implement maybe_define_freq

pandas-dev · jbrockmendel · Nov 4, 2018 · Nov 4, 2018 · Nov 4, 2018 · Nov 4, 2018
commit 98dca45aaf030a3a42ab40dbe4714f02dd553e7c
diff --git a/pandas/core/arrays/datetimelike.py b/pandas/core/arrays/datetimelike.py
@@ -888,6 +888,22 @@ def maybe_infer_freq(freq):
     return freq, freq_infer
 
 
+def maybe_define_freq(freq_infer, result):
+    """
+    If appropriate, infer the frequency of the given Datetime/Timedelta Array
+    and pin it to the object at the end of the construction.
+
+    Parameters
+    ----------
+    freq_infer : bool
+    result : DatetimeArray or TimedeltaArray
+    """
+    if freq_infer:
+        inferred = result.inferred_freq
+        if inferred:
+            result.freq = frequencies.to_offset(inferred)
+
+
 def validate_tz_from_dtype(dtype, tz):
     """
     If the given dtype is a DatetimeTZDtype, extract the implied

diff --git a/pandas/core/arrays/datetimes.py b/pandas/core/arrays/datetimes.py
@@ -217,7 +217,7 @@ def __new__(cls, values, freq=None, tz=None, dtype=None, copy=False):
         if lib.is_scalar(values):
             raise ValueError('{cls}() must be called with a '
                              'collection of some kind, {data} was passed'
-                             .format(cls=cls.__name__, data=repr(data)))
+                             .format(cls=cls.__name__, data=repr(values)))
         elif isinstance(values, DatetimeArrayMixin):
             # extract nanosecond unix timestamps
             values = values.asi8
@@ -230,10 +230,7 @@ def __new__(cls, values, freq=None, tz=None, dtype=None, copy=False):
         values = conversion.ensure_datetime64ns(values, copy=copy)
 
         result = cls._simple_new(values, freq=freq, tz=tz)
-        if freq_infer:
-            inferred = result.inferred_freq
-            if inferred:
-                result.freq = to_offset(inferred)
+        dtl.maybe_define_freq(freq_infer, result)
 
         # NB: Among other things not yet ported from the DatetimeIndex
         # constructor, this does not call _deepcopy_if_needed

diff --git a/pandas/core/arrays/timedeltas.py b/pandas/core/arrays/timedeltas.py
@@ -19,7 +19,6 @@
 from pandas.core.algorithms import checked_add_with_arr
 
 from pandas.tseries.offsets import Tick
-from pandas.tseries.frequencies import to_offset
 
 from . import datetimelike as dtl
 
@@ -152,11 +151,7 @@ def __new__(cls, values, freq=None, dtype=_TD_DTYPE, copy=False):
             values = values.astype(_TD_DTYPE)
 
         result = cls._simple_new(values, freq=freq)
-        if freq_infer:
-            inferred = result.inferred_freq
-            if inferred:
-                result.freq = to_offset(inferred)
-
+        dtl.maybe_define_freq(freq_infer, result)
         return result
 
     @classmethod

diff --git a/pandas/core/indexes/datetimes.py b/pandas/core/indexes/datetimes.py
@@ -263,7 +263,7 @@ def __new__(cls, data=None,
                              .format(cls=cls.__name__, data=repr(data)))
 
         elif not isinstance(data, (np.ndarray, Index, ABCSeries,
-                                 DatetimeArrayMixin)):
+                                   DatetimeArrayMixin)):
             if not isinstance(data, (list, tuple)):
                 data = list(data)
             data = np.asarray(data, dtype='O')
@@ -321,11 +321,7 @@ def __new__(cls, data=None,
             if freq is not None and not freq_infer:
                 cls._validate_frequency(subarr, freq, ambiguous=ambiguous)
 
-        if freq_infer:
-            inferred = subarr.inferred_freq
-            if inferred:
-                subarr.freq = to_offset(inferred)
-
+        dtl.maybe_define_freq(freq_infer, subarr)
         return subarr._deepcopy_if_needed(ref_to_data, copy)
 
     @classmethod

diff --git a/pandas/core/indexes/timedeltas.py b/pandas/core/indexes/timedeltas.py
@@ -35,7 +35,6 @@
     to_timedelta, _coerce_scalar_to_timedelta_type)
 from pandas._libs import (lib, index as libindex,
                           join as libjoin, Timedelta, NaT)
-from pandas._libs.tslibs.timedeltas import array_to_timedelta64
 
 
 class TimedeltaIndex(TimedeltaArrayMixin, DatetimeIndexOpsMixin,
@@ -182,11 +181,7 @@ def __new__(cls, data=None, unit=None, freq=None, start=None, end=None,
             if freq is not None and not freq_infer:
                 cls._validate_frequency(subarr, freq)
 
-        if freq_infer:
-            inferred = subarr.inferred_freq
-            if inferred:
-                subarr.freq = to_offset(inferred)
-
+        dtl.maybe_define_freq(freq_infer, subarr)
         return subarr
 
     @classmethod