MMMSummaryFactory.channel_share_hdi#

MMMSummaryFactory.channel_share_hdi(hdi_probs=None, dims=None, original_scale=True, output_format=None)[source]#

Create channel share of total contribution summary DataFrame.

Parameters:
hdi_probssequence of float, optional

HDI probability levels (default: uses factory default)

dimsdict, optional

Dimension filters, e.g. {"geo": ["CA"]}.

original_scalebool, default True

Whether to use original-scale channel contributions.

output_format{“pandas”, “polars”}, optional

Output DataFrame format (default: uses factory default)

Returns:
pd.DataFrame or pl.DataFrame

Summary DataFrame with columns:

  • channel: Channel name

  • mean, median: Share point estimates

  • abs_error_{prob}_lower/upper: HDI bounds for each prob

  • <custom_dims>: One column per custom dimension when present