bebi103.viz.confints

bebi103.viz.confints(summaries, p=None, marker_kwargs=None, line_kwargs=None, palette=None, **kwargs)

Make a horizontal plot of centers/conf ints with error bars.

Parameters

• summaries (list of dicts) – Each entry in summaries is a dictionary containing minimally keys ‘estimate’, ‘conf_int’, and ‘label’. The ‘estimate’ value is the point estimate, a single scalar. The ‘conf_int’ value is a two-tuple, two-list, or two-numpy array containing the low and high end of the confidence interval for the estimate. The ‘label’ value is the name of the variable. This gives the label of the y-ticks.

• p (bokeh.plotting.Figure instance or None, default None) – If not None, a figure to be populated with confidence interval plot. If specified, it is important that p.y_range be set to contain all of the values in the labels provided in the summaries input. If p is None, then a new figure is created.

• marker_kwargs (dict, default None) – Kwargs to be passed to p.circle() for plotting estimates.

• line_kwargs (dict, default None) – Kwargs passsed to p.line() to plot the confidence interval.

• palette (list, str, or None) – If None, default colors (or those given in marker_kwargs and line_kwargs are used). If a str, all glyphs are colored accordingly, e.g., ‘black’. Otherwise a list of colors is used.

• kwargs (dict) – Any additional kwargs are passed to bokeh.plotting.figure().

Returns

output – Plot of error bars.

Return type

Bokeh figure