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meridian.model.eda.meridian_eda.MeridianEDA

Handles EDA report generation and visualization for a Meridian model.

meridian.model.eda.meridian_eda.MeridianEDA(
    meridian: model.Meridian,
    *,
    n_draws_prior: int = eda_constants.DEFAULT_PRIOR_N_DRAW,
    seed: int = eda_constants.DEFAULT_PRIOR_SEED
)

Args
`meridian`	Meridian object.
`n_draws_prior`	Number of draws for prior distribution check. Only used if no prior samples exist in `meridian.inference_data`.
`seed`	Seed for prior distribution check. Only used if no prior samples exist in `meridian.inference_data`.

Attributes
`critical_outcomes`
`eda_engine`
`geo_cost_per_media_unit_check_outcome`
`geo_pairwise_correlation_check_outcome`
`geo_stdev_check_outcome`
`national_cost_per_media_unit_check_outcome`
`national_pairwise_correlation_check_outcome`
`national_stdev_check_outcome`

Methods

`generate_and_save_report`

View source

generate_and_save_report(
    filename: str, filepath: str
) -> None

Generates and saves a HTML report containing EDA findings.

Args
`filename`	The filename for the generated HTML output.
`filepath`	The path to the directory where the file will be saved.

`plot_calibration`

View source

plot_calibration(
    channel_name: (str | None) = None,
    limit_channels: (int | None) = None,
    limit_experiments: (int | None) = None,
    sort_channels: bool = True,
    sort_experiments: bool = True
) -> (alt.Chart | None)

Plots the prior calibration comparison charts (1x2 subplots).

Args
`channel_name`	Optional name of a specific channel. If None, plots all calibrated channels.
`limit_channels`	Optional maximum number of channels to display (sorted by spend).
`limit_experiments`	Optional maximum number of experiments to display per channel (sorted by SE).
`sort_channels`	If True, ranks channels by total spend.
`sort_experiments`	If True, ranks experiments by adjusted SE (ascending).

Returns
An Altair Chart containing the calibration plots, or None if no calibrated priors exist in the model.

`plot_controls_and_non_media_boxplot`

View source

plot_controls_and_non_media_boxplot(
    geos: Geos = 1, max_vars: (int | None) = None
) -> alt.Chart

Plots the boxplots for controls and non-media treatments variation.

`plot_cost_per_media_unit_time_series`

View source

plot_cost_per_media_unit_time_series(
    geos: Geos = 1, channels: (Sequence[str] | None) = None
) -> alt.Chart

Plots cost per media unit time series for paid media channels.

Args
`geos`	The geos to plot.
`channels`	The channels to plot. If None, plots all channels.

Returns
The cost per media unit time series plot and the superimposed cost with media unit time series plot for each paid media channel.

`plot_experiment_adjustments`

View source

plot_experiment_adjustments(
    channel_name: (str | None) = None,
    limit_channels: (int | None) = None,
    limit_experiments: (int | None) = None,
    sort_channels: bool = True,
    sort_experiments: bool = True
) -> (alt.Chart | None)

Plots the step-by-step experiment adjustments errorbar grid.

Args
`channel_name`	Name of the specific channel to plot. Default is None. If None, plots all calibrated channels.
`limit_channels`	Optional maximum number of channels to display (sorted by spend).
`limit_experiments`	Optional maximum number of experiments to display per channel (sorted by Standard Error).
`sort_channels`	If True, ranks channels by total spend.
`sort_experiments`	If True, ranks experiments by adjusted Standard Error (ascending).

Returns
An Altair Chart containing the experiment adjustment errorbar grid, or None if no calibrated priors exist in the model.

`plot_kpi_boxplot`

View source

plot_kpi_boxplot(
    geos: Geos = 1
) -> alt.Chart

Plots the boxplot for KPI variation.

`plot_national_kpi_with_knots_time_series`

View source

plot_national_kpi_with_knots_time_series() -> alt.Chart

Plots the national scaled KPI with knots time series plot.

