In fact, duplicate labels on <= 2D arrays are kinda hit-or-miss:

>>> arr2d = ndtest("a=a0,a1;b=x,x")
>>> arr2d.to_csv('arr2d.csv')
>>> read_csv('arr2d.csv')
a\b  x  x.1
 a0  0    1
 a1  2    3

>>> arr2d.to_excel('test.xlsx', 'arr2d')
>>> read_excel('test.xlsx', 'arr2d')
a\b  x  x
 a0  0  1
 a1  2  3

>>> arr2d.to_hdf('test.h5', 'arr2d')
ValueError: Columns index has to be unique for fixed format

>>> arr2d_t = arr2d.T
>>> arr2d_t.to_hdf('test.h5', 'arr2d_t')
>>> read_hdf('test.h5', 'arr2d_t')
b\a  a0  a1
  x   0   2
  x   1   3

More testing is necessary (other combinations of duplicates in columns vs rows vs number of dimensions) but the conclusion is that duplicate labels are very poorly supported

Full support for duplicate labels would be nice, but is probably hard to achieve. As an intermediate goal, I would be content with only supporting loading data with duplicate labels as array, changing those labels (to deduplicate them -- assuming we do not do it automatically in the loading code) and writing such arrays (some output may require it). In that case, we should make it clear in the documentation it is all we support and ideally add a warning when trying to do another operation on such an array.

I consider the lack of warning/documentation about this a bug, and the actual support an enhancement, hence the double classification 😉

see also #444

yvda bumped on this problem again, hence the priority bump. Short of better support (via actual loading or automatic deduplicate), a clear error message when reading such a file from hdf would already go a long way to improve the user experience. A warning (or even an error?) when writing would also help (it does not make sense to allow writing a file we cannot read back) but we cannot block all exports with duplicates because we need them in some final/formatted output to excel.