explore_scatter_plot_within_between

source

explore_scatter_plot_within_between(
    df,
    x=None,
    y=None,
    *,
    entity=None,
    time=None,
    show='overlay',
    alpha=None,
    title=None,
    subtitle=None,
)

Scatter that decomposes the x-y relationship into between and within parts.

Three views are drawn (switchable via a dropdown): the pooled cloud, the between cloud of unit means, and the within cloud of unit-demeaned deviations (recentered on the grand means). Their fitted slopes show how a pooled association blends a cross-unit and an over-time relationship.

Parameters

Name	Type	Description	Default
df	pd.DataFrame	Panel data frame.	required
x	str \| None	Numeric column names for the axes. When omitted, they default to the declared roles (:func:`expdpy.set_roles`): `x` to the first covariate and `y` to the main outcome.	`None`
y	str \| None	Numeric column names for the axes. When omitted, they default to the declared roles (:func:`expdpy.set_roles`): `x` to the first covariate and `y` to the main outcome.	`None`
entity	str \| None	Cross-sectional (unit) identifier. Defaults to the panel `entity`.	`None`
time	str \| None	Time identifier (carried into the hover data). Defaults to the panel `time`.	`None`
show	Literal['overlay', 'pooled', 'between', 'within']	Which view is visible initially: `"overlay"` (all), `"pooled"`, `"between"` or `"within"`.	`'overlay'`
alpha	float \| None	Marker opacity for the pooled/within clouds. Defaults to a sample-size-based value.	`None`

Returns

Name	Type	Description
	WithinBetweenScatterResult	`df` (long plotted frame), `fig` and the three slopes `slope_pooled` / `slope_between` / `slope_within`.

Examples

import expdpy as ex
from expdpy.data import load_kuznets, load_kuznets_data_def

df = ex.set_labels(load_kuznets(), load_kuznets_data_def(), set_panel=True)
ex.explore_scatter_plot_within_between(
    df, x="log_gdp_pc", y="gini_regional"
).fig