quantile_plot

hhpy.plotting.quantile_plot(x: Union[Sequence[T_co], str], data: pandas.core.frame.DataFrame = None, qs: Union[Sequence[T_co], float] = None, x2: str = None, hue: str = None, hue_order: Union[Sequence[T_co], str] = None, to_abs: bool = False, ax: matplotlib.axes._axes.Axes = None, **kwargs) → matplotlib.axes._axes.Axes

plots the specified quantiles of a Series using seaborn.barplot

Parameters:

• x – Name of the x variable in data or vector data
• data – Pandas DataFrame containing named data, optional if vector data is used
• qs – Quantile levels [optional]
• x2 – if specified: subtracts x2 from x before calculating quantiles [optional]
• hue – Further split the plot by the levels of this variable [optional]
• hue_order –

  Either a string describing how the (hue) levels or to be ordered or an explicit list of levels to be used for plotting. Accepted strings are:

  • sorted: following python standard sorting conventions (alphabetical for string, ascending for value)
  • inv: following python standard sorting conventions but in inverse order
  • count: sorted by value counts
  • mean, mean_ascending, mean_descending: sorted by mean value, defaults to descending
  • median, mean_ascending, median_descending: sorted by median value, defaults to descending
• to_abs – Whether to cast the values to absolute before proceeding [optional]
• ax – The matplotlib.pyplot.Axes object to plot on, defaults to current axis [optional]
• kwargs – other keyword arguments passed to seaborn.barplot

Returns:

The matplotlib.pyplot.Axes object with the plot on it