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.
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