for loop and indexing in Python

Question

I have a 2d array with four columns as follows:

import numpy as np
 testarray=np.array([[0, 662, 2, 12.0637], 
 [0, 662, 2, 3.197], 
 [0, 662, 1, 3.0323], 
 [1, 600, 2, 14.000], 
 [1, 600, 2, 13.000],
 [3, 500, 2, 17],
 [3, 500, 1, 15]])

For each row, if the value of the third column = 1 then I want to keep this row. I also want to keep all rows which matches the value in column 1. For example, row 3 has column 3 = 1. I want to keep this row, but also rows 1 and 2.

Expected output:

test array=[0, 662, 2, 12.0637], 
 [0, 662, 2, 3.197],
 [0, 662, 1, 3.0323],
 [3, 500, 2, 17]
 [3, 500, 1, 15]]

I have managed to extract the values in column one that I need to keep:

i=1
col3=testarray[testarray[:, 2]==i]
col1=np.delete(col3, np.s_[1:],axis=1) 
print(col1)

I just now need to somehow keep all the rows which have a corresponding value in the first column.

I am not sure if this makes sense? I feel like I need to do some sort of for loop or indexing but don't really know where to start. Please help!!!

• matheubv: What do you mean by "corresponding value in the first column"?
• okvoyce: If the 3rd column = 1, then I make a note of the value in the 1st column of that row (e.g. 0 in the first instance). I then need to keep all rows with 0 in the first column.

Answer 1

You identify the first columns where the third column is 1:

testarray[testarray[:,2]==1,0]
array([0., 3.])

Then its a matter of calling the rows whose 1st column contain these entries:

testarray[np.isin(testarray[:,0],testarray[testarray[:,2]==1,0]),:]
array([[ 0. , 662. , 2. , 12.0637],
 [ 0. , 662. , 2. , 3.197 ],
 [ 0. , 662. , 1. , 3.0323],
 [ 3. , 500. , 2. , 17. ],
 [ 3. , 500. , 1. , 15. ]])