diff --git a/pandas/core/arrays/interval.py b/pandas/core/arrays/interval.py
index 58ade1ee935ec..b55a40f5488ea 100644
--- a/pandas/core/arrays/interval.py
+++ b/pandas/core/arrays/interval.py
@@ -1235,7 +1235,6 @@ def value_counts(self, dropna: bool = True) -> Series:
 
     def _format_data(self) -> str:
         # TODO: integrate with categorical and make generic
-        # name argument is unused here; just for compat with base / categorical
         n = len(self)
         max_seq_items = min((get_option("display.max_seq_items") or n) // 10, 10)
 
@@ -1266,19 +1265,12 @@ def _format_data(self) -> str:
         return summary
 
     def __repr__(self) -> str:
-        # the short repr has no trailing newline, while the truncated
-        # repr does. So we include a newline in our template, and strip
-        # any trailing newlines from format_object_summary
         data = self._format_data()
         class_name = f"<{type(self).__name__}>\n"
 
         template = f"{class_name}{data}\nLength: {len(self)}, dtype: {self.dtype}"
         return template
 
-    def _format_space(self) -> str:
-        space = " " * (len(type(self).__name__) + 1)
-        return f"\n{space}"
-
     # ---------------------------------------------------------------------
     # Vectorized Interval Properties/Attributes
 
diff --git a/pandas/core/indexes/base.py b/pandas/core/indexes/base.py
index 147113a1e505e..c3cab965041e0 100644
--- a/pandas/core/indexes/base.py
+++ b/pandas/core/indexes/base.py
@@ -1284,25 +1284,16 @@ def __repr__(self) -> str_t:
         klass_name = type(self).__name__
         data = self._format_data()
         attrs = self._format_attrs()
-        space = self._format_space()
         attrs_str = [f"{k}={v}" for k, v in attrs]
-        prepr = f",{space}".join(attrs_str)
+        prepr = ", ".join(attrs_str)
 
         # no data provided, just attributes
         if data is None:
+            # i.e. RangeIndex
             data = ""
 
         return f"{klass_name}({data}{prepr})"
 
-    def _format_space(self) -> str_t:
-        # using space here controls if the attributes
-        # are line separated or not (the default)
-
-        # max_seq_items = get_option('display.max_seq_items')
-        # if len(self) > max_seq_items:
-        #    space = "\n%s" % (' ' * (len(klass) + 1))
-        return " "
-
     @property
     def _formatter_func(self):
         """
@@ -1319,7 +1310,7 @@ def _format_data(self, name=None) -> str_t:
 
         if self.inferred_type == "string":
             is_justify = False
-        elif self.inferred_type == "categorical":
+        elif isinstance(self.dtype, CategoricalDtype):
             self = cast("CategoricalIndex", self)
             if is_object_dtype(self.categories.dtype):
                 is_justify = False
diff --git a/pandas/core/indexes/interval.py b/pandas/core/indexes/interval.py
index ae027ea68a525..209ac84869e85 100644
--- a/pandas/core/indexes/interval.py
+++ b/pandas/core/indexes/interval.py
@@ -844,17 +844,11 @@ 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]:
         # matches base class except for whitespace padding
         return header + list(self._format_native_types(na_rep=na_rep))
 
-    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
-        return f"{self._data._format_data()},{self._format_space()}"
-
     # --------------------------------------------------------------------
     # Set Operations