Python pandas.core.dtypes.generic.ABCSparseSeries() Examples
The following are 13
code examples of pandas.core.dtypes.generic.ABCSparseSeries().
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Example #1
| Source File: test_generic.py From recruit with Apache License 2.0 | 5 votes |
|
def test_abc_types(self):
assert isinstance(pd.Index(['a', 'b', 'c']), gt.ABCIndex)
assert isinstance(pd.Int64Index([1, 2, 3]), gt.ABCInt64Index)
assert isinstance(pd.UInt64Index([1, 2, 3]), gt.ABCUInt64Index)
assert isinstance(pd.Float64Index([1, 2, 3]), gt.ABCFloat64Index)
assert isinstance(self.multi_index, gt.ABCMultiIndex)
assert isinstance(self.datetime_index, gt.ABCDatetimeIndex)
assert isinstance(self.timedelta_index, gt.ABCTimedeltaIndex)
assert isinstance(self.period_index, gt.ABCPeriodIndex)
assert isinstance(self.categorical_df.index, gt.ABCCategoricalIndex)
assert isinstance(pd.Index(['a', 'b', 'c']), gt.ABCIndexClass)
assert isinstance(pd.Int64Index([1, 2, 3]), gt.ABCIndexClass)
assert isinstance(pd.Series([1, 2, 3]), gt.ABCSeries)
assert isinstance(self.df, gt.ABCDataFrame)
with catch_warnings(record=True):
simplefilter('ignore', FutureWarning)
assert isinstance(self.df.to_panel(), gt.ABCPanel)
assert isinstance(self.sparse_series, gt.ABCSparseSeries)
assert isinstance(self.sparse_array, gt.ABCSparseArray)
assert isinstance(self.sparse_frame, gt.ABCSparseDataFrame)
assert isinstance(self.categorical, gt.ABCCategorical)
assert isinstance(pd.Period('2012', freq='A-DEC'), gt.ABCPeriod)
assert isinstance(pd.DateOffset(), gt.ABCDateOffset)
assert isinstance(pd.Period('2012', freq='A-DEC').freq,
gt.ABCDateOffset)
assert not isinstance(pd.Period('2012', freq='A-DEC'),
gt.ABCDateOffset)
assert isinstance(pd.Interval(0, 1.5), gt.ABCInterval)
assert not isinstance(pd.Period('2012', freq='A-DEC'), gt.ABCInterval)
assert isinstance(self.datetime_array, gt.ABCDatetimeArray)
assert not isinstance(self.datetime_index, gt.ABCDatetimeArray)
assert isinstance(self.timedelta_array, gt.ABCTimedeltaArray)
assert not isinstance(self.timedelta_index, gt.ABCTimedeltaArray)
Example #2
| Source File: series.py From recruit with Apache License 2.0 | 5 votes |
|
def __init__(self, data=None, index=None, sparse_index=None, kind='block',
fill_value=None, name=None, dtype=None, copy=False,
fastpath=False):
# TODO: Most of this should be refactored and shared with Series
# 1. BlockManager -> array
# 2. Series.index, Series.name, index, name reconciliation
# 3. Implicit reindexing
# 4. Implicit broadcasting
# 5. Dict construction
if data is None:
data = []
elif isinstance(data, SingleBlockManager):
index = data.index
data = data.blocks[0].values
elif isinstance(data, (ABCSeries, ABCSparseSeries)):
index = data.index if index is None else index
dtype = data.dtype if dtype is None else dtype
name = data.name if name is None else name
if index is not None:
data = data.reindex(index)
elif isinstance(data, compat.Mapping):
data, index = Series()._init_dict(data, index=index)
elif is_scalar(data) and index is not None:
data = np.full(len(index), fill_value=data)
super(SparseSeries, self).__init__(
SparseArray(data,
sparse_index=sparse_index,
kind=kind,
dtype=dtype,
fill_value=fill_value,
copy=copy),
index=index, name=name,
copy=False, fastpath=fastpath
)
Example #3
| Source File: sparse.py From recruit with Apache License 2.0 | 5 votes |
|
def __array_wrap__(self, array, context=None):
from pandas.core.dtypes.generic import ABCSparseSeries
ufunc, inputs, _ = context
