CLN: replace unnecessary freq_to_period_freqstr with PeriodDtype constructor (#56550)

* replace freq_to_period_freqstr() with PeriodDtype(freq)._freqstr in _shift_with_freq() * replace freq_to_period_freqstr with PeriodDtype()._freqstr except in frequencies.py, period.pyx * fix pre-commit errors * remove freq_to_period_freqstr from _maybe_coerce_freq and from tests * remove freq_to_period_freqstr from period.pyx * correct raise_on_incompatible * correct raise_on_incompatible again * replace warnings.simplefilter with warnings.filterwarnings in raise_on_incompatible * remove regex splitting from test_line_plot_datetime_frame * remove regex splitting from test_line_plot_period_mlt_frame

Author: natmokval

pandas/_libs/tslibs/dtypes.pxd

@@ -11,7 +11,6 @@ cpdef int64_t periods_per_second(NPY_DATETIMEUNIT reso) except? -1
 cdef NPY_DATETIMEUNIT get_supported_reso(NPY_DATETIMEUNIT reso)
 cdef bint is_supported_unit(NPY_DATETIMEUNIT reso)
 
-cpdef freq_to_period_freqstr(freq_n, freq_name)
 cdef dict c_OFFSET_TO_PERIOD_FREQSTR
 cdef dict c_OFFSET_DEPR_FREQSTR
 cdef dict c_REVERSE_OFFSET_DEPR_FREQSTR

pandas/_libs/tslibs/dtypes.pyi

@@ -7,7 +7,6 @@ OFFSET_TO_PERIOD_FREQSTR: dict[str, str]
 def periods_per_day(reso: int = ...) -> int: ...
 def periods_per_second(reso: int) -> int: ...
 def abbrev_to_npy_unit(abbrev: str | None) -> int: ...
-def freq_to_period_freqstr(freq_n: int, freq_name: str) -> str: ...
 
 class PeriodDtypeBase:
  _dtype_code: int # PeriodDtypeCode

pandas/_libs/tslibs/dtypes.pyx

@@ -334,15 +334,6 @@ cdef dict c_REVERSE_OFFSET_DEPR_FREQSTR = {
  v: k for k, v in c_OFFSET_DEPR_FREQSTR.items()
 }
 
-cpdef freq_to_period_freqstr(freq_n, freq_name):
- if freq_n == 1:
- freqstr = f"""{c_OFFSET_TO_PERIOD_FREQSTR.get(
- freq_name, freq_name)}"""
- else:
- freqstr = f"""{freq_n}{c_OFFSET_TO_PERIOD_FREQSTR.get(
- freq_name, freq_name)}"""
- return freqstr
-
 # Map deprecated resolution abbreviations to correct resolution abbreviations
 cdef dict c_DEPR_ABBREVS = {
  "A": "Y",

pandas/_libs/tslibs/offsets.pyx

@@ -4698,7 +4698,7 @@ _lite_rule_alias = {
  "ns": "ns",
 }
 
-_dont_uppercase = _dont_uppercase = {"h", "bh", "cbh", "MS", "ms", "s"}
+_dont_uppercase = {"h", "bh", "cbh", "MS", "ms", "s"}
 
 
 INVALID_FREQ_ERR_MSG = "Invalid frequency: {0}"

pandas/_libs/tslibs/period.pyx

@@ -38,10 +38,7 @@ from libc.time cimport (
  tm,
 )
 
-from pandas._libs.tslibs.dtypes cimport (
- c_OFFSET_TO_PERIOD_FREQSTR,
- freq_to_period_freqstr,
-)
+from pandas._libs.tslibs.dtypes cimport c_OFFSET_TO_PERIOD_FREQSTR
 
 from pandas._libs.tslibs.np_datetime import OutOfBoundsDatetime
 
@@ -97,9 +94,6 @@ from pandas._libs.tslibs.dtypes cimport (
  attrname_to_abbrevs,
  freq_group_code_to_npy_unit,
 )
-
-from pandas._libs.tslibs.dtypes import freq_to_period_freqstr
-
 from pandas._libs.tslibs.parsing cimport quarter_to_myear
 
 from pandas._libs.tslibs.parsing import parse_datetime_string_with_reso
@@ -1554,7 +1548,7 @@ def extract_ordinals(ndarray values, freq) -> np.ndarray:
  # if we don't raise here, we'll segfault later!
  raise TypeError("extract_ordinals values must be object-dtype")
 
