def get_indexer(source, target, fill_method):
if fill_method:
fill_method = fill_method.upper()
indexer, mask = tseries.getFillVec(source, target, source.indexMap, target.indexMap, fill_method)
return indexer, mask
def get_indexer(source, target, fill_method):
if fill_method:
fill_method = fill_method.upper()
indexer, mask = tseries.getFillVec(source, target, source.indexMap,
target.indexMap, fill_method)
return indexer, mask
def reindex(self, new_index, method=None, fillMethod=None):
"""Conform Series to new Index
Parameters
----------
new_index : array-like
Preferably an Index object (to avoid duplicating data)
method : {'backfill', 'pad', None}
Method to use for filling holes in reindexed Series
pad : propagate last valid observation forward to next valid
backfill : use NEXT valid observation to fill gap
Returns
-------
reindexed : Series
"""
if fillMethod is not None: # pragma: no cover
warnings.warn("'fillMethod' is deprecated. Use 'method' instead",
FutureWarning)
method = fillMethod
if self.index.equals(new_index):
return self.copy()
if not isinstance(new_index, Index):
new_index = Index(new_index)
if len(self.index) == 0:
return Series(NaN, index=new_index)
if method is not None:
method = method.upper()
# Cython for blazing speed
fillVec, mask = tseries.getFillVec(self.index,
new_index,
self.index.indexMap,
new_index.indexMap,
kind=method)
newValues = self.values.take(fillVec)
notmask = -mask
if notmask.any():
if issubclass(newValues.dtype.type, np.int_):
newValues = newValues.astype(float)
elif issubclass(newValues.dtype.type, np.bool_):
newValues = newValues.astype(object)
np.putmask(newValues, notmask, NaN)
return Series(newValues, index=new_index)
def reindex(self, new_index, method=None, fillMethod=None):
"""Conform Series to new Index
Parameters
----------
new_index : array-like
Preferably an Index object (to avoid duplicating data)
method : {'backfill', 'pad', None}
Method to use for filling holes in reindexed Series
pad : propagate last valid observation forward to next valid
backfill : use NEXT valid observation to fill gap
Returns
-------
reindexed : Series
"""
if fillMethod is not None: # pragma: no cover
warnings.warn("'fillMethod' is deprecated. Use 'method' instead",
FutureWarning)
method = fillMethod
if self.index.equals(new_index):
return self.copy()
if not isinstance(new_index, Index):
new_index = Index(new_index)
if len(self.index) == 0:
return Series(NaN, index=new_index)
if method is not None:
method = method.upper()
# Cython for blazing speed
fillVec, mask = tseries.getFillVec(self.index, new_index,
self.index.indexMap,
new_index.indexMap,
kind=method)
newValues = self.values.take(fillVec)
notmask = -mask
if notmask.any():
if issubclass(newValues.dtype.type, np.int_):
newValues = newValues.astype(float)
elif issubclass(newValues.dtype.type, np.bool_):
newValues = newValues.astype(object)
np.putmask(newValues, notmask, NaN)
return Series(newValues, index=new_index)
def test_pad(self):
old = Index([1, 5, 10])
new = Index(range(12))
filler, mask = tseries.getFillVec(old, new, old.indexMap, new.indexMap, "PAD")
expect_filler = [-1, 0, 0, 0, 0, 1, 1, 1, 1, 1, 2, 2]
expect_mask = np.ones(12, dtype=bool)
expect_mask[0] = False
self.assert_(np.array_equal(filler, expect_filler))
self.assert_(np.array_equal(mask, expect_mask))
# corner case
old = Index([5, 10])
new = Index(range(5))
filler, mask = tseries.getFillVec(old, new, old.indexMap, new.indexMap, "PAD")
expect_filler = [-1, -1, -1, -1, -1]
expect_mask = np.zeros(5, dtype=bool)
self.assert_(np.array_equal(filler, expect_filler))
self.assert_(np.array_equal(mask, expect_mask))
def test_getMergeVec(self):
old = Index([1, 5, 10])
new = Index(range(12))
filler, mask = tseries.getFillVec(old, new, old.indexMap, new.indexMap, None)
expect_filler = [-1, 0, -1, -1, -1, 1, -1, -1, -1, -1, 2, -1]
expect_mask = np.zeros(12, dtype=bool)
expect_mask[[1, 5, 10]] = True
self.assert_(np.array_equal(filler, expect_filler))
self.assert_(np.array_equal(mask, expect_mask))
# corner case
old = Index([1, 4])
new = Index(range(5, 10))
filler, mask = tseries.getFillVec(old, new, old.indexMap, new.indexMap, None)
expect_filler = [-1, -1, -1, -1, -1]
expect_mask = np.zeros(5, dtype=bool)
self.assert_(np.array_equal(filler, expect_filler))
self.assert_(np.array_equal(mask, expect_mask))
def reindex(self, newIndex, fillMethod=None):
"""Overloaded version of reindex for TimeSeries. Supports filling
with values based on new index.