`plot_pairwise_correlation`

View source

plot_pairwise_correlation(
    geos: Geos = 1, max_vars: (int | None) = None
) -> alt.Chart

Plots the Pairwise Correlation data.

Args
`geos`	Defines which geos to plot. - int: The number of top geos to plot, ranked by population. - Sequence[str]: A specific sequence of geo names to plot. - 'nationalize': Aggregates all geos into a single national view. Defaults to 1 (plotting the top geo). If the data is already at a national level, this parameter is ignored and a national plot is generated.
`max_vars`	The maximum number of variables to include in the correlation heatmap. Variables are selected based on their absolute correlation values. If None, all variables are included.

Returns
Altair chart(s) of the Pairwise Correlation data.

Raises
`ValueError`	If `max_vars` is less than or equal to 1.

`plot_population_raw_media_correlation`

View source

plot_population_raw_media_correlation() -> alt.Chart

Plots Spearman correlation between population and raw media units.

Returns
A bar chart showing the correlation.

Raises
`eda_engine_module.GeoLevelCheckOnNationalModelError`	If the Meridian model is national.

`plot_population_treatment_correlation`

View source

plot_population_treatment_correlation() -> alt.Chart

Plots the Spearman correlation of population vs treatments or controls.

Returns
An Altair chart showing the correlation.

Raises
`eda_engine_module.GeoLevelCheckOnNationalModelError`	If the Meridian model is national.

`plot_prior_mean`

View source

plot_prior_mean() -> alt.Chart

Plots the prior mean of contribution by channel.

Returns
A bar chart showing the prior mean of contribution by channel.

`plot_relative_impression_share_barchart`

View source

plot_relative_impression_share_barchart(
    geos: Geos = 1, n_channels: (int | None) = None, ascending: bool = True
) -> alt.Chart

Plots a bar chart of the relative impression share per media channel.

Args
`geos`	The geos to plot.
`n_channels`	The number of channels to display by impression share. If None, displays all channels.
`ascending`	Whether to sort the channels in ascending order by impression share.

Returns
The bar chart of the relative impression share of each media channel.

`plot_relative_spend_share_barchart`

View source

plot_relative_spend_share_barchart(
    geos: Geos = 1, n_channels: (int | None) = None, ascending: bool = True
) -> alt.Chart

Plots a bar chart of the relative spend share per paid media channel.

Args
`geos`	The geos to plot.
`n_channels`	The number of channels to display by spend share. If None, displays all channels.
`ascending`	Whether to sort the channels in ascending order by spend share.

Returns
The bar chart of the relative spend share of each paid media channel.

`plot_treatments_without_non_media_boxplot`

View source

plot_treatments_without_non_media_boxplot(
    geos: Geos = 1, max_vars: (int | None) = None
) -> alt.Chart

Plots the boxplot for treatments variation, excluding non-media.

meridian.model.eda.meridian_eda.MeridianEDA Stay organized with collections Save and categorize content based on your preferences.

Args

Attributes

Methods

generate_and_save_report

plot_calibration

plot_controls_and_non_media_boxplot

plot_cost_per_media_unit_time_series

plot_experiment_adjustments

plot_kpi_boxplot

plot_national_kpi_with_knots_time_series

plot_pairwise_correlation

plot_population_raw_media_correlation

plot_population_treatment_correlation

plot_prior_mean

plot_relative_impression_share_barchart

plot_relative_spend_share_barchart

plot_treatments_without_non_media_boxplot

meridian.model.eda.meridian_eda.MeridianEDA

`generate_and_save_report`

`plot_calibration`

`plot_controls_and_non_media_boxplot`

`plot_cost_per_media_unit_time_series`

`plot_experiment_adjustments`

`plot_kpi_boxplot`

`plot_national_kpi_with_knots_time_series`

`plot_pairwise_correlation`

`plot_population_raw_media_correlation`

`plot_population_treatment_correlation`

`plot_prior_mean`

`plot_relative_impression_share_barchart`

`plot_relative_spend_share_barchart`

`plot_treatments_without_non_media_boxplot`