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indicator ¤

PlotColor ¤

Bases: str, Enum

Enum plot color

AMBER class-attribute instance-attribute ¤

AMBER = '#fa0'

BLUE class-attribute instance-attribute ¤

BLUE = '#4287ff'

CYAN class-attribute instance-attribute ¤

CYAN = '#00bad6'

DEEP_ORANGE class-attribute instance-attribute ¤

DEEP_ORANGE = '#ff6e42'

DEEP_PURPLE class-attribute instance-attribute ¤

DEEP_PURPLE = '#7c4dff'

GREEN class-attribute instance-attribute ¤

GREEN = '#00c753'

INDIGO class-attribute instance-attribute ¤

INDIGO = '#526cfe'

LIGHT_BLUE class-attribute instance-attribute ¤

LIGHT_BLUE = '#0091eb'

LIGHT_GREEN class-attribute instance-attribute ¤

LIGHT_GREEN = '#63de17'

LIGHT_PINK class-attribute instance-attribute ¤

LIGHT_PINK = '#f06292'

LIGHT_RED class-attribute instance-attribute ¤

LIGHT_RED = '#e6695b'

LIGHT_YELLOW class-attribute instance-attribute ¤

LIGHT_YELLOW = '#fff176'

LIME class-attribute instance-attribute ¤

LIME = '#b0eb00'

ORANGE class-attribute instance-attribute ¤

ORANGE = '#ff9100'

PINK class-attribute instance-attribute ¤

PINK = '#f50056'

PURPLE class-attribute instance-attribute ¤

PURPLE = '#df41fb'

RED class-attribute instance-attribute ¤

RED = '#ff1947'

TEAL class-attribute instance-attribute ¤

TEAL = '#00bda4'

YELLOW class-attribute instance-attribute ¤

YELLOW = '#ffd500'

above ¤

above(
    series1: Series | str,
    series2: Series | str,
    dataframe: DataFrame = None,
    name: str | None = None,
    prefix: str = "",
    inplace: bool = False,
    plot: bool | list[str] = False,
    plot_kwargs: dict | None = None,
) -> Series

Check a Series is above another Series

Parameters:

  • series1 (Series) –

    first Series

  • series2 (Series) –

    second Series

Returns:

  • Series –

    pd.Series: True series1 is above series2 else False

Source code in lettrade/indicator/series.py 
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def above(
    series1: pd.Series | str,
    series2: pd.Series | str,
    dataframe: pd.DataFrame = None,
    name: str | None = None,
    prefix: str = "",
    inplace: bool = False,
    plot: bool | list[str] = False,
    plot_kwargs: dict | None = None,
    # **kwargs,
) -> pd.Series:
    """Check a Series is above another Series

    Args:
        series1 (pd.Series): first Series
        series2 (pd.Series): second Series

    Returns:
        pd.Series: True series1 is above series2 else False
    """
    if __debug__:
        if plot and not inplace:
            raise RuntimeError("Cannot plot when inplace=False")

    if isinstance(series1, str):
        series1 = dataframe[series1]
    if isinstance(series2, str):
        series2 = dataframe[series2]

    i = s_above(series1=series1, series2=series2)

    if inplace:
        name = name or f"{prefix}above"
        dataframe[name] = i

        if plot:
            _plot_mark(dataframe=dataframe, name=name, plot_kwargs=plot_kwargs)

    return i

below ¤

below(
    series1: Series | str,
    series2: Series | str,
    dataframe: DataFrame = None,
    name: str | None = None,
    prefix: str = "",
    inplace: bool = False,
    plot: bool | list[str] = False,
    plot_kwargs: dict | None = None,
) -> Series

Check a Series is below another Series

Parameters:

  • series1 (Series) –

    first Series

  • series2 (Series) –

    second Series

Returns:

  • Series –

    pd.Series: -100 series1 is below series2 else 0

Source code in lettrade/indicator/series.py 
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def below(
    series1: pd.Series | str,
    series2: pd.Series | str,
    dataframe: pd.DataFrame = None,
    name: str | None = None,
    prefix: str = "",
    inplace: bool = False,
    plot: bool | list[str] = False,
    plot_kwargs: dict | None = None,
    # **kwargs,
) -> pd.Series:
    """Check a Series is below another Series

    Args:
        series1 (pd.Series): first Series
        series2 (pd.Series): second Series

    Returns:
        pd.Series: -100 series1 is below series2 else 0
    """
    if __debug__:
        if plot and not inplace:
            raise RuntimeError("Cannot plot when inplace=False")

    if isinstance(series1, str):
        series1 = dataframe[series1]
    if isinstance(series2, str):
        series2 = dataframe[series2]

    i = s_below(series1, series2)

    if inplace:
        name = name or f"{prefix}below"
        dataframe[name] = i

        if plot:
            _plot_mark(dataframe=dataframe, name=name, plot_kwargs=plot_kwargs)

    return i

cdl_3blackcrows ¤

cdl_3blackcrows(
    dataframe: DataFrame,
    name: str | None = None,
    prefix: str = "cdl_",
    inplace: bool = False,
    plot: bool | list[str] = False,
    plot_type: Literal[
        "candlestick", "mark"
    ] = "candlestick",
    plot_kwargs: dict | None = None,
    **kwargs
) -> Series | DataFrame

summary

Parameters:

  • dataframe (DataFrame) –

    description

  • name (str | None, default: None ) –

    description. Defaults to None.

  • prefix (str, default: 'cdl_' ) –

    description. Defaults to "cdl_".

  • inplace (bool, default: False ) –

    description. Defaults to False.

Returns:

  • Series | DataFrame –

    pd.Series | pd.DataFrame: description

Source code in lettrade/indicator/candlestick/talib.py 
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def cdl_3blackcrows(
    dataframe: pd.DataFrame,
    name: str | None = None,
    prefix: str = "cdl_",
    inplace: bool = False,
    plot: bool | list[str] = False,
    plot_type: Literal["candlestick", "mark"] = "candlestick",
    plot_kwargs: dict | None = None,
    **kwargs,
) -> pd.Series | pd.DataFrame:
    """_summary_

    Args:
        dataframe (pd.DataFrame): _description_
        name (str | None, optional): _description_. Defaults to None.
        prefix (str, optional): _description_. Defaults to "cdl_".
        inplace (bool, optional): _description_. Defaults to False.

