示例#1
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def add_volume_ta(df: pd.DataFrame, high: str, low: str, close: str, volume: str,
                  fillna: bool = False, colprefix: str = "") -> pd.DataFrame:
    """Add volume technical analysis features to dataframe.

    Args:
        df (pandas.core.frame.DataFrame): Dataframe base.
        high (str): Name of 'high' column.
        low (str): Name of 'low' column.
        close (str): Name of 'close' column.
        volume (str): Name of 'volume' column.
        fillna(bool): if True, fill nan values.
        colprefix(str): Prefix column names inserted

    Returns:
        pandas.core.frame.DataFrame: Dataframe with new features.
    """

    # Accumulation Distribution Index
    df[f'{colprefix}volume_adi'] = AccDistIndexIndicator(
        high=df[high], low=df[low], close=df[close], volume=df[volume], fillna=fillna).acc_dist_index()

    # On Balance Volume
    df[f'{colprefix}volume_obv'] = OnBalanceVolumeIndicator(
        close=df[close], volume=df[volume], fillna=fillna).on_balance_volume()

    # Chaikin Money Flow
    df[f'{colprefix}volume_cmf'] = ChaikinMoneyFlowIndicator(
        high=df[high], low=df[low], close=df[close], volume=df[volume], fillna=fillna).chaikin_money_flow()

    # Force Index
    df[f'{colprefix}volume_fi'] = ForceIndexIndicator(
        close=df[close], volume=df[volume], n=13, fillna=fillna).force_index()

    # Money Flow Indicator
    df[f'{colprefix}volume_mfi'] = MFIIndicator(
        high=df[high], low=df[low], close=df[close], volume=df[volume], n=14, fillna=fillna).money_flow_index()

    # Ease of Movement
    indicator = EaseOfMovementIndicator(high=df[high], low=df[low], volume=df[volume], n=14, fillna=fillna)
    df[f'{colprefix}volume_em'] = indicator.ease_of_movement()
    df[f'{colprefix}volume_sma_em'] = indicator.sma_ease_of_movement()

    # Volume Price Trend
    df[f'{colprefix}volume_vpt'] = VolumePriceTrendIndicator(
        close=df[close], volume=df[volume], fillna=fillna).volume_price_trend()

    # Negative Volume Index
    df[f'{colprefix}volume_nvi'] = NegativeVolumeIndexIndicator(
        close=df[close], volume=df[volume], fillna=fillna).negative_volume_index()

    # Volume Weighted Average Price
    df[f'{colprefix}volume_vwap'] = VolumeWeightedAveragePrice(
        high=df[high], low=df[low], close=df[close], volume=df[volume], n=14, fillna=fillna
    ).volume_weighted_average_price()

    return df
示例#2
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 def test_sma_ease_of_movement2(self):
     target = 'SMA_EMV'
     result = EaseOfMovementIndicator(high=self._df['High'],
                                      low=self._df['Low'],
                                      volume=self._df['Volume'],
                                      n=14,
                                      fillna=False).sma_ease_of_movement()
     pd.testing.assert_series_equal(self._df[target].tail(),
                                    result.tail(),
                                    check_names=False)
示例#3
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 def setUpClass(cls):
     cls._df = pd.read_csv(cls._filename, sep=',')
     cls._params = dict(high=cls._df['High'],
                        low=cls._df['Low'],
                        volume=cls._df['Volume'],
                        n=14,
                        fillna=False)
     cls._indicator = EaseOfMovementIndicator(**cls._params)
示例#4
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 def setUpClass(cls):
     cls._df = pd.read_csv(cls._filename, sep=",")
     cls._params = dict(
         high=cls._df["High"],
         low=cls._df["Low"],
         volume=cls._df["Volume"],
         window=14,
         fillna=False,
     )
     cls._indicator = EaseOfMovementIndicator(**cls._params)