Numpy(Pandas)删除全为零的列的方法

在处理numpy数组，有这个需求，故写下此文：

使用np.argwhere和np.all来查找索引。要使用np.delete删除它们。

示例1

import numpy as npa = 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 nparray1 = 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)

其它查看：Python开发/ 删除全零列

from pandas import DataFramedf1=DataFrame(np.arange(16).reshape((4,4)),index=[\'a\',\'b\',\'c\',\'d\'],columns=[\'one\',\'two\',\'three\',\'four\'])   # 创建一个dataframedf1.loc[\'e\'] = 0          # 优雅地增加一行全0df1.ix[(df1==0).all(axis=1), :]  # 找到它df1.ix[~(df1==0).all(axis=1), :]  # 删了它

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