Analysis

Plotting

plotting.score_plot(data[, pipelines, ...])	Plot scores for all pipelines and all datasets
plotting.paired_plot(data, alg1, alg2)	Generate a figure with a paired plot.
plotting.summary_plot(sig_df, effect_df[, ...])	Significance matrix to compare pipelines.
plotting.meta_analysis_plot(stats_df, alg1, alg2)	Meta-analysis to compare two algorithms across several datasets.

Statistics

meta_analysis.find_significant_differences(df)	Compute differences between pipelines across datasets.
meta_analysis.compute_dataset_statistics(df)	Compute meta-analysis statistics from results dataframe.
meta_analysis.combine_effects(effects, nsubs)	Combine effects for meta-analysis statistics.
meta_analysis.combine_pvalues(p, nsubs)	Combine p-values for meta-analysis statistics.
meta_analysis.collapse_session_scores(df)	Prepare results dataframe for computing statistics.