TabViewer / gtabview

Simple graphical tabular data viewer
MIT License
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gtabview unexpectedly terminates python when there are duplicated column names #30

Closed matthewgson closed 3 years ago

matthewgson commented 5 years ago

When viewing pandas DataFrame, if there are duplicated column names in DataFrame, gtabview terminates python session.

Below is code example and result.

data = data[['a','a','b','c']] view(data)

Traceback (most recent call last): File "C:\Python\lib\site-packages\gtabview\viewer.py", line 46, in data return self._as_str(self.model.data(index.row(), index.column())) File "C:\Python\lib\site-packages\gtabview\models.py", line 230, in data return self._data.iat[y, x] File "C:\Python\lib\site-packages\pandas\core\indexing.py", line 2270, in getitem return self.obj._get_value(*key, takeable=self._takeable) File "C:\Python\lib\site-packages\pandas\core\frame.py", line 2764, in _get_value series = self._iget_item_cache(col) File "C:\Python\lib\site-packages\pandas\core\generic.py", line 3087, in _iget_item_cache lower = self._take(item, axis=self._info_axis_number) File "C:\Python\lib\site-packages\pandas\core\generic.py", line 3359, in _take verify=True) File "C:\Python\lib\site-packages\pandas\core\internals\managers.py", line 1350, in take axis=axis, allow_dups=True) File "C:\Python\lib\site-packages\pandas\core\internals\managers.py", line 1231, in reindex_indexer fill_tuple=(fill_value,)) File "C:\Python\lib\site-packages\pandas\core\internals\managers.py", line 1256, in _slice_take_blocks_ax0 slice_or_indexer, self.shape[0], allow_fill=allow_fill) File "C:\Python\lib\site-packages\pandas\core\internals\managers.py", line 2026, in _preprocess_slice_or_indexer return 'fancy', indexer, len(indexer) TypeError: len() of unsized object

C:\Users\GS\Desktop> After the error message, Python is terminated. This is unexpected behavior.

wavexx commented 5 years ago

Sadly, this is a bug in pandas. See my own report from 2015 :/

https://github.com/pandas-dev/pandas/issues/11754

axil commented 3 years ago

It looks as if the issue in pandas has been resolved recently. I guess it should be safe to close this issue now.

wavexx commented 3 years ago

Verified also on my side. Closing!