CLN: remove unused zip/enumerate/items

pandas/core/aggregation.py

@@ -162,7 +162,7 @@ def normalize_keyword_aggregation(kwargs: dict) -> Tuple[dict, List[str], List[i
     order = []
     columns, pairs = list(zip(*kwargs.items()))
 
-    for name, (column, aggfunc) in zip(columns, pairs):
+    for column, aggfunc in pairs:
         aggspec[column].append(aggfunc)
         order.append((column, com.get_callable_name(aggfunc) or aggfunc))
 

pandas/core/groupby/grouper.py

@@ -789,7 +789,7 @@ def is_in_obj(gpr) -> bool:
             #  lambda here
             return False
 
-    for i, (gpr, level) in enumerate(zip(keys, levels)):
+    for gpr, level in zip(keys, levels):
 
         if is_in_obj(gpr):  # df.groupby(df['name'])
             in_axis, name = True, gpr.name

pandas/core/indexing.py

@@ -2248,7 +2248,7 @@ def _convert_key(self, key, is_setter: bool = False):
         """
         Require integer args. (and convert to label arguments)
         """
-        for a, i in zip(self.obj.axes, key):
+        for i in key:
             if not is_integer(i):
                 raise ValueError("iAt based indexing can only have integer indexers")
         return key

pandas/core/internals/ops.py

@@ -26,7 +26,7 @@ def _iter_block_pairs(
     # At this point we have already checked the parent DataFrames for
     #  assert rframe._indexed_same(lframe)
 
-    for n, blk in enumerate(left.blocks):
+    for blk in left.blocks:
         locs = blk.mgr_locs
         blk_vals = blk.values
 
@@ -40,7 +40,7 @@ def _iter_block_pairs(
         #    assert len(rblks) == 1, rblks
         #    assert rblks[0].shape[0] == 1, rblks[0].shape
 
-        for k, rblk in enumerate(rblks):
+        for rblk in rblks:
             right_ea = rblk.values.ndim == 1
 
             lvals, rvals = _get_same_shape_values(blk, rblk, left_ea, right_ea)

pandas/io/excel/_odfreader.py

@@ -101,12 +101,12 @@ def get_sheet_data(self, sheet, convert_float: bool) -> List[List[Scalar]]:
 
         table: List[List[Scalar]] = []
 
-        for i, sheet_row in enumerate(sheet_rows):
+        for sheet_row in sheet_rows:
             sheet_cells = [x for x in sheet_row.childNodes if x.qname in cell_names]
             empty_cells = 0
             table_row: List[Scalar] = []
 
-            for j, sheet_cell in enumerate(sheet_cells):
+            for sheet_cell in sheet_cells:
                 if sheet_cell.qname == table_cell_name:
                     value = self._get_cell_value(sheet_cell, convert_float)
                 else:

pandas/io/formats/xml.py

@@ -307,7 +307,7 @@ def build_tree(self) -> bytes:
             f"{self.prefix_uri}{self.root_name}", attrib=self.other_namespaces()
         )
 
-        for k, d in self.frame_dicts.items():
+        for d in self.frame_dicts.values():
             self.d = d
             self.elem_row = SubElement(self.root, f"{self.prefix_uri}{self.row_name}")
 
@@ -477,7 +477,7 @@ def build_tree(self) -> bytes:
 
         self.root = Element(f"{self.prefix_uri}{self.root_name}", nsmap=self.namespaces)
 
-        for k, d in self.frame_dicts.items():
+        for d in self.frame_dicts.values():
             self.d = d
             self.elem_row = SubElement(self.root, f"{self.prefix_uri}{self.row_name}")
 

pandas/io/pytables.py

@@ -3540,7 +3540,7 @@ def validate_min_itemsize(self, min_itemsize):
             return
 
         q = self.queryables()
-        for k, v in min_itemsize.items():
+        for k in min_itemsize:
 