inputs = tuple(x.values if isinstance(x, ABCSparseSeries) else x
for x in inputs)
return self.__array_ufunc__(ufunc, '__call__', *inputs)
Example #4
| Source File: sparse.py From recruit with Apache License 2.0 | 5 votes |
|
def _maybe_to_sparse(array):
"""
array must be SparseSeries or SparseArray
"""
if isinstance(array, ABCSparseSeries):
array = array.values.copy()
return array
Example #5
| Source File: test_generic.py From vnpy_crypto with MIT License | 5 votes |
|
def test_abc_types(self):
assert isinstance(pd.Index(['a', 'b', 'c']), gt.ABCIndex)
assert isinstance(pd.Int64Index([1, 2, 3]), gt.ABCInt64Index)
assert isinstance(pd.UInt64Index([1, 2, 3]), gt.ABCUInt64Index)
assert isinstance(pd.Float64Index([1, 2, 3]), gt.ABCFloat64Index)
assert isinstance(self.multi_index, gt.ABCMultiIndex)
assert isinstance(self.datetime_index, gt.ABCDatetimeIndex)
assert isinstance(self.timedelta_index, gt.ABCTimedeltaIndex)
assert isinstance(self.period_index, gt.ABCPeriodIndex)
assert isinstance(self.categorical_df.index, gt.ABCCategoricalIndex)
assert isinstance(pd.Index(['a', 'b', 'c']), gt.ABCIndexClass)
assert isinstance(pd.Int64Index([1, 2, 3]), gt.ABCIndexClass)
assert isinstance(pd.Series([1, 2, 3]), gt.ABCSeries)
assert isinstance(self.df, gt.ABCDataFrame)
with catch_warnings(record=True):
assert isinstance(self.df.to_panel(), gt.ABCPanel)
assert isinstance(self.sparse_series, gt.ABCSparseSeries)
assert isinstance(self.sparse_array, gt.ABCSparseArray)
assert isinstance(self.sparse_frame, gt.ABCSparseDataFrame)
assert isinstance(self.categorical, gt.ABCCategorical)
assert isinstance(pd.Period('2012', freq='A-DEC'), gt.ABCPeriod)
assert isinstance(pd.DateOffset(), gt.ABCDateOffset)
assert isinstance(pd.Period('2012', freq='A-DEC').freq,
gt.ABCDateOffset)
assert not isinstance(pd.Period('2012', freq='A-DEC'),
gt.ABCDateOffset)
assert isinstance(pd.Interval(0, 1.5), gt.ABCInterval)
assert not isinstance(pd.Period('2012', freq='A-DEC'), gt.ABCInterval)
Example #6
| Source File: array.py From vnpy_crypto with MIT License | 5 votes |
|
def _maybe_to_sparse(array):
""" array must be SparseSeries or SparseArray """
if isinstance(array, ABCSparseSeries):
array = array.values.copy()
return array
Example #7
| Source File: test_generic.py From predictive-maintenance-using-machine-learning with Apache License 2.0 | 5 votes |
|
def test_abc_types(self):
assert isinstance(pd.Index(['a', 'b', 'c']), gt.ABCIndex)
assert isinstance(pd.Int64Index([1, 2, 3]), gt.ABCInt64Index)
assert isinstance(pd.UInt64Index([1, 2, 3]), gt.ABCUInt64Index)
assert isinstance(pd.Float64Index([1, 2, 3]), gt.ABCFloat64Index)
assert isinstance(self.multi_index, gt.ABCMultiIndex)
assert isinstance(self.datetime_index, gt.ABCDatetimeIndex)
assert isinstance(self.timedelta_index, gt.ABCTimedeltaIndex)
assert isinstance(self.period_index, gt.ABCPeriodIndex)
assert isinstance(self.categorical_df.index, gt.ABCCategoricalIndex)
assert isinstance(pd.Index(['a', 'b', 'c']), gt.ABCIndexClass)
assert isinstance(pd.Int64Index([1, 2, 3]), gt.ABCIndexClass)
assert isinstance(pd.Series([1, 2, 3]), gt.ABCSeries)
assert isinstance(self.df, gt.ABCDataFrame)
with catch_warnings(record=True):
simplefilter('ignore', FutureWarning)
assert isinstance(self.df.to_panel(), gt.ABCPanel)
assert isinstance(self.sparse_series, gt.ABCSparseSeries)
assert isinstance(self.sparse_array, gt.ABCSparseArray)
assert isinstance(self.sparse_frame, gt.ABCSparseDataFrame)
assert isinstance(self.categorical, gt.ABCCategorical)
