How to use the pingouin.anova function in pingouin

"""One-way repeated measures ANOVA
"""
import pandas as pd
from numpy import repeat
from pingouin import anova, rm_anova, mixed_anova, print_table

# Load dataset
df = pd.read_csv('sleep_dataset.csv')

# ONE-WAY ANOVA
aov = anova(dv='DV', between='Group', data=df, detailed=False)
print_table(aov, floatfmt=".3f")

# ONE-WAY REPEATED MEASURES ANOVA
aov = rm_anova(dv='DV', within='Time', data=df, correction='auto',
               remove_na=True, detailed=True)
print_table(aov)

# TWO-WAY MIXED MODEL ANOVA (Within + Between factors)
aov = mixed_anova(dv='DV', within='Time', between='Group', data=df,
                  correction='auto', export_filename='mixed_anova.csv')
print_table(aov)

data = data.reset_index().melt(id_vars=targets, value_name=ratings)

    # Check that ratings is a numeric variable
    assert data[ratings].dtype.kind in 'bfi', 'Ratings must be numeric.'
    # Check that data are fully balanced
    # This behavior is ensured by the long-to-wide-to-long transformation
    # Unbalanced data will result in rows with missing values.
    # assert data.groupby(raters)[ratings].count().nunique() == 1

    # Extract sizes
    k = data[raters].nunique()
    n = data[targets].nunique()

    # Two-way ANOVA
    with np.errstate(invalid='ignore'):
        aov = anova(dv=ratings, between=[targets, raters], data=data,
                    ss_type=2)

    # Extract mean squares
    msb = aov.at[0, 'MS']
    msw = (aov.at[1, 'SS'] + aov.at[2, 'SS']) / (aov.at[1, 'DF'] +
                                                 aov.at[2, 'DF'])
    msj = aov.at[1, 'MS']
    mse = aov.at[2, 'MS']

    # Calculate ICCs
    icc1 = (msb - msw) / (msb + (k - 1) * msw)
    icc2 = (msb - mse) / (msb + (k - 1) * mse + k * (msj - mse) / n)
    icc3 = (msb - mse) / (msb + (k - 1) * mse)
    icc1k = (msb - msw) / msb
    icc2k = (msb - mse) / (msb + (msj - mse) / n)
    icc3k = (msb - mse) / msb