Python pandas.tseries.frequencies.get_freq_code() Examples

def test_get_to_timestamp_base(self):
        tsb = frequencies.get_to_timestamp_base

        assert (tsb(frequencies.get_freq_code('D')[0]) ==
                frequencies.get_freq_code('D')[0])
        assert (tsb(frequencies.get_freq_code('W')[0]) ==
                frequencies.get_freq_code('D')[0])
        assert (tsb(frequencies.get_freq_code('M')[0]) ==
                frequencies.get_freq_code('D')[0])

        assert (tsb(frequencies.get_freq_code('S')[0]) ==
                frequencies.get_freq_code('S')[0])
        assert (tsb(frequencies.get_freq_code('T')[0]) ==
                frequencies.get_freq_code('S')[0])
        assert (tsb(frequencies.get_freq_code('H')[0]) ==
                frequencies.get_freq_code('S')[0]) 

def _end_apply_index(self, i, freq):
        """Offsets index to end of Period frequency"""

        off = i.to_perioddelta('D')

        from pandas.tseries.frequencies import get_freq_code
        base, mult = get_freq_code(freq)
        base_period = i.to_period(base)
        if self.n > 0:
            # when adding, dates on end roll to next
            roll = np.where(base_period.to_timestamp(how='end') == i - off,
                            self.n, self.n - 1)
        else:
            roll = self.n

        base = (base_period + roll).to_timestamp(how='end')
        return base + off

    # way to get around weirdness with rule_code 

def _beg_apply_index(self, i, freq):
        """Offsets index to beginning of Period frequency"""

        off = i.to_perioddelta('D')

        from pandas.tseries.frequencies import get_freq_code
        base, mult = get_freq_code(freq)
        base_period = i.to_period(base)
        if self.n <= 0:
            # when subtracting, dates on start roll to prior
            roll = np.where(base_period.to_timestamp() == i - off,
                            self.n, self.n + 1)
        else:
            roll = self.n

        base = (base_period + roll).to_timestamp()
        return base + off 

def test_get_to_timestamp_base(self):
        tsb = frequencies.get_to_timestamp_base

        assert (tsb(frequencies.get_freq_code('D')[0]) ==
                frequencies.get_freq_code('D')[0])
        assert (tsb(frequencies.get_freq_code('W')[0]) ==
                frequencies.get_freq_code('D')[0])
        assert (tsb(frequencies.get_freq_code('M')[0]) ==
                frequencies.get_freq_code('D')[0])

        assert (tsb(frequencies.get_freq_code('S')[0]) ==
                frequencies.get_freq_code('S')[0])
        assert (tsb(frequencies.get_freq_code('T')[0]) ==
                frequencies.get_freq_code('S')[0])
        assert (tsb(frequencies.get_freq_code('H')[0]) ==
                frequencies.get_freq_code('S')[0]) 

def _beg_apply_index(self, i, freq):
        """Offsets index to beginning of Period frequency"""

        off = i.to_perioddelta('D')

        from pandas.tseries.frequencies import get_freq_code
        base, mult = get_freq_code(freq)
        base_period = i.to_period(base)
        if self.n <= 0:
            # when subtracting, dates on start roll to prior
            roll = np.where(base_period.to_timestamp() == i - off,
                            self.n, self.n + 1)
        else:
            roll = self.n

        base = (base_period + roll).to_timestamp()
        return base + off 

def _end_apply_index(self, i, freq):
        """Offsets index to end of Period frequency"""

        off = i.to_perioddelta('D')

        from pandas.tseries.frequencies import get_freq_code
        base, mult = get_freq_code(freq)
        base_period = i.to_period(base)
        if self.n > 0:
            # when adding, dates on end roll to next
            roll = np.where(base_period.to_timestamp(how='end') == i - off,
                            self.n, self.n - 1)
        else:
            roll = self.n

        base = (base_period + roll).to_timestamp(how='end')
        return base + off

    # way to get around weirdness with rule_code 

def test_get_to_timestamp_base(self):
        tsb = frequencies.get_to_timestamp_base

        assert (tsb(frequencies.get_freq_code('D')[0]) ==
                frequencies.get_freq_code('D')[0])
        assert (tsb(frequencies.get_freq_code('W')[0]) ==
                frequencies.get_freq_code('D')[0])
        assert (tsb(frequencies.get_freq_code('M')[0]) ==
                frequencies.get_freq_code('D')[0])

