remove unused imports from tseries.frequencies; update imports elsewhere (pandas-dev#24834)

Author: jbrockmendel

pandas/core/arrays/period.py

@@ -4,7 +4,8 @@
 
 import numpy as np
 
-from pandas._libs.tslibs import NaT, iNaT, period as libperiod
+from pandas._libs.tslibs import (
+    NaT, frequencies as libfrequencies, iNaT, period as libperiod)
 from pandas._libs.tslibs.fields import isleapyear_arr
 from pandas._libs.tslibs.period import (
     DIFFERENT_FREQ, IncompatibleFrequency, Period, get_period_field_arr,
@@ -31,7 +32,7 @@
 
 def _field_accessor(name, alias, docstring=None):
     def f(self):
-        base, mult = frequencies.get_freq_code(self.freq)
+        base, mult = libfrequencies.get_freq_code(self.freq)
         result = get_period_field_arr(alias, self.asi8, base)
         return result
 
@@ -348,12 +349,12 @@ def to_timestamp(self, freq=None, how='start'):
                 return (self + self.freq).to_timestamp(how='start') - adjust
 
         if freq is None:
-            base, mult = frequencies.get_freq_code(self.freq)
-            freq = frequencies.get_to_timestamp_base(base)
+            base, mult = libfrequencies.get_freq_code(self.freq)
+            freq = libfrequencies.get_to_timestamp_base(base)
         else:
             freq = Period._maybe_convert_freq(freq)
 
-        base, mult = frequencies.get_freq_code(freq)
+        base, mult = libfrequencies.get_freq_code(freq)
         new_data = self.asfreq(freq, how=how)
 
         new_data = libperiod.periodarr_to_dt64arr(new_data.asi8, base)
@@ -450,8 +451,8 @@ def asfreq(self, freq=None, how='E'):
 
         freq = Period._maybe_convert_freq(freq)
 
-        base1, mult1 = frequencies.get_freq_code(self.freq)
-        base2, mult2 = frequencies.get_freq_code(freq)
+        base1, mult1 = libfrequencies.get_freq_code(self.freq)
+        base2, mult2 = libfrequencies.get_freq_code(freq)
 
         asi8 = self.asi8
         # mult1 can't be negative or 0
@@ -551,7 +552,7 @@ def _addsub_int_array(
 
     def _add_offset(self, other):
         assert not isinstance(other, Tick)
-        base = frequencies.get_base_alias(other.rule_code)
+        base = libfrequencies.get_base_alias(other.rule_code)
         if base != self.freq.rule_code:
             _raise_on_incompatible(self, other)
 
@@ -855,7 +856,7 @@ def dt64arr_to_periodarr(data, freq, tz=None):
     if isinstance(data, (ABCIndexClass, ABCSeries)):
         data = data._values
 
-    base, mult = frequencies.get_freq_code(freq)
+    base, mult = libfrequencies.get_freq_code(freq)
     return libperiod.dt64arr_to_periodarr(data.view('i8'), base, tz), freq
 
 
@@ -865,7 +866,7 @@ def _get_ordinal_range(start, end, periods, freq, mult=1):
                          'exactly two must be specified')
 
     if freq is not None:
-        _, mult = frequencies.get_freq_code(freq)
+        _, mult = libfrequencies.get_freq_code(freq)
 
     if start is not None:
         start = Period(start, freq)
@@ -919,10 +920,10 @@ def _range_from_fields(year=None, month=None, quarter=None, day=None,
     if quarter is not None:
         if freq is None:
             freq = 'Q'
-            base = frequencies.FreqGroup.FR_QTR
+            base = libfrequencies.FreqGroup.FR_QTR
         else:
-            base, mult = frequencies.get_freq_code(freq)
-            if base != frequencies.FreqGroup.FR_QTR:
+            base, mult = libfrequencies.get_freq_code(freq)
+            if base != libfrequencies.FreqGroup.FR_QTR:
                 raise AssertionError("base must equal FR_QTR")
 
         year, quarter = _make_field_arrays(year, quarter)
@@ -931,7 +932,7 @@ def _range_from_fields(year=None, month=None, quarter=None, day=None,
             val = libperiod.period_ordinal(y, m, 1, 1, 1, 1, 0, 0, base)
             ordinals.append(val)
     else:
-        base, mult = frequencies.get_freq_code(freq)
+        base, mult = libfrequencies.get_freq_code(freq)
         arrays = _make_field_arrays(year, month, day, hour, minute, second)
         for y, mth, d, h, mn, s in compat.zip(*arrays):
             ordinals.append(libperiod.period_ordinal(

