Python Change values in one list by referring to a second one

[kkhhhkk]

I have two lists, we'll call them x and n, I've been trying to write a script that goes through the elements of list n and if they are negative then to change the corresponding index element of x to a positive value
I've tried

for i in range(0,len(n),1):
    if n[i]<0:
        x[i] = abs(x[i])

However this returns the error out of range, I've also tried:

p=[]
for i in range(0,len(n),1):
    if n[i]<0:
        p.append(i)
for i in p:
    x[p[i]] = abs(x[i])

but this returns the same error

 

[menator01]

Are you trying to do something like this?

n = [1,3,5,-5,8,3,-1]
x = [1,3,5,-5,8,3,-1]

for index, item in enumerate(n):
    if n[index] < 0:
        x[index] = abs(x[index])

print(n)
print(x)

Output:

[1, 3, 5, -5, 8, 3, -1]
[1, 3, 5, -5, 8, 3, -1]

After
[1, 3, 5, -5, 8, 3, -1]
[1, 3, 5, 5, 8, 3, 1]

 

[Deleted member 2829]

Of course you can do it completely differently, as @menator01 suggests. There are always other ways.
But to simply fix the error you are getting, just use len(n)-1 instead of len(n). Recall that modern languages start counting at zero, so if you have an array n with 4 elements, the last element is n[3], not n[4].

 

[hanginthere]

Actually, range(num) evaluates from 0 to num-1 as you can see if you execute list(range(5)), so do not subtract 1 in the statement. Perhaps you should test to make sure the two lists are actually the same length.

 

[Deleted member 2829]

Actually, range(num) evaluates from 0 to num-1 as you can see if you execute list(range(5)), so do not subtract 1 in the statement. Perhaps you should test to make sure the two lists are actually the same length.

Yes you are right, I was rather jumping to conclusions here 😳
It would have helped if the OP had indicated the line where the error is reported. I wonder why so many people do not bother to give the context of an error, leaving it to others to guess the problem spot as well as the problem itself.

 

[menator01]

That's why I prefer not to use len if I can avoid it.

 

[hanginthere]

One other thing I just learned (and it makes sense when you hear the explanation) - when you are working with slices in pandas DataFrames, both the start and end values are inclusive. The reason is that you can use slices with string (column header) values so it is clearer when you are selecting columns as ['Hobbyist':'Age'].