    Returns:
        pd.Series | pd.DataFrame: _description_
    """
    return cdl_pattern(
        dataframe=dataframe,
        pattern="3blackcrows",
        name=name,
        prefix=prefix,
        inplace=inplace,
        plot=plot,
        plot_type=plot_type,
        plot_kwargs=plot_kwargs,
        **kwargs,
    )

cdl_3inside ¤

cdl_3inside(
    dataframe: DataFrame,
    name: str | None = None,
    prefix: str = "cdl_",
    inplace: bool = False,
    plot: bool | list[str] = False,
    plot_type: Literal[
        "candlestick", "mark"
    ] = "candlestick",
    plot_kwargs: dict | None = None,
    **kwargs
) -> Series | DataFrame

summary

Parameters:

  • dataframe (DataFrame) –

    description

  • name (str | None, default: None ) –

    description. Defaults to None.

  • prefix (str, default: 'cdl_' ) –

    description. Defaults to "cdl_".

  • inplace (bool, default: False ) –

    description. Defaults to False.

Returns:

  • Series | DataFrame –

    pd.Series | pd.DataFrame: description

Source code in lettrade/indicator/candlestick/talib.py 
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def cdl_3inside(
    dataframe: pd.DataFrame,
    name: str | None = None,
    prefix: str = "cdl_",
    inplace: bool = False,
    plot: bool | list[str] = False,
    plot_type: Literal["candlestick", "mark"] = "candlestick",
    plot_kwargs: dict | None = None,
    **kwargs,
) -> pd.Series | pd.DataFrame:
    """_summary_

    Args:
        dataframe (pd.DataFrame): _description_
        name (str | None, optional): _description_. Defaults to None.
        prefix (str, optional): _description_. Defaults to "cdl_".
        inplace (bool, optional): _description_. Defaults to False.

    Returns:
        pd.Series | pd.DataFrame: _description_
    """
    return cdl_pattern(
        dataframe=dataframe,
        pattern="3inside",
        name=name,
        prefix=prefix,
        inplace=inplace,
        plot=plot,
        plot_type=plot_type,
        plot_kwargs=plot_kwargs,
        **kwargs,
    )

cdl_3whitesoldiers ¤

cdl_3whitesoldiers(
    dataframe: DataFrame,
    name: str | None = None,
    prefix: str = "cdl_",
    inplace: bool = False,
    plot: bool | list[str] = False,
    plot_type: Literal[
        "candlestick", "mark"
    ] = "candlestick",
    plot_kwargs: dict | None = None,
    **kwargs
) -> Series | DataFrame

summary

Parameters:

  • dataframe (DataFrame) –

    description

  • name (str | None, default: None ) –

    description. Defaults to None.

  • prefix (str, default: 'cdl_' ) –

    description. Defaults to "cdl_".

  • inplace (bool, default: False ) –

    description. Defaults to False.

Returns:

  • Series | DataFrame –

    pd.Series | pd.DataFrame: description

Source code in lettrade/indicator/candlestick/talib.py 
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def cdl_3whitesoldiers(
    dataframe: pd.DataFrame,
    name: str | None = None,
    prefix: str = "cdl_",
    inplace: bool = False,
    plot: bool | list[str] = False,
    plot_type: Literal["candlestick", "mark"] = "candlestick",
    plot_kwargs: dict | None = None,
    **kwargs,
) -> pd.Series | pd.DataFrame:
    """_summary_

    Args:
        dataframe (pd.DataFrame): _description_
        name (str | None, optional): _description_. Defaults to None.
        prefix (str, optional): _description_. Defaults to "cdl_".
        inplace (bool, optional): _description_. Defaults to False.

    Returns:
        pd.Series | pd.DataFrame: _description_
    """
    return cdl_pattern(
        dataframe=dataframe,
        pattern="3whitesoldiers",
        name=name,
        prefix=prefix,
        inplace=inplace,
        plot=plot,
        plot_type=plot_type,
        plot_kwargs=plot_kwargs,
        **kwargs,
    )

cdl_direction ¤

cdl_direction(
    dataframe: DataFrame,
    name: str | None = None,
    prefix: str = "cdl_",
    inplace: bool = False,
) -> Series | DataFrame

Direction of candle

Parameters:

  • dataframe (DataFrame) –

    description

  • name (str | None, default: None ) –

    description. Defaults to None.

  • prefix (str, default: 'cdl_' ) –

    description. Defaults to "cdl_".

  • inplace (bool, default: False ) –

    description. Defaults to False.

Returns:

  • Series | DataFrame –

    pd.Series | pd.DataFrame: pd.Series return [100, 0 , -100] - 100 for bull bar - -100 for bear bar - 0 for None

Source code in lettrade/indicator/candlestick/candlestick.py 
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def cdl_direction(
    dataframe: pd.DataFrame,
    name: str | None = None,
    prefix: str = "cdl_",
    inplace: bool = False,
) -> pd.Series | pd.DataFrame:
    """Direction of candle

    Args:
        dataframe (pd.DataFrame): _description_
        name (str | None, optional): _description_. Defaults to None.
        prefix (str, optional): _description_. Defaults to "cdl_".
        inplace (bool, optional): _description_. Defaults to False.

    Returns:
        pd.Series | pd.DataFrame: `pd.Series` return [100, 0 , -100]
            - `100` for bull bar
            - `-100` for bear bar
            - `0` for None
    """
    if __debug__:
        if not isinstance(dataframe, pd.DataFrame):
            raise RuntimeError(
                f"dataframe type '{type(dataframe)}' "
                "is not instance of pandas.DataFrame"
            )
    i = dataframe.apply(
        lambda r: 100 if r.open < r.close else -100 if r.open > r.close else 0,
        axis=1,
    ).astype(int)

    if inplace:
        dataframe[name or f"{prefix}direction"] = i
        return dataframe

    return i

cdl_doji ¤

cdl_doji(
    dataframe: DataFrame,
    name: str | None = None,
    prefix: str = "cdl_",
    inplace: bool = False,
    plot: bool | list[str] = False,
    plot_type: Literal[
        "candlestick", "mark"
    ] = "candlestick",
    plot_kwargs: dict | None = None,
    **kwargs
) -> Series | DataFrame

summary

Parameters:

  • dataframe (DataFrame) –

    description

  • name (str | None, default: None ) –

    description. Defaults to None.

  • prefix (str, default: 'cdl_' ) –

    description. Defaults to "cdl_".

  • inplace (bool, default: False ) –

    description. Defaults to False.

Returns:

  • Series | DataFrame –

    pd.Series | pd.DataFrame: description

Source code in lettrade/indicator/candlestick/talib.py 
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def cdl_doji(
    dataframe: pd.DataFrame,
    name: str | None = None,
    prefix: str = "cdl_",
    inplace: bool = False,
    plot: bool | list[str] = False,
    plot_type: Literal["candlestick", "mark"] = "candlestick",
    plot_kwargs: dict | None = None,
    **kwargs,
) -> pd.Series | pd.DataFrame:
    """_summary_

    Args:
        dataframe (pd.DataFrame): _description_
        name (str | None, optional): _description_. Defaults to None.
        prefix (str, optional): _description_. Defaults to "cdl_".
        inplace (bool, optional): _description_. Defaults to False.

