Series.diff returns Series['float'] even for nullable integers

[MarcoGorelli]

Describe the bug
A clear and concise description of what the bug is.

To Reproduce

1. Provide a minimal runnable pandas example that is not properly checked by the stubs.
2. Indicate which type checker you are using (mypy or pyright).
3. Show the error message received from that type checker while checking your example.

import pandas as pd


reveal_type(pd.Series([1,2,3], dtype='Int64').diff())
#  note: Revealed type is "pandas.core.series.Series[builtins.float]"

Please complete the following information:

• OS: [e.g. Windows, Linux, MacOS] linux
• OS Version [e.g. 22] 22.04
• python version 3.12.5
• version of type checker mypy 1.15
• version of installed pandas-stubs 2.2.3.241126

Additional context
noticed looking into #1108

[Dr-Irv]

This one could take some work to fix, because we don't differentiate between pd.Series([1,2,3], dtype='Int64') and pd.Series([1,2,3], dtype=int) in the stubs. pd.Series([1,2,3], dtype='Int64').diff() remains a series of integers (with pd.NA as the missing value), whereas pd.Series([1,2,3], dtype=int) becomes a Series[float] because np.nan becomes the missing value.

It might be possible to introduce a class hierarchy of base class of AllInt with subclasses BaseInt and NullableInt and then we replace Series[int] with Series[AllInt] everywhere, modify Series.__new__() to return either Series[BaseInt] or Series[NullableInt] based on dtype and then in Series.diff() have overloads to return different results based on whether you had Series[BaseInt] or Series[NullableInt].

This would be a big change - would have to modify a lot of PYI files and tests.