fix style.ipynb, ignore some pylint

Author: mroeschke

doc/source/user_guide/style.ipynb

@@ -112,11 +112,9 @@ def grouped_min_max(
             continue
 
         if is_max:
-            if val > output[lab]:
-                output[lab] = val
+            output[lab] = max(val, output[lab])
         else:
-            if val < output[lab]:
-                output[lab] = val
+            output[lab] = min(val, output[lab])
 
     # Set labels that don't satisfy min_periods as np.nan
     for lab, count in enumerate(nobs):

pandas/core/_numba/kernels/min_max_.py

@@ -190,7 +190,7 @@ def __eq__(self, other: object) -> bool:
         # cannot be checked with normal `==`
         if isinstance(other, str):
             # TODO should dtype == "string" work for the NaN variant?
-            if other == "string" or other == self.name:  # noqa: PLR1714
+            if other == "string" or other == self.name:
                 return True
             try:
                 other = self.construct_from_string(other)

pandas/core/arrays/string_.py

@@ -683,9 +683,7 @@ def _maybe_promote(dtype: np.dtype, fill_value=np.nan):
 
         elif dtype.kind == "f":
             mst = np.min_scalar_type(fill_value)
-            if mst > dtype:
-                # e.g. mst is np.float64 and dtype is np.float32
-                dtype = mst
+            dtype = max(mst, dtype)
 
         elif dtype.kind == "c":
             mst = np.min_scalar_type(fill_value)
@@ -718,9 +716,7 @@ def _maybe_promote(dtype: np.dtype, fill_value=np.nan):
 
         elif dtype.kind == "c":
             mst = np.min_scalar_type(fill_value)
-            if mst > dtype:
-                # e.g. mst is np.complex128 and dtype is np.complex64
-                dtype = mst
+            dtype = max(mst, dtype)
 
     else:
         dtype = np.dtype(np.object_)

pandas/core/dtypes/cast.py

@@ -142,8 +142,7 @@ def get_sheet_data(
                         empty_cells = 0
                         table_row.extend([value] * column_repeat)
 
-            if max_row_len < len(table_row):
-                max_row_len = len(table_row)
+            max_row_len = max(max_row_len, len(table_row))
 
             row_repeat = self._get_row_repeat(sheet_row)
             if len(table_row) == 0:

pandas/io/excel/_odfreader.py

@@ -274,9 +274,7 @@ def test_numeric_arr_rdiv_tdscalar(self, three_days, numeric_idx, box_with_array
         expected = TimedeltaIndex(["3 Days", "36 Hours"])
         if isinstance(three_days, np.timedelta64):
             dtype = three_days.dtype
-            if dtype < np.dtype("m8[s]"):
-                # i.e. resolution is lower -> use lowest supported resolution
-                dtype = np.dtype("m8[s]")
+            dtype = max(dtype, np.dtype("m8[s]"))
             expected = expected.astype(dtype)
         elif type(three_days) is timedelta:
             expected = expected.astype("m8[us]")

pandas/tests/arithmetic/test_numeric.py

@@ -455,7 +455,7 @@ def test_insert_out_of_bounds(self, index, using_infer_string):
             msg = "slice indices must be integers or None or have an __index__ method"
 
         if using_infer_string and (
-            index.dtype == "string" or index.dtype == "category"  # noqa: PLR1714
+            index.dtype == "string" or index.dtype == "category"
         ):
             msg = "loc must be an integer between"
 

pandas/tests/indexes/test_old_base.py

@@ -341,8 +341,10 @@ ignore = [
   "RUF012",
   # type-comparison
   "E721",
-
-  # Additional pylint rules
+  # repeated-equality-comparison
+  "PLR1714",
+  # self-or-cls-assignment
+  "PLW0642",
   # literal-membership
   "PLR6201", # 847 errors
   # Method could be a function, class method, or static method