explore_distribution_over_time

source

explore_distribution_over_time(
    df,
    var,
    *,
    entity=None,
    time=None,
    style='ridgeline',
    bins=30,
    bandwidth=None,
    max_periods=24,
    title=None,
    subtitle=None,
)

Show how the distribution of var shifts across periods.

Parameters

Name	Type	Description	Default
df	pd.DataFrame	Panel data frame.	required
var	str	Numeric variable whose distribution is tracked.	required
entity	str \| None	Cross-sectional id (accepted for panel parity; the per-period distribution pools across units). Defaults to the panel `entity`.	`None`
time	str \| None	Time identifier. Defaults to the panel `time`.	`None`
style	Literal['ridgeline', 'animated_hist', 'animated_violin']	`"ridgeline"` (default; stacked per-period densities), `"animated_hist"` or `"animated_violin"` (Plotly animation over periods).	`'ridgeline'`
bins	int	Histogram bins (animated_hist and the KDE fallback).	`30`
bandwidth	float \| None	KDE bandwidth (`bw_method`) for the ridgeline; `None` uses Scott’s rule.	`None`
max_periods	int \| None	Cap on the number of periods drawn (evenly sampled above it).	`24`

Returns

Name	Type	Description
	DistributionOverTimeResult	`df` (the complete-case `(time, var)` frame) and the Plotly `fig`.

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_distribution_over_time(df, var="gini_regional").fig