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[python-package] make a shallow copy on dataframe rename (fixes #4596) #5254

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Jun 5, 2022
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[python-package] make a shallow copy on dataframe rename (fixes #4596) #5254

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f37b868
dont copy dataframe on rename
jmoralez May 30, 2022
072ea47
test with feature_name and 'auto'
jmoralez Jun 1, 2022
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2 changes: 1 addition & 1 deletion python-package/lightgbm/basic.py
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Original file line number Diff line number Diff line change
Expand Up @@ -537,7 +537,7 @@ def _data_from_pandas(data, feature_name, categorical_feature, pandas_categorica
if len(data.shape) != 2 or data.shape[0] < 1:
raise ValueError('Input data must be 2 dimensional and non empty.')
if feature_name == 'auto' or feature_name is None:
data = data.rename(columns=str)
data = data.rename(columns=str, copy=False)
cat_cols = [col for col, dtype in zip(data.columns, data.dtypes) if isinstance(dtype, pd_CategoricalDtype)]
cat_cols_not_ordered = [col for col in cat_cols if not data[col].cat.ordered]
if pandas_categorical is None: # train dataset
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6 changes: 2 additions & 4 deletions tests/python_package_test/test_basic.py
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Expand Up @@ -648,9 +648,7 @@ def test_no_copy_when_single_float_dtype_dataframe(dtype):
pd = pytest.importorskip('pandas')
X = np.random.rand(10, 2).astype(dtype)
df = pd.DataFrame(X)
# feature names are required to not make a copy (rename makes a copy)
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This test currently tests "when you pass a pandas DataFrame and explicit list of feature names, a copy is not made".

This PR is proposing changing it to "when you pass a pandas DataFrame and feature_names="auto", a copy is not made".

To test the broader behavior "when you pass a pandas DataFrame, a copy is not made, regardless of how you specify feature names", would you consider instead changing the tests touched in this PR such that both cases (feature_name and "auto") are tested?

feature_name = ['x1', 'x2']
built_data = lgb.basic._data_from_pandas(df, feature_name, None, None)[0]
built_data = lgb.basic._data_from_pandas(df, 'auto', None, None)[0]
assert built_data.dtype == dtype
assert np.shares_memory(X, built_data)

Expand All @@ -659,7 +657,7 @@ def test_categorical_code_conversion_doesnt_modify_original_data():
pd = pytest.importorskip('pandas')
X = np.random.choice(['a', 'b'], 100).reshape(-1, 1)
df = pd.DataFrame(X.copy(), columns=['x1'], dtype='category')
data = lgb.basic._data_from_pandas(df, ['x1'], None, None)[0]
data = lgb.basic._data_from_pandas(df, 'auto', None, None)[0]
# check that the original data wasn't modified
np.testing.assert_equal(df['x1'], X[:, 0])
# check that the built data has the codes
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