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
andDataFrame
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 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) |
Output :
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