    Returns:
        pd.Series | pd.DataFrame: _description_
    """
    return cdl_pattern(
        dataframe=dataframe,
        pattern="doji",
        name=name,
        prefix=prefix,
        inplace=inplace,
        plot=plot,
        plot_type=plot_type,
        plot_kwargs=plot_kwargs,
        **kwargs,
    )

cdl_engulfing ¤

cdl_engulfing(
    dataframe: DataFrame,
    name: str | None = None,
    prefix: str = "cdl_",
    inplace: bool = False,
    plot: bool | list[str] = False,
    plot_type: Literal[
        "candlestick", "mark"
    ] = "candlestick",
    plot_kwargs: dict | None = None,
    **kwargs
) -> Series | DataFrame

summary

Parameters:

  • dataframe (DataFrame) –

    description

  • name (str | None, default: None ) –

    description. Defaults to None.

  • prefix (str, default: 'cdl_' ) –

    description. Defaults to "cdl_".

  • inplace (bool, default: False ) –

    description. Defaults to False.

Returns:

  • Series | DataFrame –

    pd.Series | pd.DataFrame: description

Source code in lettrade/indicator/candlestick/talib.py 
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def cdl_engulfing(
    dataframe: pd.DataFrame,
    name: str | None = None,
    prefix: str = "cdl_",
    inplace: bool = False,
    plot: bool | list[str] = False,
    plot_type: Literal["candlestick", "mark"] = "candlestick",
    plot_kwargs: dict | None = None,
    **kwargs,
) -> pd.Series | pd.DataFrame:
    """_summary_

    Args:
        dataframe (pd.DataFrame): _description_
        name (str | None, optional): _description_. Defaults to None.
        prefix (str, optional): _description_. Defaults to "cdl_".
        inplace (bool, optional): _description_. Defaults to False.

    Returns:
        pd.Series | pd.DataFrame: _description_
    """
    return cdl_pattern(
        dataframe=dataframe,
        pattern="engulfing",
        name=name,
        prefix=prefix,
        inplace=inplace,
        plot=plot,
        plot_type=plot_type,
        plot_kwargs=plot_kwargs,
        **kwargs,
    )

cdl_eveningstar ¤

cdl_eveningstar(
    dataframe: DataFrame,
    name: str | None = None,
    prefix: str = "cdl_",
    inplace: bool = False,
    plot: bool | list[str] = False,
    plot_type: Literal[
        "candlestick", "mark"
    ] = "candlestick",
    plot_kwargs: dict | None = None,
    **kwargs
) -> Series | DataFrame

summary

Parameters:

  • dataframe (DataFrame) –

    description

  • name (str | None, default: None ) –

    description. Defaults to None.

  • prefix (str, default: 'cdl_' ) –

    description. Defaults to "cdl_".

  • inplace (bool, default: False ) –

    description. Defaults to False.

Returns:

  • Series | DataFrame –

    pd.Series | pd.DataFrame: description

Source code in lettrade/indicator/candlestick/talib.py 
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def cdl_eveningstar(
    dataframe: pd.DataFrame,
    name: str | None = None,
    prefix: str = "cdl_",
    inplace: bool = False,
    plot: bool | list[str] = False,
    plot_type: Literal["candlestick", "mark"] = "candlestick",
    plot_kwargs: dict | None = None,
    **kwargs,
) -> pd.Series | pd.DataFrame:
    """_summary_

    Args:
        dataframe (pd.DataFrame): _description_
        name (str | None, optional): _description_. Defaults to None.
        prefix (str, optional): _description_. Defaults to "cdl_".
        inplace (bool, optional): _description_. Defaults to False.

    Returns:
        pd.Series | pd.DataFrame: _description_
    """
    return cdl_pattern(
        dataframe=dataframe,
        pattern="eveningstar",
        name=name,
        prefix=prefix,
        inplace=inplace,
        plot=plot,
        plot_type=plot_type,
        plot_kwargs=plot_kwargs,
        **kwargs,
    )

cdl_morningstar ¤

cdl_morningstar(
    dataframe: DataFrame,
    name: str | None = None,
    prefix: str = "cdl_",
    inplace: bool = False,
    plot: bool | list[str] = False,
    plot_type: Literal[
        "candlestick", "mark"
    ] = "candlestick",
    plot_kwargs: dict | None = None,
    **kwargs
) -> Series | DataFrame

summary

Parameters:

  • dataframe (DataFrame) –

    description

  • name (str | None, default: None ) –

    description. Defaults to None.

  • prefix (str, default: 'cdl_' ) –

    description. Defaults to "cdl_".

  • inplace (bool, default: False ) –

    description. Defaults to False.

Returns:

  • Series | DataFrame –

    pd.Series | pd.DataFrame: description

Source code in lettrade/indicator/candlestick/talib.py 
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def cdl_morningstar(
    dataframe: pd.DataFrame,
    name: str | None = None,
    prefix: str = "cdl_",
    inplace: bool = False,
    plot: bool | list[str] = False,
    plot_type: Literal["candlestick", "mark"] = "candlestick",
    plot_kwargs: dict | None = None,
    **kwargs,
) -> pd.Series | pd.DataFrame:
    """_summary_

    Args:
        dataframe (pd.DataFrame): _description_
        name (str | None, optional): _description_. Defaults to None.
        prefix (str, optional): _description_. Defaults to "cdl_".
        inplace (bool, optional): _description_. Defaults to False.

    Returns:
        pd.Series | pd.DataFrame: _description_
    """
    return cdl_pattern(
        dataframe=dataframe,
        pattern="morningstar",
        name=name,
        prefix=prefix,
        inplace=inplace,
        plot=plot,
        plot_type=plot_type,
        plot_kwargs=plot_kwargs,
        **kwargs,
    )

cdl_pattern ¤

cdl_pattern(
    dataframe: DataFrame,
    pattern: str,
    name: str | None = None,
    prefix: str = "cdl_",
    inplace: bool = False,
    plot: bool | list[str] = False,
    plot_type: Literal[
        "candlestick", "mark"
    ] = "candlestick",
    plot_kwargs: dict | None = None,
    **kwargs
) -> Series | DataFrame

summary

Parameters:

  • dataframe (DataFrame) –

    pandas.DataFrame with ohlcv

  • pattern (str) –

    TA-Lib candle pattern name. Ex: 3whitesoldiers, 3blackcrows

  • name (str | None, default: None ) –

    description. Defaults to None.

