Python frequencies.get_period_alias方法代码示例

# 需要导入模块: from pandas.tseries import frequencies [as 别名]
# 或者: from pandas.tseries.frequencies import get_period_alias [as 别名]
def _get_freq(ax, series):
    # get frequency from data
    freq = getattr(series.index, 'freq', None)
    if freq is None:
        freq = getattr(series.index, 'inferred_freq', None)

    ax_freq = _get_ax_freq(ax)

    # use axes freq if no data freq
    if freq is None:
        freq = ax_freq

    # get the period frequency
    if isinstance(freq, DateOffset):
        freq = freq.rule_code
    else:
        freq = get_base_alias(freq)

    freq = frequencies.get_period_alias(freq)
    return freq, ax_freq 

# 需要导入模块: from pandas.tseries import frequencies [as 别名]
# 或者: from pandas.tseries.frequencies import get_period_alias [as 别名]
def _get_freq(ax, series):
    # get frequency from data
    freq = getattr(series.index, 'freq', None)
    if freq is None:
        freq = getattr(series.index, 'inferred_freq', None)

    ax_freq = _get_ax_freq(ax)

    # use axes freq if no data freq
    if freq is None:
        freq = ax_freq

    # get the period frequency
    if isinstance(freq, DateOffset):
        freq = freq.rule_code
    else:
        freq = frequencies.get_base_alias(freq)

    freq = frequencies.get_period_alias(freq)
    return freq, ax_freq 

# 需要导入模块: from pandas.tseries import frequencies [as 别名]
# 或者: from pandas.tseries.frequencies import get_period_alias [as 别名]
def _get_freq(ax, series):
    # get frequency from data
    freq = getattr(series.index, 'freq', None)
    if freq is None:
        freq = getattr(series.index, 'inferred_freq', None)

    ax_freq = getattr(ax, 'freq', None)

    # use axes freq if no data freq
    if freq is None:
        freq = ax_freq

    # get the period frequency
    if isinstance(freq, DateOffset):
        freq = freq.rule_code
    else:
        freq = frequencies.get_base_alias(freq)

    freq = frequencies.get_period_alias(freq)

    return freq 

# 需要导入模块: from pandas.tseries import frequencies [as 别名]
# 或者: from pandas.tseries.frequencies import get_period_alias [as 别名]
def _use_dynamic_x(ax, data):
    freq = _get_index_freq(data)
    ax_freq = _get_ax_freq(ax)

    if freq is None:  # convert irregular if axes has freq info
        freq = ax_freq
    else:  # do not use tsplot if irregular was plotted first
        if (ax_freq is None) and (len(ax.get_lines()) > 0):
            return False

    if freq is None:
        return False

    if isinstance(freq, DateOffset):
        freq = freq.rule_code
    else:
        freq = get_base_alias(freq)
    freq = frequencies.get_period_alias(freq)

    if freq is None:
        return False

    # hack this for 0.10.1, creating more technical debt...sigh
    if isinstance(data.index, ABCDatetimeIndex):
        base = get_freq(freq)
        x = data.index
        if (base <= FreqGroup.FR_DAY):
            return x[:1].is_normalized
        return Period(x[0], freq).to_timestamp(tz=x.tz) == x[0]
    return True 

# 需要导入模块: from pandas.tseries import frequencies [as 别名]
# 或者: from pandas.tseries.frequencies import get_period_alias [as 别名]
def _maybe_convert_index(ax, data):
    # tsplot converts automatically, but don't want to convert index
    # over and over for DataFrames
    if isinstance(data.index, ABCDatetimeIndex):
        freq = getattr(data.index, 'freq', None)

        if freq is None:
            freq = getattr(data.index, 'inferred_freq', None)
        if isinstance(freq, DateOffset):
            freq = freq.rule_code

        if freq is None:
            freq = _get_ax_freq(ax)

        if freq is None:
            raise ValueError('Could not get frequency alias for plotting')

        freq = get_base_alias(freq)
        freq = frequencies.get_period_alias(freq)

        data = data.to_period(freq=freq)
    return data


# Patch methods for subplot. Only format_dateaxis is currently used.
# Do we need the rest for convenience? 

# 需要导入模块: from pandas.tseries import frequencies [as 别名]
# 或者: from pandas.tseries.frequencies import get_period_alias [as 别名]
def _use_dynamic_x(ax, data):
    freq = _get_index_freq(data)
    ax_freq = _get_ax_freq(ax)

    if freq is None:  # convert irregular if axes has freq info
        freq = ax_freq
    else:  # do not use tsplot if irregular was plotted first
        if (ax_freq is None) and (len(ax.get_lines()) > 0):
            return False

    if freq is None:
        return False

    if isinstance(freq, DateOffset):
        freq = freq.rule_code
    else:
        freq = frequencies.get_base_alias(freq)
    freq = frequencies.get_period_alias(freq)

    if freq is None:
        return False

    # hack this for 0.10.1, creating more technical debt...sigh
    if isinstance(data.index, DatetimeIndex):
        base = frequencies.get_freq(freq)
        x = data.index
        if (base <= frequencies.FreqGroup.FR_DAY):
            return x[:1].is_normalized
        return Period(x[0], freq).to_timestamp(tz=x.tz) == x[0]
    return True 