pandas/core/indexes/period.py

@@ -5,7 +5,8 @@
 import numpy as np
 
 from pandas._libs import index as libindex
-from pandas._libs.tslibs import NaT, iNaT, resolution
+from pandas._libs.tslibs import (
+    NaT, frequencies as libfrequencies, iNaT, resolution)
 from pandas._libs.tslibs.period import (
     DIFFERENT_FREQ, IncompatibleFrequency, Period)
 from pandas.util._decorators import Appender, Substitution, cache_readonly
@@ -376,7 +377,7 @@ def _maybe_convert_timedelta(self, other):
                 return delta
         elif isinstance(other, DateOffset):
             freqstr = other.rule_code
-            base = frequencies.get_base_alias(freqstr)
+            base = libfrequencies.get_base_alias(freqstr)
             if base == self.freq.rule_code:
                 return other.n
 

pandas/core/resample.py

@@ -7,6 +7,7 @@
 
 from pandas._libs import lib
 from pandas._libs.tslibs import NaT, Timestamp
+from pandas._libs.tslibs.frequencies import is_subperiod, is_superperiod
 from pandas._libs.tslibs.period import IncompatibleFrequency
 import pandas.compat as compat
 from pandas.compat.numpy import function as nv
@@ -28,7 +29,7 @@
 from pandas.core.indexes.period import PeriodIndex
 from pandas.core.indexes.timedeltas import TimedeltaIndex, timedelta_range
 
-from pandas.tseries.frequencies import is_subperiod, is_superperiod, to_offset
+from pandas.tseries.frequencies import to_offset
 from pandas.tseries.offsets import (
     DateOffset, Day, Nano, Tick, delta_to_nanoseconds)
 

pandas/plotting/_converter.py

@@ -11,6 +11,7 @@
 
 from pandas._libs import lib, tslibs
 from pandas._libs.tslibs import resolution
+from pandas._libs.tslibs.frequencies import FreqGroup, get_freq
 import pandas.compat as compat
 from pandas.compat import lrange
 
@@ -25,9 +26,6 @@
 from pandas.core.indexes.period import Period, PeriodIndex, period_range
 import pandas.core.tools.datetimes as tools
 
-import pandas.tseries.frequencies as frequencies
-from pandas.tseries.frequencies import FreqGroup
-
 # constants
 HOURS_PER_DAY = 24.
 MIN_PER_HOUR = 60.
@@ -955,7 +953,7 @@ def _annual_finder(vmin, vmax, freq):
 
 def get_finder(freq):
     if isinstance(freq, compat.string_types):
-        freq = frequencies.get_freq(freq)
+        freq = get_freq(freq)
     fgroup = resolution.get_freq_group(freq)
 
     if fgroup == FreqGroup.FR_ANN:
@@ -992,7 +990,7 @@ class TimeSeries_DateLocator(Locator):
     def __init__(self, freq, minor_locator=False, dynamic_mode=True,
                  base=1, quarter=1, month=1, day=1, plot_obj=None):
         if isinstance(freq, compat.string_types):
-            freq = frequencies.get_freq(freq)
+            freq = get_freq(freq)
         self.freq = freq
         self.base = base
         (self.quarter, self.month, self.day) = (quarter, month, day)
@@ -1073,7 +1071,7 @@ class TimeSeries_DateFormatter(Formatter):
     def __init__(self, freq, minor_locator=False, dynamic_mode=True,
                  plot_obj=None):
         if isinstance(freq, compat.string_types):
-            freq = frequencies.get_freq(freq)
+            freq = get_freq(freq)
         self.format = None
         self.freq = freq
         self.locs = []

pandas/plotting/_timeseries.py

@@ -5,6 +5,8 @@
 from matplotlib import pylab
 import numpy as np
 
+from pandas._libs.tslibs.frequencies import (
+    FreqGroup, get_base_alias, get_freq, is_subperiod, is_superperiod)
 from pandas._libs.tslibs.period import Period
 import pandas.compat as compat
 
