TYP: reshape (#48099)

Author: jbrockmendel

pandas/core/frame.py

@@ -8942,7 +8942,7 @@ def explode(
         if is_scalar(column) or isinstance(column, tuple):
             columns = [column]
         elif isinstance(column, list) and all(
-            map(lambda c: is_scalar(c) or isinstance(c, tuple), column)
+            is_scalar(c) or isinstance(c, tuple) for c in column
         ):
             if not column:
                 raise ValueError("column must be nonempty")

pandas/core/generic.py

@@ -1613,7 +1613,7 @@ def __round__(self: NDFrameT, decimals: int = 0) -> NDFrameT:
     # have consistent precedence and validation logic throughout the library.
 
     @final
-    def _is_level_reference(self, key, axis=0):
+    def _is_level_reference(self, key: Level, axis=0) -> bool_t:
         """
         Test whether a key is a level reference for a given axis.
 
@@ -1625,7 +1625,7 @@ def _is_level_reference(self, key, axis=0):
 
         Parameters
         ----------
-        key : str
+        key : Hashable
             Potential level name for the given axis
         axis : int, default 0
             Axis that levels are associated with (0 for index, 1 for columns)
@@ -1644,7 +1644,7 @@ def _is_level_reference(self, key, axis=0):
         )
 
     @final
-    def _is_label_reference(self, key, axis=0) -> bool_t:
+    def _is_label_reference(self, key: Level, axis=0) -> bool_t:
         """
         Test whether a key is a label reference for a given axis.
 
@@ -1654,8 +1654,8 @@ def _is_label_reference(self, key, axis=0) -> bool_t:
 
         Parameters
         ----------
-        key : str
-            Potential label name
+        key : Hashable
+            Potential label name, i.e. Index entry.
         axis : int, default 0
             Axis perpendicular to the axis that labels are associated with
             (0 means search for column labels, 1 means search for index labels)
@@ -1674,7 +1674,7 @@ def _is_label_reference(self, key, axis=0) -> bool_t:
         )
 
     @final
-    def _is_label_or_level_reference(self, key: str, axis: int = 0) -> bool_t:
+    def _is_label_or_level_reference(self, key: Level, axis: int = 0) -> bool_t:
         """
         Test whether a key is a label or level reference for a given axis.
 
@@ -1685,7 +1685,7 @@ def _is_label_or_level_reference(self, key: str, axis: int = 0) -> bool_t:
 
         Parameters
         ----------
-        key : str
+        key : Hashable
             Potential label or level name
         axis : int, default 0
             Axis that levels are associated with (0 for index, 1 for columns)
@@ -1699,7 +1699,7 @@ def _is_label_or_level_reference(self, key: str, axis: int = 0) -> bool_t:
         )
 
     @final
-    def _check_label_or_level_ambiguity(self, key, axis: int = 0) -> None:
+    def _check_label_or_level_ambiguity(self, key: Level, axis: int = 0) -> None:
         """
         Check whether `key` is ambiguous.
 
@@ -1708,7 +1708,7 @@ def _check_label_or_level_ambiguity(self, key, axis: int = 0) -> None:
 
         Parameters
         ----------
-        key : str or object
+        key : Hashable
             Label or level name.
         axis : int, default 0
             Axis that levels are associated with (0 for index, 1 for columns).
@@ -1717,6 +1717,7 @@ def _check_label_or_level_ambiguity(self, key, axis: int = 0) -> None:
         ------
         ValueError: `key` is ambiguous
         """
+
         axis = self._get_axis_number(axis)
         other_axes = (ax for ax in range(self._AXIS_LEN) if ax != axis)
 
@@ -1743,7 +1744,7 @@ def _check_label_or_level_ambiguity(self, key, axis: int = 0) -> None:
             raise ValueError(msg)
 
     @final
-    def _get_label_or_level_values(self, key: Level, axis: int = 0) -> np.ndarray:
+    def _get_label_or_level_values(self, key: Level, axis: int = 0) -> ArrayLike:
         """
         Return a 1-D array of values associated with `key`, a label or level
         from the given `axis`.
@@ -1758,14 +1759,14 @@ def _get_label_or_level_values(self, key: Level, axis: int = 0) -> np.ndarray:
 
         Parameters
         ----------
-        key : str
+        key : Hashable
             Label or level name.
         axis : int, default 0
             Axis that levels are associated with (0 for index, 1 for columns)
 
         Returns
         -------
-        values : np.ndarray
+        np.ndarray or ExtensionArray
 
         Raises
         ------

pandas/core/reshape/merge.py

@@ -11,6 +11,7 @@
 from typing import (
     TYPE_CHECKING,
     Hashable,
+    Sequence,
     cast,
 )
 import uuid
@@ -25,6 +26,7 @@
     lib,
 )
 from pandas._typing import (
+    AnyArrayLike,
     ArrayLike,
     DtypeObj,
     IndexLabel,
@@ -609,6 +611,21 @@ class _MergeOperation:
     """
 