  • prefix (str, default: 'cdl_' ) –

    description. Defaults to "cdl_".

  • inplace (bool, default: False ) –

    description. Defaults to False.

Raises:

Returns:

  • Series | DataFrame –

    pd.Series | pd.DataFrame: description

Source code in lettrade/indicator/candlestick/talib.py 
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def cdl_pattern(
    dataframe: pd.DataFrame,
    pattern: str,
    name: str | None = None,
    prefix: str = "cdl_",
    inplace: bool = False,
    plot: bool | list[str] = False,
    plot_type: Literal["candlestick", "mark"] = "candlestick",
    plot_kwargs: dict | None = None,
    **kwargs,
) -> pd.Series | pd.DataFrame:
    """_summary_

    Args:
        dataframe (pd.DataFrame): pandas.DataFrame with ohlcv
        pattern (str): TA-Lib candle pattern name. Ex: `3whitesoldiers`, `3blackcrows`
        name (str | None, optional): _description_. Defaults to None.
        prefix (str, optional): _description_. Defaults to "cdl_".
        inplace (bool, optional): _description_. Defaults to False.

    Raises:
        RuntimeError: _description_

    Returns:
        pd.Series | pd.DataFrame: _description_
    """
    if __debug__:
        if not isinstance(dataframe, pd.DataFrame):
            raise RuntimeError(
                f"dataframe type '{type(dataframe)}' "
                "is not instance of pandas.DataFrame"
            )
        if plot and not inplace:
            raise RuntimeError("Cannot plot when inplace=False")

    i = getattr(ta, f"CDL{pattern.upper()}")(dataframe, **kwargs)

    if inplace:
        name = name or f"{prefix}{pattern.lower()}"
        dataframe[name] = i

        # Plot
        if plot:
            _plot_pattern(
                dataframe=dataframe,
                indicator=i,
                name=name,
                plot_type=plot_type,
                plot_kwargs=plot_kwargs,
            )

        return dataframe

    return i

crossover ¤

crossover(
    series1: Series | str,
    series2: Series | str,
    dataframe: DataFrame = None,
    name: str | None = None,
    prefix: str = "",
    inplace: bool = False,
    plot: bool | list[str] = False,
    plot_kwargs: dict | None = None,
) -> Series

Check if a Series cross over another Series

Parameters:

  • series1 (Series) –

    first Series

  • series2 (Series) –

    second Series

Returns:

  • Series –

    pd.Series: 100 if series1 cross over series2 else 0

Source code in lettrade/indicator/series.py 
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def crossover(
    series1: pd.Series | str,
    series2: pd.Series | str,
    dataframe: pd.DataFrame = None,
    name: str | None = None,
    prefix: str = "",
    inplace: bool = False,
    plot: bool | list[str] = False,
    plot_kwargs: dict | None = None,
    # **kwargs,
) -> pd.Series:
    """Check if a Series cross over another Series

    Args:
        series1 (pd.Series): first Series
        series2 (pd.Series): second Series

    Returns:
        pd.Series: 100 if series1 cross over series2 else 0
    """
    if __debug__:
        if plot and not inplace:
            raise RuntimeError("Cannot plot when inplace=False")

    if isinstance(series1, str):
        series1 = dataframe[series1]
    if isinstance(series2, str):
        series2 = dataframe[series2]

    below1 = s_below(series1, series2).shift(1)
    above0 = s_above(series1, series2)
    i = (-below1 + above0).apply(lambda v: 100 if v >= 200 else 0)

    if inplace:
        name = name or f"{prefix}crossover"
        dataframe[name] = i

        if plot:
            _plot_mark(dataframe=dataframe, name=name, plot_kwargs=plot_kwargs)

    return i

crossunder ¤

crossunder(
    series1: Series | str,
    series2: Series | str,
    dataframe: DataFrame = None,
    name: str | None = None,
    prefix: str = "",
    inplace: bool = False,
    plot: bool | list[str] = False,
    plot_kwargs: dict | None = None,
) -> Series

Check if a Series cross under another Series

Parameters:

  • series1 (Series) –

    first Series

  • series2 (Series) –

    second Series

Returns:

  • Series –

    pd.Series: -100 if series1 cross under series2 else 0

Source code in lettrade/indicator/series.py 
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def crossunder(
    series1: pd.Series | str,
    series2: pd.Series | str,
    dataframe: pd.DataFrame = None,
    name: str | None = None,
    prefix: str = "",
    inplace: bool = False,
    plot: bool | list[str] = False,
    plot_kwargs: dict | None = None,
    # **kwargs,
) -> pd.Series:
    """Check if a Series cross under another Series

    Args:
        series1 (pd.Series): first Series
        series2 (pd.Series): second Series

    Returns:
        pd.Series: -100 if series1 cross under series2 else 0
    """
    if __debug__:
        if plot and not inplace:
            raise RuntimeError("Cannot plot when inplace=False")

    if isinstance(series1, str):
        series1 = dataframe[series1]
    if isinstance(series2, str):
        series2 = dataframe[series2]

    above1 = s_above(series1, series2).shift(1)
    below0 = s_below(series1, series2)
    i = (below0 - above1).apply(lambda v: -100 if v <= -200 else 0)

    if inplace:
        name = name or f"{prefix}crossunder"
        dataframe[name] = i

        if plot:
            _plot_mark(dataframe=dataframe, name=name, plot_kwargs=plot_kwargs)

    return i

diff ¤

diff(
    series1: Series | str,
    series2: Series | str,
    dataframe: DataFrame = None,
    name: str | None = None,
    prefix: str = "",
    inplace: bool = False,
    plot: bool | list[str] = False,
    plot_kwargs: dict | None = None,
) -> Series

Difference between 2 series

Parameters:

  • series1 (Series) –

    description

  • series2 (Series) –

    description

  • dataframe (DataFrame, default: None ) –

    description. Defaults to None.

  • name (str | None, default: None ) –

    description. Defaults to None.

  • prefix (str, default: '' ) –

    description. Defaults to "".

  • inplace (bool, default: False ) –

    description. Defaults to False.

  • plot (bool | list, default: False ) –

    description. Defaults to False.

  • plot_kwargs (dict | None, default: None ) –

    description. Defaults to None.

