Function full

quantstats/reports.py:492–639

(
    returns,
    benchmark=None,
    rf=0.0,
    grayscale=False,
    figsize=(8, 5),
    display=True,
    compounded=True,
    periods_per_year=252,
    match_dates=True,
    **kwargs,
)

def full(
    returns,
    benchmark=None,
    rf=0.0,
    grayscale=False,
    figsize=(8, 5),
    display=True,
    compounded=True,
    periods_per_year=252,
    match_dates=True,
    **kwargs,
):

    # prepare timeseries
    if match_dates:
        returns = returns.dropna()
    returns = _utils._prepare_returns(returns)
    if benchmark is not None:
        benchmark = _utils._prepare_benchmark(benchmark, returns.index, rf)
        if match_dates is True:
            returns, benchmark = _match_dates(returns, benchmark)

    benchmark_title = None
    if benchmark is not None:
        benchmark_title = kwargs.get("benchmark_title", "Benchmark")
    strategy_title = kwargs.get("strategy_title", "Strategy")
    active = kwargs.get("active_returns", "False")

    if isinstance(returns, _pd.DataFrame):
        if len(returns.columns) > 1 and isinstance(strategy_title, str):
            strategy_title = list(returns.columns)

    if benchmark is not None:
        benchmark.name = benchmark_title
    if isinstance(returns, _pd.Series):
        returns.name = strategy_title
    elif isinstance(returns, _pd.DataFrame):
        returns.columns = strategy_title

    dd = _stats.to_drawdown_series(returns)

    if isinstance(dd, _pd.Series):
        col = _stats.drawdown_details(dd).columns[4]
        dd_info = _stats.drawdown_details(dd).sort_values(by=col, ascending=True)[:5]
        if not dd_info.empty:
            dd_info.index = range(1, min(6, len(dd_info) + 1))
            dd_info.columns = map(lambda x: str(x).title(), dd_info.columns)
    elif isinstance(dd, _pd.DataFrame):
        col = _stats.drawdown_details(dd).columns.get_level_values(1)[4]
        dd_info_dict = {}
        for ptf in dd.columns:
            dd_info = _stats.drawdown_details(dd[ptf]).sort_values(
                by=col, ascending=True
            )[:5]
            if not dd_info.empty:
                dd_info.index = range(1, min(6, len(dd_info) + 1))
                dd_info.columns = map(lambda x: str(x).title(), dd_info.columns)
            dd_info_dict[ptf] = dd_info