如何在numpy数组中选择特定的列?

时间:2015-12-27 15:52:34

标签: python arrays numpy

假设我有20x100 numpy数组。我想选择除50号之外的所有列。 所以我关注了这个帖子Extracting specific columns in numpy array 但它没有帮助。我尝试使用

 x=Z[:,[:49,51:]] 

但是给出了错误。在R中很容易做到这一点

x=Z[,c(1:49,51:100)] 

但是在Python中无法弄明白。 请帮忙。感谢

4 个答案:

答案 0 :(得分:4)

在这里获得类似R语法的一种方法是使用np.r_

>>> Z = np.arange(2000).reshape(20, 100)
>>> Z.shape
(20, 100)
>>> x = Z[:,np.r_[:49,50:100]]
>>> x.shape
(20, 99)
>>> x[0,48:52]
array([48, 50, 51, 52])

我们发现x中缺少第50列(编号49)。

答案 1 :(得分:1)

这样可行:

>>> a = np.arange(2000).reshape(20, 100)
>>> b = a[:, np.arange(a.shape[1]) != 50]
>>> b.shape
(20, 99)

答案 2 :(得分:1)

您只需使用np.delete()删除第50列:

A = np.delete(A, 50, 1)

演示:

>>> import numpy as np
>>> A = np.arange(100).reshape(25,4)
>>> A
array([[ 0,  1,  2,  3],
       [ 4,  5,  6,  7],
       [ 8,  9, 10, 11],
       [12, 13, 14, 15],
       [16, 17, 18, 19],
       [20, 21, 22, 23],
       [24, 25, 26, 27],
       [28, 29, 30, 31],
       [32, 33, 34, 35],
       [36, 37, 38, 39],
       [40, 41, 42, 43],
       [44, 45, 46, 47],
       [48, 49, 50, 51],
       [52, 53, 54, 55],
       [56, 57, 58, 59],
       [60, 61, 62, 63],
       [64, 65, 66, 67],
       [68, 69, 70, 71],
       [72, 73, 74, 75],
       [76, 77, 78, 79],
       [80, 81, 82, 83],
       [84, 85, 86, 87],
       [88, 89, 90, 91],
       [92, 93, 94, 95],
       [96, 97, 98, 99]])
>>> 
>>> A = np.delete(A, 2, 1)
>>> A
array([[ 0,  1,  3],
       [ 4,  5,  7],
       [ 8,  9, 11],
       [12, 13, 15],
       [16, 17, 19],
       [20, 21, 23],
       [24, 25, 27],
       [28, 29, 31],
       [32, 33, 35],
       [36, 37, 39],
       [40, 41, 43],
       [44, 45, 47],
       [48, 49, 51],
       [52, 53, 55],
       [56, 57, 59],
       [60, 61, 63],
       [64, 65, 67],
       [68, 69, 71],
       [72, 73, 75],
       [76, 77, 79],
       [80, 81, 83],
       [84, 85, 87],
       [88, 89, 91],
       [92, 93, 95],
       [96, 97, 99]])

答案 3 :(得分:0)

或者,您可以iloc

import numpy as np
import pandas as pd
data = np.random.normal(size=2000).reshape(20, 100)
df = pd.DataFrame(data, columns=list(range(1,101)))
df.iloc[:,list(range(49)) + list(range(50, 100))]