Use step

pandas/_libs/lib.pyi

@@ -231,7 +231,7 @@ def is_range_indexer(
     left: np.ndarray,
     n: int,  # np.ndarray[np.int64, ndim=1]
 ) -> bool: ...
-def is_range(
+def is_sequence_range(
     sequence: np.ndarray,
-    diff: int,  # np.ndarray[np.int64, ndim=1]
+    step: int,  # np.ndarray[np.int64, ndim=1]
 ) -> bool: ...

pandas/_libs/lib.pyx

@@ -680,19 +680,19 @@ def is_range_indexer(ndarray[int6432_t, ndim=1] left, Py_ssize_t n) -> bool:
 
 @cython.wraparound(False)
 @cython.boundscheck(False)
-def is_range(ndarray[int6432_t, ndim=1] sequence, int64_t diff) -> bool:
+def is_sequence_range(ndarray[intp_t, ndim=1] sequence, int64_t step) -> bool:
     """
-    Check if sequence is equivalent to a range with the specified diff.
+    Check if sequence is equivalent to a range with the specified step.
     """
     cdef:
         Py_ssize_t i, n = len(sequence)
 
-    if diff == 0:
+    if step == 0:
         return False
 
     for i in range(n):
 
-        if sequence[i] != sequence[0] + i * diff:
+        if sequence[i] != sequence[0] + i * step:
             return False
 
     return True

pandas/core/indexes/range.py

@@ -482,7 +482,7 @@ def _shallow_copy(self, values, name: Hashable = no_default):
                 new_range = range(start, start + self.step, self.step)
                 return type(self)._simple_new(new_range, name=name)
             diff = values[1] - values[0]
-            if not missing.isna(diff) and lib.is_range(values, diff):
+            if not missing.isna(diff) and lib.is_sequence_range(values, diff):
                 new_range = range(values[0], values[-1] + diff, diff)
                 return type(self)._simple_new(new_range, name=name)
         return self._constructor._simple_new(values, name=name)