        assert (tsb(frequencies.get_freq_code('S')[0]) ==
                frequencies.get_freq_code('S')[0])
        assert (tsb(frequencies.get_freq_code('T')[0]) ==
                frequencies.get_freq_code('S')[0])
        assert (tsb(frequencies.get_freq_code('H')[0]) ==
                frequencies.get_freq_code('S')[0]) 

def _period_index_cmp(opname, nat_result=False):
    """
    Wrap comparison operations to convert datetime-like to datetime64
    """

    def wrapper(self, other):
        if isinstance(other, Period):
            func = getattr(self._values, opname)
            other_base, _ = _gfc(other.freq)
            if other.freq != self.freq:
                msg = _DIFFERENT_FREQ_INDEX.format(self.freqstr, other.freqstr)
                raise IncompatibleFrequency(msg)

            result = func(other.ordinal)
        elif isinstance(other, PeriodIndex):
            if other.freq != self.freq:
                msg = _DIFFERENT_FREQ_INDEX.format(self.freqstr, other.freqstr)
                raise IncompatibleFrequency(msg)

            result = getattr(self._values, opname)(other._values)

            mask = self._isnan | other._isnan
            if mask.any():
                result[mask] = nat_result

            return result
        elif other is tslib.NaT:
            result = np.empty(len(self._values), dtype=bool)
            result.fill(nat_result)
        else:
            other = Period(other, freq=self.freq)
            func = getattr(self._values, opname)
            result = func(other.ordinal)

        if self.hasnans:
            result[self._isnan] = nat_result

        return result
    return wrapper 

def to_timestamp(self, freq=None, how='start'):
        """
        Cast to DatetimeIndex

        Parameters
        ----------
        freq : string or DateOffset, default 'D' for week or longer, 'S'
               otherwise
            Target frequency
        how : {'s', 'e', 'start', 'end'}

        Returns
        -------
        DatetimeIndex
        """
        how = _validate_end_alias(how)

        if freq is None:
            base, mult = _gfc(self.freq)
            freq = frequencies.get_to_timestamp_base(base)
        else:
            freq = Period._maybe_convert_freq(freq)

        base, mult = _gfc(freq)
        new_data = self.asfreq(freq, how)

        new_data = period.periodarr_to_dt64arr(new_data._values, base)
        return DatetimeIndex(new_data, freq='infer', name=self.name) 

def _period_index_cmp(opname, nat_result=False):
    """
    Wrap comparison operations to convert datetime-like to datetime64
    """

    def wrapper(self, other):
        if isinstance(other, Period):
            func = getattr(self._values, opname)
            other_base, _ = _gfc(other.freq)
            if other.freq != self.freq:
                msg = _DIFFERENT_FREQ_INDEX.format(self.freqstr, other.freqstr)
                raise IncompatibleFrequency(msg)

            result = func(other.ordinal)
        elif isinstance(other, PeriodIndex):
            if other.freq != self.freq:
                msg = _DIFFERENT_FREQ_INDEX.format(self.freqstr, other.freqstr)
                raise IncompatibleFrequency(msg)

            result = getattr(self._values, opname)(other._values)

            mask = self._isnan | other._isnan
            if mask.any():
                result[mask] = nat_result

            return result
        elif other is tslib.NaT:
            result = np.empty(len(self._values), dtype=bool)
            result.fill(nat_result)
        else:
            other = Period(other, freq=self.freq)
            func = getattr(self._values, opname)
            result = func(other.ordinal)

        if self.hasnans:
            result[self._isnan] = nat_result

        return result
    return wrapper 

def dt64arr_to_periodarr(data, freq, tz):
    if data.dtype != np.dtype('M8[ns]'):
        raise ValueError('Wrong dtype: %s' % data.dtype)

    freq = Period._maybe_convert_freq(freq)
    base, mult = _gfc(freq)
    return period.dt64arr_to_periodarr(data.view('i8'), base, tz)

