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
GlyphRendererandDataFrame
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 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) |
Output :
Example 2 : In this example we will be plotting the hexagon bins with various parameters
# 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 binssize = 0.5 # color palette of the graphpalette = "Plasma256" # plotting the graph graph.hexbin(x, y, size = 0.5, palette = palette) # displaying the model show(graph) |
Output :
Attention geek! Strengthen your foundations with the Python Programming Foundation Course and learn the basics.
To begin with, your interview preparations Enhance your Data Structures concepts with the Python DS Course. And to begin with your Machine Learning Journey, join the Machine Learning – Basic Level Course