See analogous method for DataFrame, will be faster for multiple
TimeSeries
Parameters
----------
newIndex : array-like, preferably an Index object (to avoid
duplicating data)
fillMethod : {'backfill', 'pad', 'interpolate', None}
Method to use for filling holes in reindexed Series
Returns
-------
TimeSeries
"""
if self.index.equals(newIndex):
return self.copy()
if not isinstance(newIndex, Index):
newIndex = Index(newIndex)
if len(self.index) == 0:
return Series.fromValue(NaN, index=newIndex)
if fillMethod is not None:
fillMethod = fillMethod.upper()
# Cython for blazing speed
fillVec, mask = tseries.getFillVec(self.index,
newIndex,
self.index.indexMap,
newIndex.indexMap,
kind=fillMethod)
newValues = self.values.take(fillVec)
notmask = -mask
if notmask.any():
if issubclass(newValues.dtype.type, np.int_):
newValues = newValues.astype(float)
elif issubclass(newValues.dtype.type, np.bool_):
newValues = newValues.astype(object)
np.putmask(newValues, notmask, NaN)
return Series(newValues, index=newIndex)
def test_pad(self):
old = Index([1, 5, 10])
new = Index(range(12))
filler, mask = tseries.getFillVec(old, new, old.indexMap, new.indexMap,
'PAD')
expect_filler = [-1, 0, 0, 0, 0, 1, 1, 1, 1, 1, 2, 2]
expect_mask = np.ones(12, dtype=bool)
expect_mask[0] = False
self.assert_(np.array_equal(filler, expect_filler))
self.assert_(np.array_equal(mask, expect_mask))
# corner case
old = Index([5, 10])
new = Index(range(5))
filler, mask = tseries.getFillVec(old, new, old.indexMap, new.indexMap,
'PAD')
expect_filler = [-1, -1, -1, -1, -1]
expect_mask = np.zeros(5, dtype=bool)
self.assert_(np.array_equal(filler, expect_filler))
self.assert_(np.array_equal(mask, expect_mask))
def test_getMergeVec(self):
old = Index([1, 5, 10])
new = Index(range(12))
filler, mask = tseries.getFillVec(old, new, old.indexMap, new.indexMap,
None)
expect_filler = [-1, 0, -1, -1, -1, 1, -1, -1, -1, -1, 2, -1]
expect_mask = np.zeros(12, dtype=bool)
expect_mask[[1, 5, 10]] = True
self.assert_(np.array_equal(filler, expect_filler))
self.assert_(np.array_equal(mask, expect_mask))
# corner case
old = Index([1, 4])
new = Index(range(5, 10))
filler, mask = tseries.getFillVec(old, new, old.indexMap, new.indexMap,
None)
expect_filler = [-1, -1, -1, -1, -1]
expect_mask = np.zeros(5, dtype=bool)
self.assert_(np.array_equal(filler, expect_filler))
self.assert_(np.array_equal(mask, expect_mask))
def reindex(self, newIndex, fillMethod=None):
"""Overloaded version of reindex for TimeSeries. Supports filling
with values based on new index.
See analogous method for DataFrame, will be faster for multiple
TimeSeries
Parameters
----------
newIndex : array-like, preferably an Index object (to avoid
duplicating data)
fillMethod : {'backfill', 'pad', 'interpolate', None}
Method to use for filling holes in reindexed Series
Returns
-------
TimeSeries
"""
if self.index.equals(newIndex):
return self.copy()
if not isinstance(newIndex, Index):
newIndex = Index(newIndex)
if len(self.index) == 0:
return Series.fromValue(NaN, index=newIndex)
if fillMethod is not None:
fillMethod = fillMethod.upper()
# Cython for blazing speed
fillVec, mask = tseries.getFillVec(self.index, newIndex,
self.index.indexMap,
newIndex.indexMap,
kind=fillMethod)
newValues = self.values.take(fillVec)
notmask = -mask
if notmask.any():
if issubclass(newValues.dtype.type, np.int_):
newValues = newValues.astype(float)
elif issubclass(newValues.dtype.type, np.bool_):
newValues = newValues.astype(object)
np.putmask(newValues, notmask, NaN)
return Series(newValues, index=newIndex)