assert isinstance(pd.Period('2012', freq='A-DEC'), gt.ABCPeriod)
assert isinstance(pd.DateOffset(), gt.ABCDateOffset)
assert isinstance(pd.Period('2012', freq='A-DEC').freq,
gt.ABCDateOffset)
assert not isinstance(pd.Period('2012', freq='A-DEC'),
gt.ABCDateOffset)
assert isinstance(pd.Interval(0, 1.5), gt.ABCInterval)
assert not isinstance(pd.Period('2012', freq='A-DEC'), gt.ABCInterval)
assert isinstance(self.datetime_array, gt.ABCDatetimeArray)
assert not isinstance(self.datetime_index, gt.ABCDatetimeArray)
assert isinstance(self.timedelta_array, gt.ABCTimedeltaArray)
assert not isinstance(self.timedelta_index, gt.ABCTimedeltaArray)
Example #8
| Source File: series.py From predictive-maintenance-using-machine-learning with Apache License 2.0 | 5 votes |
|
def __init__(self, data=None, index=None, sparse_index=None, kind='block',
fill_value=None, name=None, dtype=None, copy=False,
fastpath=False):
# TODO: Most of this should be refactored and shared with Series
# 1. BlockManager -> array
# 2. Series.index, Series.name, index, name reconciliation
# 3. Implicit reindexing
# 4. Implicit broadcasting
# 5. Dict construction
if data is None:
data = []
elif isinstance(data, SingleBlockManager):
index = data.index
data = data.blocks[0].values
elif isinstance(data, (ABCSeries, ABCSparseSeries)):
index = data.index if index is None else index
dtype = data.dtype if dtype is None else dtype
name = data.name if name is None else name
if index is not None:
data = data.reindex(index)
elif isinstance(data, compat.Mapping):
data, index = Series()._init_dict(data, index=index)
elif is_scalar(data) and index is not None:
data = np.full(len(index), fill_value=data)
super(SparseSeries, self).__init__(
SparseArray(data,
sparse_index=sparse_index,
kind=kind,
dtype=dtype,
fill_value=fill_value,
copy=copy),
index=index, name=name,
copy=False, fastpath=fastpath
)
Example #9
| Source File: sparse.py From predictive-maintenance-using-machine-learning with Apache License 2.0 | 5 votes |
|
def __array_wrap__(self, array, context=None):
from pandas.core.dtypes.generic import ABCSparseSeries
ufunc, inputs, _ = context
inputs = tuple(x.values if isinstance(x, ABCSparseSeries) else x
for x in inputs)
return self.__array_ufunc__(ufunc, '__call__', *inputs)
Example #10
| Source File: sparse.py From predictive-maintenance-using-machine-learning with Apache License 2.0 | 5 votes |
|
def _maybe_to_sparse(array):
"""
array must be SparseSeries or SparseArray
"""
if isinstance(array, ABCSparseSeries):
array = array.values.copy()
return array
Example #11
| Source File: test_generic.py From elasticintel with GNU General Public License v3.0 | 5 votes |
|
def test_abc_types(self):
assert isinstance(pd.Index(['a', 'b', 'c']), gt.ABCIndex)
assert isinstance(pd.Int64Index([1, 2, 3]), gt.ABCInt64Index)
assert isinstance(pd.UInt64Index([1, 2, 3]), gt.ABCUInt64Index)
assert isinstance(pd.Float64Index([1, 2, 3]), gt.ABCFloat64Index)
assert isinstance(self.multi_index, gt.ABCMultiIndex)
assert isinstance(self.datetime_index, gt.ABCDatetimeIndex)
assert isinstance(self.timedelta_index, gt.ABCTimedeltaIndex)
assert isinstance(self.period_index, gt.ABCPeriodIndex)
assert isinstance(self.categorical_df.index, gt.ABCCategoricalIndex)
assert isinstance(pd.Index(['a', 'b', 'c']), gt.ABCIndexClass)
assert isinstance(pd.Int64Index([1, 2, 3]), gt.ABCIndexClass)
assert isinstance(pd.Series([1, 2, 3]), gt.ABCSeries)
assert isinstance(self.df, gt.ABCDataFrame)
