trevismd

with sns.plotting_context('notebook', font_scale = 1.4):
    # ... same as before

    # Add annotations
    annotator.new_plot(ax, pairs=pairs, **plotting_parameters)
    annotator.configure(test='Mann-Whitney', verbose=True).apply_and_annotate()

    # ... same as before

trevismd

states_palette = states_palette = sns.color_palette("YlGnBu", n_colors=5)
states_order = ["Successful", "Failed", "Live", "Suspended", "Canceled"]

trevismd

# Also disabling printed output as it is the same
annotator.configure(text_offset=3, verbose=0) 

trevismd

# Add annotations
annotator.new_plot(ax, **plotting_parameters)
annotator.configure(test_short_name="MWW")  # text_format is still simple
annotator.set_pvalues_and_annotate(pvalues)

trevismd

# Add annotations
annotator = Annotator(ax, pairs, **plotting_parameters)
annotator.configure(text_format="simple")
annotator.set_pvalues_and_annotate(pvalues)

trevismd

with sns.plotting_context("notebook", font_scale = 1.4):
    # ...Same as previous
    
    # Add annotations
    annotator = Annotator(ax, pairs, **plotting_parameters)
    annotator.set_pvalues(pvalues)
    annotator.annotate()

    # ... same as previous

trevismd

# Putting the parameters in a dictionary avoids code duplication
# since we use the same for `sns.boxplot` and `Annotator` calls
plotting_parameters = {
    'data':    rfs,
    'x':       'Subcategory',
    'y':       'Goal',
    'palette': subcat_palette[1:]
}

pairs = [('Robots', 'Flight'),

trevismd

annotator.annotate()

trevismd

annotator.set_custom_annotations(formatted_pvalues)

trevismd

pvalues = [
    sci_stats.mannwhitneyu(robots, flight, alternative="two-sided").pvalue,
    sci_stats.mannwhitneyu(flight, sound, alternative="two-sided").pvalue,
    sci_stats.mannwhitneyu(robots, sound, alternative="two-sided").pvalue
]

# pvalues
# [0.00013485140468088997, 0.2557331102364572, 0.00022985464929005115]

# Transform each p-value to "p=" in scientific notation