     _merge_type = "merge"
+    how: str
+    on: IndexLabel | None
+    # left_on/right_on may be None when passed, but in validate_specification
+    #  get replaced with non-None.
+    left_on: Sequence[Hashable | AnyArrayLike]
+    right_on: Sequence[Hashable | AnyArrayLike]
+    left_index: bool
+    right_index: bool
+    axis: int
+    bm_axis: int
+    sort: bool
+    suffixes: Suffixes
+    copy: bool
+    indicator: bool
+    validate: str | None
 
     def __init__(
         self,
@@ -819,8 +836,16 @@ def _maybe_restore_index_levels(self, result: DataFrame) -> None:
             self.join_names, self.left_on, self.right_on
         ):
             if (
-                self.orig_left._is_level_reference(left_key)
-                and self.orig_right._is_level_reference(right_key)
+                # Argument 1 to "_is_level_reference" of "NDFrame" has incompatible
+                # type "Union[Hashable, ExtensionArray, Index, Series]"; expected
+                # "Hashable"
+                self.orig_left._is_level_reference(left_key)  # type: ignore[arg-type]
+                # Argument 1 to "_is_level_reference" of "NDFrame" has incompatible
+                # type "Union[Hashable, ExtensionArray, Index, Series]"; expected
+                # "Hashable"
+                and self.orig_right._is_level_reference(
+                    right_key  # type: ignore[arg-type]
+                )
                 and left_key == right_key
                 and name not in result.index.names
             ):
@@ -1049,13 +1074,13 @@ def _get_merge_keys(self):
 
         Returns
         -------
-        left_keys, right_keys
+        left_keys, right_keys, join_names
         """
-        left_keys = []
-        right_keys = []
-        # error: Need type annotation for 'join_names' (hint: "join_names: List[<type>]
-        # = ...")
-        join_names = []  # type: ignore[var-annotated]
+        # left_keys, right_keys entries can actually be anything listlike
+        #  with a 'dtype' attr
+        left_keys: list[AnyArrayLike] = []
+        right_keys: list[AnyArrayLike] = []
+        join_names: list[Hashable] = []
         right_drop = []
         left_drop = []
 
@@ -1078,11 +1103,16 @@ def _get_merge_keys(self):
         if _any(self.left_on) and _any(self.right_on):
             for lk, rk in zip(self.left_on, self.right_on):
                 if is_lkey(lk):
+                    lk = cast(AnyArrayLike, lk)
                     left_keys.append(lk)
                     if is_rkey(rk):
+                        rk = cast(AnyArrayLike, rk)
                         right_keys.append(rk)
                         join_names.append(None)  # what to do?
                     else:
+                        # Then we're either Hashable or a wrong-length arraylike,
+                        #  the latter of which will raise
+                        rk = cast(Hashable, rk)
                         if rk is not None:
                             right_keys.append(right._get_label_or_level_values(rk))
                             join_names.append(rk)
@@ -1092,6 +1122,9 @@ def _get_merge_keys(self):
                             join_names.append(right.index.name)
                 else:
                     if not is_rkey(rk):
+                        # Then we're either Hashable or a wrong-length arraylike,
+                        #  the latter of which will raise
+                        rk = cast(Hashable, rk)
                         if rk is not None:
                             right_keys.append(right._get_label_or_level_values(rk))
                         else:
@@ -1104,8 +1137,12 @@ def _get_merge_keys(self):
                             else:
                                 left_drop.append(lk)
                     else:
+                        rk = cast(AnyArrayLike, rk)
                         right_keys.append(rk)
                     if lk is not None:
+                        # Then we're either Hashable or a wrong-length arraylike,
+                        #  the latter of which will raise
+                        lk = cast(Hashable, lk)
                         left_keys.append(left._get_label_or_level_values(lk))
                         join_names.append(lk)
                     else:
@@ -1115,9 +1152,13 @@ def _get_merge_keys(self):
         elif _any(self.left_on):
             for k in self.left_on:
                 if is_lkey(k):
+                    k = cast(AnyArrayLike, k)
                     left_keys.append(k)
                     join_names.append(None)
                 else:
+                    # Then we're either Hashable or a wrong-length arraylike,
+                    #  the latter of which will raise
+                    k = cast(Hashable, k)
                     left_keys.append(left._get_label_or_level_values(k))
                     join_names.append(k)
             if isinstance(self.right.index, MultiIndex):
@@ -1132,9 +1173,13 @@ def _get_merge_keys(self):
         elif _any(self.right_on):
             for k in self.right_on:
                 if is_rkey(k):
+                    k = cast(AnyArrayLike, k)
                     right_keys.append(k)
                     join_names.append(None)
                 else:
+                    # Then we're either Hashable or a wrong-length arraylike,
+                    #  the latter of which will raise
+                    k = cast(Hashable, k)
                     right_keys.append(right._get_label_or_level_values(k))
                     join_names.append(k)
             if isinstance(self.left.index, MultiIndex):

pandas/core/reshape/reshape.py

@@ -1,7 +1,10 @@
 from __future__ import annotations
 
 import itertools
-from typing import TYPE_CHECKING
+from typing import (
+    TYPE_CHECKING,
+    cast,
+)
 import warnings
 
 import numpy as np
@@ -452,7 +455,7 @@ def _unstack_multiple(data, clocs, fill_value=None):
     return unstacked
 
