Fixes

Author: MartinBraquet

pandas/_typing.py

@@ -416,8 +416,8 @@ def closed(self) -> bool:
 SortKind: TypeAlias = Literal["quicksort", "mergesort", "heapsort", "stable"]
 NaPosition: TypeAlias = Literal["first", "last"]
 
-# Arguments for nsorted, nsmallest and nlargest.
-NsmallestNlargestKeep = Literal["first", "last", "all"]
+# Arguments for nsorted, nsmallest and nlargest
+NsmallestNlargestKeep: TypeAlias = Literal["first", "last", "all"]
 
 # quantile interpolation
 QuantileInterpolation: TypeAlias = Literal[

pandas/core/frame.py

@@ -7747,9 +7747,6 @@ def nlargest(
         descending order. The columns that are not specified are returned as
         well, but not used for ordering.
 
-        This method is equivalent to
-        ``df.nsorted(n, columns, ascending=False)``.
-
         This method is equivalent to
         ``df.sort_values(columns, ascending=False).head(n)``, but more
         performant.
@@ -7891,9 +7888,6 @@ def nsmallest(
         ascending order. The columns that are not specified are returned as
         well, but not used for ordering.
 
-        This method is equivalent to
-        ``df.nsorted(n, columns, ascending=True)``.
-
         This method is equivalent to
         ``df.sort_values(columns, ascending=True).head(n)``, but more
         performant.

pandas/core/methods/selectn.py

@@ -115,7 +115,7 @@ def compute(self, ascending: bool | Sequence[bool]) -> Series:
         n = self.n
         dtype = self.obj.dtype
         if not self.is_valid_dtype_n_method(dtype):
-            raise TypeError(f"Cannot use n-sorting with dtype {dtype}")
+            raise TypeError(f"Cannot sort with dtype {dtype}")
 
         if n <= 0:
             return self.obj[[]]