python - 返回 Pandas 数据系列中第 n 个最大值的索引和列名

Question

我如何(对于比提供的示例大得多的矩阵有效地)返回第 n 最大或最小值的列名和索引(或行名)

import pandas as pd
import numpy as np

dates = pd.date_range('20130101', periods=6)
df = pd.DataFrame(np.random.randn(6,4), index=dates, columns=list('ABCD'))
matrix = df.corr()
matrix
          A         B         C         D
A  1.000000 -0.814913  0.495993 -0.880296
B -0.814913  1.000000 -0.211421  0.551441
C  0.495993 -0.211421  1.000000 -0.414037
D -0.880296  0.551441 -0.414037  1.000000

然后我会做一些事情，比如

def get_n_smallest(matrix, n):
    # can return as two variables, list, tuple, whatever...
    return row_name, col_name

get_n_smallest(matrix,0)
# would return D, A for the value -.880296

Answer 1

我想你可以使用 stack对于 Series，然后通过 drop_duplicates 删除重复项, sort_values并通过索引 index 获取 MultiIndex 值:

np.random.seed(100)
dates = pd.date_range('20130101', periods=6)
df = pd.DataFrame(np.random.randn(6,4), index=dates, columns=list('ABCD'))
matrix = df.corr()
print (matrix)
          A         B         C         D
A  1.000000  0.570860 -0.558334 -0.434793
B  0.570860  1.000000 -0.358834 -0.564178
C -0.558334 -0.358834  1.000000  0.170589
D -0.434793 -0.564178  0.170589  1.000000

print (matrix.stack().drop_duplicates().sort_values())
B  D   -0.564178
A  C   -0.558334
   D   -0.434793
B  C   -0.358834
C  D    0.170589
A  B    0.570860
   A    1.000000
dtype: float64

def get_n_smallest(matrix, n):
    return matrix.stack().drop_duplicates().sort_values().index[n]

print (get_n_smallest(matrix,0))
('B', 'D')

print (get_n_smallest(matrix,1))
('A', 'C')

print (get_n_smallest(matrix,2))
('A', 'D')

---

def get_n_largest(matrix, n):
    return matrix.stack().drop_duplicates().sort_values(ascending=False).index[n]


print (get_n_largest(matrix,0))
('A', 'A')

print (get_n_largest(matrix,1))
('A', 'B')

print (get_n_largest(matrix,2))
('C', 'D')