explore_value_heatmap

source

explore_value_heatmap(
    df,
    var,
    *,
    entity=None,
    time=None,
    standardize='none',
    aggfunc='mean',
    max_units=200,
    sort_by='mean',
    title=None,
    subtitle=None,
)

Heatmap of a variable over the unit-by-time grid (units by periods, colour = value).

Parameters

Name	Type	Description	Default
df	pd.DataFrame	Panel data frame.	required
var	str	Numeric variable to display.	required
entity	str | None	Cross-sectional (unit) identifier. Defaults to the panel entity.	None
time	str | None	Time identifier. Defaults to the panel time.	None
standardize	Literal['none', 'by_time', 'by_entity', 'global']	"none" shows raw values; "global" z-scores over all cells; "by_time" / "by_entity" z-score within each period / unit (revealing relative position).	'none'
aggfunc	str	Aggregator for duplicate (entity, time) cells (default "mean").	'mean'
max_units	int | None	Cap on the number of units drawn (evenly sampled above it).	200
sort_by	Literal['mean', 'first_value', 'label']	Row order: by "mean" (default, descending), "first_value" or "label".	'mean'

Returns

Name	Type	Description
	ValueHeatmapResult	df (the unit-by-time pivot) 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_value_heatmap(df, var="gini_regional", standardize="by_time").fig