如何從 DataFrame 中獲取元組的行、列列表？

Question

試圖從df中獲取滿足某些條件的行、列元組列表。

我引用了這篇文章： Get column and row index pairs of Pandas DataFrame matching some criteria

A = pd.DataFrame([(1.0,0.8,0.6708203932499369,0.6761234037828132,0.7302967433402214),
                  (0.8,1.0,0.6708203932499369,0.8451542547285166,0.9128709291752769),
        (0.6708203932499369,0.6708203932499369,1.0,0.5669467095138409,0.6123724356957946),
        (0.6761234037828132,0.8451542547285166,0.5669467095138409,1.0,0.9258200997725514),
        (0.7302967433402214,0.9128709291752769,0.6123724356957946,0.9258200997725514,1.0)
                  ])

c2 = A.copy()
c2.values[np.tril_indices_from(c2)] = np.nan
[(c2.index[i], c2.columns[j]) for i, j in np.argwhere(c2 > 0.8)]

Shape of passed values is (2, 3), indices imply (5, 5)

我做錯了什么？

Answer 1

您可能想使用 numpy 數組而不是數據c2.values本身，即c2.values

[(c2.index[i], c2.columns[j]) for i, j in np.argwhere(c2.values > 0.8)]

Answer 2

我將使用np.column_stack(np.where(condition))來達到目的：

import pandas as pd 
import numpy as np

A = pd.DataFrame([(1.0,0.8,0.6708203932499369,0.6761234037828132,0.7302967433402214),
                  (0.8,1.0,0.6708203932499369,0.8451542547285166,0.9128709291752769),
        (0.6708203932499369,0.6708203932499369,1.0,0.5669467095138409,0.6123724356957946),
        (0.6761234037828132,0.8451542547285166,0.5669467095138409,1.0,0.9258200997725514),
        (0.7302967433402214,0.9128709291752769,0.6123724356957946,0.9258200997725514,1.0)
                  ])

c2 = A.copy()
c2.values[np.tril_indices_from(c2)] = np.nan

np.column_stack(np.where(c2>0.8))
Out[4]: 
array([[1, 3],
       [1, 4],
       [3, 4]], dtype=int64)

Answer 3

您可以mask DataFrame，然后stack您留下滿足條件的(index, column)的 MultiIndex 元組。

m = A.gt(0.8) & np.triu(np.ones(A.shape), k=1).astype('bool')
A[m].stack().index.tolist()
#[(1, 3), (1, 4), (3, 4)]