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BUG: AttributeError raised by map inside groupby reduction #29160

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BUG: AttributeError raised by map inside groupby reduction #29160

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BUG: AttributeError raised by map inside groupby reduction
jbrockmendel Oct 22, 2019
f18144d
Merge branch 'master' of https://github.com/pandas-dev/pandas into in…
jbrockmendel Oct 23, 2019
4180d3b
Merge branch 'master' of https://github.com/pandas-dev/pandas into in…
jbrockmendel Oct 23, 2019
69426cc
Merge branch 'master' of https://github.com/pandas-dev/pandas into in…
jbrockmendel Oct 23, 2019
e652b0d
Merge branch 'master' of https://github.com/pandas-dev/pandas into in…
jbrockmendel Oct 24, 2019
4582436
CLN: revert catch
jbrockmendel Oct 24, 2019
5a0ab54
Merge branch 'master' of https://github.com/pandas-dev/pandas into in…
jbrockmendel Oct 24, 2019
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2 changes: 1 addition & 1 deletion pandas/core/groupby/generic.py
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Expand Up @@ -262,7 +262,7 @@ def aggregate(self, func=None, *args, **kwargs):

try:
return self._python_agg_general(func, *args, **kwargs)
except (AssertionError, TypeError):
except (AssertionError, TypeError, AttributeError):
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you need to remove AttributeError from the clause below

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can you indicate where the errors come from here as much as possible

raise
except Exception:
result = self._aggregate_named(func, *args, **kwargs)
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4 changes: 3 additions & 1 deletion pandas/core/indexes/datetimelike.py
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Expand Up @@ -731,7 +731,9 @@ def astype(self, dtype, copy=True):
# Ensure that self.astype(self.dtype) is self
return self

new_values = self._data.astype(dtype, copy=copy)
# use _eadata since _data links to _index_data which can be
# overwritten in groupby-reduction
new_values = self._eadata.astype(dtype, copy=copy)
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Can you explain why this is needed in astype, while the comment is about groupby?

And it's not possible to prevent that _data gets written in the first place? (or is it done in a try/except that only fails later .. ). Adding yet another data like attribute doesn't seem ideal ..

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And it's not possible to prevent that _data gets written in the first place?

Take a look at how we patch _index_data in libreduction. I spent some time trying to find a way around that and didn't find any.

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Could we make the _index_data in a settable property that on setting also updates the underlying data of the EA? (to keep both synced)

(didn't look in detail, so this might be nonsense)

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_index_data is set using object.__setattr__, so I don't think that would work.

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_index_data is set using object.setattr, so I don't think that would work.

Based on a quick test, it seems that setattr still goes through a property's setter (now, if the actual idea can help, I would need to take a further look)

Do you have an example test that hits this (a failing test if you don't do the above change) ?

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Do you have an example test that hits this (a failing test if you don't do the above change) ?

If you make the groupby change to stop catching AttributeError but don't change the index code, there is a test (dont know which off the top of my head) that raises an AttributeError in DatetimeIndex.map because index._data is an ndarray instead of a DTA.


# pass copy=False because any copying will be done in the
# _data.astype call above
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2 changes: 2 additions & 0 deletions pandas/core/indexes/datetimes.py
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Expand Up @@ -368,6 +368,8 @@ def _simple_new(cls, values, name=None, freq=None, tz=None, dtype=None):
result.name = name
# For groupby perf. See note in indexes/base about _index_data
result._index_data = dtarr._data
result._eadata = dtarr

result._reset_identity()
return result

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2 changes: 2 additions & 0 deletions pandas/core/indexes/period.py
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Expand Up @@ -298,6 +298,8 @@ def _simple_new(cls, values, name=None, freq=None, **kwargs):
result._data = values
# For groupby perf. See note in indexes/base about _index_data
result._index_data = values._data
result._eadata = values

result.name = name
result._reset_identity()
return result
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1 change: 1 addition & 0 deletions pandas/core/indexes/timedeltas.py
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Expand Up @@ -273,6 +273,7 @@ def _simple_new(cls, values, name=None, freq=None, dtype=_TD_DTYPE):
result.name = name
# For groupby perf. See note in indexes/base about _index_data
result._index_data = tdarr._data
result._eadata = tdarr

result._reset_identity()
return result
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