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PERF: Fixed regression in Series(index=idx) constructor #20865

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Merged
merged 4 commits into from
Apr 30, 2018
Merged

PERF: Fixed regression in Series(index=idx) constructor #20865

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f31cb6b
PERF: Fixed regression in Series(index=idx) constructor
TomAugspurger Apr 29, 2018
cf8c047
Handle dtype correctly
TomAugspurger Apr 29, 2018
0988df1
Moved to init_dict
TomAugspurger Apr 30, 2018
d8b1312
More special cases
TomAugspurger Apr 30, 2018
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18 changes: 16 additions & 2 deletions pandas/core/series.py
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Original file line number Diff line number Diff line change
Expand Up @@ -41,7 +41,11 @@
maybe_cast_to_datetime, maybe_castable,
construct_1d_arraylike_from_scalar,
construct_1d_object_array_from_listlike)
from pandas.core.dtypes.missing import isna, notna, remove_na_arraylike
from pandas.core.dtypes.missing import (
isna,
notna,
remove_na_arraylike,
na_value_for_dtype)

from pandas.core.index import (Index, MultiIndex, InvalidIndexError,
Float64Index, _ensure_index)
Expand Down Expand Up @@ -207,10 +211,20 @@ def __init__(self, data=None, index=None, dtype=None, name=None,
else:
data = data.reindex(index, copy=copy)
data = data._data
elif isinstance(data, dict):
elif isinstance(data, dict) and (len(data) or index is None):
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rather than doing this here, why not inside _init_dict itself? (you can simply return early if these conditions ar met). you can also return the type, copy parameter as well. ideally like to locate all of a single 'type' code in the same place (dict here)

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I agree - in particular, _init_dict already checks whether data is empty

# Include the len(data) check here, since _init_dict contains
# a relatively expensive reindex. When called with
# Series(data=None, index=idx`, that is unnescessary. We know
# we're all NaN anyway, so we handle this in the next block.
# https://github.com/pandas-dev/pandas/pull/18496/
data, index = self._init_dict(data, index, dtype)
dtype = None
copy = False
elif isinstance(data, dict):
# Same as previous block, but special cased for data=None,
# for performance when creating empty arrays.
data = na_value_for_dtype(dtype)

elif isinstance(data, SingleBlockManager):
if index is None:
index = data.index
Expand Down
11 changes: 11 additions & 0 deletions pandas/tests/series/test_constructors.py
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Expand Up @@ -122,6 +122,17 @@ def test_constructor_nan(self, input_arg):

assert_series_equal(empty, empty2, check_index_type=False)

@pytest.mark.parametrize('dtype', [
'f8', 'i8', 'M8[ns]', 'm8[ns]', 'category', 'object',
'datetime64[ns, UTC]',
])
@pytest.mark.parametrize('index', [None, pd.Index([])])
def test_constructor_dtype_only(self, dtype, index):
# GH-20865
result = pd.Series(dtype=dtype, index=index)
assert result.dtype == dtype
assert len(result) == 0

def test_constructor_series(self):
index1 = ['d', 'b', 'a', 'c']
index2 = sorted(index1)
Expand Down