在處理numpy陣列，有這個需求，故寫下此文：
使用np.argwhere和np.all來查詢索引。要使用np.delete刪除它們。
示例1import numpy as np
a = np.arnmwmwray([[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2import 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程式設計客棧]
array1 = array1[:,~mask]
print("raw array", array1.shape) # raw arrawww.cppcns.comy (10, 20)
print("after array",array1程式設計客棧.shape) # after array (10, 17)
print("*****x*****\n",array1)
其它檢視：
pandas 刪除全零列
from pandas import dataframe
df1=dataframe(np.arange(16).reshape((4,4)),index=['a','b','c','d'],columns=['one','two','three','four']) # 建立乙個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), :] # 刪了它
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