       
# instantiating the figure object 
graph = figure(title = "Bokeh Hexagon Bin Graph"
    
# the points to be plotted 
x = np.array([1, 2, 3, 4, 5, 6, 7, 8, 9])
y = np.array([1, 2, 3, 4, 5, 6, 7, 8, 9])
  
# plotting the graph 
graph.hexbin(x, y, size = 1
     
# displaying the model 
show(graph) 

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Output :

Example 2 : In this example we will be plotting the hexagon bins with various parameters

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# importing the modules 
from bokeh.plotting import figure, output_file, show 
import numpy as np
  
# file to save the model 
output_file("gfg.html"
       
# instantiating the figure object 
graph = figure(title = "Bokeh Hexagon Bin 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 = np.random.standard_normal(500)
y = np.random.standard_normal(500)
  
# size of the bins
size = 0.5
  
# color palette of the graph
palette = "Plasma256"
  
# plotting the graph 
graph.hexbin(x, y,
             size = 0.5,
             palette = palette) 
     
# displaying the model 
show(graph)  

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Output :

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