fix(docs): handle NaN metadata cells in macro table generator

docs/source/whats_new.rst

@@ -74,6 +74,8 @@ Bugs
 - Fix missing electrode positions (NaN xyz) in six motor-imagery datasets so topographic maps, interpolation, and spatial methods work: :class:`moabb.datasets.Forenzo2023` and :class:`moabb.datasets.GuttmannFlury2025_MI`/``_ME`` normalize Neuroscan ALL_CAPS labels and apply ``standard_1005`` (CB1/CB2 kept as ``misc``); :class:`moabb.datasets.Dreyer2023` falls back to ``standard_1005`` when the BIDS archive ships no ``electrodes.tsv``; :class:`moabb.datasets.BNCI2003_004` maps its 26 legacy Berlin channel labels to their modern 10-5 equivalents for exact positions; :class:`moabb.datasets.BNCI2014_002` applies an approximate 3x5 grid for its unlabeled small-Laplacian channels; and :class:`moabb.datasets.Zhang2017` applies the ``GSN-HydroCel-32`` montage in EGI sensor order. Adds the shared :func:`moabb.datasets.utils.set_neuroscan_montage` helper (:gh:`1089` by `Bruno Aristimunha`_).
 - Fix ``BaseEvaluation._aggregate_fold_results`` aborting the whole evaluation with ``TypeError: agg function failed [how->mean,dtype->object]`` when a single fold contributes a non-numeric ``score`` (e.g. an error fold). The numeric aggregation columns are now coerced with ``pandas.to_numeric(errors="coerce")`` before ``groupby.agg``, so a bad fold becomes ``NaN`` and is skipped instead of taking down every subject/pipeline (:gh:`1095` by `Bruno Aristimunha`_).
 - Fix :class:`moabb.evaluations.splitters.WithinSessionSplitter` and :class:`moabb.evaluations.splitters.WithinSubjectSplitter` overwriting an explicit ``n_splits`` passed through ``cv_kwargs`` with the ``n_folds`` default; the caller-provided ``n_splits`` now takes precedence, so a single holdout split can be requested directly via ``cv_class=StratifiedShuffleSplit, n_splits=1``. :class:`moabb.evaluations.WithinSessionEvaluation` and :class:`moabb.evaluations.WithinSubjectEvaluation` now honour the ``n_splits`` argument instead of always running 5 folds, and :class:`moabb.evaluations.splitters.WithinSubjectSplitter` now yields reproducible per-subject folds for a fixed ``random_state`` (:gh:`1106` by `Bruno Aristimunha`_).
+- Fix ``make html`` crash in ``scripts/generate_macro_table.py`` when a dataset has a missing (``NaN``) value in an optional metadata column (country, DOI, data URL, ...): the float ``NaN`` is truthy, so it slipped past the ``if not value`` guards and crashed the string formatters (``TypeError: object of type 'float' has no len()``). ``NaN`` cells are now normalized to ``""`` before formatting (:gh:`1117` by `Bhargav Kowshik`_).
+
 Code health
 ~~~~~~~~~~~
 - Install CPU-only PyTorch wheels in CI by setting ``UV_TORCH_BACKEND=cpu`` in the test, braindecode, and docs workflows, so runners no longer download multi-GB CUDA builds of ``torch`` (pulled transitively via the ``deeplearning`` extra / braindecode) (:gh:`1083` by `Bhargav Kowshik`_).

scripts/generate_macro_table.py

@@ -490,6 +490,12 @@ def _truncate(text: str, max_len: int = _TRUNCATE_LEN) -> str:
 
 def _format_cell(value, fmt: str, row=None) -> str:
     """Format a single cell value according to its type."""
+    # pandas stores missing cells as float NaN, which is truthy and therefore
+    # slips past the ``if not value`` guards in the formatters below (country,
+    # _doi_link, _data_url_link, _health_tag), then crashes on str/len ops.
+    # Normalize it to "" once here so every formatter sees a clean empty value.
+    if isinstance(value, float) and pd.isna(value):
+        value = ""
     if fmt == "link":
         return _dataset_link(value)
     if fmt == "paradigm_tag":