BTable

BTable(
    df,
    vars,
    group,
    *,
    labels=None,
    digits=2,
    pdigits=3,
    vcov='iid',
    fixed_effects=None,
    stats=None,
    stats_labels=None,
    format_spec=None,
    hide_stats=False,
    counts_row_below=False,
    observed=False,
    notes='',
    **kwargs,
)

Balancing table: descriptive stats by group + per-variable p-values from group tests.

Inherits DTable to build the stats table, then adds a ‘p-value’ column: - For 2 groups: p-value of the single group indicator (t test). - For >2 groups: joint Wald test that all group indicators are zero. You can add fixed_effects and specify the vcov option, for instance to implement clustering (see pyfixest documentation).

Parameters

Name	Type	Description	Default
df	pd.DataFrame	Source data.	required
vars	list[str]	Variables to include.	required
group	str | list[str]	Grouping column(s) in df.	required
labels	dict	Variable labels (used for display and in notes).	None
digits	int	Rounding for stats in the DTable. Default 2.	2
pdigits	int	Rounding for p-values. Default 3.	3
vcov	str | dict	VCV for the p-value models (“iid”, “hetero”, “HC1”, “HC2”, “HC3” or {“CRV1”: “cluster”}). Default “iid”.	'iid'
fixed_effects	list[str] | None	Optional fixed effects for the p-value models (cosmetic in notes). Default None.	None
stats	list[str] | None	Stats for DTable (default [“mean”, “std”]).	None
stats_labels	dict[str, str] | None	Custom labels for stats (used in header/notes).	None
hide_stats	bool	Hide stats names in the header (list them in notes instead). Default False.	False
counts_row_below	bool	If True and balanced N, show a single counts row at bottom. Default False.	False
observed	bool	Only consider observed categories when grouping. Default False.	False
notes	str	Custom notes. If ““, a default is generated mentioning stats/SE/FE.	''
kwargs	dict	Passed through to DTable/MTable (e.g., caption, tab_label, rgroup_display).	{}