with catch_warnings(record=True):
assert isinstance(self.df.to_panel(), gt.ABCPanel)
assert isinstance(self.sparse_series, gt.ABCSparseSeries)
assert isinstance(self.sparse_array, gt.ABCSparseArray)
assert isinstance(self.categorical, gt.ABCCategorical)
assert isinstance(pd.Period('2012', freq='A-DEC'), gt.ABCPeriod)
assert isinstance(pd.DateOffset(), gt.ABCDateOffset)
assert isinstance(pd.Period('2012', freq='A-DEC').freq,
gt.ABCDateOffset)
assert not isinstance(pd.Period('2012', freq='A-DEC'),
gt.ABCDateOffset)
Example #12
| Source File: test_generic.py From twitter-stock-recommendation with MIT License | 5 votes |
|
def test_abc_types(self):
assert isinstance(pd.Index(['a', 'b', 'c']), gt.ABCIndex)
assert isinstance(pd.Int64Index([1, 2, 3]), gt.ABCInt64Index)
assert isinstance(pd.UInt64Index([1, 2, 3]), gt.ABCUInt64Index)
assert isinstance(pd.Float64Index([1, 2, 3]), gt.ABCFloat64Index)
assert isinstance(self.multi_index, gt.ABCMultiIndex)
assert isinstance(self.datetime_index, gt.ABCDatetimeIndex)
assert isinstance(self.timedelta_index, gt.ABCTimedeltaIndex)
assert isinstance(self.period_index, gt.ABCPeriodIndex)
assert isinstance(self.categorical_df.index, gt.ABCCategoricalIndex)
assert isinstance(pd.Index(['a', 'b', 'c']), gt.ABCIndexClass)
assert isinstance(pd.Int64Index([1, 2, 3]), gt.ABCIndexClass)
assert isinstance(pd.Series([1, 2, 3]), gt.ABCSeries)
assert isinstance(self.df, gt.ABCDataFrame)
with catch_warnings(record=True):
assert isinstance(self.df.to_panel(), gt.ABCPanel)
assert isinstance(self.sparse_series, gt.ABCSparseSeries)
assert isinstance(self.sparse_array, gt.ABCSparseArray)
assert isinstance(self.sparse_frame, gt.ABCSparseDataFrame)
assert isinstance(self.categorical, gt.ABCCategorical)
assert isinstance(pd.Period('2012', freq='A-DEC'), gt.ABCPeriod)
assert isinstance(pd.DateOffset(), gt.ABCDateOffset)
assert isinstance(pd.Period('2012', freq='A-DEC').freq,
gt.ABCDateOffset)
assert not isinstance(pd.Period('2012', freq='A-DEC'),
gt.ABCDateOffset)
assert isinstance(pd.Interval(0, 1.5), gt.ABCInterval)
assert not isinstance(pd.Period('2012', freq='A-DEC'), gt.ABCInterval)
Example #13
| Source File: array.py From vnpy_crypto with MIT License | 4 votes |
|
def __new__(cls, data, sparse_index=None, index=None, kind='integer',
fill_value=None, dtype=None, copy=False):
if index is not None:
if data is None:
data = np.nan
if not is_scalar(data):
raise Exception("must only pass scalars with an index ")
dtype = infer_dtype_from_scalar(data)[0]
data = construct_1d_arraylike_from_scalar(
data, len(index), dtype)
if isinstance(data, ABCSparseSeries):
data = data.values
is_sparse_array = isinstance(data, SparseArray)
if dtype is not None:
dtype = np.dtype(dtype)
if is_sparse_array:
sparse_index = data.sp_index
values = data.sp_values
fill_value = data.fill_value
else:
# array-like
if sparse_index is None:
if dtype is not None:
data = np.asarray(data, dtype=dtype)
res = make_sparse(data, kind=kind, fill_value=fill_value)
values, sparse_index, fill_value = res
else:
values = _sanitize_values(data)
if len(values) != sparse_index.npoints:
raise AssertionError("Non array-like type {type} must "
"have the same length as the index"
.format(type=type(values)))
# Create array, do *not* copy data by default
if copy:
subarr = np.array(values, dtype=dtype, copy=True)
else:
subarr = np.asarray(values, dtype=dtype)
# Change the class of the array to be the subclass type.
return cls._simple_new(subarr, sparse_index, fill_value)
