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# skfolio.distribution.plot_tail_concentration

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### skfolio.distribution.plot_tail_concentration(tail_concentration_dict, quantiles, title='Empirical Tail Dependencies', smoothing=0.5)

Plot the empirical tail concentration curves.

This function takes a dictionary where keys are dataset names and values are the
corresponding tail concentration arrays computed at the given quantiles. It then
creates a Plotly figure with the tail concentration curves. The x-axis (quantiles)
and y-axis (tail concentration) are both formatted as percentages.

* **Parameters:**
  **tail_concentration_dict** *dict[str, ArrayLike]*
  : A dictionary mapping dataset names to their tail concentration values.

  **quantiles** *array-like of shape (n_quantiles,)*
  : The quantile levels at which the tail concentration has been computed.

  **title** *str, default=”Empirical Tail Dependencies”*
  : The title for the plot.

  **smoothing** *float or None, default=0.5*
  : Smoothing parameter for the spline line shape. If provided, the curves will be
    smoothed using a spline interpolation.
* **Returns:**
  **fig** *go.Figure*
  : A Plotly figure object containing the tail concentration curves.
* **Raises:**
  ValueError
  : If the smoothing parameter is not in the allowed range.