REF: remove unnecessary IntervalIndex._format_native_types (#55416)

* REF: make _format_with_header keyword-only

* REF: remove IntervalIndex._format_native_types

Author: jbrockmendel

pandas/core/indexes/base.py

@@ -1390,9 +1390,9 @@ def format(
         if formatter is not None:
             return header + list(self.map(formatter))
 
-        return self._format_with_header(header, na_rep=na_rep)
+        return self._format_with_header(header=header, na_rep=na_rep)
 
-    def _format_with_header(self, header: list[str_t], na_rep: str_t) -> list[str_t]:
+    def _format_with_header(self, *, header: list[str_t], na_rep: str_t) -> list[str_t]:
         from pandas.io.formats.format import format_array
 
         values = self._values

pandas/core/indexes/category.py

@@ -356,7 +356,7 @@ def _format_attrs(self):
         extra = super()._format_attrs()
         return attrs + extra
 
-    def _format_with_header(self, header: list[str], na_rep: str) -> list[str]:
+    def _format_with_header(self, *, header: list[str], na_rep: str) -> list[str]:
         result = [
             pprint_thing(x, escape_chars=("\t", "\r", "\n")) if notna(x) else na_rep
             for x in self._values

pandas/core/indexes/datetimelike.py

@@ -209,10 +209,12 @@ def format(
         if formatter is not None:
             return header + list(self.map(formatter))
 
-        return self._format_with_header(header, na_rep=na_rep, date_format=date_format)
+        return self._format_with_header(
+            header=header, na_rep=na_rep, date_format=date_format
+        )
 
     def _format_with_header(
-        self, header: list[str], na_rep: str = "NaT", date_format: str | None = None
+        self, *, header: list[str], na_rep: str, date_format: str | None = None
     ) -> list[str]:
         # matches base class except for whitespace padding and date_format
         return header + list(

pandas/core/indexes/interval.py

@@ -846,16 +846,10 @@ def length(self) -> Index:
     # Rendering Methods
     # __repr__ associated methods are based on MultiIndex
 
-    def _format_with_header(self, header: list[str], na_rep: str) -> list[str]:
+    def _format_with_header(self, *, header: list[str], na_rep: str) -> list[str]:
         # matches base class except for whitespace padding
         return header + list(self._format_native_types(na_rep=na_rep))
 
-    def _format_native_types(
-        self, *, na_rep: str = "NaN", quoting=None, **kwargs
-    ) -> npt.NDArray[np.object_]:
-        # GH 28210: use base method but with different default na_rep
-        return super()._format_native_types(na_rep=na_rep, quoting=quoting, **kwargs)
-
     def _format_data(self, name=None) -> str:
         # TODO: integrate with categorical and make generic
         # name argument is unused here; just for compat with base / categorical

pandas/core/indexes/range.py

@@ -266,7 +266,7 @@ def _format_data(self, name=None):
         # we are formatting thru the attributes
         return None
 
-    def _format_with_header(self, header: list[str], na_rep: str) -> list[str]:
+    def _format_with_header(self, *, header: list[str], na_rep: str) -> list[str]:
         # Equivalent to Index implementation, but faster
         if not len(self._range):
             return header

pandas/tests/indexes/interval/test_formats.py

@@ -104,7 +104,7 @@ def test_repr_floats(self):
     def test_to_native_types(self, tuples, closed, expected_data):
         # GH 28210
         index = IntervalIndex.from_tuples(tuples, closed=closed)
-        result = index._format_native_types()
+        result = index._format_native_types(na_rep="NaN")
         expected = np.array(expected_data)
         tm.assert_numpy_array_equal(result, expected)