analyze_panel_view

source

analyze_panel_view(
    df,
    *,
    unit=None,
    time=None,
    treat=None,
    cohort=None,
    outcome=None,
    never_treated_value=0,
    sort_by_timing=True,
    max_units=200,
    title=None,
)

Visualize the treatment structure of a panel (a themed panelview).

Provide either a binary treat column or a first-treatment cohort column (from which the indicator is derived). With outcome given, plots each unit’s outcome over time instead of the treatment quilt.

Parameters

Name	Type	Description	Default
df	pd.DataFrame	Long panel data frame.	required
unit	str \| None	Unit and time identifiers. Default to the declared panel entity and time.	`None`
time	str \| None	Unit and time identifiers. Default to the declared panel entity and time.	`None`
treat	str \| None	Binary (0/1) treatment-status column.	`None`
cohort	str \| None	First-treated period column (used to derive `treat` when `treat` is omitted).	`None`
outcome	str \| None	If given, draw an outcome-over-time line per unit instead of the treatment quilt.	`None`
never_treated_value	int	Value of `cohort` marking never-treated units (default `0`).	`0`
sort_by_timing	bool	Order units by their first treated period (clearest staggered-adoption picture).	`True`
max_units	int \| None	Cap the number of units shown (an even spread is sampled when there are more).	`200`
title	str \| None	Optional figure title.	`None`

Returns

Name	Type	Description
	PanelViewResult	`df` (the treatment quilt, or the tidy outcome frame) and `fig`.

Examples

Basic — the staggered-adoption treatment quilt (derived from cohort):

import expdpy as ex
from expdpy.data import load_staggered_did, load_staggered_did_data_def

df = ex.set_labels(
    load_staggered_did(), load_staggered_did_data_def(), set_panel=True
)
# Panel is declared, so unit=/time= are resolved automatically.
ex.analyze_panel_view(df, cohort="cohort").fig

Advanced — outcome trajectories per unit instead of the treatment quilt:

import expdpy as ex
from expdpy.data import load_staggered_did, load_staggered_did_data_def

df = ex.set_labels(
    load_staggered_did(), load_staggered_did_data_def(), set_panel=True
)
ex.analyze_panel_view(df, cohort="cohort", outcome="outcome").fig