1、语法参数如下:

matplotlib.pyplot.legend(*args, **kwargs)

2、参数

keyword	Description
loc	Location code string, or tuple (see below).图例所有figure位置
prop	the font property字体参数
fontsize	the font size (used only if prop is not specified)
markerscale	the relative size of legend markers vs. original 图例标记与原始标记的相对大小
markerfirst	If True (default), marker is to left of the label. 如果为True，则图例标记位于图例标签的左侧
numpoints	the number of points in the legend for line 为线条图图例条目创建的标记点数
scatterpoints	the number of points in the legend for scatter plot 为散点图图例条目创建的标记点数
scatteryoffsets	a list of yoffsets for scatter symbols in legend 为散点图图例条目创建的标记的垂直偏移量
frameon	If True, draw the legend on a patch (frame). 控制是否应在图例周围绘制框架
fancybox	If True, draw the frame with a round fancybox. 控制是否应在构成图例背景的FancyBboxPatch周围启用圆边
shadow	If True, draw a shadow behind legend. 控制是否在图例后面画一个阴
framealpha	Transparency of the frame. 控制图例框架的 Alpha 透明度
edgecolor	Frame edgecolor.
facecolor	Frame facecolor.
ncol	number of columns 设置图例分为n列展示
borderpad	the fractional whitespace inside the legend border 图例边框的内边距
labelspacing	the vertical space between the legend entries 图例条目之间的垂直间距
handlelength	the length of the legend handles 图例句柄的长度
handleheight	the height of the legend handles 图例句柄的高度
handletextpad	the pad between the legend handle and text 图例句柄和文本之间的间距
borderaxespad	the pad between the axes and legend border 轴与图例边框之间的距离
columnspacing	the spacing between columns 列间距
title	the legend title
bbox_to_anchor	the bbox that the legend will be anchored.指定图例在轴的位置
bbox_transform	the transform for the bbox. transAxes if None.

3、常用的几个参数：

3.1设置图例位置

plt.legend(loc='upper center')

loc的取值分别为：

0: ‘best'

1: ‘upper right'

2: ‘upper left'

3: ‘lower left'

4: ‘lower right'

5: ‘right'

6: ‘center left'

7: ‘center right'

8: ‘lower center'

9: ‘upper center'

10: ‘center'

3.2设置图例字体大小

fontsize : int or float or {‘xx-small’, ‘x-small’, ‘small’, ‘medium’, ‘large’, ‘x-large’, ‘xx-large’}

3.3设置图例边框及背景

plt.legend(loc='best',frameon=False) #去掉图例边框plt.legend(loc='best',edgecolor='blue') #设置图例边框颜色plt.legend(loc='best',facecolor='blue') #设置图例背景颜色,若无边框,参数无效

对于边框还可以采用面向对象方式：

legend = plt.legend(["First", "Second"])frame = legend.get_frame()frame.set_facecolor('blue')

3.4设置图例标题

legend = plt.legend(["CH", "US"], title='China VS Us')

3.5设置图例名字及对应关系

legend = plt.legend([p1, p2], ["CH", "US"])

4、实例

4.1 实例1

from matplotlib import pyplot as plt
import numpy as nptrain_x = np.linspace(-1, 1, 100)
train_y_1 = 2 * train_x + np.random.rand(*train_x.shape) * 0.3
train_y_2 = train_x ** 2 + np.random.randn(*train_x.shape) * 0.3# 画散点图
p1 = plt.scatter(train_x, train_y_1, c='red', marker='v')
p2 = plt.scatter(train_x, train_y_2, c='blue', marker='o')# 设置图例标题title,
# 设置图例名字及对应关系[p1, p2], ["CH", "US"]
# 设置图例背景颜色facecolor
# 设置图例位置loc
legend = plt.legend([p1, p2], ["CH", "US"],title='China VS Us', facecolor='y',loc='lower right')plt.show()

运行结果

4.2 实例2

import numpy as np
import matplotlib.pyplot as pltX = np.linspace(0, 2*np.pi, 32, endpoint=True)
C,S = np.cos(X), np.sin(X)#plt.plot(X,C)
#plt.plot(X,S)
plt.plot(X, C, 'go--', color='blue', label='cos')
plt.plot(X,S, color='green', marker='o', linestyle='dashed', label='sin')
# 一个是fmt，一个是线属性，但是它们的格式是一样的plt.legend(loc='lower left')
plt.show()

运行结果