fix & ignore failures

pandas/core/apply.py

@@ -246,12 +246,8 @@ def transform(self) -> DataFrame | Series:
             and not obj.empty
         ):
             raise ValueError("Transform function failed")
-        # error: Argument 1 to "__get__" of "AxisProperty" has incompatible type
-        # "Union[Series, DataFrame, GroupBy[Any], SeriesGroupBy,
-        # DataFrameGroupBy, BaseWindow, Resampler]"; expected "Union[DataFrame,
-        # Series]"
         if not isinstance(result, (ABCSeries, ABCDataFrame)) or not result.index.equals(
-            obj.index  # type: ignore[arg-type]
+            obj.index
         ):
             raise ValueError("Function did not transform")
 

pandas/core/arraylike.py

@@ -403,12 +403,12 @@ def _reconstruct(result):
             # for np.<ufunc>(..) calls
             # kwargs cannot necessarily be handled block-by-block, so only
             # take this path if there are no kwargs
-            mgr = inputs[0]._mgr
+            mgr = inputs[0]._mgr  # pyright: ignore[reportGeneralTypeIssues]
             result = mgr.apply(getattr(ufunc, method))
         else:
             # otherwise specific ufunc methods (eg np.<ufunc>.accumulate(..))
             # Those can have an axis keyword and thus can't be called block-by-block
-            result = default_array_ufunc(inputs[0], ufunc, method, *inputs, **kwargs)
+            result = default_array_ufunc(inputs[0], ufunc, method, *inputs, **kwargs)  # pyright: ignore[reportGeneralTypeIssues]
             # e.g. np.negative (only one reached), with "where" and "out" in kwargs
 
     result = reconstruct(result)

pandas/core/arrays/arrow/array.py

@@ -2426,7 +2426,7 @@ def _str_rindex(self, sub: str, start: int = 0, end: int | None = None) -> Self:
         result = self._apply_elementwise(predicate)
         return type(self)(pa.chunked_array(result))
 
-    def _str_normalize(self, form: str) -> Self:
+    def _str_normalize(self, form: Literal["NFC", "NFD", "NFKC", "NFKD"]) -> Self:
         predicate = lambda val: unicodedata.normalize(form, val)
         result = self._apply_elementwise(predicate)
         return type(self)(pa.chunked_array(result))

pandas/core/arrays/boolean.py

@@ -369,7 +369,7 @@ def _coerce_to_array(
             assert dtype == "boolean"
         return coerce_to_array(value, copy=copy)
 
-    def _logical_method(self, other, op):
+    def _logical_method(self, other, op):  # type: ignore[override]
         assert op.__name__ in {"or_", "ror_", "and_", "rand_", "xor", "rxor"}
         other_is_scalar = lib.is_scalar(other)
         mask = None

pandas/core/computation/expr.py

@@ -168,7 +168,7 @@ def _preparse(
     the ``tokenize`` module and ``tokval`` is a string.
     """
     assert callable(f), "f must be callable"
-    return tokenize.untokenize(f(x) for x in tokenize_string(source))
+    return tokenize.untokenize(f(x) for x in tokenize_string(source))  # pyright: ignore[reportArgumentType]
 
 
 def _is_type(t):

pandas/core/frame.py

@@ -2306,7 +2306,7 @@ def maybe_reorder(
 
         if any(exclude):
             arr_exclude = (x for x in exclude if x in arr_columns)
-            to_remove = {arr_columns.get_loc(col) for col in arr_exclude}
+            to_remove = {arr_columns.get_loc(col) for col in arr_exclude}  # pyright: ignore[reportUnhashable]
             arrays = [v for i, v in enumerate(arrays) if i not in to_remove]
 
             columns = columns.drop(exclude)

pandas/core/groupby/groupby.py

@@ -3719,7 +3719,7 @@ def blk_func(values: ArrayLike) -> ArrayLike:
             mask = isna(values)
             if values.ndim == 1:
                 indexer = np.empty(values.shape, dtype=np.intp)
-                col_func(out=indexer, mask=mask)
+                col_func(out=indexer, mask=mask)  # type: ignore[arg-type]
                 return algorithms.take_nd(values, indexer)
 
             else:
@@ -4081,7 +4081,9 @@ def _nth(
     def quantile(
         self,
         q: float | AnyArrayLike = 0.5,
-        interpolation: str = "linear",
+        interpolation: Literal[
+            "linear", "lower", "higher", "nearest", "midpoint"
+        ] = "linear",
         numeric_only: bool = False,
     ):
         """
@@ -4270,7 +4272,7 @@ def blk_func(values: ArrayLike) -> ArrayLike:
                 func(
                     out[0],
                     values=vals,
-                    mask=mask,
+                    mask=mask,  # type: ignore[arg-type]
                     result_mask=result_mask,
                     is_datetimelike=is_datetimelike,
                 )

pandas/core/indexes/interval.py

@@ -991,7 +991,7 @@ def length(self) -> Index:
     # --------------------------------------------------------------------
     # Set Operations
 
