trevismd

robots = rfs.loc[(rfs.Subcategory == "Robots"), "Goal"].values
flight = rfs.loc[(rfs.Subcategory == "Flight"), "Goal"].values
sound = rfs.loc[(rfs.Subcategory == "Sound"), "Goal"].values

log_robots = np.log(robots)
log_flight = np.log(flight)
log_sound = np.log(sound)

trevismd

print("Robots: ", normaltest(robots).pvalue)
print("Flight: ", normaltest(flight).pvalue)
print("Sound: ", normaltest(sound).pvalue)
print()
print("Log(robots): ", normaltest(log_robots).pvalue)
print("Log(Flight): ", normaltest(log_flight).pvalue)
print("Log(Sound): ", normaltest(log_sound).pvalue)

trevismd

# pvalues with scipy:
stat_results = [
  mannwhitneyu(robots, flight, alternative="two-sided"),
  mannwhitneyu(flight, sound, alternative="two-sided"),
  mannwhitneyu(robots, sound, alternative="two-sided")
]

pvalues = [result.pvalue for result in stat_results]

print("Robots vs Flight: \n", stat_results[0], "\n")

trevismd

pairs = [('Robots', 'Flight'),  # 'Robots' vs 'Flight'
         ('Flight', 'Sound'),   # 'Flight' vs 'Sound'
         ('Robots', 'Sound')]   # 'Robots' vs 'Sound'

trevismd

from statannotations.Annotator import Annotator

trevismd

 # With ... = all parameters passed to seaborn's plotter
  annotator = Annotator(ax, box_pairs, ...) 

trevismd

# With ... = all parameters passed to seaborn's plotter
annotator = Annotator(ax, pairs, ...)

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

trevismd

annotator.set_custom_annotations(formatted_pvalues)

trevismd

annotator.annotate()