来源：自学PHP网 时间：2020-09-27 14:46 作者：小飞侠 阅读:次
[导读] Numpy(Pandas)删除全为零的列的方法...
|
今天带来Numpy(Pandas)删除全为零的列的方法教程详解
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 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)
其它查看：https://moonbooks.org/Articles/How-to-remove-array-rows-that-contain-only-0-in-python/ pandas 删除全零列 from pandas import DataFrame df1=DataFrame(np.arange(16).reshape((4,4)),index=['a','b','c','d'],columns=['one','two','three','four']) # 创建一个dataframe df1.loc['e'] = 0 # 优雅地增加一行全0 df1.ix[(df1==0).all(axis=1), :] # 找到它 df1.ix[~(df1==0).all(axis=1), :] # 删了它 到此这篇关于Numpy(Pandas)删除全为零的列的方法的文章就介绍到这了,更多相关Numpy删除全为零的列内容请搜索自学php网以前的文章或继续浏览下面的相关文章希望大家以后多多支持自学php网！ 以上就是关于Numpy(Pandas)删除全为零的列的方法全部内容,感谢大家支持自学php网。 |
自学PHP网专注网站建设学习,PHP程序学习,平面设计学习，以及操作系统学习
京ICP备14009008号-1@版权所有www.zixuephp.com
网站声明：本站所有视频，教程都由网友上传，站长收集和分享给大家学习使用，如由牵扯版权问题请联系站长邮箱904561283@qq.com
