fix(skore): Convert DataFrame column names to strings

[waridrox]

Closes #2029
CC: @thomass-dev

When debugging, in the data_accessor.py file:

skore/skore/src/skore/_sklearn/_estimator/data_accessor.py

Lines 49 to 67 in eb0d6e9

	if X is None:
	raise ValueError(err_msg.format(f"X_{dataset}", data_source))
	elif not sbd.is_dataframe(X):
	X = pd.DataFrame(X, columns=[f"Feature {i}" for i in range(X.shape[1])])
	if with_y:
	if y is None:
	raise ValueError(err_msg.format(f"y_{dataset}", data_source))
	if isinstance(y, pd.Series) and y.name is not None:
	y = y.to_frame()
	elif not sbd.is_dataframe(y):
	if y.ndim == 1:
	columns = ["Target"]
	else:
	columns = [f"Target {i}" for i in range(y.shape[1])]
	y = pd.DataFrame(y, columns=columns)
	return X, y

This method only converts numpy arrays to DataFrames with string column names, but doesn't handle the case if DataFrames already exist but have integer type column names.

This then further passes down to the skrub functions (which expects strings), and the final error of TypeError: cannot use a string pattern on a bytes-like object occurs because suggested_name is an integer from the RangeIndex columns.

def _get_new_name(suggested_name, forbidden_names):
    """Get a new name for a column."""
    # .......    
    tags = re.findall(tag_pattern, suggested_name)  # <==== 
    # .......

tag_pattern is a string regex pattern and re.findall(tag_pattern, suggested_name) method expects both arguments to be strings or both to be bytes-like objects.

I tried to overcome this by ensuring that the DataFrame object has string column names if it already exists to avoid issues with skrub later when passing down from data_accessor.py function.

Alternatively, should I simply just raise exception errors if the compute fails in subsequent steps instead of this?

[thomass-dev]

Thanks for your investigation and your contribution. Please add a dedicated test.

[auguste-probabl]

Thanks for this!

Simplified the tests a bit.

[github-actions]

Coverage Report for skore/

File	Stmts	Miss	Cover	Missing
skore/src/skore
__init__.py	23	0	100%
_config.py	31	0	100%
exceptions.py	4	4	0%	4, 15, 19, 23
skore/src/skore/_sklearn
__init__.py	6	0	100%
_base.py	198	14	92%	45, 58, 127, 130, 183, 186–187, 189–192, 225, 228–229
find_ml_task.py	61	0	100%
types.py	27	1	96%	28
skore/src/skore/_sklearn/_comparison
__init__.py	7	0	100%
feature_importance_accessor.py	39	2	94%	90, 109
metrics_accessor.py	178	3	98%	173, 253, 1215
report.py	107	0	100%
utils.py	54	0	100%
skore/src/skore/_sklearn/_cross_validation
__init__.py	9	0	100%
data_accessor.py	45	3	93%	128, 131, 134
feature_importance_accessor.py	24	0	100%
metrics_accessor.py	182	1	99%	244
report.py	135	1	99%	487
skore/src/skore/_sklearn/_estimator
__init__.py	9	0	100%
data_accessor.py	66	1	98%	76
feature_importance_accessor.py	144	2	98%	223–224
metrics_accessor.py	356	8	97%	200, 202, 209, 300, 369, 373, 388, 423
report.py	167	2	98%	448–449
skore/src/skore/_sklearn/_plot
__init__.py	3	0	100%
base.py	102	7	93%	61–62, 200, 224–226, 230
utils.py	77	0	100%
skore/src/skore/_sklearn/_plot/data
__init__.py	2	0	100%
table_report.py	185	1	99%	706
skore/src/skore/_sklearn/_plot/metrics
__init__.py	6	0	100%
confusion_matrix.py	70	4	94%	92, 100, 122, 230
feature_importance_display.py	67	21	68%	88, 121–122, 124, 142–146, 148–155, 158–160, 162
metrics_summary_display.py	8	0	100%
precision_recall_curve.py	280	5	98%	455, 555, 559, 619, 751
prediction_error.py	227	5	97%	179, 186, 422, 505, 705
roc_curve.py	292	8	97%	385, 508, 513, 614, 619, 623, 692, 832
skore/src/skore/_sklearn/train_test_split
__init__.py	0	0	100%
train_test_split.py	58	0	100%
skore/src/skore/_sklearn/train_test_split/warning
__init__.py	8	0	100%
high_class_imbalance_too_few_examples_warning.py	19	1	94%	83
high_class_imbalance_warning.py	20	0	100%
random_state_unset_warning.py	10	0	100%
shuffle_true_warning.py	9	0	100%
stratify_is_set_warning.py	10	0	100%
time_based_column_warning.py	21	0	100%
train_test_split_warning.py	3	0	100%
skore/src/skore/_utils
__init__.py	6	2	66%	8, 13
_accessor.py	90	3	96%	34, 146, 190
_environment.py	27	0	100%
_fixes.py	8	0	100%
_index.py	5	0	100%
_logger.py	22	4	81%	15–17, 19
_measure_time.py	10	0	100%
_parallel.py	38	3	92%	23, 33, 124
_patch.py	13	5	61%	21, 23–24, 35, 37
_progress_bar.py	46	0	100%
_repr_html.py	8	0	100%
_show_versions.py	38	0	100%
_testing.py	55	0	100%
skore/src/skore/project
__init__.py	2	0	100%
project.py	48	0	100%
summary.py	75	1	98%	120
widget.py	165	6	96%	436, 439–441, 525–526
TOTAL	4005	118	97%

Tests	Skipped	Failures	Errors	Time
1074	5 💤	0 ❌	0 🔥	4m 21s ⏱️

[github-actions]

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