             # ok, apply generally
             if k == "values":

pandas/plotting/_matplotlib/boxplot.py

@@ -84,7 +84,7 @@ def _validate_color_args(self):
 
             if isinstance(self.color, dict):
                 valid_keys = ["boxes", "whiskers", "medians", "caps"]
-                for key, values in self.color.items():
+                for key in self.color:
                     if key not in valid_keys:
                         raise ValueError(
                             f"color dict contains invalid key '{key}'. "

pandas/tests/frame/constructors/test_from_records.py

@@ -149,7 +149,7 @@ def test_from_records_dictlike(self):
         # from the dict
         blocks = df._to_dict_of_blocks()
         columns = []
-        for dtype, b in blocks.items():
+        for b in blocks.values():
             columns.extend(b.columns)
 
         asdict = {x: y for x, y in df.items()}

pandas/tests/frame/methods/test_to_dict_of_blocks.py

@@ -20,7 +20,7 @@ def test_copy_blocks(self, float_frame):
 
         # use the default copy=True, change a column
         blocks = df._to_dict_of_blocks(copy=True)
-        for dtype, _df in blocks.items():
+        for _df in blocks.values():
             if column in _df:
                 _df.loc[:, column] = _df[column] + 1
 
@@ -34,7 +34,7 @@ def test_no_copy_blocks(self, float_frame):
 
         # use the copy=False, change a column
         blocks = df._to_dict_of_blocks(copy=False)
-        for dtype, _df in blocks.items():
+        for _df in blocks.values():
             if column in _df:
                 _df.loc[:, column] = _df[column] + 1
 

pandas/tests/plotting/test_datetimelike.py

@@ -417,7 +417,7 @@ def test_finder_daily(self):
         xpl1 = xpl2 = [Period("1999-1-1", freq="B").ordinal] * len(day_lst)
         rs1 = []
         rs2 = []
-        for i, n in enumerate(day_lst):
+        for n in day_lst:
             rng = bdate_range("1999-1-1", periods=n)
             ser = Series(np.random.randn(len(rng)), rng)
             _, ax = self.plt.subplots()
@@ -439,7 +439,7 @@ def test_finder_quarterly(self):
         xpl1 = xpl2 = [Period("1988Q1").ordinal] * len(yrs)
         rs1 = []
         rs2 = []
-        for i, n in enumerate(yrs):
+        for n in yrs:
             rng = period_range("1987Q2", periods=int(n * 4), freq="Q")
             ser = Series(np.random.randn(len(rng)), rng)
             _, ax = self.plt.subplots()
@@ -461,7 +461,7 @@ def test_finder_monthly(self):
         xpl1 = xpl2 = [Period("Jan 1988").ordinal] * len(yrs)
         rs1 = []
         rs2 = []
-        for i, n in enumerate(yrs):
+        for n in yrs:
             rng = period_range("1987Q2", periods=int(n * 12), freq="M")
             ser = Series(np.random.randn(len(rng)), rng)
             _, ax = self.plt.subplots()
@@ -491,7 +491,7 @@ def test_finder_annual(self):
         xp = [1987, 1988, 1990, 1990, 1995, 2020, 2070, 2170]
         xp = [Period(x, freq="A").ordinal for x in xp]
         rs = []
-        for i, nyears in enumerate([5, 10, 19, 49, 99, 199, 599, 1001]):
+        for nyears in [5, 10, 19, 49, 99, 199, 599, 1001]:
             rng = period_range("1987", periods=nyears, freq="A")
             ser = Series(np.random.randn(len(rng)), rng)
             _, ax = self.plt.subplots()

pandas/tests/scalar/period/test_period.py

@@ -646,7 +646,7 @@ def _ex(p):
                 return p.start_time + Timedelta(days=1, nanoseconds=-1)
             return Timestamp((p + p.freq).start_time.value - 1)
 
-        for i, fcode in enumerate(from_lst):
+        for fcode in from_lst:
             p = Period("1982", freq=fcode)
             result = p.to_timestamp().to_period(fcode)
             assert result == p

scripts/validate_docstrings.py

@@ -223,7 +223,7 @@ def pandas_validate(func_name: str):
         )
 
     if doc.see_also:
-        for rel_name, rel_desc in doc.see_also.items():
+        for rel_name in doc.see_also:
             if rel_name.startswith("pandas."):
                 result["errors"].append(
                     pandas_error(