# pandas.io.formats.style.Styler.hide_columns

Styler.hide_columns(subset=None)

  Hide the column headers or specific keys in the columns from rendering.

  This method has dual functionality:

  > - if `subset` is `None` then the entire column headers row will be hidden whilst the data-values remain visible.

  > - if a `subset` is given then those specific columns, including the data-values will be hidden, whilst the column headers row remains visible.

  Changed in version 1.3.0.

  Parameters
    subset label, array-like, IndexSlice, optional

      A valid 1d input or single key along the columns axis within DataFrame.loc[:, <subset>], to limit `data` to before applying the function.

  Returns
    self Styler

  See also

  `Styler.hide_index`

    Hide the entire index, or specific keys in the index.

  Examples

  Simple application hiding specific columns:

      >>> df = pd.DataFrame([[1, 2, 3], [4, 5, 6]], columns=["a", "b", "c"])
      >>> df.style.hide_columns(["a", "b"])
           c
      0    3
      1    6

  Hide column headers 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_columns()
      x   d    0.1    0.0    0.4    1.3    0.6   -1.4
          e    0.7    1.0    1.3    1.5   -0.0   -0.2
          f    1.4   -0.8    1.6   -0.2   -0.4   -0.3
      y   d    0.4    1.0   -0.2   -0.8   -1.2    1.1
          e   -0.6    1.2    1.8    1.9    0.3    0.3
          f    0.8    0.5   -0.3    1.2    2.2   -0.8

  Hide specific columns but retain the column headers:

      >>> df.style.format("{:.1f}").hide_columns(subset=(slice(None), ["a", "c"]))
                 x      y
                 b      b
      x   a    0.0    0.6
          b    1.0   -0.0
          c   -0.8   -0.4
      y   a    1.0   -1.2
          b    1.2    0.3
          c    0.5    2.2

  Hide specific columns and the column headers:

      >>> df.style.format("{:.1f}").hide_columns(subset=(slice(None), ["a", "c"]))
      ...     .hide_columns()
      x   a    0.0    0.6
          b    1.0   -0.0
          c   -0.8   -0.4
      y   a    1.0   -1.2
          b    1.2    0.3
          c    0.5    2.2