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CLN: Remove redundant initialization from Int64Index and Float64Index constructor #5117

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Merged
merged 1 commit into from
Oct 5, 2013
+6 −33
Merged

CLN: Remove redundant initialization from Int64Index and Float64Index constructor #5117

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39 changes: 6 additions & 33 deletions pandas/core/index.py
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Original file line number Diff line number Diff line change
Expand Up @@ -201,6 +201,8 @@ def _string_data_error(cls, data):

@classmethod
def _coerce_to_ndarray(cls, data):
"""coerces data to ndarray, raises on scalar data. Converts other
iterables to list first and then to array. Does not touch ndarrays."""

if not isinstance(data, np.ndarray):
if np.isscalar(data):
Expand Down Expand Up @@ -1624,7 +1626,7 @@ class Int64Index(Index):
Parameters
----------
data : array-like (1-dimensional)
dtype : NumPy dtype (default: object)
dtype : NumPy dtype (default: int64)
copy : bool
Make a copy of input ndarray
name : object
Expand All @@ -1651,33 +1653,8 @@ def __new__(cls, data, dtype=None, copy=False, name=None, fastpath=False):
subarr.name = name
return subarr

if not isinstance(data, np.ndarray):
if np.isscalar(data):
cls._scalar_data_error(data)

data = cls._coerce_to_ndarray(data)

if issubclass(data.dtype.type, compat.string_types):
cls._string_data_error(data)

elif issubclass(data.dtype.type, np.integer):
# don't force the upcast as we may be dealing
# with a platform int
if dtype is None or not issubclass(np.dtype(dtype).type, np.integer):
dtype = np.int64

subarr = np.array(data, dtype=dtype, copy=copy)
else:
subarr = np.array(data, dtype=np.int64, copy=copy)
if len(data) > 0:
if (subarr != data).any():
raise TypeError('Unsafe NumPy casting, you must '
'explicitly cast')

# other iterable of some kind
if not isinstance(data, (list, tuple)):
data = list(data)
data = np.asarray(data)
# isscalar, generators handled in coerce_to_ndarray
data = cls._coerce_to_ndarray(data)

if issubclass(data.dtype.type, compat.string_types):
cls._string_data_error(data)
Expand Down Expand Up @@ -1767,11 +1744,7 @@ def __new__(cls, data, dtype=None, copy=False, name=None, fastpath=False):
subarr.name = name
return subarr

if not isinstance(data, np.ndarray):
if np.isscalar(data):
cls._scalar_data_error(data)

data = cls._coerce_to_ndarray(data)
data = cls._coerce_to_ndarray(data)

if issubclass(data.dtype.type, compat.string_types):
cls._string_data_error(data)
Expand Down