parameters: (self, subset: Subset | None = None)
return_statement: return self
docstring: Hide the entire index, or specific keys in the index from rendering.
  
          This method has dual functionality:
  
            - if ``subset`` is ``None`` then the entire index will be hidden whilst
              displaying all data-rows.
            - if a ``subset`` is given then those specific rows will be hidden whilst the
              index itself remains visible.
  
          .. versionchanged:: 1.3.0
  
          Parameters
          ----------
          subset : label, array-like, IndexSlice, optional
              A valid 1d input or single key along the index axis within
              `DataFrame.loc[<subset>, :]`, to limit ``data`` to *before* applying
              the function.
  
          Returns
          -------
          self : Styler
  
          See Also
          --------
          Styler.hide_columns: Hide the entire column headers row, or specific columns.
  
          Examples
          --------
          Simple application hiding specific rows:
  
          >>> df = pd.DataFrame([[1,2], [3,4], [5,6]], index=["a", "b", "c"])
          >>> df.style.hide_index(["a", "b"])
               0    1
          c    5    6
  
          Hide the index and retain the data values:
  
          >>> midx = pd.MultiIndex.from_product([["x", "y"], ["a", "b", "c"]])
          >>> df = pd.DataFrame(np.random.randn(6,6), index=midx, columns=midx)
          >>> df.style.format("{:.1f}").hide_index()
                           x                    y
             a      b      c      a      b      c
           0.1    0.0    0.4    1.3    0.6   -1.4
           0.7    1.0    1.3    1.5   -0.0   -0.2
           1.4   -0.8    1.6   -0.2   -0.4   -0.3
           0.4    1.0   -0.2   -0.8   -1.2    1.1
          -0.6    1.2    1.8    1.9    0.3    0.3
           0.8    0.5   -0.3    1.2    2.2   -0.8
  
          Hide specific rows but retain the index:
  
          >>> df.style.format("{:.1f}").hide_index(subset=(slice(None), ["a", "c"]))
                                   x                    y
                     a      b      c      a      b      c
          x   b    0.7    1.0    1.3    1.5   -0.0   -0.2
          y   b   -0.6    1.2    1.8    1.9    0.3    0.3
  
          Hide specific rows and the index:
  
          >>> df.style.format("{:.1f}").hide_index(subset=(slice(None), ["a", "c"]))
          ...     .hide_index()
                           x                    y
             a      b      c      a      b      c
           0.7    1.0    1.3    1.5   -0.0   -0.2
          -0.6    1.2    1.8    1.9    0.3    0.3
docstring_summary: Hide the entire index, or specific keys in the index from rendering.
docstring_tokens: Hide the entire index or specific keys in the index from rendering .
function: def hide_index(self, subset: Subset | None = None) -> Styler:
          """
          Hide the entire index, or specific keys in the index from rendering.
  
          This method has dual functionality:
  
            - if ``subset`` is ``None`` then the entire index will be hidden whilst
              displaying all data-rows.
            - if a ``subset`` is given then those specific rows will be hidden whilst the
              index itself remains visible.
  
          .. versionchanged:: 1.3.0
  
          Parameters
          ----------
          subset : label, array-like, IndexSlice, optional
              A valid 1d input or single key along the index axis within
              `DataFrame.loc[<subset>, :]`, to limit ``data`` to *before* applying
              the function.
  
          Returns
          -------
          self : Styler
  
          See Also
          --------
          Styler.hide_columns: Hide the entire column headers row, or specific columns.
  
          Examples
          --------
          Simple application hiding specific rows:
  
          >>> df = pd.DataFrame([[1,2], [3,4], [5,6]], index=["a", "b", "c"])
          >>> df.style.hide_index(["a", "b"])
               0    1
          c    5    6
  
          Hide the index and retain the data values:
  
          >>> midx = pd.MultiIndex.from_product([["x", "y"], ["a", "b", "c"]])
          >>> df = pd.DataFrame(np.random.randn(6,6), index=midx, columns=midx)
          >>> df.style.format("{:.1f}").hide_index()
                           x                    y
             a      b      c      a      b      c
           0.1    0.0    0.4    1.3    0.6   -1.4
           0.7    1.0    1.3    1.5   -0.0   -0.2
           1.4   -0.8    1.6   -0.2   -0.4   -0.3
           0.4    1.0   -0.2   -0.8   -1.2    1.1
          -0.6    1.2    1.8    1.9    0.3    0.3
           0.8    0.5   -0.3    1.2    2.2   -0.8
  
          Hide specific rows but retain the index:
  
          >>> df.style.format("{:.1f}").hide_index(subset=(slice(None), ["a", "c"]))
                                   x                    y
                     a      b      c      a      b      c
          x   b    0.7    1.0    1.3    1.5   -0.0   -0.2
          y   b   -0.6    1.2    1.8    1.9    0.3    0.3
  
          Hide specific rows and the index:
  
          >>> df.style.format("{:.1f}").hide_index(subset=(slice(None), ["a", "c"]))
          ...     .hide_index()
                           x                    y
             a      b      c      a      b      c
           0.7    1.0    1.3    1.5   -0.0   -0.2
          -0.6    1.2    1.8    1.9    0.3    0.3
          """
          if subset is None:
              self.hide_index_ = True
          else:
              subset_ = IndexSlice[subset, :]  # new var so mypy reads not Optional
              subset = non_reducing_slice(subset_)
              hide = self.data.loc[subset]
              hrows = self.index.get_indexer_for(hide.index)
              # error: Incompatible types in assignment (expression has type
              # "ndarray", variable has type "Sequence[int]")
              self.hidden_rows = hrows  # type: ignore[assignment]
          return self
function_tokens: def hide_index ( self , subset : Subset | None = None ) -> Styler : if subset is None : self . hide_index_ = True else : subset_ = IndexSlice [ subset , : ] # new var so mypy reads not Optional subset = non_reducing_slice ( subset_ ) hide = self . data . loc [ subset ] hrows = self . index . get_indexer_for ( hide . index ) # error: Incompatible types in assignment (expression has type # "ndarray", variable has type "Sequence[int]") self . hidden_rows = hrows # type: ignore[assignment] return self