BUG: pd.SparseDtype('int', 0) == pd.SparseDtype('int', pd.NA) returns pd.NA

[zfaee]

Pandas version checks

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Reproducible Example

import pandas as pd

int_fill_0 = pd.SparseDtype('int', 0)
int_fill_n = pd.SparseDtype('int', pd.NA)

r = (int_fill_0 == int_fill_n)
# pd.NA

r_reverse = (int_fill_n == int_fill_0)
# False

Issue Description

Equality comparison of SparseDtype filled by pd.NA and SparseDtype filled by non-na returns pd.NA, and is not symmetric.

Expected Behavior

It should return False.

Installed Versions

Replace this line with the output of pd.show_versions()

[kshitiz305]

take

[tqa236]

take

[joooeey]

It should return False.

The docs say that comparisons with pd.NA should evaulate to pd.NA (not to a boolean).

The fix #57783 implements NaN-like two-valued logic as exemplified by the tests: assert a != b and assert b != a where b = SparseDtype(float, pd.NA). That is, after the fix, both comparisons in the OP evaluate to False but by the docs both should evaluate to pd.NA.