Numpy（Pandas） 删除全為零的列

在處理numpy數組，有這個需求，故寫下此文：

使用​

​np.argwhere​

​​和​

​np.all​

​​來查找索引。要使用​

​np.delete​

​删除它們。

示例1

import numpy as np


a = np.array([[1, 2, 0, 3, 0],
              [4, 5, 0, 6, 0],
              [7, 8, 0, 9, 0]])

idx = np.argwhere(np.all(a[..., :] == 0, axis=0))
a2 = np.delete(a, idx, axis=1)

print(a2)

"""
[[1 2 3]
 [4 5 6]
 [7 8 9]]
"""      

示例2

import numpy as np


array1 = np.array([[1,0,1,0,0,0,0,0,0,1,1,0,0,0,1,1,0,1,0,0],
                   [0,1,1,0,0,1,1,1,1,0,0,0,1,0,1,0,0,1,1,1],
                   [0,0,1,0,0,1,1,1,0,0,0,0,0,0,0,1,0,0,1,1],
                   [0,1,1,0,0,1,1,1,1,0,1,1,1,0,0,1,0,0,1,1],
                   [0,0,1,0,0,1,1,1,0,1,0,1,1,0,1,1,0,0,1,0],
                   [1,0,1,0,0,0,1,0,0,1,1,1,1,0,1,1,0,0,1,0],
                   [1,0,1,0,1,1,0,0,0,0,1,0,0,0,1,0,0,0,1,1],
                   [0,1,0,0,1,0,0,0,1,0,1,1,1,0,1,0,0,1,1,0],
                   [0,1,0,0,1,0,0,1,1,0,1,1,1,0,0,1,0,1,0,0],
                   [1,0,0,0,0,1,0,1,0,0,0,1,1,0,0,1,0,1,0,0]])

mask = (array1 == 0).all(0)
column_indices = np.where(mask)[0]
array1 = array1[:,~mask]

print("raw  array", array1.shape)   # raw  array (10, 20)
print("after array",array1.shape)  # after array (10, 17)
print("=====x=====\n",array1)      

from pandas import DataFrame

df1=DataFrame(np.arange(16).reshape((4,4)),index=['a','b','c','d'],columns=['one','two','three','four'])      # 建立一個dataframe
df1.loc['e'] = 0                   # 優雅地增加一行全0
df1.ix[(df1==0).all(axis=1), :]    # 找到它
df1.ix[~(df1==0).all(axis=1), :]   # 删了它