Python Bokeh – 在图表上绘制点

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 可用于在图形上绘制点。可以使用plotting模块的dot()方法在图形上绘制点。

plotting.figure.dot()

Syntax : dot(parameters)

Parameters :

• x : x-coordinates of the center of the dot markers
• y : y-coordinates of the center of the dot markers
• size : diameter of the dot markers, default is 4
• angle : angle of rotation of the dot markers, default is 0
• angle_units : unit of the angle, default is rad
• fill_alpha : fill alpha value of the dot markers
• fill_color : fill color value of the dot markers
• 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。我们提供了 size 属性以使字形可见。

# 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 Dot Graph")
    
# the points to be plotted
x = [-5, -4, -3, -2, -1, 0, 1, 2, 3, 4, 5]
y = [i ** 2 for i in x]
   
# plotting the graph
graph.dot(x, y, size = 25)
    
# displaying the model
show(graph)

输出 ：

示例 2：在此示例中，我们将使用random()函数生成点并传递一些参数。

# importing the modules
from bokeh.plotting import figure, output_file, show
import random
     
# file to save the model
output_file("gfg.html")
     
# instantiating the figure object
graph = figure(title = "Bokeh Dot Graph")
   
# name of the x-axis
graph.xaxis.axis_label = "x-axis"
    
# name of the y-axis
graph.yaxis.axis_label = "y-axis"
   
# generating the points to be plotted
x = []
y = []
for i in range(100):
    x.append(i)
for i in range(100):
    y.append(random.random())
   
# size of the points
size = [i * 40 for i in y]
   
# fill color value
fill_color = "yellow"
  
# name of the legend
legend_label = "Sample Dots"
    
# plotting the graph
graph.dot(x, y,
      size = size,
      fill_color = fill_color,
      legend_label = legend_label)
     
# displaying the model
show(graph)

输出 ：

在评论中写代码？请使用 ide.geeksforgeeks.org，生成链接并在此处分享链接。