Raises:

Returns:

  • Series –

    pd.Series: Difference of 2 series (series1 - series2)

Source code in lettrade/indicator/series.py 
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def diff(
    series1: pd.Series | str,
    series2: pd.Series | str,
    dataframe: pd.DataFrame = None,
    name: str | None = None,
    prefix: str = "",
    inplace: bool = False,
    plot: bool | list[str] = False,
    plot_kwargs: dict | None = None,
    # **kwargs,
) -> pd.Series:
    """Difference between 2 series

    Args:
        series1 (pd.Series): _description_
        series2 (pd.Series): _description_
        dataframe (pd.DataFrame, optional): _description_. Defaults to None.
        name (str | None, optional): _description_. Defaults to None.
        prefix (str, optional): _description_. Defaults to "".
        inplace (bool, optional): _description_. Defaults to False.
        plot (bool | list, optional): _description_. Defaults to False.
        plot_kwargs (dict | None, optional): _description_. Defaults to None.

    Raises:
        RuntimeError: _description_

    Returns:
        pd.Series: Difference of 2 series (series1 - series2)
    """
    if __debug__:
        if plot and not inplace:
            raise RuntimeError("Cannot plot when inplace=False")

    if isinstance(series1, str):
        series1 = dataframe[series1]
    if isinstance(series2, str):
        series2 = dataframe[series2]

    i = series1 - series2

    if inplace:
        name = name or f"{prefix}diff"
        dataframe[name] = i

        if plot:
            _plot_mark(dataframe=dataframe, name=name, plot_kwargs=plot_kwargs)

    return i

direction ¤

direction(
    series1: Series | str,
    series2: Series | str,
    dataframe: DataFrame = None,
    name: str | None = None,
    prefix: str = "",
    inplace: bool = False,
    plot: bool | list[str] = False,
    plot_kwargs: dict | None = None,
) -> Series

Check a Series is direction another Series

Parameters:

  • series1 (Series) –

    first Series

  • series2 (Series) –

    second Series

Returns:

  • Series –

    pd.Series: -100 if series1 < series2, 100 if series1 > series2, else 0

Source code in lettrade/indicator/series.py 
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def direction(
    series1: pd.Series | str,
    series2: pd.Series | str,
    dataframe: pd.DataFrame = None,
    name: str | None = None,
    prefix: str = "",
    inplace: bool = False,
    plot: bool | list[str] = False,
    plot_kwargs: dict | None = None,
    # **kwargs,
) -> pd.Series:
    """Check a Series is direction another Series

    Args:
        series1 (pd.Series): first Series
        series2 (pd.Series): second Series

    Returns:
        pd.Series: -100 if series1 < series2, 100 if series1 > series2, else 0
    """
    if __debug__:
        if plot and not inplace:
            raise RuntimeError("Cannot plot when inplace=False")

    if isinstance(series1, str):
        series1 = dataframe[series1]
    if isinstance(series2, str):
        series2 = dataframe[series2]

    i = s_direction(series1, series2)

    if inplace:
        name = name or f"{prefix}direction"
        dataframe[name] = i

        if plot:
            _plot_mark(dataframe=dataframe, name=name, plot_kwargs=plot_kwargs)

    return i

ema ¤

ema(
    series: Series | str = "close",
    window: int = None,
    dataframe: DataFrame = None,
    name: str | None = None,
    prefix: str = "",
    inplace: bool = False,
    plot: bool | list[str] = False,
    plot_kwargs: dict | None = None,
    **kwargs
) -> Series | DataFrame

Exponential Moving Average

Parameters:

  • series (Series | str, default: 'close' ) –

    description. Defaults to "close".

  • window (int, default: None ) –

    description. Defaults to None.

  • dataframe (DataFrame, default: None ) –

    description. Defaults to None.

  • name (str | None, default: None ) –

    description. Defaults to None.

  • prefix (str, default: '' ) –

    description. Defaults to "".

  • inplace (bool, default: False ) –

    description. Defaults to False.

  • plot (bool | list, default: False ) –

    description. Defaults to False.

  • plot_kwargs (dict | None, default: None ) –

    description. Defaults to None.

Example 
df.i.ema(window=21, name="ema", inplace=True, plot=True)

Returns:

  • Series | DataFrame –

    pd.Series | pd.DataFrame: description

Source code in lettrade/indicator/trend/ma.py 
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def ema(
    series: pd.Series | str = "close",
    window: int = None,
    dataframe: pd.DataFrame = None,
    name: str | None = None,
    prefix: str = "",
    inplace: bool = False,
    plot: bool | list[str] = False,
    plot_kwargs: dict | None = None,
    **kwargs,
) -> pd.Series | pd.DataFrame:
    """Exponential Moving Average

    Args:
        series (pd.Series | str, optional): _description_. Defaults to "close".
        window (int, optional): _description_. Defaults to None.
        dataframe (pd.DataFrame, optional): _description_. Defaults to None.
        name (str | None, optional): _description_. Defaults to None.
        prefix (str, optional): _description_. Defaults to "".
        inplace (bool, optional): _description_. Defaults to False.
        plot (bool | list, optional): _description_. Defaults to False.
        plot_kwargs (dict | None, optional): _description_. Defaults to None.

    Example:
        ```python
        df.i.ema(window=21, name="ema", inplace=True, plot=True)
        ```

    Returns:
        pd.Series | pd.DataFrame: _description_
    """
    return ma(
        series=series,
        window=window,
        mode="ema",
        dataframe=dataframe,
        name=name,
        prefix=prefix,
        inplace=inplace,
        plot=plot,
        plot_kwargs=plot_kwargs,
        **kwargs,
    )

indicators_inject_pandas ¤

indicators_inject_pandas(obj: object | None = None)

Inject indicators to Pandas

Source code in lettrade/indicator/__init__.py 
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def indicators_inject_pandas(obj: object | None = None):
    """Inject indicators to Pandas"""
    if obj is None:
        from pandas.core.base import PandasObject

        obj = PandasObject

    # Flag to mark indicators injected
    if hasattr(obj, "_lt_indicators_injected"):
        if __debug__:
            print("[WARN] Re-injected indicators")
        return

    from .candlestick import pandas_inject as candlestick_pandas_inject
    from .dataframe import pandas_inject as dataframe_pandas_inject
    from .momentum import pandas_inject as momentum_pandas_inject
    from .series import pandas_inject as series_pandas_inject
    from .trend import pandas_inject as trend_pandas_inject
    from .volatility import pandas_inject as volatility_pandas_inject

    series_pandas_inject(obj)
    dataframe_pandas_inject(obj)

    candlestick_pandas_inject(obj)
    trend_pandas_inject(obj)
    volatility_pandas_inject(obj)
    momentum_pandas_inject(obj)

    # Flag to mark indicators injected
    obj._lt_indicators_injected = True

rolling_above ¤

rolling_above(
    series1: Series,
    series2: Series,
    window: int = 20,
    min_periods: int | None = None,
    dataframe: DataFrame = None,
    name: str | None = None,
    prefix: str = "",
    inplace: bool = False,
    plot: bool | list[str] = False,
    plot_kwargs: dict | None = None,
) -> Series