# 需要导入模块: from pandas.tseries import frequencies [as 别名]
# 或者: from pandas.tseries.frequencies import get_period_alias [as 别名]
def _maybe_convert_index(ax, data):
    # tsplot converts automatically, but don't want to convert index
    # over and over for DataFrames
    if isinstance(data.index, DatetimeIndex):
        freq = getattr(data.index, 'freq', None)

        if freq is None:
            freq = getattr(data.index, 'inferred_freq', None)
        if isinstance(freq, DateOffset):
            freq = freq.rule_code

        if freq is None:
            freq = _get_ax_freq(ax)

        if freq is None:
            raise ValueError('Could not get frequency alias for plotting')

        freq = frequencies.get_base_alias(freq)
        freq = frequencies.get_period_alias(freq)

        data = data.to_period(freq=freq)
    return data


# Patch methods for subplot. Only format_dateaxis is currently used.
# Do we need the rest for convenience? 

# 需要导入模块: from pandas.tseries import frequencies [as 别名]
# 或者: from pandas.tseries.frequencies import get_period_alias [as 别名]
def _is_dynamic_freq(self, freq):
        if isinstance(freq, DateOffset):
            freq = freq.rule_code
        else:
            freq = get_base_alias(freq)
        freq = get_period_alias(freq)
        return freq is not None and self._no_base(freq) 

# 需要导入模块: from pandas.tseries import frequencies [as 别名]
# 或者: from pandas.tseries.frequencies import get_period_alias [as 别名]
def _maybe_convert_index(self, data):
        # tsplot converts automatically, but don't want to convert index
        # over and over for DataFrames
        from pandas.core.frame import DataFrame
        if (isinstance(data.index, DatetimeIndex) and
                isinstance(data, DataFrame)):
            freq = getattr(data.index, 'freq', None)

            if freq is None:
                freq = getattr(data.index, 'inferred_freq', None)
            if isinstance(freq, DateOffset):
                freq = freq.rule_code
            freq = get_base_alias(freq)
            freq = get_period_alias(freq)

            if freq is None:
                ax = self._get_ax(0)
                freq = getattr(ax, 'freq', None)

            if freq is None:
                raise ValueError('Could not get frequency alias for plotting')

            data = DataFrame(data.values,
                             index=data.index.to_period(freq=freq),
                             columns=data.columns)
        return data 

# 需要导入模块: from pandas.tseries import frequencies [as 别名]
# 或者: from pandas.tseries.frequencies import get_period_alias [as 别名]
def to_period(self, freq=None):
        """
        Cast to PeriodArray/Index at a particular frequency.

        Converts DatetimeArray/Index to PeriodArray/Index.

        Parameters
        ----------
        freq : string or Offset, optional
            One of pandas' :ref:`offset strings <timeseries.offset_aliases>`
            or an Offset object. Will be inferred by default.

        Returns
        -------
        PeriodArray/Index

        Raises
        ------
        ValueError
            When converting a DatetimeArray/Index with non-regular values,
            so that a frequency cannot be inferred.

        See Also
        --------
        PeriodIndex: Immutable ndarray holding ordinal values.
        DatetimeIndex.to_pydatetime: Return DatetimeIndex as object.

        Examples
        --------
        >>> df = pd.DataFrame({"y": [1,2,3]},
        ...                   index=pd.to_datetime(["2000-03-31 00:00:00",
        ...                                         "2000-05-31 00:00:00",
        ...                                         "2000-08-31 00:00:00"]))
        >>> df.index.to_period("M")
        PeriodIndex(['2000-03', '2000-05', '2000-08'],
                    dtype='period[M]', freq='M')

        Infer the daily frequency

        >>> idx = pd.date_range("2017-01-01", periods=2)
        >>> idx.to_period()
        PeriodIndex(['2017-01-01', '2017-01-02'],
                    dtype='period[D]', freq='D')
        """
        from pandas.core.arrays import PeriodArray

        if self.tz is not None:
            warnings.warn("Converting to PeriodArray/Index representation "
                          "will drop timezone information.", UserWarning)

        if freq is None:
            freq = self.freqstr or self.inferred_freq

            if freq is None:
                raise ValueError("You must pass a freq argument as "
                                 "current index has none.")

            freq = get_period_alias(freq)

        return PeriodArray._from_datetime64(self._data, freq, tz=self.tz) 

# 需要导入模块: from pandas.tseries import frequencies [as 别名]
# 或者: from pandas.tseries.frequencies import get_period_alias [as 别名]
def to_period(self, freq=None):
        """
        Cast to PeriodIndex at a particular frequency.

        Converts DatetimeIndex to PeriodIndex.

        Parameters
        ----------
        freq : string or Offset, optional
            One of pandas' :ref:`offset strings <timeseries.offset_aliases>`
            or an Offset object. Will be inferred by default.

        Returns
        -------
        PeriodIndex

        Raises
        ------
        ValueError
            When converting a DatetimeIndex with non-regular values, so that a
            frequency cannot be inferred.

        Examples
        --------
        >>> df = pd.DataFrame({"y": [1,2,3]},
        ...                   index=pd.to_datetime(["2000-03-31 00:00:00",
        ...                                         "2000-05-31 00:00:00",
        ...                                         "2000-08-31 00:00:00"]))
        >>> df.index.to_period("M")
        PeriodIndex(['2000-03', '2000-05', '2000-08'],
                    dtype='period[M]', freq='M')

        Infer the daily frequency

        >>> idx = pd.date_range("2017-01-01", periods=2)
        >>> idx.to_period()
        PeriodIndex(['2017-01-01', '2017-01-02'],
                    dtype='period[D]', freq='D')

        See also
        --------
        pandas.PeriodIndex: Immutable ndarray holding ordinal values
        pandas.DatetimeIndex.to_pydatetime: Return DatetimeIndex as object
        """
        from pandas.core.indexes.period import PeriodIndex

        if freq is None:
            freq = self.freqstr or self.inferred_freq

            if freq is None:
                msg = ("You must pass a freq argument as "
                       "current index has none.")
                raise ValueError(msg)

            freq = get_period_alias(freq)

        return PeriodIndex(self.values, name=self.name, freq=freq, tz=self.tz)