# Buggy code
def _count_level(self, level, axis=0, numeric_only=False):
    if numeric_only:
        frame = self._get_numeric_data()
    else:
        frame = self

    count_axis = frame._get_axis(axis)
    agg_axis = frame._get_agg_axis(axis)

    if not isinstance(count_axis, ABCMultiIndex):
        raise TypeError(
            f"Can only count levels on hierarchical {self._get_axis_name(axis)}."
        )

    if frame._is_mixed_type:
        # Since we have mixed types, calling notna(frame.values) might
        # upcast everything to object
        mask = notna(frame).values
    else:
        # But use the speedup when we have homogeneous dtypes
        mask = notna(frame.values)

    if axis == 1:
        # We're transposing the mask rather than frame to avoid potential
        # upcasts to object, which induces a ~20x slowdown
        mask = mask.T

    if isinstance(level, str):
        level = count_axis._get_level_number(level)

    level_name = count_axis._names[level]
    level_index = count_axis.levels[level]._shallow_copy(name=level_name)
    level_codes = ensure_int64(count_axis.codes[level])
    counts = lib.count_level_2d(mask, level_codes, len(level_index), axis=0)

    result = DataFrame(counts, index=level_index, columns=agg_axis)

    if axis == 1:
        # Undo our earlier transpose
        return result.T
    else:
        return result


# Traceback (IndexError)
Traceback (most recent call last):
File "<stdin>", line 1, in <module>
File "/pandas/pandas/core/groupby/generic.py", line 1784, in count
blocks = [make_block(val, placement=loc) for val, loc in zip(counted, locs)]
File "/pandas/pandas/core/groupby/generic.py", line 1784, in <listcomp>
blocks = [make_block(val, placement=loc) for val, loc in zip(counted, locs)]
File "/pandas/pandas/core/groupby/generic.py", line 1782, in <genexpr>
lib.count_level_2d(x, labels=ids, max_bin=ngroups, axis=1) for x in vals
File "pandas/_libs/lib.pyx", line 803, in pandas._libs.lib.count_level_2d
counts[i, labels[j]] += mask[i, j]
IndexError: Out of bounds on buffer access (axis 1)

# Fixed code
def _count_level(self, level, axis=0, numeric_only=False):
    if numeric_only:
        frame = self._get_numeric_data()
    else:
        frame = self

    count_axis = frame._get_axis(axis)
    agg_axis = frame._get_agg_axis(axis)

    if not isinstance(count_axis, ABCMultiIndex):
        raise TypeError(
            f"Can only count levels on hierarchical {self._get_axis_name(axis)}."
        )

    # Mask NaNs: Mask rows or columns where the index level is NaN, and all
    # values in the DataFrame that are NaN
    if frame._is_mixed_type:
        # Since we have mixed types, calling notna(frame.values) might
        # upcast everything to object
        values_mask = notna(frame).values
    else:
        # But use the speedup when we have homogeneous dtypes
        values_mask = notna(frame.values)

    index_mask = notna(count_axis.get_level_values(level=level))
    if axis == 1:
        mask = index_mask & values_mask
    else:
        mask = index_mask.reshape(-1, 1) & values_mask

    if isinstance(level, str):
        level = count_axis._get_level_number(level)

    level_name = count_axis._names[level]
    level_index = count_axis.levels[level]._shallow_copy(name=level_name)
    level_codes = ensure_int64(count_axis.codes[level])
    counts = lib.count_level_2d(mask, level_codes, len(level_index), axis=axis)

    if axis == 1:
        result = DataFrame(counts, index=agg_axis, columns=level_index)
    else:
        result = DataFrame(counts, index=level_index, columns=agg_axis)

    return result