Check a Series is rolling above another Series

Parameters:

  • series1 (Series) –

    first Series

  • series2 (Series) –

    second Series

Returns:

  • Series –

    pd.Series: 100 mean series1 is rolling above series2 else 0

Source code in lettrade/indicator/series.py 
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def rolling_above(
    series1: pd.Series,
    series2: pd.Series,
    window: int = 20,
    min_periods: int | None = None,
    dataframe: pd.DataFrame = None,
    name: str | None = None,
    prefix: str = "",
    inplace: bool = False,
    plot: bool | list[str] = False,
    plot_kwargs: dict | None = None,
    # **kwargs,
) -> pd.Series:
    """Check a Series is rolling above another Series

    Args:
        series1 (pd.Series): first Series
        series2 (pd.Series): second Series

    Returns:
        pd.Series: 100 mean series1 is rolling above series2 else 0
    """
    if __debug__:
        if plot and not inplace:
            raise RuntimeError("Cannot plot when inplace=False")

    if isinstance(series1, str):
        series1 = dataframe[series1]
    if isinstance(series2, str):
        series2 = dataframe[series2]

    min_periods = window if min_periods is None else min_periods

    i = s_above(series1, series2)
    i = i.rolling(window=window, min_periods=min_periods).min()
    i = i.apply(lambda v: 100 if v >= 100 else 0).astype(int)

    if inplace:
        name = name or f"{prefix}rolling_above"
        dataframe[name] = i

        if plot:
            _plot_mark(dataframe=dataframe, name=name, plot_kwargs=plot_kwargs)

    return i

rolling_below ¤

rolling_below(
    series1: Series,
    series2: Series,
    window: int = 20,
    min_periods: int | None = None,
    dataframe: DataFrame = None,
    name: str | None = None,
    prefix: str = "",
    inplace: bool = False,
    plot: bool | list[str] = False,
    plot_kwargs: dict | None = None,
) -> Series

Check a Series is rolling below another Series

Parameters:

  • series1 (Series) –

    first Series

  • series2 (Series) –

    second Series

Returns:

  • Series –

    pd.Series: -100 mean series1 is rolling below series2 else 0

Source code in lettrade/indicator/series.py 
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def rolling_below(
    series1: pd.Series,
    series2: pd.Series,
    window: int = 20,
    min_periods: int | None = None,
    dataframe: pd.DataFrame = None,
    name: str | None = None,
    prefix: str = "",
    inplace: bool = False,
    plot: bool | list[str] = False,
    plot_kwargs: dict | None = None,
    # **kwargs,
) -> pd.Series:
    """Check a Series is rolling below another Series

    Args:
        series1 (pd.Series): first Series
        series2 (pd.Series): second Series

    Returns:
        pd.Series: -100 mean series1 is rolling below series2 else 0
    """
    if __debug__:
        if plot and not inplace:
            raise RuntimeError("Cannot plot when inplace=False")

    if isinstance(series1, str):
        series1 = dataframe[series1]
    if isinstance(series2, str):
        series2 = dataframe[series2]

    min_periods = window if min_periods is None else min_periods

    i = s_below(series1, series2)
    i = i.rolling(window=window, min_periods=min_periods).max()
    i = i.apply(lambda v: -100 if v <= -100 else 0).astype(int)

    if inplace:
        name = name or f"{prefix}rolling_below"
        dataframe[name] = i

        if plot:
            _plot_mark(dataframe=dataframe, name=name, plot_kwargs=plot_kwargs)

    return i

rolling_direction ¤

rolling_direction(
    series1: Series,
    series2: Series,
    window: int = 20,
    min_periods: int | None = None,
    dataframe: DataFrame = None,
    name: str | None = None,
    prefix: str = "",
    inplace: bool = False,
    plot: bool | list[str] = False,
    plot_kwargs: dict | None = None,
) -> Series

Check a Series is rolling on one side with another Series

Parameters:

  • series1 (Series) –

    first Series

  • series2 (Series) –

    second Series

Returns:

  • Series –

    pd.Series: 100 mean series1 keep consistences above series2 at least window bars -100 mean series1 keep consistences below series2 at least window bars 0 else cases

Source code in lettrade/indicator/series.py 
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def rolling_direction(
    series1: pd.Series,
    series2: pd.Series,
    window: int = 20,
    min_periods: int | None = None,
    dataframe: pd.DataFrame = None,
    name: str | None = None,
    prefix: str = "",
    inplace: bool = False,
    plot: bool | list[str] = False,
    plot_kwargs: dict | None = None,
    # **kwargs,
) -> pd.Series:
    """Check a Series is rolling on one side with another Series

    Args:
        series1 (pd.Series): first Series
        series2 (pd.Series): second Series

    Returns:
        pd.Series:  100 mean series1 keep consistences above series2 at least `window` bars
                    -100 mean series1 keep consistences below series2 at least `window` bars
                    0 else cases
    """
    if __debug__:
        if plot and not inplace:
            raise RuntimeError("Cannot plot when inplace=False")

    if isinstance(series1, str):
        series1 = dataframe[series1]
    if isinstance(series2, str):
        series2 = dataframe[series2]

    min_periods = window if min_periods is None else min_periods

    i = s_direction(series1, series2)
    i = i.rolling(window=window, min_periods=min_periods).mean()
    i = i.apply(lambda v: -100 if v <= -100 else 100 if v >= 100 else 0).astype(int)

    if inplace:
        name = name or f"{prefix}rolling_direction"
        dataframe[name] = i

        if plot:
            _plot_mark(dataframe=dataframe, name=name, plot_kwargs=plot_kwargs)

    return i

signal_condiction ¤

signal_condiction(
    dataframe: DataFrame,
    condictions: list[dict],
    name: str,
    value: int | float = np.nan,
    inplace: bool = False,
    plot: bool | list[str] = False,
    plot_type: Literal["line", "mark"] = "mark",
    **kwargs
) -> Series | DataFrame

Define a signal with multiple condiction

Parameters:

  • dataframe (DataFrame) –

    description

  • condictions (list[list[Series | Any]]) –

    Pairs of condiction [<pandas.Series condiction>, <value>]

  • name (str) –

    Name of signal, column name when add to DataFrame with inplace=True.

  • value (int, default: nan ) –

    Default value when condiction is not matched. Defaults to 0.

  • inplace (bool, default: False ) –

    description. Defaults to False.

  • plot (bool | list, default: False ) –

    description. Defaults to False.

  • plot_type (Literal['line', 'mark'], default: 'mark' ) –

    description. Defaults to "line".