# --- Period index sketch 

def test_frequency_misc(self):
        assert (frequencies.get_freq_group('T') ==
                frequencies.FreqGroup.FR_MIN)

        code, stride = frequencies.get_freq_code(offsets.Hour())
        assert code == frequencies.FreqGroup.FR_HR

        code, stride = frequencies.get_freq_code((5, 'T'))
        assert code == frequencies.FreqGroup.FR_MIN
        assert stride == 5

        offset = offsets.Hour()
        result = frequencies.to_offset(offset)
        assert result == offset

        result = frequencies.to_offset((5, 'T'))
        expected = offsets.Minute(5)
        assert result == expected

        pytest.raises(ValueError, frequencies.get_freq_code, (5, 'baz'))

        pytest.raises(ValueError, frequencies.to_offset, '100foo')

        pytest.raises(ValueError, frequencies.to_offset, ('', ''))

        with tm.assert_produces_warning(FutureWarning, check_stacklevel=False):
            result = frequencies.get_standard_freq(offsets.Hour())
        assert result == 'H' 

def _range_from_fields(year=None, month=None, quarter=None, day=None,
                       hour=None, minute=None, second=None, freq=None):
    if hour is None:
        hour = 0
    if minute is None:
        minute = 0
    if second is None:
        second = 0
    if day is None:
        day = 1

    ordinals = []

    if quarter is not None:
        if freq is None:
            freq = 'Q'
            base = frequencies.FreqGroup.FR_QTR
        else:
            base, mult = _gfc(freq)
            if base != frequencies.FreqGroup.FR_QTR:
                raise AssertionError("base must equal FR_QTR")

        year, quarter = _make_field_arrays(year, quarter)
        for y, q in zip(year, quarter):
            y, m = _quarter_to_myear(y, q, freq)
            val = period.period_ordinal(y, m, 1, 1, 1, 1, 0, 0, base)
            ordinals.append(val)
    else:
        base, mult = _gfc(freq)
        arrays = _make_field_arrays(year, month, day, hour, minute, second)
        for y, mth, d, h, mn, s in zip(*arrays):
            ordinals.append(period.period_ordinal(
                y, mth, d, h, mn, s, 0, 0, base))

    return np.array(ordinals, dtype=np.int64), freq 

def to_timestamp(self, freq=None, how='start'):
        """
        Cast to DatetimeIndex

        Parameters
        ----------
        freq : string or DateOffset, default 'D' for week or longer, 'S'
               otherwise
            Target frequency
        how : {'s', 'e', 'start', 'end'}

        Returns
        -------
        DatetimeIndex
        """
        how = _validate_end_alias(how)

        if freq is None:
            base, mult = _gfc(self.freq)
            freq = frequencies.get_to_timestamp_base(base)
        else:
            freq = Period._maybe_convert_freq(freq)

        base, mult = _gfc(freq)
        new_data = self.asfreq(freq, how)

        new_data = period.periodarr_to_dt64arr(new_data._values, base)
        return DatetimeIndex(new_data, freq='infer', name=self.name) 

def dt64arr_to_periodarr(data, freq, tz):
    if data.dtype != np.dtype('M8[ns]'):
        raise ValueError('Wrong dtype: %s' % data.dtype)

    freq = Period._maybe_convert_freq(freq)
    base, mult = _gfc(freq)
    return period.dt64arr_to_periodarr(data.view('i8'), base, tz)

# --- Period index sketch 

def _field_accessor(name, alias, docstring=None):
    def f(self):
        base, mult = _gfc(self.freq)
        result = get_period_field_arr(alias, self._values, base)
        return Index(result, name=self.name)
    f.__name__ = name
    f.__doc__ = docstring
    return property(f) 

def test_frequency_misc(self):
        self.assertEquals(fmod.get_freq_group('T'),
                          fmod.FreqGroup.FR_MIN)

        code, stride = fmod.get_freq_code(offsets.Hour())
        self.assertEquals(code, fmod.FreqGroup.FR_HR)

        code, stride = fmod.get_freq_code((5, 'T'))
        self.assertEquals(code, fmod.FreqGroup.FR_MIN)
        self.assertEquals(stride, 5)

        offset = offsets.Hour()
        result = fmod.to_offset(offset)
        self.assertEquals(result, offset)

        result = fmod.to_offset((5, 'T'))
        expected = offsets.Minute(5)
        self.assertEquals(result, expected)

