TargetLeakageDataCheck wipes user-selected logical types

[freddyaboulton]

Repro

import pandas as pd
import woodwork as ww
from evalml.data_checks import TargetLeakageDataCheck

X = pd.DataFrame({"A": pd.Series([1, 2, 3]),
                  "B": pd.Series([4, 5, 6])})
y = pd.Series([1, 2, 3])

X.ww.init(logical_types={"A": "Unknown", "B": "Double"})

assert any(w['message'].startswith("Column 'A'") for w in TargetLeakageDataCheck().validate(X, y)['warnings'])

Woodwork only allows mutual information on numeric, categorical, boolean, and datetime features so if the TargetLeakageDataCheck were preserving the typing information set by the user, the mutual information for column A should not be calculated!

The issue is that in the TargetLeakageDataCheck, we create a dataframe without going through the ww accessor, so this wipes the logical types by mistake.