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Fixes grouping by nan values after update pandas to 1.3.0 #21

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Merged
merged 1 commit into from
Jul 10, 2021
Merged

Fixes grouping by nan values after update pandas to 1.3.0 #21

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3 changes: 2 additions & 1 deletion _unittests/ut_df/test_pandas_groupbynan.py
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Original file line number Diff line number Diff line change
Expand Up @@ -35,7 +35,8 @@ def test_pandas_groupbynan(self):
self.assertTrue(numpy.isnan(li[-1]))
except AssertionError as e:
raise AssertionError(
"Issue with value {0}\n--df--\n{1}\n--co--\n{2}".format(li, df, co)) from e
"Issue with value {}\n--df--\n{}\n--gr--\n{}\n--co--\n{}".format(
li, df, gr.count(), co)) from e

for ty in types:
data = [{"this": "cst", "type": "tt1=" + str(ty[0]), "value": ty[1]},
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27 changes: 20 additions & 7 deletions pandas_streaming/df/dataframe_helpers.py
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Original file line number Diff line number Diff line change
Expand Up @@ -419,14 +419,27 @@ def pandas_groupby_nan(df, by, axis=0, as_index=False, suffix=None, nanback=True
res.grouper.groupings[0]._group_index = Index(new_val)
res.grouper.groupings[0].obj[b].replace(
fnan, numpy.nan, inplace=True)
if isinstance(res.grouper.groupings[0].grouper, numpy.ndarray):
arr = numpy.array(new_val)
res.grouper.groupings[0].grouper = arr
if hasattr(res.grouper.groupings[0], '_cache') and 'result_index' in res.grouper.groupings[0]._cache:
del res.grouper.groupings[0]._cache['result_index']
if hasattr(res.grouper, 'grouping'):
if isinstance(res.grouper.groupings[0].grouper, numpy.ndarray):
arr = numpy.array(new_val)
res.grouper.groupings[0].grouper = arr
if (hasattr(res.grouper.groupings[0], '_cache') and
'result_index' in res.grouper.groupings[0]._cache):
del res.grouper.groupings[0]._cache['result_index']
else:
raise NotImplementedError("Not implemented for type: {0}".format(
type(res.grouper.groupings[0].grouper)))
else:
raise NotImplementedError("Not implemented for type: {0}".format(
type(res.grouper.groupings[0].grouper)))
grouper = res.grouper._get_grouper()
if isinstance(grouper, numpy.ndarray):
arr = numpy.array(new_val)
res.grouper.groupings[0].grouping_vector = arr
if (hasattr(res.grouper.groupings[0], '_cache') and
'result_index' in res.grouper.groupings[0]._cache):
res.grouper.groupings[0]._cache = {}
else:
raise NotImplementedError("Not implemented for type: {0}".format(
type(res.grouper.groupings[0].grouper)))
res.grouper._cache['result_index'] = res.grouper.groupings[0]._group_index
else:
if not nanback:
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