explore_quantile_trend_plot

source

explore_quantile_trend_plot(
    df,
    quantiles=(0.05, 0.25, 0.5, 0.75, 0.95),
    var=None,
    *,
    time=None,
    points=True,
    title=None,
    subtitle=None,
)

Line-plot quantiles of a single variable over time.

Parameters

Name	Type	Description	Default
df	pd.DataFrame	Data frame containing `time` and the variable to plot.	required
quantiles	Sequence[float]	Quantile levels to plot (each in `(0, 1)`).	`(0.05, 0.25, 0.5, 0.75, 0.95)`
var	str \| None	Variable to plot. Defaults to the last numeric column that is not `time`.	`None`
time	str \| None	Column name of the time identifier. Defaults to the panel `time` declared via :func:`expdpy.set_panel`.	`None`
points	bool	Whether to mark each observation with a point.	`True`

Returns

Name	Type	Description
	QuantileTrendGraphResult	`df` (long format: `time`, `quantile`, value) and the Plotly `fig`.

Examples

Basic — the default quantiles of a variable over time:

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_quantile_trend_plot(df, var="log_gdp_pc").fig

Advanced — custom quantile levels and no per-observation points:

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_quantile_trend_plot(
    df, quantiles=(0.1, 0.5, 0.9), var="log_gdp_pc", points=False
).fig