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REF: remove unnecessary exception in groupby #29538

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Nov 11, 2019
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REF: remove unnecessary exception in groupby #29538

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93 changes: 42 additions & 51 deletions pandas/core/groupby/generic.py
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Original file line number Diff line number Diff line change
Expand Up @@ -1227,61 +1227,52 @@ def first_not_none(values):
# GH 8467
return self._concat_objects(keys, values, not_indexed_same=True)

try:
if self.axis == 0 and isinstance(v, ABCSeries):
# GH6124 if the list of Series have a consistent name,
# then propagate that name to the result.
index = v.index.copy()
if index.name is None:
# Only propagate the series name to the result
# if all series have a consistent name. If the
# series do not have a consistent name, do
# nothing.
names = {v.name for v in values}
if len(names) == 1:
index.name = list(names)[0]

# normally use vstack as its faster than concat
# and if we have mi-columns
if (
isinstance(v.index, MultiIndex)
or key_index is None
or isinstance(key_index, MultiIndex)
):
stacked_values = np.vstack([np.asarray(v) for v in values])
result = DataFrame(
stacked_values, index=key_index, columns=index
)
else:
# GH5788 instead of stacking; concat gets the
# dtypes correct
from pandas.core.reshape.concat import concat

result = concat(
values,
keys=key_index,
names=key_index.names,
axis=self.axis,
).unstack()
result.columns = index
elif isinstance(v, ABCSeries):
if self.axis == 0 and isinstance(v, ABCSeries):
# GH6124 if the list of Series have a consistent name,
# then propagate that name to the result.
index = v.index.copy()
if index.name is None:
# Only propagate the series name to the result
# if all series have a consistent name. If the
# series do not have a consistent name, do
# nothing.
names = {v.name for v in values}
if len(names) == 1:
index.name = list(names)[0]

# normally use vstack as its faster than concat
# and if we have mi-columns
if (
isinstance(v.index, MultiIndex)
or key_index is None
or isinstance(key_index, MultiIndex)
):
stacked_values = np.vstack([np.asarray(v) for v in values])
result = DataFrame(
stacked_values.T, index=v.index, columns=key_index
stacked_values, index=key_index, columns=index
)
else:
# GH#1738: values is list of arrays of unequal lengths
# fall through to the outer else clause
# TODO: sure this is right? we used to do this
# after raising AttributeError above
return Series(
values, index=key_index, name=self._selection_name
)

except ValueError:
# TODO: not reached in tests; is this still needed?
# GH1738: values is list of arrays of unequal lengths fall
# through to the outer else clause
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Are there tests illustrating that that is unnecessary?

# GH5788 instead of stacking; concat gets the
# dtypes correct
from pandas.core.reshape.concat import concat

result = concat(
values,
keys=key_index,
names=key_index.names,
axis=self.axis,
).unstack()
result.columns = index
elif isinstance(v, ABCSeries):
stacked_values = np.vstack([np.asarray(v) for v in values])
result = DataFrame(
stacked_values.T, index=v.index, columns=key_index
)
else:
# GH#1738: values is list of arrays of unequal lengths
# fall through to the outer else clause
# TODO: sure this is right? we used to do this
# after raising AttributeError above
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Is there a way to test for that?

return Series(values, index=key_index, name=self._selection_name)

# if we have date/time like in the original, then coerce dates
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