1. matplotlib.legend(*args, **kwargs)图例语法及基础参数设置
legend语法中各参数含义如下如下:
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Keyword
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Description
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loc
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Location code string, or tuple (see below).图例所有figure位置
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prop
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the font property字体参数
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fontsize
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the font size (used only if prop is not specified)
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markerscale
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the relative size of legend markers vs. original
图例标记与原始标记的相对大小
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markerfirst
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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
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numpoints
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the number of points in the legend for line
为线条图图例条目创建的标记点数
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scatterpoints
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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
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scatteryoffsets
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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
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frameon
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If True, draw the legend on a patch (frame).
控制是否应在图例周围绘制框架
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fancybox
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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
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shadow
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If True, draw a shadow behind legend.
控制是否在图例后面画一个阴影
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framealpha
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Transparency of the frame.
控制图例框架的 Alpha 透明度
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edgecolor
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Frame edgecolor.
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facecolor
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Frame facecolor.
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ncol
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number of columns 设置图例分为n列展示
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borderpad
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the fractional whitespace inside the legend border
图例边框的内边距
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labelspacing
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the vertical space between the legend entries
图例条目之间的垂直间距
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handlelength
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the length of the legend handles
图例句柄的长度
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handleheight
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the height of the legend handles
图例句柄的高度
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handletextpad
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the pad between the legend handle and text
图例句柄和文本之间的间距
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borderaxespad
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the pad between the axes and legend border
轴与图例边框之间的距离
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columnspacing
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the spacing between columns 列间距
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title
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the legend title
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bbox_to_anchor
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the bbox that the legend will be anchored.指定图例在轴的位置
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bbox_transform
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the transform for the bbox. transAxes if None.
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2.图例不需要方框，可以设置 ‘frameon=False’：
# -- coding:utf-8 --
import numpy as np
import matplotlib.pyplot as plt
x = np.linspace(0,11,10)
y = x*x+1
plt.plot(x, y, label="The picture doesn't have frame")
plt.legend(loc="best", frameon=False)
plt.show()结果为：
3.去掉坐标轴刻度：plt.xticks([])、plt.yticks([])
# -- coding:utf-8 --
import numpy as np
import matplotlib.pyplot as plt
x = np.linspace(0,11,10)
y = x*x+1
plt.plot(x, y, label="The picture doesn't have frame")
plt.legend(loc="best", frameon=False)
ax = plt.gca()
ax.spines['top'].set_visible(False)
ax.spines['right'].set_visible(False)
# 方法一
# ax.set_xticks([])
# ax.set_yticks([])
# 方法二
plt.xticks([])
plt.yticks([])
plt.show()结果如下：
