数据文件在百度网盘
数据文件下载
https://pan.baidu.com/s/1OdP5kflPBw2gXfaZfaPCqA
提取码:520y
相关性分析的ipynb文件
相关性分析
https://pan.baidu.com/s/1hk9gmGdqBk3bfFKm8QMccQ
提取码:520y
data_raw = pd.read_csv(“total.csv”, engine=‘python’, header=0)
plt.savefig(path_name)
# 1. 加载数据集 import numpy as np import pandas as pd import matplotlib.pyplot as plt import matplotlib.pyplot as plt import seaborn as sns # %matplotlib inline data_raw = pd.read_csv("total.csv", engine='python', header=0) Target = ['real_label'] # ot 中数据杂乱,去除 data_columns = ['age50', 'shoushu', 'hpv', 'xhdb', 'bxb', 'lxb', 'xxb', 'alt', 'ast', 'bdb', 'jl', 'xn', 'nt', 'dbn', 'fsxcy', 'fsxpgy', 'ydl', 'pl', 'fr', 'bl', 'fq'] columns = Target + data_columns data = data_raw[columns] # 直接计算相关性 # data.corr() # sns.pairplot(data) # sns.heatmap(data.corr()) for name in data_columns: plt.scatter(data_raw[name],data_raw['real_label'],s=1) path_name = str(name)+".png" plt.savefig(path_name) # plt.show()
别的也没啥说的, 如果觉得 ok 就给我一键三连吧!
欢迎各位大佬留言吐槽,也可以深入交流~