Parameters data pandas.DataFrame, numpy.ndarray, mapping, or sequence The distinction between figure-level and axes-level functions is explainedįurther in the user guide. In-depth discussion of the relative strengths and weaknesses of each approach. See the distribution plots tutorial for a more Refer to the documentation for each to understand the complete set of options Histplot() (with kind='hist' the default)Įcdfplot() (with kind='ecdf' univariate-only)Īdditionally, a rugplot() can be added to any kind of plot to showĮxtra keyword arguments are passed to the underlying function, so you should Kind parameter selects the approach to use:
Univariate or bivariate distribution of data, including subsets of dataĭefined by semantic mapping and faceting across multiple subplots.
This function provides access to several approaches for visualizing the displot ( data = None, *, x = None, y = None, hue = None, row = None, col = None, weights = None, kind = 'hist', rug = False, rug_kws = None, log_scale = None, legend = True, palette = None, hue_order = None, hue_norm = None, color = None, col_wrap = None, row_order = None, col_order = None, height = 5, aspect = 1, facet_kws = None, ** kwargs ) ¶įigure-level interface for drawing distribution plots onto a FacetGrid.
