Python: Replacing modified Pandas Series elements based on index

I have a series, (call it x) which is generated according to the following logic:

1. Extract x from y (x is a subset of y, both are Series)
2. perform a number of manipulations on the elements of x

Now what I wnat to do is to put the elements of x (different values now) back to where they came from in y

To be concrete, here is (a subset of) what x and y look like:

>>> x         
2     0.026610
5     0.128612
8    -0.208833
11   -0.148410
14   -0.110574
17    0.187002


>>> y
0     0.259825
1     0.171325
2     0.195750
3     0.290775
4     0.319075
5     0.278700
6    -0.036125
7     0.102525
8    -0.044000
9    -0.539275
10   -0.573875
11   -0.008500
12    0.141325
13    0.186975
14    0.074875
15    0.079925
16    0.224075
17    0.358475
18   -0.107125

What I'm trying to do is to re-insert the elemnents of x back into y, based on their index. SO that, for example when I'm done, the y value associated with index=2 (currently 0.195750) would be replaced with the x value associated with index = 2 (0.026610).

Certainly I could brute force this, but looking for a better way.

A conditional list comprehension does at least put things in the right place, like so:

z = [y[i] if y.index[i] not in x.index else x[i] for i in range(len(y))]

But if I do the above, now I have a list and have the convert back to a Series, applying the index from y.

zS = pd.Series(z, index = y.index)

Could do that. I'm just wondering if there is some built in Pandas-magic that would get me there perhaps more cleanly and/or simply - going stright to a Series. Seems like there must be such a thing.

Thanks in advance.