@@ -73,7 +75,7 @@ def _maybe_resample(series, ax, kwargs):
         series = series.to_period(freq=freq)
 
     if ax_freq is not None and freq != ax_freq:
-        if frequencies.is_superperiod(freq, ax_freq):  # upsample input
+        if is_superperiod(freq, ax_freq):  # upsample input
             series = series.copy()
             series.index = series.index.asfreq(ax_freq, how='s')
             freq = ax_freq
@@ -82,21 +84,21 @@ def _maybe_resample(series, ax, kwargs):
             series = getattr(series.resample('D'), how)().dropna()
             series = getattr(series.resample(ax_freq), how)().dropna()
             freq = ax_freq
-        elif frequencies.is_subperiod(freq, ax_freq) or _is_sub(freq, ax_freq):
+        elif is_subperiod(freq, ax_freq) or _is_sub(freq, ax_freq):
             _upsample_others(ax, freq, kwargs)
         else:  # pragma: no cover
             raise ValueError('Incompatible frequency conversion')
     return freq, series
 
 
 def _is_sub(f1, f2):
-    return ((f1.startswith('W') and frequencies.is_subperiod('D', f2)) or
-            (f2.startswith('W') and frequencies.is_subperiod(f1, 'D')))
+    return ((f1.startswith('W') and is_subperiod('D', f2)) or
+            (f2.startswith('W') and is_subperiod(f1, 'D')))
 
 
 def _is_sup(f1, f2):
-    return ((f1.startswith('W') and frequencies.is_superperiod('D', f2)) or
-            (f2.startswith('W') and frequencies.is_superperiod(f1, 'D')))
+    return ((f1.startswith('W') and is_superperiod('D', f2)) or
+            (f2.startswith('W') and is_superperiod(f1, 'D')))
 
 
 def _upsample_others(ax, freq, kwargs):
@@ -209,7 +211,7 @@ def _get_freq(ax, series):
     if isinstance(freq, DateOffset):
         freq = freq.rule_code
     else:
-        freq = frequencies.get_base_alias(freq)
+        freq = get_base_alias(freq)
 
     freq = frequencies.get_period_alias(freq)
     return freq, ax_freq
@@ -231,17 +233,17 @@ def _use_dynamic_x(ax, data):
     if isinstance(freq, DateOffset):
         freq = freq.rule_code
     else:
-        freq = frequencies.get_base_alias(freq)
+        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 = frequencies.get_freq(freq)
+        base = get_freq(freq)
         x = data.index
-        if (base <= frequencies.FreqGroup.FR_DAY):
+        if (base <= FreqGroup.FR_DAY):
             return x[:1].is_normalized
         return Period(x[0], freq).to_timestamp(tz=x.tz) == x[0]
     return True
@@ -275,7 +277,7 @@ def _maybe_convert_index(ax, data):
         if freq is None:
             raise ValueError('Could not get frequency alias for plotting')
 
-        freq = frequencies.get_base_alias(freq)
+        freq = get_base_alias(freq)
         freq = frequencies.get_period_alias(freq)
 
         data = data.to_period(freq=freq)

pandas/tests/indexes/datetimes/test_construction.py

@@ -366,8 +366,8 @@ def test_construction_with_ndarray(self):
         dates = [datetime(2013, 10, 7),
                  datetime(2013, 10, 8),
                  datetime(2013, 10, 9)]
-        data = DatetimeIndex(dates, freq=pd.tseries.frequencies.BDay()).values
-        result = DatetimeIndex(data, freq=pd.tseries.frequencies.BDay())
+        data = DatetimeIndex(dates, freq=pd.offsets.BDay()).values
+        result = DatetimeIndex(data, freq=pd.offsets.BDay())
         expected = DatetimeIndex(['2013-10-07',
                                   '2013-10-08',
                                   '2013-10-09'],

pandas/tests/series/test_dtypes.py

@@ -292,7 +292,7 @@ def test_astype_categorical_to_other(self):
         tm.assert_series_equal(s.astype('category'), expected)
         tm.assert_series_equal(s.astype(CategoricalDtype()), expected)
         msg = (r"could not convert string to float: '(0 - 499|9500 - 9999)'|"
-               r"invalid literal for float\(\): 9500 - 9999")
+               r"invalid literal for float\(\): (0 - 499|9500 - 9999)")
         with pytest.raises(ValueError, match=msg):
             s.astype('float64')