Matplotlib子图中的图例|极客笔记

Matplotlib子图中的图例

在本教程中，我们将学习如何使用Matplotlib在子图中包含图例。可以在创建图表后使用legend()函数添加图例。

语法：

子图中图例的语法是：

axes[position].legend(loc = '')

在此示例中，我们将使用对数和指数子图绘制散点图：

# First, we will import the required modules
from matplotlib import pyplot as PPlt
import numpy as nmp

# here we will assign the value to x axis
x_axis1 = nmp.arange(2, 22, 1.5)

# Now, we will get the value of log10
y_axis_log10_1 = nmp.log10(x_axis)

# then, we will get the value of exponential
y_axix_exp1 = nmp.exp(x_axis)

# Here, we will create subplots by using subplot() function
fig, axes = PPlt.subplots(2)

# now, we will depicte the visualization
axes[0].plot(x_axis1, y_axis_log10_1, color = 'Red', label = "log10")
axes[1].plot(x_axis1, y_axix_exp1, color = 'Pink', label = "exponential")

# Here, we will select the position at which legend to be added
axes[0].legend(loc = 'best')
axes[1].legend(loc = 'best')

# At last, we will display the plot

PPlt.show()

输出

Matplotlib子图中的图例

示例2：

在此示例中，我们将使用正弦和余弦的subplot绘制散点图：

# First, we will import the required modules
from matplotlib import pyplot as PPlt
import numpy as nmp

# here we will assign the value to x axis
x_axis1 = nmp.arange(-2, 3, 0.5)

# Now, we will get the value of sine
y_axis_sine1 = nmp.sin(x_axis)

# Now, we will get the value of cos
y_axix_cose1 = nmp.cos(x_axis)

# Here, we will create subplots by using subplot() function
fig, axes = PPlt.subplots(2)

# now, we will depicte the visualization
axes[0].scatter(x_axis1, y_axis_sine1, color = 'Red', marker = '*', label = "sine")
axes[1].scatter(x_axis1, y_axix_cose1, color = 'Black', marker = '*', label = "cos")

# Here, we will select the position at which legend to be added
axes[0].legend(loc = 'best')
axes[1].legend(loc = 'best')

# At last, we will display the plot
PPlt.show()

输出

Matplotlib子图中的图例

示例3：

在这个示例中，我们将使用子图绘制散点图 (y = x^2) 和 (y = x^3)：

# First, we will import the required modules
from matplotlib import pyplot as PPlt

# here we will assign value to x axis
x_axis = list(range(-15, 15))

# here, we will get the value of x * x
y_axis_1 = [x * x for x in x_axis]

# here, we will get the value of x * x * x
y_axix_2 = [x * x * x for x in x_axis]

# Now, we will create subplots by using subplot() function
fig, axes = PPlt.subplots(2)

# Now, we will depicte the visualization
axes[0].scatter(x_axis, y_axis_1, color = 'Blue', marker = '*', label = "y = x ^ 2")
axes[1].scatter(x_axis, y_axix_2, color = 'Brown', marker = '*', label = "y = x ^ 3")

# Here, we will select the position at which legend to be added
axes[0].legend(loc = 'upper center')
axes[1].legend(loc = 'upper left')

# At last, we will display the plot
PPlt.show()

输出

Matplotlib子图中的图例