Python Bokeh - Plotting Hexagon Bins on a Graph Last Updated : 10 Jul, 2020 Comments Improve Suggest changes Like Article Like Report 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. Python3 # 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 Python3 # 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 : Comment More infoAdvertise with us Next Article What is Data Visualization and Why is It Important? 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