explore_scatter_plot

source

explore_scatter_plot(
    df,
    x=None,
    y=None,
    *,
    color=None,
    size=None,
    loess=0,
    alpha=None,
    entity=None,
    time=None,
    connect=False,
    title=None,
    subtitle=None,
)

Scatter plot of y against x with optional aesthetics and a LOESS smoother.

Parameters

Name	Type	Description	Default
df	pd.DataFrame	Data frame containing the variables.	required
x	str \| None	Column names for the axes (both must be numeric). 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	Column names for the axes (both must be numeric). When omitted, they default to the declared roles (:func:`expdpy.set_roles`): `x` to the first covariate and `y` to the main outcome.	`None`
color	str \| None	Optional column mapped to marker color (numeric -> colorbar, otherwise discrete).	`None`
size	str \| None	Optional numeric column mapped to marker size.	`None`
loess	Literal[0, 1, 2]	`0` no smoother, `1` unweighted LOESS, `2` LOESS weighted by `size`.	`0`
alpha	float \| None	Marker opacity. If `None`, a sample-size-based default is used.	`None`
entity	str \| None	Cross-sectional (unit) identifier. Defaults to the panel `entity` declared via :func:`expdpy.set_panel`. Only used when `connect=True`.	`None`
time	str \| None	Time identifier used to order each unit’s trajectory when `connect=True`. Defaults to the panel `time`.	`None`
connect	bool	If `True` (and an `entity` is available), draw a faint line connecting each unit’s points in time order — turning the scatter into a panel trajectory plot.	`False`

Returns

Name	Type	Description
	ScatterPlotResult	`df` (the complete-case frame plotted) and `fig` (the Plotly scatter).

Examples

Basic — a plain scatter of two variables:

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(df, x="log_gdp_pc", y="gini_regional").fig

Advanced — map color and marker size to other columns, add a size-weighted LOESS smoother (the N-shaped Kuznets curve) and tune opacity:

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(
    df, x="log_gdp_pc", y="gini_regional",
    color="continent", size="population", loess=2, alpha=0.6,
).fig