📜  在Python中使用 Plotly 注释热图

📅  最后修改于: 2022-05-13 01:54:52.827000             🧑  作者: Mango

在Python中使用 Plotly 注释热图

Plotly 是一个Python库,用于设计图形,尤其是交互式图形。它可以绘制各种图形和图表,如直方图、条形图、箱线图、散布图等等。它主要用于数据分析和财务分析。 plotly 是一个交互式可视化库。

带注释的热图

带注释的热图是热图最重要的组成部分,因为它们显示了与热图中的行或列相关的附加信息。注释热图将表示为网格行,通过这些网格可以将多个指标与其他指标进行比较。

例子:

Python3
import plotly.figure_factory as ff
import numpy as np
  
feature_x = np.arange(0, 10, 2)
feature_y = np.arange(0, 10, 3)
  
# Creating 2-D grid of features
[X, Y] = np.meshgrid(feature_x, feature_y)
  
Z = np.cos(X / 2) + np.sin(Y / 4)
  
fig = ff.create_annotated_heatmap(Z)
fig.show()


Python3
import plotly.figure_factory as ff
import numpy as np
  
feature_x = np.arange(0, 10, 2)
feature_y = np.arange(0, 10, 3)
  
# Creating 2-D grid of features
[X, Y] = np.meshgrid(feature_x, feature_y)
  
Z = np.cos(X / 2) + np.sin(Y / 4)
  
fig = ff.create_annotated_heatmap(Z, colorscale='rainbow')
fig.show()


Python3
import plotly.figure_factory as ff
import numpy as np
  
feature_x = np.arange(0, 10, 2)
feature_y = np.arange(0, 10, 3)
  
# Creating 2-D grid of features
[X, Y] = np.meshgrid(feature_x, feature_y)
  
Z = np.cos(X / 2) + np.sin(Y / 4)
  
custom = [[0, 'green'], [0.5, 'red']]
  
fig = ff.create_annotated_heatmap(Z, colorscale=custom)
fig.show()


输出:

定义色阶

在 plotly 中,色阶或颜色图表是具有不同颜色类型的平面物理对象。可以使用colorscale参数在此图中设置它。

示例 1:

Python3

import plotly.figure_factory as ff
import numpy as np
  
feature_x = np.arange(0, 10, 2)
feature_y = np.arange(0, 10, 3)
  
# Creating 2-D grid of features
[X, Y] = np.meshgrid(feature_x, feature_y)
  
Z = np.cos(X / 2) + np.sin(Y / 4)
  
fig = ff.create_annotated_heatmap(Z, colorscale='rainbow')
fig.show()

输出:

示例 2:添加自定义色阶

Python3

import plotly.figure_factory as ff
import numpy as np
  
feature_x = np.arange(0, 10, 2)
feature_y = np.arange(0, 10, 3)
  
# Creating 2-D grid of features
[X, Y] = np.meshgrid(feature_x, feature_y)
  
Z = np.cos(X / 2) + np.sin(Y / 4)
  
custom = [[0, 'green'], [0.5, 'red']]
  
fig = ff.create_annotated_heatmap(Z, colorscale=custom)
fig.show()

输出: