使用pandas绘制最高相关性

import pandas as pd

# 读取数据
data = pd.read_csv('data.csv')

# 计算相关性
correlation = data.corr()

# 找到最高相关性
max_correlation = correlation.stack().idxmax()
max_correlation_row = max_correlation[0]
max_correlation_col = max_correlation[1]

import seaborn as sns
import matplotlib.pyplot as plt

# 绘制相关性热力图
plt.figure(figsize=(10, 8))
sns.heatmap(correlation, annot=True, cmap='coolwarm')
plt.title('Correlation Heatmap')
plt.show()

import pandas as pd
import seaborn as sns
import matplotlib.pyplot as plt

# 读取数据
data = pd.read_csv('data.csv')

# 计算相关性
correlation = data.corr()

# 找到最高相关性
max_correlation = correlation.stack().idxmax()
max_correlation_row = max_correlation[0]
max_correlation_col = max_correlation[1]

# 绘制相关性热力图
plt.figure(figsize=(10, 8))
sns.heatmap(correlation, annot=True, cmap='coolwarm')
plt.title('Correlation Heatmap')
plt.show()

print("最高相关性的行索引：", max_correlation_row)
print("最高相关性的列索引：", max_correlation_col)