Usage 
df.i.signal_condiction(
    [df["close"] > df["open"], 100],
    [df["close"] < df["open"], -100],
    name="cdl_direction",
    inplace=True,
    plot=True,
)

Raises:

Returns:

  • Series | DataFrame –

    pd.Series | pd.DataFrame: description

Source code in lettrade/indicator/dataframe.py 
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def signal_condiction(
    dataframe: pd.DataFrame,
    condictions: list[dict],
    name: str,
    value: int | float = np.nan,
    inplace: bool = False,
    plot: bool | list[str] = False,
    plot_type: Literal["line", "mark"] = "mark",
    **kwargs,
) -> pd.Series | pd.DataFrame:
    """Define a signal with multiple condiction

    Args:
        dataframe (pd.DataFrame): _description_
        condictions (list[list[pd.Series | Any]]): Pairs of condiction [`<pandas.Series condiction>`, `<value>`]
        name (str): Name of signal, column name when add to DataFrame with inplace=True.
        value (int, optional): Default value when condiction is not matched. Defaults to 0.
        inplace (bool, optional): _description_. Defaults to False.
        plot (bool | list, optional): _description_. Defaults to False.
        plot_type (Literal["line", "mark"], optional): _description_. Defaults to "line".

    Usage:
        ```python
        df.i.signal_condiction(
            [df["close"] > df["open"], 100],
            [df["close"] < df["open"], -100],
            name="cdl_direction",
            inplace=True,
            plot=True,
        )
        ```

    Raises:
        RuntimeError: _description_

    Returns:
        pd.Series | pd.DataFrame: _description_
    """
    if __debug__:
        if not isinstance(dataframe, pd.DataFrame):
            raise RuntimeError(
                f"dataframe type '{type(dataframe)}' "
                "is not instance of pandas.DataFrame"
            )

    # Series
    indicators = []
    plots = {}
    for condiction in condictions:
        series_value = pd.to_numeric(condiction["value"], errors="coerce")
        series_index = dataframe.loc[condiction["series"]].index
        series = pd.Series(
            series_value,
            index=series_index,
            name=condiction["name"],
            **kwargs,
        )
        indicators.append(series)

        if plot and "plot_kwargs" in condiction:
            plots[condiction["name"]] = condiction["plot_kwargs"]

    # Plot
    if plot:
        from lettrade.indicator.plot import IndicatorPlotter
        from lettrade.plot.plotly import plot_line, plot_mark

        for series in indicators:
            if series.name not in plots:
                continue

            plot_kwargs = plots[series.name]
            plot_kwargs.update(series=series, name=series.name)

            plotter = plot_mark if plot_type == "mark" else plot_line
            IndicatorPlotter(dataframe=dataframe, plotter=plotter, **plot_kwargs)

    # Merge
    series = pd.Series(value, index=dataframe.index, name=name, **kwargs)
    for s in indicators:
        series.update(s)

    if inplace:
        dataframe[name] = series
        return dataframe

    return series

signal_direction ¤

signal_direction(
    dataframe: DataFrame,
    up: Series,
    down: Series,
    name: str = "direction",
    value: int = 0,
    value_up: int = 100,
    value_down: int = -100,
    inplace: bool = False,
    plot: bool | list[str] = False,
    plot_type: Literal["line", "mark"] = "mark",
    plot_up_kwargs: dict | None = None,
    plot_down_kwargs: dict | None = None,
    **kwargs
) -> Series | DataFrame

Define a signal with 2 direction Up and Down with fixed value

Parameters:

  • dataframe (DataFrame) –

    description

  • up (Series) –

    description

  • down (Series) –

    description

  • name (str, default: 'direction' ) –

    Name of signal, column name when add to DataFrame with inplace=True.

  • value (int, default: 0 ) –

    Default value when condiction is not matched. Defaults to 0.

  • value_up (int, default: 100 ) –

    description. Defaults to 100.

  • value_down (int, default: -100 ) –

    description. Defaults to -100.

  • inplace (bool, default: False ) –

    Whether to add to the DataFrame and return DataFrame rather than return result. Defaults to False.

  • plot (bool | list[str], default: False ) –

    description. Defaults to False.

  • plot_type (Literal['line', 'mark'], default: 'mark' ) –

    description. Defaults to "mark".

  • plot_up_kwargs (dict | None, default: None ) –

    description. Defaults to None.

  • plot_down_kwargs (dict | None, default: None ) –

    description. Defaults to None.

Returns:

  • Series | DataFrame –

    pd.Series | pd.DataFrame: description

Source code in lettrade/indicator/dataframe.py 
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def signal_direction(
    dataframe: pd.DataFrame,
    up: pd.Series,
    down: pd.Series,
    name: str = "direction",
    value: int = 0,
    value_up: int = 100,
    value_down: int = -100,
    inplace: bool = False,
    plot: bool | list[str] = False,
    plot_type: Literal["line", "mark"] = "mark",
    plot_up_kwargs: dict | None = None,
    plot_down_kwargs: dict | None = None,
    **kwargs,
) -> pd.Series | pd.DataFrame:
    """Define a signal with 2 direction Up and Down with fixed value

    Args:
        dataframe (pd.DataFrame): _description_
        up (pd.Series): _description_
        down (pd.Series): _description_
        name (str): Name of signal, column name when add to DataFrame with inplace=True.
        value (int, optional): Default value when condiction is not matched. Defaults to 0.
        value_up (int, optional): _description_. Defaults to 100.
        value_down (int, optional): _description_. Defaults to -100.
        inplace (bool, optional): Whether to add to the DataFrame and return DataFrame rather than return result. Defaults to False.
        plot (bool | list[str], optional): _description_. Defaults to False.
        plot_type (Literal["line", "mark"], optional): _description_. Defaults to "mark".
        plot_up_kwargs (dict | None, optional): _description_. Defaults to None.
        plot_down_kwargs (dict | None, optional): _description_. Defaults to None.

