Pandas Int64Dtype conversion seems to casts to double first in the Series constructor

Constructing a Series with dtype=Int64Dtype() suggests that there can be an intermiediate conversion to double if the input contains NaNs:

import pandas as pd
n = 2**62+5
print(n, int(float(n)))
print(pd.Series([n, float('nan')]))
print(pd.Series([n, float('nan')], dtype=pd.Int64Dtype()))
print(pd.Series([n, float('nan')], dtype=object).astype(pd.Int64Dtype()))

In both latter cases we end up with a Series with dtype=Int64 containing integer NaNs. However, in the penultimate case we get the int-float-int converted value of n (4611686018427387904), and we only get the exact Int64 result (4611686018427387909) if we instantiate the Series with dtype=object and convert afterward.

This doesn't happen if the input doesn't contain any NaNs:

print(pd.Series([n, n+3], dtype=pd.Int64Dtype()))

Expected output is 4611686018427387909 inside the Series constructed with dtype=Int64Dtype(). Issue is there in master.

Comment From: ztane

It does work with None though:

>>> pandas.Series([2 ** 62 + 5, None], dtype='Int64')
0    4611686018427387909
1                    NaN
dtype: Int64