plt的补充_plt.scatter zorder

1. plt.scatter()

这里主要想说说常见的c=y的这种操作，他会给定一个颜色的变换范围，数值越小则越趋近于一个颜色，越大则趋近另一个

1.1

还有一个额外的变量 zorder=num,设置这个可以让scatter描绘的图案在别的上面

mp.scatter(x[:, 0], x[:, 1], c=y, cmap='jet', s=80,zorder=3)
mp.pcolormesh(grid_x,grid_y,grid_z,cmap='gray')
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mp.scatter(x[:, 0], x[:, 1], c=y, cmap='jet', s=80)
mp.pcolormesh(grid_x,grid_y,grid_z,cmap='gray')
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效果对比

1.2.

说下cmp，这是个颜色控制器，决定呈现的颜色的变化范围
详情见 https://blog.csdn.net/weixin_39580795/article/details/102622004
写的特别好，
应用举例
这里主要想说说常见的c=y(一般这个y是一个列表)的这种操作，他会给定一份颜色的变换范围（由cmp这个决定），数值越小则越趋近于一个颜色，越大则趋近另一个
比如：

import numpy as np
import matplotlib.pyplot as plt
import matplotlib.pyplot as mp
x = np.array([
    [3, 1],
    [2, 5],
    [1, 8],
    [6, 4],
    [5, 2],
    [3, 5],
    [4, 7],
    [4, -1]])
y = np.array([0, 1, 1, 0, 0, 1, 1, 0])
l, r = x[:, 0].min() - 1, x[:, 0].max() + 1
b, t = x[:, 1].min() - 1, x[:, 1].max() + 1
n = 500
grid_x, grid_y = np.meshgrid(np.linspace(l, r, n), np.linspace(b, t, n))
grid_z = np.piecewise(grid_x, [grid_x>grid_y, grid_x<grid_y], [1, 0])

plt.figure('Simple Classification', facecolor='lightgray')
plt.title('Simple Classification', fontsize=16)
plt.xlabel('x', fontsize=14)
plt.ylabel('y', fontsize=14)
#关于 c=y这里，数越小越蓝，数越大越红
plt.scatter(x[:, 0], x[:, 1], c=y, cmap='jet', s=80)
plt.show()
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2.plt.pcolormesh()

这是用来生成分割线的

3.plt.bar()

这个是用来画柱形图的
效果如下

bar(x, height, width=0.8, bottom=None, ***, align=‘center’, data=None, **kwargs)

import matplotlib.pyplot as plt
import numpy as np
N = 5
y = [20, 30, 10, 25, 15]
index = np.arange(N)
plt.bar(x=index, height=y)
plt.show()

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结果为上方柱状图

4. plt.xticks()

这个主要是用来设置x轴上的坐标，或者柱状图的标签
xticks(ticks, [labels], **kwargs)
ticks：数组类型，用于设置X轴刻度间隔
[labels]：数组类型，用于设置每个间隔的显示标签
**kwargs：用于设置标签字体倾斜度和颜色等外观属性。

import numpy as np
import matplotlib.pyplot as plt
import calendar
x = range(1,13,1)
y = range(1,13,1)
plt.plot(x,y)
plt.xticks(x, calendar.month_name[1:13],color='blue',rotation=60)  #参数x空值X轴的间隔，第二个参数控制每个间隔显示的文本，后面两个参数控制标签的颜色和旋转角度
plt.show()

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refernce

1.https://blog.csdn.net/TeFuirnever/article/details/88944438
2.https://blog.csdn.net/bug_12/article/details/93983782
3.https://blog.csdn.net/Asher117/article/details/111492094?ops_request_misc=%257B%2522request%255Fid%2522%253A%2522163005549316780255283469%2522%252C%2522scm%2522%253A%252220140713.130102334.pc%255Fall.%2522%257D&request_id=163005549316780255283469&biz_id=0&utm_medium=distribute.pc_search_result.none-task-blog-2_allfirst_rank_v2~rank_v29-4-111492094.pc_search_result_cache&utm_term=plt.bar&spm=1018.2226.3001.4187
4.https://blog.csdn.net/u011208984/article/details/90720516?ops_request_misc=%257B%2522request%255Fid%2522%253A%2522163005639316780366578282%2522%252C%2522scm%2522%253A%252220140713.130102334.pc%255Fall.%2522%257D&request_id=163005639316780366578282&biz_id=0&utm_medium=distribute.pc_search_result.none-task-blog-2_allfirst_rank_v2~rank_v29-1-90720516.pc_search_result_cache&utm_term=plt.xticks&spm=1018.2226.3001.4187