MMMPlotlyFactory.contributions

MMMPlotlyFactory.contributions(hdi_prob=0.94, component='channel', frequency=None, round_digits=0, auto_facet=True, single_dim_facet='col', **plotly_kwargs)

Plot contributions bar chart with optional error bars and faceting.

Creates an interactive Plotly bar chart showing contributions from channels, controls, seasonality, or baseline. Automatically applies faceting for multi-dimensional MMM models.

Parameters:

hdi_probfloat, optional

HDI probability for error bars (default: 0.94). If None, no error bars.

component{“channel”, “control”, “seasonality”, “baseline”}

Which contribution component to plot (default: “channel”)

frequencystr, optional

Time aggregation (e.g., “monthly”, “all_time”). None = no aggregation.

round_digitsint, default 0

Number of decimal places for rounding values in hover text.

auto_facetbool, default True

Automatically detect and apply faceting for custom dimensions.

single_dim_facet{“col”, “row”}, default “col”

When auto_facet is enabled and there is exactly one custom dimension, this controls whether it is applied as facet_col or facet_row.

**plotly_kwargs

Additional Plotly Express arguments including: - title: Figure title (default: “{Component} Contributions”) - facet_row: Column for row facets (e.g., “country”) - facet_col: Column for column facets (e.g., “brand”) - facet_col_wrap: Max columns before wrapping - barmode: “group” (side-by-side) or “stack”

Returns:

go.Figure

Interactive Plotly figure

Examples

>>> # Basic channel contributions
>>> fig = mmm.plot_interactive.contributions()
>>> fig.show()

>>> # Contributions by country (auto-faceted)
>>> fig = mmm.plot_interactive.contributions(facet_col="country")
>>> fig.show()

>>> # Control contributions with custom title
>>> fig = mmm.plot_interactive.contributions(
...     component="control", title="Control Variable Effects"
... )
>>> fig.show()