# 导入库
import numpy as np
from scipy.stats import pearsonr
import csv
# 导入数据
Housing_dataset = np.loadtxt(r"D:\neural networks\YOLOX-main\Train_345.csv", delimiter="," ,dtype='float64',skiprows=0)
# 切分数据
X = Housing_dataset[:, :8]
y = Housing_dataset[:,7].reshape(-1, 1)
# 输出X,y的维度
print(X.shape)
print(y.shape)
# Pearsonr分析
for i in range(8):
x = X[:, i].reshape(-1, 1)
x = np.squeeze(x)
y = np.squeeze(y)
# print(x.shape)
# ------------pearsonr(x,y)-------------
result = pearsonr(x, y)
# ------------保存结果--------------------
print(result)
with open('pearson.csv', 'a+', encoding='utf-8', newline="")as file_write:
result_writer = csv.writer(file_write)
result_writer.writerow(result)
结果:
(23186, 8) (23186, 1) (0.390683095221516, 0.0) (0.18241386058426853, 1.2316591621612489e-172) (0.2814844413956121, 0.0) (0.36491437308758456, 0.0) (0.19467749938433787, 8.352024672327669e-197) (0.10470869965723154, 1.5732394786086808e-57) (0.511663840712641, 0.0) (0.9999999999999999, 0.0)
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