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FIX Do not use deprecated API in fetch_20newsgroups_vectorized #21216

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Oct 5, 2021
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2 changes: 1 addition & 1 deletion sklearn/datasets/_twenty_newsgroups.py
Original file line number Diff line number Diff line change
Expand Up @@ -479,7 +479,7 @@ def fetch_20newsgroups_vectorized(
vectorizer = CountVectorizer(dtype=np.int16)
X_train = vectorizer.fit_transform(data_train.data).tocsr()
X_test = vectorizer.transform(data_test.data).tocsr()
feature_names = vectorizer.get_feature_names()
feature_names = vectorizer.get_feature_names_out()

joblib.dump((X_train, X_test, feature_names), target_file, compress=9)

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8 changes: 4 additions & 4 deletions sklearn/utils/tests/test_validation.py
Original file line number Diff line number Diff line change
Expand Up @@ -1414,8 +1414,8 @@ def test_check_pandas_sparse_invalid(ntype1, ntype2):
pd = pytest.importorskip("pandas", minversion="0.25.0")
df = pd.DataFrame(
{
"col1": pd.arrays.SparseArray([0, 1, 0], dtype=ntype1),
"col2": pd.arrays.SparseArray([1, 0, 1], dtype=ntype2),
"col1": pd.arrays.SparseArray([0, 1, 0], dtype=ntype1, fill_value=0),
"col2": pd.arrays.SparseArray([1, 0, 1], dtype=ntype2, fill_value=0),
Comment on lines +1417 to +1418
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@thomasjpfan thomasjpfan Oct 3, 2021

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These are causing issues on pandas because the fill value is different depending on the dtype.

https://pandas.pydata.org/docs/reference/api/pandas.arrays.SparseArray.html#pandas-arrays-sparsearray

And this is raising a ValueError on the dev version of pandas

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Does your change then fix the issue? Can't tell from your explanation

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I would guess that this fixes the issue but to double-check I pushed an empty commit with [scipy-dev] to trigger the scipy-dev nightly build in this PR.

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@thomasjpfan thomasjpfan Oct 4, 2021

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Yea it fixes the original issue.

There were two issues. With the fix to fetch_20newsgroups_vectorized, it alloed the tests to run, which revealed the pandas issue.

}
)

Expand Down Expand Up @@ -1456,8 +1456,8 @@ def test_check_pandas_sparse_valid(ntype1, ntype2, expected_subtype):
pd = pytest.importorskip("pandas", minversion="0.25.0")
df = pd.DataFrame(
{
"col1": pd.arrays.SparseArray([0, 1, 0], dtype=ntype1),
"col2": pd.arrays.SparseArray([1, 0, 1], dtype=ntype2),
"col1": pd.arrays.SparseArray([0, 1, 0], dtype=ntype1, fill_value=0),
"col2": pd.arrays.SparseArray([1, 0, 1], dtype=ntype2, fill_value=0),
}
)
arr = check_array(df, accept_sparse=["csr", "csc"])
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