I'm trying to hide an index level from a pandas Styler with pandas 1.3.5. i.e. to replicate the behavior of hide(axis="index", level="level_name") in pandas 1.4.

Here is a minimale example of what I'm trying :

def multi_highlighter(row, range_colors):
    def find_color(value):
        for color, threshold in range_colors.items():
            if value < threshold:
                return color
        return "white"

    return [f"background-color: {find_color(v)}" for v in row]

range_colors = {"red": 18, "orange": 100}

data = pd.DataFrame({
    "Ex Date": ['2022-06-20', '2022-06-20', '2022-06-20', '2022-06-20', '2022-06-20', '2022-06-20', '2022-07-30', '2022-07-30', '2022-07-30'], 
    "Portfolio": ['UUU-SSS', 'UUU-SSS', 'UUU-SSS', 'RRR-DDD', 'RRR-DDD', 'RRR-DDD', 'KKK-VVV', 'KKK-VVV', 'KKK-VVV'],
    "Position": [120, 90, 110, 113, 111, 92, 104, 110, 110],
    "Strike": [18, 18, 19, 19, 20, 20, 15, 18, 19],
    })
(
    data
    .reset_index()
    .set_index(["Ex Date", "Portfolio", "index"])
    .style
    .apply(multi_highlighter, range_colors=range_colors, axis=1)
)

Adding some borders, it produces the following table:

Now to hide the "index" index level, I tried to achieve this by adding CSS styling from this

CodePudding user response：

There are a few options in pandas 1.3.5, though this is a non-trivial operation without the use of the hide function available in 1.4.0.

Removing Index Levels >= 1

nth-child is not working here due to the use of rowspans in the MultiIndex. However, we can take advantage of the default CSS classes that are added by the Styler (

Removing Index level 0

If trying to remove level0 we only need to hide level0:

hide_column_styles = [
    {
        # Remove all values associated with level0 (including the first header row)
        'selector': f'th.level0:not(.col_heading)',
        'props': [('display', 'none')]
    }
]

The first index column will have the class .level0 and be hidden without needing an additional selector:

<tr>
  <th >&nbsp;</th>
  <th >&nbsp;</th>
  <th >&nbsp;</th> <!-- This will match and be hidden -->
  <th >Position</th>
  <th >Strike</th>
</tr>

Hiding levels that do not affect MultiIndex Uniqueness

If the index levels would remain unique after removing a level it is possible just to

If a level is dropped causing a non-unique MultiIndex (like level 2) a KeyError will occur when using Styler.apply or Styler.applymap:

KeyError: 'Styler.apply and .applymap are not compatible with non-unique index or columns.'

Pandas 1.4.0 and newer

Just to be super clear for any future readers of this question, this is a workaround for versions prior to 1.4.0. It is much simpler to use the