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Reproducible Example

>>>import pandas as pd
>>>s = pd.Series([5.4954145E+29, -9.791984E-21, 9.3715776E-26, pd.NA, 1.8790257E-28], dtype="Float64")
>>>s.rank(method="min")
0    4.0
1    1.0
2    1.0
3    NaN
4    1.0
dtype: float64
>>>s1 = s.astype("float64")
>>>s1.rank("min")
0    4.0
1    1.0
2    3.0
3    NaN
4    2.0
dtype: float64

Issue Description

From the above example code, we can see different "Float64" type data values, -9.791984E-21, 9.3715776E-26, and 1.8790257E-28, when we rank them with method="min", they are assigned with same rank. If we cast the type to "float64" and call s.rank(method="min"), we can get the right results.

Expected Behavior

For "Float64" type data values, -9.791984E-21, 9.3715776E-26, and 1.8790257E-28, when we rank them with method="min", they should be assigned with different ranks.

Installed Versions