    Returns:
        pd.Series | pd.DataFrame: _description_
    """

    # Up
    if plot_up_kwargs is None:
        plot_up_kwargs = dict()
    plot_up_kwargs.setdefault("color", PlotColor.CYAN)

    # Down
    if plot_down_kwargs is None:
        plot_down_kwargs = dict()
    plot_down_kwargs.setdefault("color", PlotColor.ORANGE)

    return signal_condiction(
        dataframe=dataframe,
        condictions=[
            dict(
                series=up,
                value=value_up,
                name=f"{name}_up",
                plot_kwargs=plot_up_kwargs,
            ),
            dict(
                series=down,
                value=value_down,
                name=f"{name}_down",
                plot_kwargs=plot_down_kwargs,
            ),
        ],
        name=name,
        value=value,
        inplace=inplace,
        plot=plot,
        plot_type=plot_type,
        **kwargs,
    )

signal_exist ¤

signal_exist(
    dataframe: DataFrame,
    series: Series,
    window: int,
    value_exist_up: int = 100,
    value_exist_down: int = -100,
    name: str = "exist",
    value_up: int = 100,
    value_down: int = -100,
    inplace: bool = False,
    plot: bool | list[str] = False,
    plot_up_kwargs: dict | None = None,
    plot_down_kwargs: dict | None = None,
    **kwargs
) -> Series | DataFrame

summary

Parameters:

  • dataframe (DataFrame) –

    description

  • series (Series) –

    description

  • window (int) –

    description

  • value_exist_up (int, default: 100 ) –

    description. Defaults to 100.

  • value_exist_down (int, default: -100 ) –

    description. Defaults to -100.

  • name (str, default: 'exist' ) –

    description. Defaults to "exist".

  • value_up (int, default: 100 ) –

    description. Defaults to 100.

  • value_down (int, default: -100 ) –

    description. Defaults to -100.

  • inplace (bool, default: False ) –

    description. Defaults to False.

  • plot (bool | list[str], default: False ) –

    description. Defaults to False.

  • plot_up_kwargs (dict | None, default: None ) –

    description. Defaults to None.

  • plot_down_kwargs (dict | None, default: None ) –

    description. Defaults to None.

Returns:

  • Series | DataFrame –

    pd.Series | pd.DataFrame: description

Source code in lettrade/indicator/dataframe.py 
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def signal_exist(
    dataframe: pd.DataFrame,
    series: pd.Series,
    window: int,
    value_exist_up: int = 100,
    value_exist_down: int = -100,
    name: str = "exist",
    value_up: int = 100,
    value_down: int = -100,
    inplace: bool = False,
    plot: bool | list[str] = False,
    plot_up_kwargs: dict | None = None,
    plot_down_kwargs: dict | None = None,
    **kwargs,
) -> pd.Series | pd.DataFrame:
    """_summary_

    Args:
        dataframe (pd.DataFrame): _description_
        series (pd.Series): _description_
        window (int): _description_
        value_exist_up (int, optional): _description_. Defaults to 100.
        value_exist_down (int, optional): _description_. Defaults to -100.
        name (str, optional): _description_. Defaults to "exist".
        value_up (int, optional): _description_. Defaults to 100.
        value_down (int, optional): _description_. Defaults to -100.
        inplace (bool, optional): _description_. Defaults to False.
        plot (bool | list[str], optional): _description_. Defaults to False.
        plot_up_kwargs (dict | None, optional): _description_. Defaults to None.
        plot_down_kwargs (dict | None, optional): _description_. Defaults to None.

    Returns:
        pd.Series | pd.DataFrame: _description_
    """
    up_rolling_max = series.rolling(window=window).max()
    down_rolling_min = series.rolling(window=window).min()

    signal = signal_direction(
        dataframe=dataframe,
        up=(up_rolling_max >= value_exist_up),
        down=(down_rolling_min <= value_exist_down),
        name=name,
        value_up=value_up,
        value_down=value_down,
        inplace=inplace,
        plot=plot,
        plot_up_kwargs=plot_up_kwargs,
        plot_down_kwargs=plot_down_kwargs,
        **kwargs,
    )
    return signal

signal_repeat ¤

signal_repeat(
    dataframe: DataFrame,
    series: Series,
    window: int,
    value_repeat_up: int = 100,
    value_repeat_down: int = -100,
    name: str = "repeat",
    value_up: int = 100,
    value_down: int = -100,
    inplace: bool = False,
    plot: bool | list[str] = False,
    plot_up_kwargs: dict | None = None,
    plot_down_kwargs: dict | None = None,
    **kwargs
) -> Series | DataFrame

summary

Parameters:

  • dataframe (DataFrame) –

    description

  • series (Series) –

    description

  • window (int) –

    description

  • value_repeat_up (int, default: 100 ) –

    description. Defaults to 100.

  • value_repeat_down (int, default: -100 ) –

    description. Defaults to -100.

  • name (str, default: 'repeat' ) –

    description. Defaults to "repeat".

  • value_up (int, default: 100 ) –

    description. Defaults to 100.

  • value_down (int, default: -100 ) –

    description. Defaults to -100.

  • inplace (bool, default: False ) –

    description. Defaults to False.

  • plot (bool | list[str], default: False ) –

    description. Defaults to False.

  • plot_up_kwargs (dict | None, default: None ) –

    description. Defaults to None.

  • plot_down_kwargs (dict | None, default: None ) –

    description. Defaults to None.

Returns:

  • Series | DataFrame –

    pd.Series | pd.DataFrame: description

Source code in lettrade/indicator/dataframe.py 
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def signal_repeat(
    dataframe: pd.DataFrame,
    series: pd.Series,
    window: int,
    value_repeat_up: int = 100,
    value_repeat_down: int = -100,
    name: str = "repeat",
    value_up: int = 100,
    value_down: int = -100,
    inplace: bool = False,
    plot: bool | list[str] = False,
    plot_up_kwargs: dict | None = None,
    plot_down_kwargs: dict | None = None,
    **kwargs,
) -> pd.Series | pd.DataFrame:
    """_summary_

    Args:
        dataframe (pd.DataFrame): _description_
        series (pd.Series): _description_
        window (int): _description_
        value_repeat_up (int, optional): _description_. Defaults to 100.
        value_repeat_down (int, optional): _description_. Defaults to -100.
        name (str, optional): _description_. Defaults to "repeat".
        value_up (int, optional): _description_. Defaults to 100.
        value_down (int, optional): _description_. Defaults to -100.
        inplace (bool, optional): _description_. Defaults to False.
        plot (bool | list[str], optional): _description_. Defaults to False.
        plot_up_kwargs (dict | None, optional): _description_. Defaults to None.
        plot_down_kwargs (dict | None, optional): _description_. Defaults to None.

    Returns:
        pd.Series | pd.DataFrame: _description_
    """
    up_rolling_min = series.rolling(window=window).min()
    down_rolling_max = series.rolling(window=window).max()

    signal = signal_direction(
        up=(up_rolling_min >= value_repeat_up),
        down=(down_rolling_max <= value_repeat_down),
        dataframe=dataframe,
        name=name,
        value_up=value_up,
        value_down=value_down,
        inplace=inplace,
        plot=plot,
        plot_up_kwargs=plot_up_kwargs,
        plot_down_kwargs=plot_down_kwargs,
        **kwargs,
    )
    return signal