Open In App

Python Bokeh - Plotting Horizontal Bar Graphs

Last Updated : 03 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 horizontal bar graphs. Plotting horizontal bar graphs can be done using the hbar() method of the plotting module.

plotting.figure.hbar()

Syntax : hbar(parameters) Parameters :
  • y : y-coordinates of the center of the horizontal bars
  • height : thickness of the horizontal bars
  • right : x-coordinates of the right edges
  • left : x-coordinates of the left edges, default is 0
  • fill_alpha : fill alpha value of the horizontal bars
  • fill_color : fill color value of the horizontal bars
  • hatch_alpha : hatch alpha value of the horizontal bars, default is 1
  • hatch_color : hatch color value of the horizontal bars, default is black
  • hatch_extra : hatch extra value of the horizontal bars
  • hatch_pattern : hatch pattern value of the horizontal bars
  • hatch_scale : hatch scale value of the horizontal bars, default is 12
  • hatch_weight : hatch weight value of the horizontal 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. Python3
# 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 Horizontal Bar Graph")

# y-coordinates to be plotted
y = [1, 2, 3, 4, 5]

# x-coordinates of the right edges
right = [1, 2, 3, 4, 5]

# height / thickness of the bars 
height = 0.5

# plotting the graph
graph.hbar(y,
           right = right,
           height = height)

# displaying the model
show(graph)
Output : Example 2 :In this example we will be plotting horizontal bars with different parameters. Python3
# 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 Horizontal Bar Graph")

# name of the x-axis
graph.xaxis.axis_label = "x-axis"
    
# name of the y-axis
graph.yaxis.axis_label = "y-axis"

# y-coordinates to be plotted
y = [1, 2, 3, 4, 5]

# x-coordinates of the right edges
right = [1, 2, 3, 4, 5]

# height / thickness of the bars 
height = [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.hbar(y,
           right = right,
           height = height,
           fill_color = fill_color)

# displaying the model
show(graph)
Output :

Next Article

Similar Reads