Iterate over two columns at the same time and change value of cells based on conditions

Question

I have a dataframe in the following format:

Index	Object1-Length	Object1-Height	Object2-Length	Object2-Height
0	19	49	21	52
1	20	50	21	51
2	20	51	20	52
3	19	50	19	52
4	20	50	20	52

It continues with Object3, Object4 and so on...

I want to check two columns at the same time in the following way:

if ObjectX-Length >= 20 and ObjectX-Height >= 50 

then set both cells of ObjectX to 1, else set them to 0

So this is the table I want:

Index	Object1-Length	Object1-Height	Object2-Length	Object2-Height
0	0	0	1	1
1	1	1	1	1
2	1	1	1	1
3	0	0	0	0
4	1	1	1	1

Is there any way to do this?

EDIT: Combining both columns of each object into one column and setting that cell to 0 or 1 would also work!

Answer 1

Let's try:

# length like columns
l = df.filter(like='-Length').columns

# corresponding height columns
h = l.str.rstrip('Length') + 'Height'

# create boolean mask
m = (df[l].ge(20).values & df[h].ge(50).values).astype(int)

# assign the values
df[h], df[l] = m, m

Details:

First filter the Length like columns, then create the corresponding Height columns:

print(l)
['Object1-Length', 'Object2-Length']

print(h)
['Object1-Height', 'Object2-Height']

Create boolean mask representing the condition where the ObjectX-Length >= 20 and ObjectX-Height >= 50:

print(m)
array([[0, 1],
       [1, 1],
       [1, 1],
       [0, 0],
       [1, 1]])

assign the mask to corresponding columns:

print(df)
       Object1-Length  Object1-Height  Object2-Length  Object2-Height
Index                                                                
0                   0               0               1               1
1                   1               1               1               1
2                   1               1               1               1
3                   0               0               0               0
4                   1               1               1               1