-    def _intersection(self, other, sort):
+    def _intersection(self, other, sort: bool = False):
         """
         intersection specialized to the case with matching dtypes.
         """
@@ -1006,7 +1006,7 @@ def _intersection(self, other, sort):
             # duplicates
             taken = self._intersection_non_unique(other)
 
-        if sort is None:
+        if sort:
             taken = taken.sort_values()
 
         return taken

pandas/core/resample.py

@@ -404,7 +404,7 @@ def transform(self, arg, *args, **kwargs):
             arg, *args, **kwargs
         )
 
-    def _downsample(self, f, **kwargs):
+    def _downsample(self, how, **kwargs):
         raise AbstractMethodError(self)
 
     def _upsample(self, f, limit: int | None = None, fill_value=None):

pandas/core/series.py

@@ -813,8 +813,7 @@ def _values(self):
     def _references(self) -> BlockValuesRefs:
         return self._mgr._block.refs
 
-    # error: Decorated property not supported
-    @Appender(base.IndexOpsMixin.array.__doc__)  # type: ignore[misc]
+    @Appender(base.IndexOpsMixin.array.__doc__)
     @property
     def array(self) -> ExtensionArray:
         return self._mgr.array_values()

pandas/core/tools/datetimes.py

@@ -1000,7 +1000,7 @@ def to_datetime(
         dayfirst=dayfirst,
         yearfirst=yearfirst,
         errors=errors,
-        exact=exact,
+        exact=exact,  # type: ignore[arg-type]
     )
     result: Timestamp | NaTType | Series | Index
 

pandas/core/window/rolling.py

@@ -1507,7 +1507,7 @@ def _generate_cython_apply_func(
             window_aggregations.roll_apply,
             args=args,
             kwargs=kwargs,
-            raw=raw,
+            raw=bool(raw),
             function=function,
         )
 

pandas/io/excel/_odswriter.py

@@ -34,7 +34,7 @@ class ODSWriter(ExcelWriter):
     _engine = "odf"
     _supported_extensions = (".ods",)
 
-    def __init__(
+    def __init__(  # pyright: ignore[reportInconsistentConstructor]
         self,
         path: FilePath | WriteExcelBuffer | ExcelWriter,
         engine: str | None = None,

pandas/io/excel/_openpyxl.py

@@ -42,7 +42,7 @@ class OpenpyxlWriter(ExcelWriter):
     _engine = "openpyxl"
     _supported_extensions = (".xlsx", ".xlsm")
 
-    def __init__(
+    def __init__(  # pyright: ignore[reportInconsistentConstructor]
         self,
         path: FilePath | WriteExcelBuffer | ExcelWriter,
         engine: str | None = None,

pandas/io/excel/_xlsxwriter.py

@@ -181,7 +181,7 @@ class XlsxWriter(ExcelWriter):
     _engine = "xlsxwriter"
     _supported_extensions = (".xlsx",)
 
-    def __init__(
+    def __init__(  # pyright: ignore[reportInconsistentConstructor]
         self,
         path: FilePath | WriteExcelBuffer | ExcelWriter,
         engine: str | None = None,

pandas/io/parsers/python_parser.py

@@ -1203,7 +1203,7 @@ def _rows_to_cols(self, content: list[list[Scalar]]) -> list[np.ndarray]:
                     if callable(self.on_bad_lines):
                         new_l = self.on_bad_lines(_content)
                         if new_l is not None:
-                            content.append(new_l)
+                            content.append(new_l)  # pyright: ignore[reportArgumentType]
                     elif self.on_bad_lines in (
                         self.BadLineHandleMethod.ERROR,
                         self.BadLineHandleMethod.WARN,

pandas/io/sas/sas7bdat.py

@@ -516,7 +516,7 @@ def _process_columntext_subheader(self, offset: int, length: int) -> None:
                 buf = self._read_bytes(offset1, self._lcs)
                 self.creator_proc = buf[0 : self._lcp]
             if hasattr(self, "creator_proc"):
-                self.creator_proc = self._convert_header_text(self.creator_proc)
+                self.creator_proc = self._convert_header_text(self.creator_proc)  # pyright: ignore[reportArgumentType]
 
     def _process_columnname_subheader(self, offset: int, length: int) -> None:
         int_len = self._int_length

pandas/io/sql.py

@@ -233,7 +233,7 @@ def _wrap_result_adbc(
 
 
 @overload
-def read_sql_table(
+def read_sql_table(  # pyright: ignore[reportOverlappingOverload]
     table_name: str,
     con,
     schema=...,
@@ -364,7 +364,7 @@ def read_sql_table(
 
