Keep up with pandas21_compat changes

Merge in important bugfixes for `na_value` handling.  And keep `black` happy.

Signed-off-by: Michael Tiemann <[email protected]>

pint_pandas/pint_array.py

@@ -601,9 +601,9 @@ def _values_for_factorize(self):
  if HAS_UNCERTAINTIES and arr.size > 0:
  # Canonicalize uncertain NaNs and pd.NA to np.nan
  arr = arr.map(
- lambda x: self.dtype.na_value.m if x is pd.NA or unp.isnan(x) else x
+ lambda x: self.dtype.na_value if x is pd.NA or unp.isnan(x) else x
  )
- return np.array(arr, copy=False), self.dtype.na_value.m
+ return np.array(arr, copy=False), self.dtype.na_value
  return arr._values_for_factorize()
 
  def value_counts(self, dropna=True):
@@ -631,7 +631,7 @@ def value_counts(self, dropna=True):
  # compute counts on the data with no nans
  data = self._data
  nafilt = data.map(lambda x: x is pd.NA or unp.isnan(x))
- na_value = self.dtype.na_value.m
+ na_value = self.dtype.na_value
  data = data[~nafilt]
  if HAS_UNCERTAINTIES and data.dtype.kind == "O":
  unique_data = []
@@ -661,7 +661,7 @@ def unique(self):
  from pandas import unique
 
  data = self._data
- na_value = self.dtype.na_value.m
+ na_value = self.dtype.na_value
  if HAS_UNCERTAINTIES and data.dtype.kind == "O":
  unique_data = []
  for item in data:
@@ -824,7 +824,7 @@ def __array__(self, dtype=None, copy=False):
  def _to_array_of_quantity(self, copy=False):
  qtys = [
  self._Q(item, self._dtype.units)
- if item is not self.dtype.na_value.m
+ if item is not self.dtype.na_value
  else self.dtype.na_value
  for item in self._data
  ]

pint_pandas/testsuite/test_pandas_extensiontests.py

@@ -540,10 +540,18 @@ def _get_expected_exception(
  if op_name in ["__pow__", "__rpow__"]:
  return DimensionalityError
  complex128_dtype = pd.core.dtypes.dtypes.NumpyEADtype("complex128")
- if ((isinstance(obj, pd.Series) and obj.dtype == complex128_dtype)
- or (isinstance(obj, pd.DataFrame) and any([dtype == complex128_dtype for dtype in obj.dtypes]))
+ if (
+ (isinstance(obj, pd.Series) and obj.dtype == complex128_dtype)
+ or (
+ isinstance(obj, pd.DataFrame)
+ and any([dtype == complex128_dtype for dtype in obj.dtypes])
+ )
  or (isinstance(other, pd.Series) and other.dtype == complex128_dtype)
- or (isinstance(other, pd.DataFrame) and any([dtype == complex128_dtype for dtype in other.dtypes]))):
+ or (
+ isinstance(other, pd.DataFrame)
+ and any([dtype == complex128_dtype for dtype in other.dtypes])
+ )
+ ):
  if op_name in ["__floordiv__", "__rfloordiv__", "__mod__", "__rmod__"]:
  return TypeError
  return super()._get_expected_exception(op_name, obj, other)
@@ -611,7 +619,11 @@ class TestMissing(base.BaseMissingTests):
 class TestNumericReduce(base.BaseNumericReduceTests):
  def _supports_reduction(self, obj, op_name: str) -> bool:
  # Specify if we expect this reduction to succeed.
- if USE_UNCERTAINTIES and op_name in _all_numeric_reductions and op_name not in _uncertain_numeric_reductions:
+ if (
+ USE_UNCERTAINTIES
+ and op_name in _all_numeric_reductions
+ and op_name not in _uncertain_numeric_reductions
+ ):
  if any([isinstance(v, UFloat) for v in obj.values.quantity._magnitude]):
  pytest.skip(f"reduction {op_name} not implemented in uncertainties")
  return super()._supports_reduction(obj, op_name)
@@ -646,7 +658,11 @@ def test_reduce_scaling(
  This verifies that the result units are sensible.
  """
  op_name = all_numeric_reductions
- if USE_UNCERTAINTIES and op_name in _all_numeric_reductions and op_name not in _uncertain_numeric_reductions:
+ if (
+ USE_UNCERTAINTIES
+ and op_name in _all_numeric_reductions
+ and op_name not in _uncertain_numeric_reductions
+ ):
  if any([isinstance(v, UFloat) for v in data.quantity._magnitude]):
  pytest.skip(f"reduction {op_name} not implemented in uncertainties")
  s_nm = pd.Series(data)
@@ -683,7 +699,11 @@ def test_reduce_series(
  self, data, all_numeric_reductions, skipna, USE_UNCERTAINTIES
  ):
  op_name = all_numeric_reductions
- if USE_UNCERTAINTIES and op_name in _all_numeric_reductions and op_name not in _uncertain_numeric_reductions:
+ if (
+ USE_UNCERTAINTIES
+ and op_name in _all_numeric_reductions
+ and op_name not in _uncertain_numeric_reductions
+ ):
  if any([isinstance(v, UFloat) for v in data.quantity._magnitude]):
  pytest.skip(f"reduction {op_name} not implemented in uncertainties")
  s = pd.Series(data)