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Draw the following scatter chart as required, first draw three boxes, and then add data in sequence.
It should be noted that since the value of the scatter plot is randomly generated, the value generated during each plot is different.
Block diagram drawing
// An highlighted block
import numpy as np
import matplotlib.pyplot as plt
'''先画三个框'''
#框图的背景设置为“ggplot”
plt.style.use('ggplot')
#根据图中的四个变量进行初始化
margin_border=0.1
width=0.6
height=0.2
margin_between=0.03
#设计主图(正方形)
left_s=margin_border
bottom_s=margin_border
height_s=width
width_s=width
#左边的图(长方形)
left_x=margin_border
bottom_x=margin_border+width+margin_between #底部距离在最上边
height_x=height
width_x=width
#
#右边的图(长方形，尺寸与上图相同)
left_y=margin_border+width+margin_between #离左边的底部距离为最右边
bottom_y=margin_border
height_y=width
width_y=height
#整个图形的尺寸
plt.figure(1,figsize=(8,8)) #画布为（8*8）
rect_s=[left_s,bottom_s,width_s,height_s]
rect_x=[left_x,bottom_x,width_x,height_x]
rect_y=[left_y,bottom_y,width_y,height_y]
#生成图形
axScatter=plt.axes(rect_s)
axHisX=plt.axes(rect_x)
axHisY=plt.axes(rect_y)
plt.show()
Remove part of the coordinates on both sides
// An highlighted block
#将左边的图的x轴坐标去掉
#将右边的图的y轴坐标去掉
axHisX.set_xticks([])
axHisY.set_yticks([])
plt.show()
Content rendering
The content of the main image
// An highlighted block
在x轴产生200个随机数据
x=np.random.randn(200)
#在x轴附近随机振动
y=x+np.random.randn(200)*0.5
axScatter.scatter(x,y)
plt.show()
Picture on the left
// An highlighted block
#设置柱状图的宽度
bin_width=0.25
#寻找x，y的绝对值的最大值作为轴边界
xymax=np.max([np.max(np.fabs(x)),np.max(np.fabs(y))])
#共有多少个bin
slim=int(xymax/bin_width+1)
#slim个bin的总宽度
lim=slim*bin_width
#设置x的最大值，最小值
axScatter.set_xlim(-lim,lim)
#定义每个bin的坐标值
bins=np.arange(-lim,lim+bin_width,bin_width)
#绘制图形
axHisX.hist(x,bins=bins)
axHisX.set_xlim(axScatter.get_xlim())
plt.show()
Picture on the right
// An highlighted block
#设置y轴的最大值，最小值
axScatter.set_ylim(-lim,lim)
#绘制图形(注意 右边的图是横过来的)
axHisY.hist(y,bins=bins,orientation='horizontal')
axHisY.set_ylim(axScatter.get_ylim())
#增加标题
plt.title('Scatter and Hist')
plt.show()
General procedure
// An highlighted block
'''散点图'''
#先画三个框
plt.style.use('ggplot')
#四个变量作为不同的高度和宽度
margin_border=0.1
width=0.6
margin_between=0.03
height=0.2
#设计主图
left_s=margin_border
bottom_s=margin_border
height_s=width
width_s=width
#左边的图
left_x=margin_border
bottom_x=margin_border+width+margin_between
height_x=height
width_x=width
#
#右边的图
left_y=margin_border+width+margin_between
bottom_y=margin_border
height_y=width
width_y=height
#设置为正方形
plt.figure(1,figsize=(8,8))
rect_s=[left_s,bottom_s,width_s,height_s]
rect_x=[left_x,bottom_x,width_x,height_x]
rect_y=[left_y,bottom_y,width_y,height_y]
#生成图
axScatter=plt.axes(rect_s)
axHisX=plt.axes(rect_x)
axHisY=plt.axes(rect_y)
#去掉两边的部分坐标
axHisX.set_xticks([])
axHisY.set_yticks([])
#开始画图
#主图
x=np.random.randn(200)
#在x轴附近随机振动
y=x+np.random.randn(200)*0.5
axScatter.scatter(x,y)
#设置柱状图的宽度
bin_width=0.25
#寻找x，y轴边界
xymax=np.max([np.max(np.fabs(x)),np.max(np.fabs(y))])
#共有多少个bin
slim=int(xymax/bin_width+1)
#slim个bin的总宽度
lim=slim*bin_width
#设置x轴的最大值，最小值
axScatter.set_xlim(-lim,lim)
axScatter.set_ylim(-lim,lim)
#定义每个bin的坐标值
bins=np.arange(-lim,lim+bin_width,bin_width)
#绘制图形
axHisX.hist(x,bins=bins)
axHisY.hist(y,bins=bins,orientation='horizontal')
axHisX.set_xlim(axScatter.get_xlim())
axHisY.set_ylim(axScatter.get_ylim())
#添加标签
plt.title('Scatter and Hist')
plt.show()