Skip to main content
`Ctrl`+`K`

# pandas.io.formats.style.Styler.highlight_between

Styler.highlight_between(subset=None, color='yellow', axis=0, left=None, right=None, inclusive='both', props=None)

  Highlight a defined range with a style.

  Added in version 1.3.0.

  Parameters:
    subsetlabel, array-like, IndexSlice, optional

      A valid 2d input to DataFrame.loc[<subset>], or, in the case of a 1d input or single key, to DataFrame.loc[:, <subset>] where the columns are prioritised, to limit `data` to before applying the function.

    colorstr, default ‘yellow’

      Background color to use for highlighting.

    axis{0 or ‘index’, 1 or ‘columns’, None}, default 0

      If `left` or `right` given as sequence, axis along which to apply those boundaries. See examples.

    leftscalar or datetime-like, or sequence or array-like, default None

      Left bound for defining the range.

    rightscalar or datetime-like, or sequence or array-like, default None

      Right bound for defining the range.

    inclusive{‘both’, ‘neither’, ‘left’, ‘right’}

      Identify whether bounds are closed or open.

    propsstr, default None

      CSS properties to use for highlighting. If `props` is given, `color` is not used.

  Returns:
    Styler

  See also

  `Styler.highlight_null`

    Highlight missing values with a style.

  `Styler.highlight_max`

    Highlight the maximum with a style.

  `Styler.highlight_min`

    Highlight the minimum with a style.

  `Styler.highlight_quantile`

    Highlight values defined by a quantile with a style.

  Notes

  If `left` is `None` only the right bound is applied. If `right` is `None` only the left bound is applied. If both are `None` all values are highlighted.

  `axis` is only needed if `left` or `right` are provided as a sequence or an array-like object for aligning the shapes. If `left` and `right` are both scalars then all `axis` inputs will give the same result.

  This function only works with compatible `dtypes`. For example a datetime-like region can only use equivalent datetime-like `left` and `right` arguments. Use `subset` to control regions which have multiple `dtypes`.

  Examples

  Basic usage

      >>> df = pd.DataFrame({
      ...     'One': [1.2, 1.6, 1.5],
      ...     'Two': [2.9, 2.1, 2.5],
      ...     'Three': [3.1, 3.2, 3.8],
      ... })
      >>> df.style.highlight_between(left=2.1, right=2.9)

  Using a range input sequence along an `axis`, in this case setting a `left` and `right` for each column individually

      >>> df.style.highlight_between(left=[1.4, 2.4, 3.4], right=[1.6, 2.6, 3.6],
      ...     axis=1, color="#fffd75")

  Using `axis=None` and providing the `left` argument as an array that matches the input DataFrame, with a constant `right`

      >>> df.style.highlight_between(left=[[2,2,3],[2,2,3],[3,3,3]], right=3.5,
      ...     axis=None, color="#fffd75")

  Using `props` instead of default background coloring

      >>> df.style.highlight_between(left=1.5, right=3.5,
      ...     props='font-weight:bold;color:#e83e8c')