bokeh.plotting.figure.circle_x() function in Python Last Updated : 17 Jun, 2020 Comments Improve Suggest changes Like Article Like Report Bokeh is a data visualization library in Python that provides high-performance interactive charts and plots and the output can be obtained in various mediums like notebook, html and server. The Figure Class create a new Figure for plotting. It is a subclass of Plot that simplifies plot creation with default axes, grids, tools, etc. bokeh.plotting.figure.circle_x() Function The circle_x() function in plotting module of bokeh library is used to Configure and add circle_x glyphs to this Figure. Syntax: circle_x(x, y, size=4, angle=0.0, *, angle_units='rad', fill_alpha=1.0, fill_color='gray', line_alpha=1.0, line_cap='butt', line_color='black', line_dash=[], line_dash_offset=0, line_join='bevel', line_width=1, name=None, tags=[], **kwargs) Parameters: This method accept the following parameters that are described below: x: This parameter is the x-coordinates for the center of the markers. y: This parameter is the y-coordinates for the center of the markers. size: This parameter is the size (diameter) values for the markers in screen space units. angle: This parameter is the angles to rotate the markers. fill_alpha: This parameter is the fill alpha values for the markers. fill_color: This parameter is the fill color values for the markers. line_alpha: This parameter is the line alpha values for the markers with default value of 1.0 . line_cap: This parameter is the line cap values for the markers with default value of butt. line_color: This parameter is the line color values for the markers with default value of black. line_dash: This parameter is the line dash values for the markers with default value of []. line_dash_offset: This parameter is the line dash offset values for the markers with default value of 0. line_join: This parameter is the line join values for the markers with default value of bevel. line_width: This parameter is the line width values for the markers with default value of 1. mode: This parameter can be one of three values : ["before", "after", "center"]. name: This parameter is the user-supplied name for this model. tags: This parameter is the user-supplied values for this model. Other Parameters: These parameters are **kwargs that are described below: alpha: This parameter is used to set all alpha keyword arguments at once. color: This parameter is used to to set all color keyword arguments at once. legend_field: This parameter is the name of a column in the data source that should be used or the grouping. legend_group: This parameter is the name of a column in the data source that should be used or the grouping. legend_label: This parameter is the legend entry is labeled with exactly the text supplied here. muted: This parameter contains the bool value. name: This parameter is the optional user-supplied name to attach to the renderer. source: This parameter is the user-supplied data source. view: This parameter is the view for filtering the data source. visible: This parameter contains the bool value. x_range_name: This parameter is the name of an extra range to use for mapping x-coordinates. y_range_name: This parameter is the name of an extra range to use for mapping y-coordinates. level: This parameter specify the render level order for this glyph. Return: This method return the GlyphRenderer value. Below examples illustrate the bokeh.plotting.figure.circle_x() function in bokeh.plotting: Example 1: Python3 # Implementation of bokeh function import numpy as np from bokeh.plotting import figure, output_file, show plot = figure(plot_width = 300, plot_height = 300) plot.circle_x(x = [1, 2, 3], y = [3, 7, 5], size = 20, color ="green", alpha = 0.6) show(plot) Output: Example 2: Python3 # Implementation of bokeh function import numpy as np from bokeh.plotting import figure, output_file, show x = [1, 2, 3, 4, 5] y = [6, 7, 8, 7, 3] output_file("geeksforgeeks.html") p = figure(plot_width = 300, plot_height = 300) # add both a line and circles on the same plot p.line(x, y, line_width = 2) p.circle_x(x, y, fill_color ="red", line_color ="green", size = 8) show(p) Output: Comment More infoAdvertise with us Next Article bokeh.plotting.figure.circle() function in Python S SHUBHAMSINGH10 Follow Improve Article Tags : Python Python-Bokeh Practice Tags : python Similar Reads Python Bokeh tutorial - Interactive Data Visualization with Bokeh Python Bokeh is a Data Visualization library that provides interactive charts and plots. 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