        self.assertRaises(ValueError, fmod.get_freq_code, (5, 'baz'))

        self.assertRaises(ValueError, fmod.to_offset, '100foo')

        self.assertRaises(ValueError, fmod.to_offset, ('', ''))

        result = fmod.get_standard_freq(offsets.Hour())
        self.assertEquals(result, 'H') 

def _range_from_fields(year=None, month=None, quarter=None, day=None,
                       hour=None, minute=None, second=None, freq=None):
    if hour is None:
        hour = 0
    if minute is None:
        minute = 0
    if second is None:
        second = 0
    if day is None:
        day = 1

    ordinals = []

    if quarter is not None:
        if freq is None:
            freq = 'Q'
            base = frequencies.FreqGroup.FR_QTR
        else:
            base, mult = _gfc(freq)
            if base != frequencies.FreqGroup.FR_QTR:
                raise AssertionError("base must equal FR_QTR")

        year, quarter = _make_field_arrays(year, quarter)
        for y, q in zip(year, quarter):
            y, m = _quarter_to_myear(y, q, freq)
            val = period.period_ordinal(y, m, 1, 1, 1, 1, 0, 0, base)
            ordinals.append(val)
    else:
        base, mult = _gfc(freq)
        arrays = _make_field_arrays(year, month, day, hour, minute, second)
        for y, mth, d, h, mn, s in zip(*arrays):
            ordinals.append(period.period_ordinal(
                y, mth, d, h, mn, s, 0, 0, base))

    return np.array(ordinals, dtype=np.int64), freq 

def to_timestamp(self, freq=None, how='start'):
        """
        Cast to DatetimeIndex

        Parameters
        ----------
        freq : string or DateOffset, optional
            Target frequency. The default is 'D' for week or longer,
            'S' otherwise
        how : {'s', 'e', 'start', 'end'}

        Returns
        -------
        DatetimeIndex
        """
        how = _validate_end_alias(how)

        if freq is None:
            base, mult = _gfc(self.freq)
            freq = frequencies.get_to_timestamp_base(base)
        else:
            freq = Period._maybe_convert_freq(freq)

        base, mult = _gfc(freq)
        new_data = self.asfreq(freq, how)

        new_data = period.periodarr_to_dt64arr(new_data._ndarray_values, base)
        return DatetimeIndex(new_data, freq='infer', name=self.name) 

def dt64arr_to_periodarr(data, freq, tz):
    if data.dtype != np.dtype('M8[ns]'):
        raise ValueError('Wrong dtype: %s' % data.dtype)

    freq = Period._maybe_convert_freq(freq)
    base, mult = _gfc(freq)
    return period.dt64arr_to_periodarr(data.view('i8'), base, tz)

# --- Period index sketch 

def _field_accessor(name, alias, docstring=None):
    def f(self):
        base, mult = _gfc(self.freq)
        result = get_period_field_arr(alias, self._ndarray_values, base)
        return Index(result, name=self.name)
    f.__name__ = name
    f.__doc__ = docstring
    return property(f) 

def test_frequency_misc(self):
        assert (resolution.get_freq_group('T') ==
                frequencies.FreqGroup.FR_MIN)

        code, stride = frequencies.get_freq_code(offsets.Hour())
        assert code == frequencies.FreqGroup.FR_HR

        code, stride = frequencies.get_freq_code((5, 'T'))
        assert code == frequencies.FreqGroup.FR_MIN
        assert stride == 5

        offset = offsets.Hour()
        result = frequencies.to_offset(offset)
        assert result == offset

        result = frequencies.to_offset((5, 'T'))
        expected = offsets.Minute(5)
        assert result == expected

        with tm.assert_raises_regex(ValueError, 'Invalid frequency'):
            frequencies.get_freq_code((5, 'baz'))

        with tm.assert_raises_regex(ValueError, 'Invalid frequency'):
            frequencies.to_offset('100foo')

        with tm.assert_raises_regex(ValueError, 'Could not evaluate'):
            frequencies.to_offset(('', '')) 

def test_frequency_misc(self):
        assert (resolution.get_freq_group('T') ==
                frequencies.FreqGroup.FR_MIN)