 
 @overload
-def read_sql_query(
+def read_sql_query(  # pyright: ignore[reportOverlappingOverload]
     sql,
     con,
     index_col: str | list[str] | None = ...,
@@ -500,7 +500,7 @@ def read_sql_query(
 
 
 @overload
-def read_sql(
+def read_sql(  # pyright: ignore[reportOverlappingOverload]
     sql,
     con,
     index_col: str | list[str] | None = ...,

pandas/plotting/_matplotlib/converter.py

@@ -527,7 +527,7 @@ def _get_periods_per_ymd(freq: BaseOffset) -> tuple[int, int, int]:
 
     ppd = -1  # placeholder for above-day freqs
 
-    if dtype_code >= FreqGroup.FR_HR.value:
+    if dtype_code >= FreqGroup.FR_HR.value:  # pyright: ignore[reportAttributeAccessIssue]
         # error: "BaseOffset" has no attribute "_creso"
         ppd = periods_per_day(freq._creso)  # type: ignore[attr-defined]
         ppm = 28 * ppd
@@ -684,7 +684,7 @@ def _second_finder(label_interval: int) -> None:
     elif span <= periodsperyear // 4:
         month_start = _period_break(dates_, "month")
         info_maj[month_start] = True
-        if dtype_code < FreqGroup.FR_HR.value:
+        if dtype_code < FreqGroup.FR_HR.value:  # pyright: ignore[reportAttributeAccessIssue]
             info["min"] = True
         else:
             day_start = _period_break(dates_, "day")
@@ -910,7 +910,7 @@ def get_finder(freq: BaseOffset):
         return _quarterly_finder
     elif fgroup == FreqGroup.FR_MTH:
         return _monthly_finder
-    elif (dtype_code >= FreqGroup.FR_BUS.value) or fgroup == FreqGroup.FR_WK:
+    elif (dtype_code >= FreqGroup.FR_BUS.value) or fgroup == FreqGroup.FR_WK:  # pyright: ignore[reportAttributeAccessIssue]
         return _daily_finder
     else:  # pragma: no cover
         raise NotImplementedError(f"Unsupported frequency: {dtype_code}")

pandas/tests/frame/test_ufunc.py

@@ -66,14 +66,14 @@ def test_binary_input_dispatch_binop(dtype):
     [
         (np.add, 1, [2, 3, 4, 5]),
         (
-            partial(np.add, where=[[False, True], [True, False]]),
+            partial(np.add, where=[[False, True], [True, False]]),  # type: ignore[misc]
             np.array([[1, 1], [1, 1]]),
             [0, 3, 4, 0],
         ),
         (np.power, np.array([[1, 1], [2, 2]]), [1, 2, 9, 16]),
         (np.subtract, 2, [-1, 0, 1, 2]),
         (
-            partial(np.negative, where=np.array([[False, True], [True, False]])),
+            partial(np.negative, where=np.array([[False, True], [True, False]])),  # type: ignore[misc]
             None,
             [0, -2, -3, 0],
         ),

pandas/tests/indexes/test_base.py

@@ -1635,7 +1635,7 @@ def test_generated_op_names(opname, index):
         partial(DatetimeIndex, data=["2020-01-01"]),
         partial(PeriodIndex, data=["2020-01-01"]),
         partial(TimedeltaIndex, data=["1 day"]),
-        partial(RangeIndex, data=range(1)),
+        partial(RangeIndex, start=range(1)),
         partial(IntervalIndex, data=[pd.Interval(0, 1)]),
         partial(Index, data=["a"], dtype=object),
         partial(MultiIndex, levels=[1], codes=[0]),

pandas/util/_exceptions.py

@@ -4,7 +4,10 @@
 import inspect
 import os
 import re
-from typing import TYPE_CHECKING
+from typing import (
+    TYPE_CHECKING,
+    Any,
+)
 import warnings
 
 if TYPE_CHECKING:
@@ -24,7 +27,7 @@ def rewrite_exception(old_name: str, new_name: str) -> Generator[None]:
             raise
         msg = str(err.args[0])
         msg = msg.replace(old_name, new_name)
-        args: tuple[str, ...] = (msg,)
+        args: tuple[Any, ...] = (msg,)
         if len(err.args) > 1:
             args = args + err.args[1:]
         err.args = args