pingouin_ttest_effect_size_penguins_species_comparison.py

1import pandas as pd
2import pingouin as pg
3
4# Load an example dataset
5df = pg.read_dataset('penguins')
6
7# 1. T-test
8# Compare the flipper length of Adelie and Gentoo penguins
9t_test = pg.ttest(df[df['species'] == 'Adelie']['flipper_length_mm'],
10                  df[df['species'] == 'Gentoo']['flipper_length_mm'])
11
12print("T-test results:")
13print(t_test)
14
15# 2. Effect size (Cohen's d)
16# Calculate the effect size between the same two groups
17eff = pg.compute_effsize(df[df['species'] == 'Adelie']['flipper_length_mm'],
18                         df[df['species'] == 'Gentoo']['flipper_length_mm'],
19                         eftype='cohen')
20
21print(f"\nCohen's d effect size: {eff:.3f}")
22
23# 3. Correlation matrix
24# Calculate partial correlation between bill length and bill depth, controlling for body mass
25cor = pg.partial_corr(data=df, x='bill_length_mm', y='bill_depth_mm', covar='body_mass_g')
26
27print("\nPartial correlation:")
28print(cor)