Last Updated : 30 Nov, 2021
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 vertical bar graphs. Plotting vertical bar graphs can be done using the vbar() method of the plotting module.
Syntax : vbar(parameters)
Parameters :
- x : x-coordinates of the center of the vertical bars
- width : thickness of the vertical bars
- top : y-coordinates of the top edges
- bottom : y-coordinates of the bottom edges, default is 0
- fill_alpha : fill alpha value of the vertical bars
- fill_color : fill color value of the vertical bars
- hatch_alpha : hatch alpha value of the vertical bars, default is 1
- hatch_color : hatch color value of the vertical bars, default is black
- hatch_extra : hatch extra value of the vertical bars
- hatch_pattern : hatch pattern value of the vertical bars
- hatch_scale : hatch scale value of the vertical bars, default is 12
- hatch_weight : hatch weight value of the vertical bars, default is 1
- line_alpha : percentage value of line alpha, default is 1
- line_cap : value of line cap for the line, default is butt
- line_color : color of the line, default is black
- line_dash : value of line dash such as :
- solid
- dashed
- dotted
- dotdash
- dashdot
default is solid
- line_dash_offset : value of line dash offset, default is 0
- line_join : value of line join, default in bevel
- line_width : value of the width of the line, default is 1
- name : user-supplied name for the model
- tags : user-supplied values for the model
Other Parameters :
- alpha : sets all alpha keyword arguments at once
- color : sets all color keyword arguments at once
- legend_field : name of a column in the data source that should be used
- legend_group : name of a column in the data source that should be used
- legend_label : labels the legend entry
- muted : determines whether the glyph should be rendered as muted or not, default is False
- name : optional user-supplied name to attach to the renderer
- source : user-supplied data source
- view : view for filtering the data source
- visible : determines whether the glyph should be rendered or not, default is True
- x_range_name : name of an extra range to use for mapping x-coordinates
- y_range_name : name of an extra range to use for mapping y-coordinates
- level : specifies the render level order for this glyph
Returns : an object of class GlyphRenderer
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
# file to save the model
output_file("gfg.html")
# instantiating the figure object
graph = figure(title = "Bokeh Vertical Bar Graph")
# x-coordinates to be plotted
x = [1, 2, 3, 4, 5]
# x-coordinates of the top edges
top = [1, 2, 3, 4, 5]
# width / thickness of the bars
width = 0.5
# plotting the graph
graph.vbar(x,
top = top,
width = width)
# displaying the model
show(graph)
Output :
Example 2 :In this example we will be plotting vertical bars with different parameters.
# importing the modules
from bokeh.plotting import figure, output_file, show
# file to save the model
output_file("gfg.html")
# instantiating the figure object
graph = figure(title = "Bokeh Vertical Bar Graph")
# name of the x-axis
graph.xaxis.axis_label = "x-axis"
# name of the y-axis
graph.yaxis.axis_label = "y-axis"
# x-coordinates to be plotted
x = [1, 2, 3, 4, 5]
# x-coordinates of the top edges
top = [1, 2, 3, 4, 5]
# width / thickness of the bars
width = [0.5, 0.4, 0.3, 0.2, 0.1]
# color values of the bars
fill_color = ["yellow", "pink", "blue", "green", "purple"]
# plotting the graph
graph.vbar(x,
top = top,
width = width,
fill_color = fill_color)
# displaying the model
show(graph)
Output :
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