STYLE: fix some consider-using-enumerate pylint warnings

pandas/core/array_algos/take.py

@@ -549,13 +549,9 @@ def _take_2d_multi_object(
             out[row_mask, :] = fill_value
         if col_needs:
             out[:, col_mask] = fill_value
-    for i in range(len(row_idx)):
-        u_ = row_idx[i]
-
+    for i, u_ in enumerate(row_idx):
         if u_ != -1:
-            for j in range(len(col_idx)):
-                v = col_idx[j]
-
+            for j, v in enumerate(col_idx):
                 if v != -1:
                     out[i, j] = arr[u_, v]
 

pandas/core/arrays/interval.py

@@ -1438,11 +1438,11 @@ def __array__(self, dtype: NpDtype | None = None) -> np.ndarray:
         closed = self.closed
 
         result = np.empty(len(left), dtype=object)
-        for i in range(len(left)):
+        for i, left_value in enumerate(left):
             if mask[i]:
                 result[i] = np.nan
             else:
-                result[i] = Interval(left[i], right[i], closed)
+                result[i] = Interval(left_value, right[i], closed)
         return result
 
     def __arrow_array__(self, type=None):

pandas/core/frame.py

@@ -5762,11 +5762,11 @@ def _replace_columnwise(
         res = self if inplace else self.copy()
         ax = self.columns
 
-        for i in range(len(ax)):
-            if ax[i] in mapping:
+        for i, ax_value in enumerate(ax):
+            if ax_value in mapping:
                 ser = self.iloc[:, i]
 
-                target, value = mapping[ax[i]]
+                target, value = mapping[ax_value]
                 newobj = ser.replace(target, value, regex=regex)
 
                 res._iset_item(i, newobj)

pandas/core/groupby/groupby.py

@@ -2889,11 +2889,11 @@ def blk_func(values: ArrayLike) -> ArrayLike:
                 else:
                     out = type(values)._empty(values.shape, dtype=values.dtype)
 
-                for i in range(len(values)):
+                for i, value_element in enumerate(values):
                     # call group_fillna_indexer column-wise
                     indexer = np.empty(values.shape[1], dtype=np.intp)
                     col_func(out=indexer, mask=mask[i])
-                    out[i, :] = algorithms.take_nd(values[i], indexer)
+                    out[i, :] = algorithms.take_nd(value_element, indexer)
                 return out
 
         obj = self._obj_with_exclusions

pandas/core/reshape/merge.py

@@ -2152,12 +2152,12 @@ def _get_multiindex_indexer(
         rcodes = list(map(i8copy, index.codes))
 
     # fix right labels if there were any nulls
-    for i in range(len(join_keys)):
+    for i, join_key in enumerate(join_keys):
         mask = index.codes[i] == -1
         if mask.any():
             # check if there already was any nulls at this location
             # if there was, it is factorized to `shape[i] - 1`
-            a = join_keys[i][lcodes[i] == shape[i] - 1]
+            a = join_key[lcodes[i] == shape[i] - 1]
             if a.size == 0 or not a[0] != a[0]:
                 shape[i] += 1
 

pandas/core/reshape/reshape.py

@@ -424,8 +424,8 @@ def _unstack_multiple(data, clocs, fill_value=None):
     else:
         if isinstance(data.columns, MultiIndex):
             result = data
-            for i in range(len(clocs)):
-                val = clocs[i]
+            while clocs:
+                val = clocs.pop(0)
                 result = result.unstack(val, fill_value=fill_value)
                 clocs = [v if v < val else v - 1 for v in clocs]
 
@@ -634,20 +634,12 @@ def stack_multiple(frame, level, dropna: bool = True):
         # negative numbers to positive
         level = [frame.columns._get_level_number(lev) for lev in level]
 
-        # Can't iterate directly through level as we might need to change
-        # values as we go
-        for index in range(len(level)):
-            lev = level[index]
+        while level:
+            lev = level.pop(0)
             result = stack(result, lev, dropna=dropna)
             # Decrement all level numbers greater than current, as these
             # have now shifted down by one
-            updated_level = []
-            for other in level:
-                if other > lev:
-                    updated_level.append(other - 1)
-                else:
-                    updated_level.append(other)
-            level = updated_level
+            level = [v if v <= lev else v - 1 for v in level]
 
     else:
         raise ValueError(

pandas/io/formats/html.py

@@ -522,7 +522,7 @@ def _write_hierarchical_rows(
                     level_lengths[lnum] = rec_new
 
                 level_lengths[inner_lvl][ins_row] = 1
-                for ix_col in range(len(fmt_values)):
+                for ix_col in fmt_values:
                     fmt_values[ix_col].insert(ins_row, "...")
                 nrows += 1
 

pandas/io/formats/printing.py

@@ -426,17 +426,17 @@ def best_len(values: list[str]) -> int:
         summary = ""
         line = space2
 
