Question

我有一系列的numpy数组：

import pandas as pd
import numpy as np
pd.Series({10: np.array([[0.72260683, 0.27739317, 0.        ],
                         [0.7187053 , 0.2812947 , 0.        ],
                         [0.71435467, 0.28564533, 1.        ],
                         [0.3268072 , 0.6731928 , 0.        ],
                         [0.31941951, 0.68058049, 1.        ],
                         [0.31260015, 0.68739985, 0.        ]]), 
           20: np.array([[0.7022099 , 0.2977901 , 0.        ],
                         [0.6983866 , 0.3016134 , 0.        ],
                         [0.69411673, 0.30588327, 1.        ],
                         [0.33857735, 0.66142265, 0.        ],
                         [0.33244109, 0.66755891, 1.        ],
                         [0.32675582, 0.67324418, 0.        ]]), 
           38: np.array([[0.68811957, 0.31188043, 0.        ],
                         [0.68425783, 0.31574217, 0.        ],
                         [0.67994496, 0.32005504, 1.        ],
                         [0.34872593, 0.65127407, 0.        ],
                         [0.34276171, 0.65723829, 1.        ],
                         [0.33722803, 0.66277197, 0.        ]])}
)

和索引np.array([1, 4, 1])的数组，该索引指示应从连续数组中过滤出哪些行。预期的输出将是这样的：

pd.Series({10: np.array([[0.7187053 , 0.2812947 , 0.        ]]), 
           20: np.array([[0.33244109, 0.66755891, 1.        ]]), 
           38: np.array([[0.68425783, 0.31574217, 0.        ]])}
)

我该怎么做？如果我想从每个结果数组中取出第三个元素以获得以下Series，会有什么不同？

pd.Series({10: 0, 20: 1, 30: 0})

Answer 1

如果可能，将2d数组系列转换为每个2d数组的3d数组（相同长度）：

a = np.array([1, 4, 1])

b = np.array(s.tolist())[np.arange(len(s)), a, 2]
print (b)
[0. 1. 0.]

c = pd.Series(b, index=s.index)
print (c)
10    0.0
20    1.0
38    0.0
dtype: float64

如果要按索引数组选择：

b1 = np.array(s.tolist())[np.arange(len(s)), a]
print (b1)

[[0.7187053  0.2812947  0.        ]
 [0.33244109 0.66755891 1.        ]
 [0.68425783 0.31574217 0.        ]]

如何从熊猫系列中存储的后续numpy数组中选择元素

1 个答案: