[英]filter by array numpy
I am trying to filter my ndarray by another array I have collected (with the same values) 我正在尝试通过收集的另一个数组(具有相同的值)来过滤我的ndarray
My main ndarray looks like 我的主要ndarray看起来像
[['Name' 'Col1' 'Count']
['test' '' '413']
['erd' ' ' '60']
...,
['Td1' 'f' '904']
['Td2' 'K' '953']
['Td3' 'r' '111']]
I have another list with various matching names 我还有另一个带有各种匹配名称的列表
names = ['Td1','test','erd']
What I'd Like to Do 我想做什么
I'd like to use the list names as a filter against the ndarray above? 我想将列表名称用作针对上述ndarray的过滤器?
What I've Tried 我尝试过的
name_filter = main_ndarray[:,0] == names
This does not work 这行不通
What I'd Expect 我期望什么
[['Name' 'Col1' 'Count']
['test' '' '413']
['erd' ' ' '60']
['Td1' 'f' '904']]
You can use the filter
function too. 您也可以使用
filter
功能。
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)
gives: 给出:
[array(['test', '', '413'],
dtype='|S5'), array(['erd', ' ', '60'],
dtype='|S5'), array(['Td1', 'f', '904'],
dtype='|S5')]
Consider using Pandas for this kind of data: 考虑将Pandas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)]
Results: 结果:
>>> df
Name Col1 Count
0 test 413
1 erd 60
2 Td1 f 904
3 Td2 K 953
4 Td3 r 111
>>> result
Name Col1 Count
0 test 413
1 erd 60
2 Td1 f 904
>>>
References 参考文献
I would also go with @YXD's Pandas solution but just for the sake of completeness I also provide a simple solution based on list comprehension: 我也将使用@YXD的Pandas解决方案,但是出于完整性考虑,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])
which then gives you the desired output: 然后为您提供所需的输出:
[['Name', 'Col1', 'Count'],
['test', '', '413'],
['erd', ' ', '60'],
['Td1', 'f', '904']]
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