Python NDFrame.__init__方法代码示例

# 需要导入模块: from pandas.core.generic import NDFrame [as 别名]
# 或者: from pandas.core.generic.NDFrame import __init__ [as 别名]
    def _init_data(self, data, copy, dtype, **kwargs):
        """
        Generate ND initialization; axes are passed
        as required objects to __init__
        """
        if data is None:
            data = {}
        if dtype is not None:
            dtype = self._validate_dtype(dtype)

        passed_axes = [kwargs.get(a) for a in self._AXIS_ORDERS]
        axes = None
        if isinstance(data, BlockManager):
            if any(x is not None for x in passed_axes):
                axes = [x if x is not None else y
                        for x, y in zip(passed_axes, data.axes)]
            mgr = data
        elif isinstance(data, dict):
            mgr = self._init_dict(data, passed_axes, dtype=dtype)
            copy = False
            dtype = None
        elif isinstance(data, (np.ndarray, list)):
            mgr = self._init_matrix(data, passed_axes, dtype=dtype, copy=copy)
            copy = False
            dtype = None
        else:  # pragma: no cover
            raise PandasError('Panel constructor not properly called!')

        NDFrame.__init__(self, mgr, axes=axes, copy=copy, dtype=dtype)

# 需要导入模块: from pandas.core.generic import NDFrame [as 别名]
# 或者: from pandas.core.generic.NDFrame import __init__ [as 别名]
    def __init__(self, data=None, items=None, major_axis=None, minor_axis=None,
                 copy=False, dtype=None):
        """
        Represents wide format panel data, stored as 3-dimensional array

        Parameters
        ----------
        data : ndarray (items x major x minor), or dict of DataFrames
        items : Index or array-like
            axis=1
        major_axis : Index or array-like
            axis=1
        minor_axis : Index or array-like
            axis=2
        dtype : dtype, default None
            Data type to force, otherwise infer
        copy : boolean, default False
            Copy data from inputs. Only affects DataFrame / 2d ndarray input
        """
        if data is None:
            data = {}

        passed_axes = [items, major_axis, minor_axis]
        axes = None
        if isinstance(data, BlockManager):
            if any(x is not None for x in passed_axes):
                axes = [x if x is not None else y
                        for x, y in zip(passed_axes, data.axes)]
            mgr = data
        elif isinstance(data, dict):
            mgr = self._init_dict(data, passed_axes, dtype=dtype)
            copy = False
            dtype = None
        elif isinstance(data, (np.ndarray, list)):
            mgr = self._init_matrix(data, passed_axes, dtype=dtype, copy=copy)
            copy = False
            dtype = None
        else: # pragma: no cover
            raise PandasError('Panel constructor not properly called!')

        NDFrame.__init__(self, mgr, axes=axes, copy=copy, dtype=dtype)

# 需要导入模块: from pandas.core.generic import NDFrame [as 别名]
# 或者: from pandas.core.generic.NDFrame import __init__ [as 别名]
    def __init__(self, data=None, index=None, columns=None,
                 default_kind=None, default_fill_value=None,
                 dtype=None, copy=False):

        # pick up the defaults from the Sparse structures
        if isinstance(data, SparseDataFrame):
            if index is None:
                index = data.index
            if columns is None:
                columns = data.columns
            if default_fill_value is None:
                default_fill_value = data.default_fill_value
            if default_kind is None:
                default_kind = data.default_kind
        elif isinstance(data, (SparseSeries, SparseArray)):
            if index is None:
                index = data.index
            if default_fill_value is None:
                default_fill_value = data.fill_value
            if columns is None and hasattr(data, 'name'):
                columns = [data.name]
            if columns is None:
                raise Exception("cannot pass a series w/o a name or columns")
            data = {columns[0]: data}

        if default_fill_value is None:
            default_fill_value = np.nan
        if default_kind is None:
            default_kind = 'block'

        self._default_kind = default_kind
        self._default_fill_value = default_fill_value

        if isinstance(data, dict):
            mgr = self._init_dict(data, index, columns)
            if dtype is not None:
                mgr = mgr.astype(dtype)
        elif isinstance(data, (np.ndarray, list)):
            mgr = self._init_matrix(data, index, columns)
            if dtype is not None:
                mgr = mgr.astype(dtype)
        elif isinstance(data, SparseDataFrame):
            mgr = self._init_mgr(
                data._data, dict(index=index, columns=columns), dtype=dtype, copy=copy)
        elif isinstance(data, DataFrame):
            mgr = self._init_dict(data, data.index, data.columns)
            if dtype is not None:
                mgr = mgr.astype(dtype)
        elif isinstance(data, BlockManager):
            mgr = self._init_mgr(
                data, axes=dict(index=index, columns=columns), dtype=dtype, copy=copy)
        elif data is None:
            data = {}

            if index is None:
                index = Index([])
            else:
                index = _ensure_index(index)

            if columns is None:
                columns = Index([])
            else:
                for c in columns:
                    data[c] = SparseArray(np.nan,
                                          index=index,
                                          kind=self._default_kind,
                                          fill_value=self._default_fill_value)
            mgr = dict_to_manager(data, columns, index)
            if dtype is not None:
                mgr = mgr.astype(dtype)

        NDFrame.__init__(self, mgr)