        code, stride = frequencies.get_freq_code(offsets.Hour())
        assert code == frequencies.FreqGroup.FR_HR

        code, stride = frequencies.get_freq_code((5, 'T'))
        assert code == frequencies.FreqGroup.FR_MIN
        assert stride == 5

        offset = offsets.Hour()
        result = frequencies.to_offset(offset)
        assert result == offset

        result = frequencies.to_offset((5, 'T'))
        expected = offsets.Minute(5)
        assert result == expected

        with tm.assert_raises_regex(ValueError, 'Invalid frequency'):
            frequencies.get_freq_code((5, 'baz'))

        with tm.assert_raises_regex(ValueError, 'Invalid frequency'):
            frequencies.to_offset('100foo')

        with tm.assert_raises_regex(ValueError, 'Could not evaluate'):
            frequencies.to_offset(('', '')) 

def _get_ordinal_range(start, end, periods, freq, mult=1):
    if com._count_not_none(start, end, periods) != 2:
        raise ValueError('Of the three parameters: start, end, and periods, '
                         'exactly two must be specified')

    if freq is not None:
        _, mult = _gfc(freq)

    if start is not None:
        start = Period(start, freq)
    if end is not None:
        end = Period(end, freq)

    is_start_per = isinstance(start, Period)
    is_end_per = isinstance(end, Period)

    if is_start_per and is_end_per and start.freq != end.freq:
        raise ValueError('start and end must have same freq')
    if (start is tslib.NaT or end is tslib.NaT):
        raise ValueError('start and end must not be NaT')

    if freq is None:
        if is_start_per:
            freq = start.freq
        elif is_end_per:
            freq = end.freq
        else:  # pragma: no cover
            raise ValueError('Could not infer freq from start/end')

    if periods is not None:
        periods = periods * mult
        if start is None:
            data = np.arange(end.ordinal - periods + mult,
                             end.ordinal + 1, mult,
                             dtype=np.int64)
        else:
            data = np.arange(start.ordinal, start.ordinal + periods, mult,
                             dtype=np.int64)
    else:
        data = np.arange(start.ordinal, end.ordinal + 1, mult, dtype=np.int64)

    return data, freq 

def test_get_freq_code(self):
        # frequency str
        assert (frequencies.get_freq_code('A') ==
                (frequencies.get_freq('A'), 1))
        assert (frequencies.get_freq_code('3D') ==
                (frequencies.get_freq('D'), 3))
        assert (frequencies.get_freq_code('-2M') ==
                (frequencies.get_freq('M'), -2))

        # tuple
        assert (frequencies.get_freq_code(('D', 1)) ==
                (frequencies.get_freq('D'), 1))
        assert (frequencies.get_freq_code(('A', 3)) ==
                (frequencies.get_freq('A'), 3))
        assert (frequencies.get_freq_code(('M', -2)) ==
                (frequencies.get_freq('M'), -2))

        # numeric tuple
        assert frequencies.get_freq_code((1000, 1)) == (1000, 1)

        # offsets
        assert (frequencies.get_freq_code(offsets.Day()) ==
                (frequencies.get_freq('D'), 1))
        assert (frequencies.get_freq_code(offsets.Day(3)) ==
                (frequencies.get_freq('D'), 3))
        assert (frequencies.get_freq_code(offsets.Day(-2)) ==
                (frequencies.get_freq('D'), -2))

        assert (frequencies.get_freq_code(offsets.MonthEnd()) ==
                (frequencies.get_freq('M'), 1))
        assert (frequencies.get_freq_code(offsets.MonthEnd(3)) ==
                (frequencies.get_freq('M'), 3))
        assert (frequencies.get_freq_code(offsets.MonthEnd(-2)) ==
                (frequencies.get_freq('M'), -2))

        assert (frequencies.get_freq_code(offsets.Week()) ==
                (frequencies.get_freq('W'), 1))
        assert (frequencies.get_freq_code(offsets.Week(3)) ==
                (frequencies.get_freq('W'), 3))
        assert (frequencies.get_freq_code(offsets.Week(-2)) ==
                (frequencies.get_freq('W'), -2))