- freqstr = freq_to_period_freqstr(freq.n, freq.name)
+ freqstr = PeriodDtypeBase(freq._period_dtype_code, freq.n)._freqstr
 
  for i in range(n):
  # Analogous to: p = values[i]
@@ -1722,8 +1716,15 @@ cdef class PeriodMixin:
  condition = self.freq != other
 
  if condition:
- freqstr = freq_to_period_freqstr(self.freq.n, self.freq.name)
- other_freqstr = freq_to_period_freqstr(other.n, other.name)
+ freqstr = PeriodDtypeBase(
+ self.freq._period_dtype_code, self.freq.n
+ )._freqstr
+ if hasattr(other, "_period_dtype_code"):
+ other_freqstr = PeriodDtypeBase(
+ other._period_dtype_code, other.n
+ )._freqstr
+ else:
+ other_freqstr = other.freqstr
  msg = DIFFERENT_FREQ.format(
  cls=type(self).__name__,
  own_freq=freqstr,
@@ -2479,7 +2480,7 @@ cdef class _Period(PeriodMixin):
  >>> pd.Period('2020-01', 'D').freqstr
  'D'
  """
- freqstr = freq_to_period_freqstr(self.freq.n, self.freq.name)
+ freqstr = PeriodDtypeBase(self.freq._period_dtype_code, self.freq.n)._freqstr
  return freqstr
 
  def __repr__(self) -> str:

pandas/core/arrays/period.py

@@ -37,7 +37,6 @@
 from pandas._libs.tslibs.dtypes import (
  FreqGroup,
  PeriodDtypeBase,
- freq_to_period_freqstr,
 )
 from pandas._libs.tslibs.fields import isleapyear_arr
 from pandas._libs.tslibs.offsets import (
@@ -325,7 +324,7 @@ def _from_datetime64(cls, data, freq, tz=None) -> Self:
  PeriodArray[freq]
  """
  if isinstance(freq, BaseOffset):
- freq = freq_to_period_freqstr(freq.n, freq.name)
+ freq = PeriodDtype(freq)._freqstr
  data, freq = dt64arr_to_periodarr(data, freq, tz)
  dtype = PeriodDtype(freq)
  return cls(data, dtype=dtype)
@@ -399,7 +398,7 @@ def freq(self) -> BaseOffset:
 
  @property
  def freqstr(self) -> str:
- return freq_to_period_freqstr(self.freq.n, self.freq.name)
+ return PeriodDtype(self.freq)._freqstr
 
  def __array__(self, dtype: NpDtype | None = None) -> np.ndarray:
  if dtype == "i8":
@@ -1002,13 +1001,17 @@ def raise_on_incompatible(left, right) -> IncompatibleFrequency:
  if isinstance(right, (np.ndarray, ABCTimedeltaArray)) or right is None:
  other_freq = None
  elif isinstance(right, BaseOffset):
- other_freq = freq_to_period_freqstr(right.n, right.name)
+ with warnings.catch_warnings():
+ warnings.filterwarnings(
+ "ignore", r"PeriodDtype\[B\] is deprecated", category=FutureWarning
+ )
+ other_freq = PeriodDtype(right)._freqstr
  elif isinstance(right, (ABCPeriodIndex, PeriodArray, Period)):
  other_freq = right.freqstr
  else:
  other_freq = delta_to_tick(Timedelta(right)).freqstr
 
