Python 利用循环画散点图

Posted 2021-01-25 Christina_笔记

 1 import pandas as pd
 2 data = pd.read_csv(‘D:/suning/iris.csv‘)
 3 data = data.iloc[:,1:]
 4 
 5 ###2维散点图
 6 import matplotlib.pyplot as plt
 7 
 8 k=[
 9 ‘Sepal.Length‘,
10 ‘Sepal.Width‘,
11 ‘Petal.Length‘,
12 ‘Petal.Width‘,]
13 for i in k:
14     for m in k:
15         if i != m:
16             plt.figure(figsize=(10,10))
17             result =data.Species.unique()
18             plt.scatter(data.loc[data.Species == result[2], i], data.loc[data.Species == result[2],m], s = 35, marker=‘*‘, c =‘g‘)
19             plt.scatter(data.loc[data.Species == result[1], i], data.loc[data.Species == result[1],m], s = 35, marker=‘+‘, c =‘r‘)
20             plt.scatter(data.loc[data.Species == result[0], i], data.loc[data.Species == result[0],m], s = 35, marker=‘o‘,c = ‘y‘)
21             # 添加轴标签和标题
22             plt.title( ‘‘)
23             plt.xlabel(i)
24             plt.ylabel(m)
25             # 去除图边框的顶部刻度和右边刻度
26             #lt.tick_params(top = ‘off‘, right = ‘off‘)
27             # 添加图例plt.legend(loc = ‘upper left‘)
28             plt.show()
29 
30 ####三维散点图
31 import numpy as np
32 import matplotlib.pyplot as plt
33 from mpl_toolkits.mplot3d import Axes3D
34 
35 k=[
36 ‘Sepal.Length‘,
37 ‘Sepal.Width‘,
38 ‘Petal.Length‘,
39 ‘Petal.Width‘,]
40 for i in k:
41     for m in k:
42         for z in k:
43             if i != m and m!=z and 1!=z:  
44                 plt.figure(figsize=(10,10))
45                 result = data.Species.unique() 
46                 ax = plt.subplot(111, projection=‘3d‘)  # 创建一个三维的绘图工程
47                 ax.scatter(data.loc[data.Species == result[2], i], data.loc[data.Species == result[2], m], data.loc[data.Species == result[2], z], c=‘g‘,marker=‘*‘)  # 绘制数据点
48                 ax.scatter(data.loc[data.Species == result[1], i], data.loc[data.Species == result[1], m], data.loc[data.Species == result[1], z], c=‘r‘,marker=‘+‘)  # 绘制数据点
49                 ax.scatter(data.loc[data.Species == result[0], i], data.loc[data.Species == result[0], m], data.loc[data.Species == result[0], z], c=‘y‘,marker=‘o‘)  # 绘制数据点
50                 ax.set_zlabel(z)  # 坐标轴
51                 ax.set_ylabel(m)
52                 ax.set_xlabel(i)
53                 plt.show()
54