 
-def unstack(obj, level, fill_value=None):
+def unstack(obj: Series | DataFrame, level, fill_value=None):
 
     if isinstance(level, (tuple, list)):
         if len(level) != 1:
@@ -489,19 +492,20 @@ def unstack(obj, level, fill_value=None):
         )
 
 
-def _unstack_frame(obj, level, fill_value=None):
+def _unstack_frame(obj: DataFrame, level, fill_value=None):
+    assert isinstance(obj.index, MultiIndex)  # checked by caller
+    unstacker = _Unstacker(obj.index, level=level, constructor=obj._constructor)
+
     if not obj._can_fast_transpose:
-        unstacker = _Unstacker(obj.index, level=level)
         mgr = obj._mgr.unstack(unstacker, fill_value=fill_value)
         return obj._constructor(mgr)
     else:
-        unstacker = _Unstacker(obj.index, level=level, constructor=obj._constructor)
         return unstacker.get_result(
             obj._values, value_columns=obj.columns, fill_value=fill_value
         )
 
 
-def _unstack_extension_series(series, level, fill_value):
+def _unstack_extension_series(series: Series, level, fill_value) -> DataFrame:
     """
     Unstack an ExtensionArray-backed Series.
 
@@ -534,14 +538,14 @@ def _unstack_extension_series(series, level, fill_value):
     return result
 
 
-def stack(frame, level=-1, dropna=True):
+def stack(frame: DataFrame, level=-1, dropna: bool = True):
     """
     Convert DataFrame to Series with multi-level Index. Columns become the
     second level of the resulting hierarchical index
 
     Returns
     -------
-    stacked : Series
+    stacked : Series or DataFrame
     """
 
     def factorize(index):
@@ -676,8 +680,10 @@ def _stack_multi_column_index(columns: MultiIndex) -> MultiIndex:
     )
 
 
-def _stack_multi_columns(frame, level_num=-1, dropna=True):
-    def _convert_level_number(level_num: int, columns):
+def _stack_multi_columns(
+    frame: DataFrame, level_num: int = -1, dropna: bool = True
+) -> DataFrame:
+    def _convert_level_number(level_num: int, columns: Index):
         """
         Logic for converting the level number to something we can safely pass
         to swaplevel.
@@ -690,32 +696,36 @@ def _convert_level_number(level_num: int, columns):
 
         return level_num
 
-    this = frame.copy()
+    this = frame.copy(deep=False)
+    mi_cols = this.columns  # cast(MultiIndex, this.columns)
+    assert isinstance(mi_cols, MultiIndex)  # caller is responsible
 
     # this makes life much simpler
-    if level_num != frame.columns.nlevels - 1:
+    if level_num != mi_cols.nlevels - 1:
         # roll levels to put selected level at end
-        roll_columns = this.columns
-        for i in range(level_num, frame.columns.nlevels - 1):
+        roll_columns = mi_cols
+        for i in range(level_num, mi_cols.nlevels - 1):
             # Need to check if the ints conflict with level names
             lev1 = _convert_level_number(i, roll_columns)
             lev2 = _convert_level_number(i + 1, roll_columns)
             roll_columns = roll_columns.swaplevel(lev1, lev2)
-        this.columns = roll_columns
+        this.columns = mi_cols = roll_columns
 
-    if not this.columns._is_lexsorted():
+    if not mi_cols._is_lexsorted():
         # Workaround the edge case where 0 is one of the column names,
         # which interferes with trying to sort based on the first
         # level
-        level_to_sort = _convert_level_number(0, this.columns)
+        level_to_sort = _convert_level_number(0, mi_cols)
         this = this.sort_index(level=level_to_sort, axis=1)
+        mi_cols = this.columns
 
-    new_columns = _stack_multi_column_index(this.columns)
+    mi_cols = cast(MultiIndex, mi_cols)
+    new_columns = _stack_multi_column_index(mi_cols)
 
     # time to ravel the values
     new_data = {}
-    level_vals = this.columns.levels[-1]
-    level_codes = sorted(set(this.columns.codes[-1]))
+    level_vals = mi_cols.levels[-1]
+    level_codes = sorted(set(mi_cols.codes[-1]))
     level_vals_nan = level_vals.insert(len(level_vals), None)
 
     level_vals_used = np.take(level_vals_nan, level_codes)