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Fixes for the latest pandas. (#10266)

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Co-authored-by: Philip Hyunsu Cho <chohyu01@cs.washington.edu>
This commit is contained in:
Jiaming Yuan
2024-05-12 11:15:46 +08:00
committed by GitHub
parent 5e816e616a
commit d81e319e78
2 changed files with 36 additions and 28 deletions
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24
tests/python/test_with_pandas.py
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@@ -280,10 +280,12 @@ class TestPandas:
}
)
y = pd.Series(pd.arrays.SparseArray(np.random.randn(rows)))
dtrain = xgb.DMatrix(X, y)
with pytest.warns(UserWarning, match="Sparse arrays from pandas"):
dtrain = xgb.DMatrix(X, y)
booster = xgb.train({}, dtrain, num_boost_round=4)
predt_sparse = booster.predict(xgb.DMatrix(X))
predt_dense = booster.predict(xgb.DMatrix(X.sparse.to_dense()))
with pytest.warns(UserWarning, match="Sparse arrays from pandas"):
predt_sparse = booster.predict(xgb.DMatrix(X))
predt_dense = booster.predict(xgb.DMatrix(X.sparse.to_dense()))
np.testing.assert_allclose(predt_sparse, predt_dense)
def test_pandas_label(
@@ -572,14 +574,16 @@ class TestPandas:
y = pd.Series(pd.arrays.SparseArray(np.random.randn(rows)))
def verify_pandas_sparse():
dtrain = xgb.DMatrix(X, y, data_split_mode=DataSplitMode.COL)
with pytest.warns(UserWarning, match="Sparse arrays from pandas"):
dtrain = xgb.DMatrix(X, y, data_split_mode=DataSplitMode.COL)
booster = xgb.train({}, dtrain, num_boost_round=4)
predt_sparse = booster.predict(
xgb.DMatrix(X, data_split_mode=DataSplitMode.COL)
)
predt_dense = booster.predict(
xgb.DMatrix(X.sparse.to_dense(), data_split_mode=DataSplitMode.COL)
)
with pytest.warns(UserWarning, match="Sparse arrays from pandas"):
predt_sparse = booster.predict(
xgb.DMatrix(X, data_split_mode=DataSplitMode.COL)
)
predt_dense = booster.predict(
xgb.DMatrix(X.sparse.to_dense(), data_split_mode=DataSplitMode.COL)
)
np.testing.assert_allclose(predt_sparse, predt_dense)
tm.run_with_rabit(world_size=3, test_fn=verify_pandas_sparse)