- own_freq = freq_to_period_freqstr(left.freq.n, left.freq.name)
+ own_freq = PeriodDtype(left.freq)._freqstr
  msg = DIFFERENT_FREQ.format(
  cls=type(left).__name__, own_freq=own_freq, other_freq=other_freq
  )

pandas/core/generic.py

@@ -34,7 +34,6 @@
  Timestamp,
  to_offset,
 )
-from pandas._libs.tslibs.dtypes import freq_to_period_freqstr
 from pandas._typing import (
  AlignJoin,
  AnyArrayLike,
@@ -123,6 +122,7 @@
 from pandas.core.dtypes.dtypes import (
  DatetimeTZDtype,
  ExtensionDtype,
+ PeriodDtype,
 )
 from pandas.core.dtypes.generic import (
  ABCDataFrame,
@@ -10358,9 +10358,9 @@ def _shift_with_freq(self, periods: int, axis: int, freq) -> Self:
  if freq != orig_freq:
  assert orig_freq is not None # for mypy
  raise ValueError(
- f"Given freq {freq_to_period_freqstr(freq.n, freq.name)} "
+ f"Given freq {PeriodDtype(freq)._freqstr} "
  f"does not match PeriodIndex freq "
- f"{freq_to_period_freqstr(orig_freq.n, orig_freq.name)}"
+ f"{PeriodDtype(orig_freq)._freqstr}"
  )
  new_ax: Index = index.shift(periods)
  else:

pandas/core/indexes/datetimelike.py

@@ -28,7 +28,6 @@
  parsing,
  to_offset,
 )
-from pandas._libs.tslibs.dtypes import freq_to_period_freqstr
 from pandas.compat.numpy import function as nv
 from pandas.errors import (
  InvalidIndexError,
@@ -45,7 +44,10 @@
  is_list_like,
 )
 from pandas.core.dtypes.concat import concat_compat
-from pandas.core.dtypes.dtypes import CategoricalDtype
+from pandas.core.dtypes.dtypes import (
+ CategoricalDtype,
+ PeriodDtype,
+)
 
 from pandas.core.arrays import (
  DatetimeArray,
@@ -139,7 +141,7 @@ def freqstr(self) -> str:
  if self._data.freqstr is not None and isinstance(
  self._data, (PeriodArray, PeriodIndex)
  ):
- freq = freq_to_period_freqstr(self._data.freq.n, self._data.freq.name)
+ freq = PeriodDtype(self._data.freq)._freqstr
  return freq
  else:
  return self._data.freqstr # type: ignore[return-value]

pandas/core/resample.py

@@ -25,7 +25,6 @@
  Timestamp,
  to_offset,
 )
-from pandas._libs.tslibs.dtypes import freq_to_period_freqstr
 from pandas._typing import NDFrameT
 from pandas.errors import AbstractMethodError
 from pandas.util._decorators import (
@@ -38,7 +37,10 @@
  rewrite_warning,
 )
 
-from pandas.core.dtypes.dtypes import ArrowDtype
+from pandas.core.dtypes.dtypes import (
+ ArrowDtype,
+ PeriodDtype,
+)
 from pandas.core.dtypes.generic import (
  ABCDataFrame,
  ABCSeries,
@@ -2650,7 +2652,7 @@ def asfreq(
 
  if isinstance(freq, BaseOffset):
  if hasattr(freq, "_period_dtype_code"):
- freq = freq_to_period_freqstr(freq.n, freq.name)
+ freq = PeriodDtype(freq)._freqstr
 
  new_obj = obj.copy()
  new_obj.index = obj.index.asfreq(freq, how=how)

pandas/io/json/_table_schema.py

@@ -15,7 +15,6 @@
 from pandas._libs import lib
 from pandas._libs.json import ujson_loads
 from pandas._libs.tslibs import timezones
-from pandas._libs.tslibs.dtypes import freq_to_period_freqstr
 from pandas.util._exceptions import find_stack_level
 
 from pandas.core.dtypes.base import _registry as registry
@@ -212,8 +211,7 @@ def convert_json_field_to_pandas_type(field) -> str | CategoricalDtype:
  elif field.get("freq"):
  # GH#9586 rename frequency M to ME for offsets
  offset = to_offset(field["freq"])
- freq_n, freq_name = offset.n, offset.name
- freq = freq_to_period_freqstr(freq_n, freq_name)
+ freq = PeriodDtype(offset)._freqstr
  # GH#47747 using datetime over period to minimize the change surface
  return f"period[{freq}]"
  else: