How to use the pingouin._export_table function in pingouin

for c in covar:
        formula += ' + ' + c
    model = ols(formula, data=data).fit()
    aov = stats.anova_lm(model, typ=2).reset_index()

    aov.rename(columns={'index': 'Source', 'sum_sq': 'SS',
                        'df': 'DF', 'PR(>F)': 'p-unc'}, inplace=True)

    aov.at[0, 'Source'] = between

    aov['DF'] = aov['DF'].astype(int)
    aov[['SS', 'F']] = aov[['SS', 'F']].round(3)

    # Export to .csv
    if export_filename is not None:
        _export_table(aov, export_filename)

    return aov

'p-GG-corr': [p_a_corr, p_b_corr, p_ab_corr],
                        'np2': [eta_a, eta_b, eta_ab],
                        'eps': [eps_a, eps_b, eps_ab],
                        })

    col_order = ['Source', 'SS', 'ddof1', 'ddof2', 'MS', 'F', 'p-unc',
                 'p-GG-corr', 'np2', 'eps']

    # Round
    aov[['SS', 'MS', 'F', 'eps', 'np2']] = aov[['SS', 'MS', 'F', 'eps',
                                                'np2']].round(3)

    aov = aov.reindex(columns=col_order)
    # Export to .csv
    if export_filename is not None:
        _export_table(aov, export_filename)
    return aov

'SS': np.round([ss_fac1, ss_fac2, ss_inter,
                                        ss_resid], 3),
                        'DF': [df_fac1, df_fac2, df_inter, df_resid],
                        'MS': np.round([ms_fac1, ms_fac2, ms_inter,
                                        ms_resid], 3),
                        'F': [fval_fac1, fval_fac2, fval_inter, np.nan],
                        'p-unc': [pval_fac1, pval_fac2, pval_inter, np.nan],
                        'np2': [np2_fac1, np2_fac2, np2_inter, np.nan]
                        })
    col_order = ['Source', 'SS', 'DF', 'MS', 'F', 'p-unc', 'np2']

    aov = aov.reindex(columns=col_order)
    aov.dropna(how='all', axis=1, inplace=True)
    # Export to .csv
    if export_filename is not None:
        _export_table(aov, export_filename)
    return aov

f_b = ms_b / ms_w
    # P-values
    p_c = f(df_c, df_w).sf(f_c)
    p_b = f(df_b, df_w).sf(f_b)

    # Create dataframe
    aov = pd.DataFrame({'Source': [between, covar, 'Residual'],
                        'SS': [ss_b, ss_c, ss_w],
                        'DF': [df_b, df_c, df_w],
                        'F': [f_b, f_c, np.nan],
                        'p-unc': [p_b, p_c, np.nan],
                        })

    # Export to .csv
    if export_filename is not None:
        _export_table(aov, export_filename)

    # Add bw as an attribute (for rm_corr function)
    aov.bw_ = bw
    return aov

col_order = ['Source', 'SS', 'DF1', 'DF2', 'MS', 'F', 'p-unc',
                 'p-GG-corr', 'np2', 'eps', 'sphericity', 'W-spher',
                 'p-spher']

    # Replace NaN
    aov = aov.fillna('-')

    aov = aov.reindex(columns=col_order)
    aov.dropna(how='all', axis=1, inplace=True)

    # Round
    aov[['F', 'eps', 'np2']] = aov[['F', 'eps', 'np2']].round(3)

    # Export to .csv
    if export_filename is not None:
        _export_table(aov, export_filename)
    return aov

return x.replace(':', ' * ')

    aov['Source'] = aov['Source'].apply(format_source)

    # Re-index and round
    col_order = ['Source', 'SS', 'DF', 'MS', 'F', 'p-unc', 'np2']
    aov = aov.reindex(columns=col_order)
    aov[['SS', 'MS', 'F', 'np2']] = aov[['SS', 'MS', 'F', 'np2']].round(3)
    aov.dropna(how='all', axis=1, inplace=True)

    # Add formula to dataframe
    aov.formula_ = formula

    # Export to .csv
    if export_filename is not None:
        _export_table(aov, export_filename)
    return aov

# Create output dataframe
    stats = pd.DataFrame({'Source': between,
                          'ddof1': ddof1,
                          'H': np.round(H, 3),
                          'p-unc': p_unc,
                          }, index=['Kruskal'])

    col_order = ['Source', 'ddof1', 'H', 'p-unc']

    stats = stats.reindex(columns=col_order)
    stats.dropna(how='all', axis=1, inplace=True)

    # Export to .csv
    if export_filename is not None:
        _export_table(stats, export_filename)
    return stats