        # Monday is weekday=0
        assert (frequencies.get_freq_code(offsets.Week(weekday=1)) ==
                (frequencies.get_freq('W-TUE'), 1))
        assert (frequencies.get_freq_code(offsets.Week(3, weekday=0)) ==
                (frequencies.get_freq('W-MON'), 3))
        assert (frequencies.get_freq_code(offsets.Week(-2, weekday=4)) ==
                (frequencies.get_freq('W-FRI'), -2)) 

def _get_ordinal_range(start, end, periods, freq, mult=1):
    if com._count_not_none(start, end, periods) != 2:
        raise ValueError('Of the three parameters: start, end, and periods, '
                         'exactly two must be specified')

    if freq is not None:
        _, mult = _gfc(freq)

    if start is not None:
        start = Period(start, freq)
    if end is not None:
        end = Period(end, freq)

    is_start_per = isinstance(start, Period)
    is_end_per = isinstance(end, Period)

    if is_start_per and is_end_per and start.freq != end.freq:
        raise ValueError('start and end must have same freq')
    if (start is tslib.NaT or end is tslib.NaT):
        raise ValueError('start and end must not be NaT')

    if freq is None:
        if is_start_per:
            freq = start.freq
        elif is_end_per:
            freq = end.freq
        else:  # pragma: no cover
            raise ValueError('Could not infer freq from start/end')

    if periods is not None:
        periods = periods * mult
        if start is None:
            data = np.arange(end.ordinal - periods + mult,
                             end.ordinal + 1, mult,
                             dtype=np.int64)
        else:
            data = np.arange(start.ordinal, start.ordinal + periods, mult,
                             dtype=np.int64)
    else:
        data = np.arange(start.ordinal, end.ordinal + 1, mult, dtype=np.int64)

    return data, freq 

def asfreq(self, freq=None, how='E'):
        """
        Convert the PeriodIndex to the specified frequency `freq`.

        Parameters
        ----------

        freq : str
            a frequency
        how : str {'E', 'S'}
            'E', 'END', or 'FINISH' for end,
            'S', 'START', or 'BEGIN' for start.
            Whether the elements should be aligned to the end
            or start within pa period. January 31st ('END') vs.
            Janury 1st ('START') for example.

        Returns
        -------

        new : PeriodIndex with the new frequency

        Examples
        --------
        >>> pidx = pd.period_range('2010-01-01', '2015-01-01', freq='A')
        >>> pidx
        <class 'pandas.core.indexes.period.PeriodIndex'>
        [2010, ..., 2015]
        Length: 6, Freq: A-DEC

        >>> pidx.asfreq('M')
        <class 'pandas.core.indexes.period.PeriodIndex'>
        [2010-12, ..., 2015-12]
        Length: 6, Freq: M

        >>> pidx.asfreq('M', how='S')
        <class 'pandas.core.indexes.period.PeriodIndex'>
        [2010-01, ..., 2015-01]
        Length: 6, Freq: M
        """
        how = _validate_end_alias(how)

        freq = Period._maybe_convert_freq(freq)

        base1, mult1 = _gfc(self.freq)
        base2, mult2 = _gfc(freq)

        asi8 = self.asi8
        # mult1 can't be negative or 0
        end = how == 'E'
        if end:
            ordinal = asi8 + mult1 - 1
        else:
            ordinal = asi8

        new_data = period.period_asfreq_arr(ordinal, base1, base2, end)

        if self.hasnans:
            new_data[self._isnan] = tslib.iNaT

        return self._simple_new(new_data, self.name, freq=freq) 

def test_get_freq_code(self):
        # frequency str
        assert (frequencies.get_freq_code('A') ==
                (frequencies.get_freq('A'), 1))
        assert (frequencies.get_freq_code('3D') ==
                (frequencies.get_freq('D'), 3))
        assert (frequencies.get_freq_code('-2M') ==
                (frequencies.get_freq('M'), -2))

        # tuple
        assert (frequencies.get_freq_code(('D', 1)) ==
                (frequencies.get_freq('D'), 1))
        assert (frequencies.get_freq_code(('A', 3)) ==
                (frequencies.get_freq('A'), 3))
        assert (frequencies.get_freq_code(('M', -2)) ==
                (frequencies.get_freq('M'), -2))