-        for max_items in range(len(head)):
-            word = head[max_items] + sep + " "
+        for head_value in head:
+            word = head_value + sep + " "
             summary, line = _extend_line(summary, line, word, display_width, space2)
 
         if is_truncated:
             # remove trailing space of last line
             summary += line.rstrip() + space2 + "..."
             line = space2
 
-        for max_items in range(len(tail) - 1):
-            word = tail[max_items] + sep + " "
+        for tail_item in tail[:-1]:
+            word = tail_item + sep + " "
             summary, line = _extend_line(summary, line, word, display_width, space2)
 
         # last value: no sep added + 1 space of width used for trailing ','

pandas/tests/arrays/sparse/test_indexing.py

@@ -15,8 +15,8 @@
 class TestGetitem:
     def test_getitem(self):
         dense = arr.to_dense()
-        for i in range(len(arr)):
-            tm.assert_almost_equal(arr[i], dense[i])
+        for i, value in enumerate(arr):
+            tm.assert_almost_equal(value, dense[i])
             tm.assert_almost_equal(arr[-i], dense[-i])
 
     def test_getitem_arraylike_mask(self):

pandas/tests/frame/methods/test_replace.py

@@ -873,8 +873,8 @@ def test_replace_input_formats_listlike(self):
         values = [-2, -1, "missing"]
         result = df.replace(to_rep, values)
         expected = df.copy()
-        for i in range(len(to_rep)):
-            return_value = expected.replace(to_rep[i], values[i], inplace=True)
+        for rep, value in zip(to_rep, values):
+            return_value = expected.replace(rep, value, inplace=True)
             assert return_value is None
         tm.assert_frame_equal(result, expected)
 
@@ -901,8 +901,8 @@ def test_replace_input_formats_scalar(self):
         to_rep = [np.nan, 0, ""]
         result = df.replace(to_rep, -1)
         expected = df.copy()
-        for i in range(len(to_rep)):
-            return_value = expected.replace(to_rep[i], -1, inplace=True)
+        for rep in to_rep:
+            return_value = expected.replace(rep, -1, inplace=True)
             assert return_value is None
         tm.assert_frame_equal(result, expected)
 

pandas/tests/indexes/multi/test_indexing.py

@@ -884,9 +884,9 @@ def test_pyint_engine():
     # keys would collide; if truncating the last levels, the fifth and
     # sixth; if rotating bits rather than shifting, the third and fifth.
 
-    for idx in range(len(keys)):
+    for idx, key_value in enumerate(keys):
         index = MultiIndex.from_tuples(keys)
-        assert index.get_loc(keys[idx]) == idx
+        assert index.get_loc(key_value) == idx
 
         expected = np.arange(idx + 1, dtype=np.intp)
         result = index.get_indexer([keys[i] for i in expected])

pandas/tests/io/test_stata.py

@@ -774,15 +774,15 @@ def test_big_dates(self, datapath):
         mm = [0, 0, 59, 0, 0, 0]
         ss = [0, 0, 59, 0, 0, 0]
         expected = []
-        for i in range(len(yr)):
+        for year, month, day, hour, minute, second in zip(yr, mo, dd, hr, mm, ss):
             row = []
             for j in range(7):
                 if j == 0:
-                    row.append(datetime(yr[i], mo[i], dd[i], hr[i], mm[i], ss[i]))
+                    row.append(datetime(year, month, day, hour, minute, second))
                 elif j == 6:
-                    row.append(datetime(yr[i], 1, 1))
+                    row.append(datetime(year, 1, 1))
                 else:
-                    row.append(datetime(yr[i], mo[i], dd[i]))
+                    row.append(datetime(year, month, day))
             expected.append(row)
         expected.append([pd.NaT] * 7)
         columns = [

pandas/tests/series/indexing/test_setitem.py

@@ -578,7 +578,7 @@ def test_setitem_scalar_into_readonly_backing_data():
     array.flags.writeable = False  # make the array immutable
     series = Series(array)
 
-    for n in range(len(series)):
+    for n in series.index:
         msg = "assignment destination is read-only"
         with pytest.raises(ValueError, match=msg):
             series[n] = 1

pyproject.toml

@@ -81,7 +81,6 @@ disable = [
  # pylint type "C": convention, for programming standard violation
   "consider-iterating-dictionary",
   "consider-using-dict-items",
-  "consider-using-enumerate",
   "consider-using-f-string",
   "disallowed-name",
   "import-outside-toplevel",