Online Pingouin Compiler

Online Pingouin Compiler and Playground.

Python
import pingouin as pg
import pandas as pd

# One-sample t-test
ttest = pg.ttest([5.5, 2.4, 6.8, 9.6, 4.2], 4.0)
print("One-sample t-test:")
print(ttest.to_string())

# Pearson correlation
df = pd.DataFrame({
    'x': [1, 2, 3, 4, 5, 6, 7],
    'y': [2, 4, 5, 4, 5, 7, 9]
})
corr = pg.corr(df['x'], df['y'])
print("\nPearson correlation:")
print(corr.to_string())

# One-way ANOVA
data = pd.DataFrame({
    'score': [23, 25, 28, 30, 22, 26, 33, 35, 38, 40, 29, 32],
    'group': ['A']*4 + ['B']*4 + ['C']*4
})
aov = pg.anova(data=data, dv='score', between='group')
print("\nOne-way ANOVA:")
print(aov.to_string())
One-sample t-test:
               T  dof alternative     p_val          CI95   cohen_d     power   BF10
T_test  1.397391    4   two-sided  0.234824  [2.32, 9.08]  0.624932  0.191796  0.766

Pearson correlation:
         n         r          CI95     p_val    BF10     power
pearson  7  0.918559  [0.54, 0.99]  0.003478  14.059  0.910838

One-way ANOVA:
  Source  ddof1  ddof2         F     p_unc       np2
0  group      2      9  2.958668  0.102915  0.396675