Python generic.ABCPeriodIndex方法代碼示例

# 需要導入模塊: from pandas.core.dtypes import generic [as 別名]
# 或者: from pandas.core.dtypes.generic import ABCPeriodIndex [as 別名]
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) 

# 需要導入模塊: from pandas.core.dtypes import generic [as 別名]
# 或者: from pandas.core.dtypes.generic import ABCPeriodIndex [as 別名]
def _format_regular_rows(self):
        has_aliases = isinstance(self.header, (tuple, list, np.ndarray, Index))
        if has_aliases or self.header:
            self.rowcounter += 1

        # output index and index_label?
        if self.index:
            # check aliases
            # if list only take first as this is not a MultiIndex
            if (self.index_label and
                    isinstance(self.index_label, (list, tuple, np.ndarray,
                                                  Index))):
                index_label = self.index_label[0]
            # if string good to go
            elif self.index_label and isinstance(self.index_label, str):
                index_label = self.index_label
            else:
                index_label = self.df.index.names[0]

            if isinstance(self.columns, ABCMultiIndex):
                self.rowcounter += 1

            if index_label and self.header is not False:
                yield ExcelCell(self.rowcounter - 1, 0, index_label,
                                self.header_style)

            # write index_values
            index_values = self.df.index
            if isinstance(self.df.index, ABCPeriodIndex):
                index_values = self.df.index.to_timestamp()

            for idx, idxval in enumerate(index_values):
                yield ExcelCell(self.rowcounter + idx, 0, idxval,
                                self.header_style)

            coloffset = 1
        else:
            coloffset = 0

        for cell in self._generate_body(coloffset):
            yield cell 

# 需要導入模塊: from pandas.core.dtypes import generic [as 別名]
# 或者: from pandas.core.dtypes.generic import ABCPeriodIndex [as 別名]
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) 

# 需要導入模塊: from pandas.core.dtypes import generic [as 別名]
# 或者: from pandas.core.dtypes.generic import ABCPeriodIndex [as 別名]
def _simple_new(cls, left, right, closed=None, name=None,
                    copy=False, verify_integrity=True):
        result = IntervalMixin.__new__(cls)

        if closed is None:
            closed = 'right'
        left = _ensure_index(left, copy=copy)
        right = _ensure_index(right, copy=copy)

        # coerce dtypes to match if needed
        if is_float_dtype(left) and is_integer_dtype(right):
            right = right.astype(left.dtype)
        if is_float_dtype(right) and is_integer_dtype(left):
            left = left.astype(right.dtype)

        if type(left) != type(right):
            raise ValueError("must not have differing left [{}] "
                             "and right [{}] types".format(
                                 type(left), type(right)))

        if isinstance(left, ABCPeriodIndex):
            raise ValueError("Period dtypes are not supported, "
                             "use a PeriodIndex instead")

        result._left = left
        result._right = right
        result._closed = closed
        result.name = name
        if verify_integrity:
            result._validate()
        result._reset_identity()
        return result 

# 需要導入模塊: from pandas.core.dtypes import generic [as 別名]
# 或者: from pandas.core.dtypes.generic import ABCPeriodIndex [as 別名]
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) 

# 需要導入模塊: from pandas.core.dtypes import generic [as 別名]
# 或者: from pandas.core.dtypes.generic import ABCPeriodIndex [as 別名]
def _simple_new(cls, left, right, closed=None, name=None, copy=False,
                    dtype=None, verify_integrity=True):
        result = IntervalMixin.__new__(cls)

        closed = closed or 'right'
        left = _ensure_index(left, copy=copy)
        right = _ensure_index(right, copy=copy)

        if dtype is not None:
            # GH 19262: dtype must be an IntervalDtype to override inferred
            dtype = pandas_dtype(dtype)
            if not is_interval_dtype(dtype):
                msg = 'dtype must be an IntervalDtype, got {dtype}'
                raise TypeError(msg.format(dtype=dtype))
            elif dtype.subtype is not None:
                left = left.astype(dtype.subtype)
                right = right.astype(dtype.subtype)

        # coerce dtypes to match if needed
        if is_float_dtype(left) and is_integer_dtype(right):
            right = right.astype(left.dtype)
        elif is_float_dtype(right) and is_integer_dtype(left):
            left = left.astype(right.dtype)

        if type(left) != type(right):
            msg = ('must not have differing left [{ltype}] and right '
                   '[{rtype}] types')
            raise ValueError(msg.format(ltype=type(left).__name__,
                                        rtype=type(right).__name__))
        elif is_categorical_dtype(left.dtype) or is_string_dtype(left.dtype):
            # GH 19016
            msg = ('category, object, and string subtypes are not supported '
                   'for IntervalIndex')
            raise TypeError(msg)
        elif isinstance(left, ABCPeriodIndex):
            msg = 'Period dtypes are not supported, use a PeriodIndex instead'
            raise ValueError(msg)
        elif (isinstance(left, ABCDatetimeIndex) and
                str(left.tz) != str(right.tz)):
            msg = ("left and right must have the same time zone, got "
                   "'{left_tz}' and '{right_tz}'")
            raise ValueError(msg.format(left_tz=left.tz, right_tz=right.tz))

        result._left = left
        result._right = right
        result._closed = closed
        result.name = name
        if verify_integrity:
            result._validate()
        result._reset_identity()
        return result