修改

盘荣博/数据可视化/week1.py

@@ -1,5 +1,7 @@
 import pandas as pd
+import numpy as np
 from  scipy.stats import zscore
+from sklearn.decomposition import PCA
 import matplotlib.pyplot as plt
 from matplotlib.pyplot import ylabel
 df = pd.read_excel("棉花产量论文作业的数据.xlsx")
@@ -38,5 +40,22 @@ plt.scatter(data2[:,:1],data2[:,1:2],c='g')
 plt.xlabel('压缩到0~1')
 print(data==data1)
 
-plt.savefig("shuju.jpg",dpi=2000)
+# plt.savefig("shuju.jpg",dpi=2000)
-plt.show()
+# plt.show()
+md= PCA().fit(data)
+cf = np.cov(data.T)#求协方差矩阵
+print(cf)
+c, d= np.linalg.eig(cf)
+print("特征值：\n",c)
+print(md.explained_variance_)
+e=c/c.sum()
+# for _ in range(len(e)):
+#     if(_!=0):
+#         e[_]+=e[_-1]
+print('贡献率：')
+print(e)
+print(md.explained_variance_ratio_)
+print('特征向量：')
+print(d.T)
+print(md.components_)
+print(md.components_-d.T<=0.1)