按数组数筛选

Question

我正在尝试用我收集的另一个数组（具有相同的值）筛选我的ndarray

我的主要任务是

[['Name' 'Col1' 'Count']
 ['test' '' '413']
 ['erd' ' ' '60']
 ..., 
 ['Td1' 'f' '904']
 ['Td2' 'K' '953']
 ['Td3' 'r' '111']]

我有另一份名单，上面有各种匹配的名字

^{pr2}$

我想做什么

我想用列表名称作为对上面的ndarray的过滤器？在

我尝试过的

name_filter = main_ndarray[:,0] == names

这不管用

我所期望的

[['Name' 'Col1' 'Count']
 ['test' '' '413']
 ['erd' ' ' '60']
 ['Td1' 'f' '904']]

Answer 1

您也可以使用filter函数。在

cats_array = numpy.array(
 [['Name' ,'Col1', 'Count'],
 ['test', '' ,'413'],
 ['erd' ,' ' ,'60'],
 ['Td1' ,'f' ,'904'],
 ['Td2' ,'K' ,'953'],
 ['Td3' ,'r', '111']]
 )

 names = ['Td1','test','erd']

 filter(lambda x: x[0] in names, cats_array)

给出：

^{pr2}$

Answer 2

我也会使用@YXD的Pandas解决方案，但为了完整起见，我还提供了一个基于列表理解的简单解决方案：

data = [['Name', 'Col1', 'Count'],
 ['test', '', '413'],
 ['erd', ' ', '60'],
 ['Td1', 'f', '904'],
 ['Td2', 'K', '953'],
 ['Td3', 'r', '111']]

names = ['Td1', 'test', 'erd']

# select all sublist of data
res = [l for l in data if l[0] in names]

# insert the first row of data
res.insert(0, data[0]) 

然后得到所需的输出：

^{pr2}$

Answer 3

考虑将熊猫用于此类数据：

import pandas as pd

data = [['Name', 'Col1', 'Count'],
        ['test', '', '413'],
        ['erd', ' ', '60'],
        ['Td1', 'f', '904'],
        ['Td2', 'K', '953'],
        ['Td3', 'r', '111']]

df = pd.DataFrame(data[1:], columns=data[0])
names = ['Td1','test','erd']
result = df[df.Name.isin(names)]

结果：

^{pr2}$

参考文献

• http://pandas.pydata.org/
• Filter dataframe rows if value in column is in a set list of values