DeepSource
Dashboard Resources Pricing Discover Directory Log in

Run your first analysis.

Find thousands of code security and quality issues in your codebase, before they end up in production.

Start now

ranaroussi / quantstats

Line too long FLK-E501
Style
Minor
14 occurrences in this check
line too long (99 > 88 characters)
quantstats/reports.py
1004    # best/worst
1005    if mode.lower() == "full":
1006        metrics["~~~"] = blank
1007        metrics["Best Day %"] = _stats.best(df, compounded=compounded, prepare_returns=False) * pct1008        metrics["Worst Day %"] = _stats.worst(df, prepare_returns=False) * pct
1009        metrics["Best Month %"] = (
1010            _stats.best(df, compounded=compounded, aggregate="M", prepare_returns=False) * pct
line too long (94 > 88 characters)
quantstats/reports.py
1013            _stats.worst(df, aggregate="M", prepare_returns=False) * pct
1014        )
1015        metrics["Best Year %"] = (
1016            _stats.best(df, compounded=compounded, aggregate="A", prepare_returns=False) * pct1017        )
1018        metrics["Worst Year %"] = (
1019            _stats.worst(df, compounded=compounded, aggregate="A", prepare_returns=False) * pct
line too long (98 > 88 characters)
quantstats/reports.py
1038        )
1039        metrics["Win Days %%"] = _stats.win_rate(df, prepare_returns=False) * pct
1040        metrics["Win Month %%"] = (
1041            _stats.win_rate(df, compounded=compounded, aggregate="M", prepare_returns=False) * pct1042        )
1043        metrics["Win Quarter %%"] = (
1044            _stats.win_rate(df, compounded=compounded, aggregate="Q", prepare_returns=False) * pct
line too long (97 > 88 characters)
quantstats/reports.py
1031    if mode.lower() == "full":
1032        metrics["~~~~~"] = blank
1033        metrics["Avg. Up Month %"] = (
1034            _stats.avg_win(df, compounded=compounded, aggregate="M", prepare_returns=False) * pct1035        )
1036        metrics["Avg. Down Month %"] = (
1037            _stats.avg_loss(df, compounded=compounded, aggregate="M", prepare_returns=False) * pct
line too long (98 > 88 characters)
quantstats/reports.py
1034            _stats.avg_win(df, compounded=compounded, aggregate="M", prepare_returns=False) * pct
1035        )
1036        metrics["Avg. Down Month %"] = (
1037            _stats.avg_loss(df, compounded=compounded, aggregate="M", prepare_returns=False) * pct1038        )
1039        metrics["Win Days %%"] = _stats.win_rate(df, prepare_returns=False) * pct
1040        metrics["Win Month %%"] = (
line too long (90 > 88 characters)
quantstats/reports.py
 930        metrics["~~~~~~~~~~"] = blank
 931
 932        metrics["Expected Daily %%"] = (
 933            _stats.expected_return(df, compounded=compounded, prepare_returns=False) * pct 934        )
 935        metrics["Expected Monthly %%"] = (
 936            _stats.expected_return(df, compounded=compounded, aggregate="M", prepare_returns=False) * pct
line too long (105 > 88 characters)
quantstats/reports.py
 933            _stats.expected_return(df, compounded=compounded, prepare_returns=False) * pct
 934        )
 935        metrics["Expected Monthly %%"] = (
 936            _stats.expected_return(df, compounded=compounded, aggregate="M", prepare_returns=False) * pct 937        )
 938        metrics["Expected Yearly %%"] = (
 939            _stats.expected_return(df, compounded=compounded, aggregate="A", prepare_returns=False) * pct
line too long (105 > 88 characters)
quantstats/reports.py
 936            _stats.expected_return(df, compounded=compounded, aggregate="M", prepare_returns=False) * pct
 937        )
 938        metrics["Expected Yearly %%"] = (
 939            _stats.expected_return(df, compounded=compounded, aggregate="A", prepare_returns=False) * pct 940        )
 941        metrics["Kelly Criterion %"] = (
 942            _stats.kelly_criterion(df, prepare_returns=False) * pct
line too long (95 > 88 characters)
quantstats/reports.py
1016            _stats.best(df, compounded=compounded, aggregate="A", prepare_returns=False) * pct
1017        )
1018        metrics["Worst Year %"] = (
1019            _stats.worst(df, compounded=compounded, aggregate="A", prepare_returns=False) * pct1020        )
1021
1022    # dd
line too long (94 > 88 characters)
quantstats/reports.py
1007        metrics["Best Day %"] = _stats.best(df, compounded=compounded, prepare_returns=False) * pct
1008        metrics["Worst Day %"] = _stats.worst(df, prepare_returns=False) * pct
1009        metrics["Best Month %"] = (
1010            _stats.best(df, compounded=compounded, aggregate="M", prepare_returns=False) * pct1011        )
1012        metrics["Worst Month %"] = (
1013            _stats.worst(df, aggregate="M", prepare_returns=False) * pct
line too long (98 > 88 characters)
quantstats/reports.py
1041            _stats.win_rate(df, compounded=compounded, aggregate="M", prepare_returns=False) * pct
1042        )
1043        metrics["Win Quarter %%"] = (
1044            _stats.win_rate(df, compounded=compounded, aggregate="Q", prepare_returns=False) * pct1045        )
1046        metrics["Win Year %%"] = (
1047            _stats.win_rate(df, compounded=compounded, aggregate="A", prepare_returns=False) * pct
line too long (98 > 88 characters)
quantstats/reports.py
1044            _stats.win_rate(df, compounded=compounded, aggregate="Q", prepare_returns=False) * pct
1045        )
1046        metrics["Win Year %%"] = (
1047            _stats.win_rate(df, compounded=compounded, aggregate="A", prepare_returns=False) * pct1048        )
1049
1050        if "benchmark" in df:
line too long (119 > 88 characters)
quantstats/_plotting/wrappers.py
 104        _plt.figtext(
 105            0,
 106            -0.05,
 107            "            * When a multi-column DataFrame is passed, the mean of all columns will be used as returns.\n" 108            "              To change this behavior, use a pandas Series or pass the column name in the `strategy_col` parameter.",
 109            ha="left",
 110            fontsize=11,
line too long (130 > 88 characters)
quantstats/_plotting/wrappers.py
 105            0,
 106            -0.05,
 107            "            * When a multi-column DataFrame is passed, the mean of all columns will be used as returns.\n"
 108            "              To change this behavior, use a pandas Series or pass the column name in the `strategy_col` parameter.", 109            ha="left",
 110            fontsize=11,
 111            color="black",