        # numeric tuple
        assert frequencies.get_freq_code((1000, 1)) == (1000, 1)

        # offsets
        assert (frequencies.get_freq_code(offsets.Day()) ==
                (frequencies.get_freq('D'), 1))
        assert (frequencies.get_freq_code(offsets.Day(3)) ==
                (frequencies.get_freq('D'), 3))
        assert (frequencies.get_freq_code(offsets.Day(-2)) ==
                (frequencies.get_freq('D'), -2))

        assert (frequencies.get_freq_code(offsets.MonthEnd()) ==
                (frequencies.get_freq('M'), 1))
        assert (frequencies.get_freq_code(offsets.MonthEnd(3)) ==
                (frequencies.get_freq('M'), 3))
        assert (frequencies.get_freq_code(offsets.MonthEnd(-2)) ==
                (frequencies.get_freq('M'), -2))

        assert (frequencies.get_freq_code(offsets.Week()) ==
                (frequencies.get_freq('W'), 1))
        assert (frequencies.get_freq_code(offsets.Week(3)) ==
                (frequencies.get_freq('W'), 3))
        assert (frequencies.get_freq_code(offsets.Week(-2)) ==
                (frequencies.get_freq('W'), -2))

        # Monday is weekday=0
        assert (frequencies.get_freq_code(offsets.Week(weekday=1)) ==
                (frequencies.get_freq('W-TUE'), 1))
        assert (frequencies.get_freq_code(offsets.Week(3, weekday=0)) ==
                (frequencies.get_freq('W-MON'), 3))
        assert (frequencies.get_freq_code(offsets.Week(-2, weekday=4)) ==
                (frequencies.get_freq('W-FRI'), -2)) 

def get_anlz_factor(freq):
    """Find the number of periods per year given a frequency.

    Parameters
    ----------
    freq : str
        Any frequency str or anchored offset str recognized by Pandas.

    Returns
    -------
    float

    Example
    -------
    >>> get_anlz_factor('D')
    252.0
    >>> get_anlz_factor('5D')  # 5-business-day periods per year
    50.4

    >>> get_anlz_factor('Q')
    4.0
    >>> get_anlz_factor('Q-DEC')
    4.0
    >>> get_anlz_factor('BQS-APR')
    4.0
    """

    # 'Q-NOV' would give us (2001, 1); we just want (2000, 1).
    try:
        base, mult = get_freq_code(freq)
    except ValueError:
        # The above will fail for a bunch of irregular frequencies, such
        # as 'Q-NOV' or 'BQS-APR'
        freq = freq.upper()
        if freq.startswith(("A-", "BA-", "AS-", "BAS-")):
            freq = "A"
        elif freq.startswith(("Q-", "BQ-", "QS-", "BQS-")):
            freq = "Q"
        elif freq in {"MS", "BMS"}:
            freq = "M"
        else:
            raise ValueError("Invalid frequency: %s" % freq)
        base, mult = get_freq_code(freq)
    return PERIODS_PER_YEAR[(base // 1000) * 1000] / mult 

def _get_ordinal_range(start, end, periods, freq, mult=1):
    if com._count_not_none(start, end, periods) != 2:
        raise ValueError('Of the three parameters: start, end, and periods, '
                         'exactly two must be specified')

    if freq is not None:
        _, mult = _gfc(freq)

    if start is not None:
        start = Period(start, freq)
    if end is not None:
        end = Period(end, freq)

    is_start_per = isinstance(start, Period)
    is_end_per = isinstance(end, Period)

    if is_start_per and is_end_per and start.freq != end.freq:
        raise ValueError('start and end must have same freq')
    if (start is tslib.NaT or end is tslib.NaT):
        raise ValueError('start and end must not be NaT')

    if freq is None:
        if is_start_per:
            freq = start.freq
        elif is_end_per:
            freq = end.freq
        else:  # pragma: no cover
            raise ValueError('Could not infer freq from start/end')

    if periods is not None:
        periods = periods * mult
        if start is None:
            data = np.arange(end.ordinal - periods + mult,
                             end.ordinal + 1, mult,
                             dtype=np.int64)
        else:
            data = np.arange(start.ordinal, start.ordinal + periods, mult,
                             dtype=np.int64)
    else:
        data = np.arange(start.ordinal, end.ordinal + 1, mult, dtype=np.int64)

    return data, freq