我使用pandas
和numpy
个库来计算两个简单列表中的pearson correlation个.以下代码的输出是相关矩阵:
import numpy as np
import pandas as pd
x = np.array([0, 1, 2, 3, 4, 5, 6, 7, 8, 9])
y = np.array([2, 1, 4, 5, 8, 12, 18, 25, 96, 48])
x, y = pd.Series(x), pd.Series(y)
xy = pd.DataFrame({'dist-values': x, 'uptime-values': y})
matrix = xy.corr(method="pearson")
在输出上使用.unstack()
和.to_dict()
函数后,我们可以得到以下格式的字典:
result = matrix.unstack().to_dict()
# {('dist-values', 'dist-values'): 1.0,
# ('dist-values', 'uptime-values'): 0.7586402890911869,
# ('uptime-values', 'dist-values'): 0.7586402890911869,
# ('uptime-values', 'uptime-values'): 1.0}
但我需要将其转换为字典列表,输出应该如下所示:
#[ {'f1': 'dist-values', 'f2': 'dist-values', 'value': '1.0'},
# {'f1': 'dist-values', 'f2': 'uptime-values', 'value': '0.7586402890911869'},
# {'f1': 'uptime-values', 'f2': 'dist-values', 'value': '0.7586402890911869'},
# {'f1': 'uptime-values', 'f2': 'uptime-values', 'value': '1.0'}
# ]
做这件事的最佳有效方式是什么?