util.py 文件源码

def applyFeatures(dataset, delta):
    """
    applies rolling mean and delayed returns to each dataframe in the list
    """
    columns = dataset.columns
    close = columns[-3]
    returns = columns[-1]
    for n in delta:
        addFeatures(dataset, close, returns, n)

    dataset = dataset.drop(dataset.index[0:max(delta)]) #drop NaN due to delta spanning

    # normalize columns
    scaler = preprocessing.MinMaxScaler()
    return pd.DataFrame(scaler.fit_transform(dataset),\
            columns=dataset.columns, index=dataset.index)