Why I get NAN when calculate corr of those two pandas series?

I have two pandas Series object:

print(s1)
print("="*80)
print(s2)

# output

0   -0.443538
1   -0.255012
2   -0.582948
3   -0.393485
4    0.430831
5    0.232216
6   -0.014269
7   -0.133158
8    0.127162
9   -1.855860
Name: s1, dtype: float64
================================================================================
29160   -0.650857
29161   -0.135428
29162    0.039544
29163    0.241506
29164   -0.793352
29165   -0.054500
29166    0.901152
29167   -0.660474
29168    0.098551
29169    0.822022
Name: s2, dtype: float64

And I want to calculate corr of those two series:

s1.corr(s2)

#output

nan

I don’t know why I get ‘nan’ here, using numpy gives the correct result:

np.corrcoef(s1,s2)[0][1]

#output

-0.4918385039519204

Did I do something wrong in the above code?

>Solution :

Your series indices are not aligned. Pandas realigns s2 on s1 yielding only NaNs.

You can force the index of s1 on s2 using set_axis:

s1.corr(s2.set_axis(s1.index))

Output: -0.49183852303556697