Python generic.ABCSparseSeries方法代码示例

# 需要导入模块: from pandas.core.dtypes import generic [as 别名]
# 或者: from pandas.core.dtypes.generic import ABCSparseSeries [as 别名]
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) 

# 需要导入模块: from pandas.core.dtypes import generic [as 别名]
# 或者: from pandas.core.dtypes.generic import ABCSparseSeries [as 别名]
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
        ) 

# 需要导入模块: from pandas.core.dtypes import generic [as 别名]
# 或者: from pandas.core.dtypes.generic import ABCSparseSeries [as 别名]
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) 

# 需要导入模块: from pandas.core.dtypes import generic [as 别名]
# 或者: from pandas.core.dtypes.generic import ABCSparseSeries [as 别名]
def _maybe_to_sparse(array):
    """
    array must be SparseSeries or SparseArray
    """
    if isinstance(array, ABCSparseSeries):
        array = array.values.copy()
    return array 

# 需要导入模块: from pandas.core.dtypes import generic [as 别名]
# 或者: from pandas.core.dtypes.generic import ABCSparseSeries [as 别名]
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) 

# 需要导入模块: from pandas.core.dtypes import generic [as 别名]
# 或者: from pandas.core.dtypes.generic import ABCSparseSeries [as 别名]
def _maybe_to_sparse(array):
    """ array must be SparseSeries or SparseArray """
    if isinstance(array, ABCSparseSeries):
        array = array.values.copy()
    return array 

# 需要导入模块: from pandas.core.dtypes import generic [as 别名]
# 或者: from pandas.core.dtypes.generic import ABCSparseSeries [as 别名]
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) 

# 需要导入模块: from pandas.core.dtypes import generic [as 别名]
# 或者: from pandas.core.dtypes.generic import ABCSparseSeries [as 别名]
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)