Python Bokeh – 绘制垂直条形图

Bokeh 是一个Python交互式数据可视化。它使用 HTML 和 JavaScript 渲染其绘图。它针对现代 Web 浏览器进行演示，提供具有高性能交互性的新颖图形的优雅、简洁构造。
Bokeh 可用于绘制垂直条形图。可以使用绘图模块的 vbar() 方法绘制垂直条形图。

plotting.figure.vbar()

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 
 

示例 1：在此示例中，我们将使用默认值来绘制图形。

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 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)

输出 ：

示例 2：在此示例中，我们将绘制具有不同参数的垂直条。

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 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)

输出 ：