I am using the following library to fill a Dataframe with modified data (indicator of financial data) https://technical-analysis-library-in-python.readthedocs.io/en/latest/

However, the library has a number of classes that seem to miss certain attributes; or lack the inheritance from another class.

I have created a pandas.Series filled with ones to demonstrate. I call the method aroon_up() from class AroonIndicator with the aforementioned series as input, but I get a 'Series' object has no attribute '_check_fillna'" error. I see that there is no attribute _check_fillna in the AroonIndicator class, but there is in the IndicatorMixin. I have tried to run the Series through the IndicatorMixin class, but it states that this class takes no arguments.

Can someone explain to me what I am doing wrong?

Library

class IndicatorMixin:
"""Util mixin indicator class"""

_fillna = False

def _check_fillna(self, series: pd.Series, value: int = 0) -> pd.Series:
    """Check if fillna flag is True.

    Args:
        series(pandas.Series): calculated indicator series.
        value(int): value to fill gaps; if -1 fill values using 'backfill' mode.

    Returns:
        pandas.Series: New feature generated.
    """
    if self._fillna:
        series_output = series.copy(deep=False)
        series_output = series_output.replace([np.inf, -np.inf], np.nan)
        if isinstance(value, int) and value == -1:
            series = series_output.fillna(method="ffill").fillna(method='bfill')
        else:
            series = series_output.fillna(method="ffill").fillna(value)
    return series

@staticmethod
def _true_range(
    high: pd.Series, low: pd.Series, prev_close: pd.Series
) -> pd.Series:
    tr1 = high - low
    tr2 = (high - prev_close).abs()
    tr3 = (low - prev_close).abs()
    true_range = pd.DataFrame(data={"tr1": tr1, "tr2": tr2, "tr3": tr3}).max(axis=1)
    return true_range

class AroonIndicator(IndicatorMixin):
"""Aroon Indicator

Identify when trends are likely to change direction.

Aroon Up = ((N - Days Since N-day High) / N) x 100
Aroon Down = ((N - Days Since N-day Low) / N) x 100
Aroon Indicator = Aroon Up - Aroon Down

https://www.investopedia.com/terms/a/aroon.asp

Args:
    close(pandas.Series): dataset 'Close' column.
    window(int): n period.
    fillna(bool): if True, fill nan values.
"""

def __init__(self, close: pd.Series, window: int = 25, fillna: bool = False):
    self._close = close
    self._window = window
    self._fillna = fillna
    # self._check_fillna = checkfillna
    self._run()
    self._check_fillna(IndicatorMixin._check_fillna())

def _run(self):
    min_periods = 0 if self._fillna else self._window
    rolling_close = self._close.rolling(
        self._window, min_periods=min_periods)
    self._aroon_up = rolling_close.apply(
        lambda x: float(np.argmax(x)   1) / self._window * 100, raw=True
    )

def aroon_up(self) -> pd.Series:
    """Aroon Up Channel

    Returns:
        pandas.Series: New feature generated.
    """
    aroon_up_series = self._check_fillna(self._aroon_up, value=0)
    return pd.Series(aroon_up_series, name=f"aroon_up_{self._window}")

My program

# Create an empty DataFrame
table = pd.DataFrame()

# Create a serie of ones
list = np.ones((100))
sr = pd.Series(list)
# fill the empty Dataframe with the indicator of the Series
'try 1:'
table['numbers'] = AroonIndicator.aroon_up(sr)

'try 2:'
table['numbers'] = AroonIndicator.aroon_up(IndicatorMixin(sr))

# print the table
print(table)

CodePudding user response：

The Aroon functions return values as panda Series, however you are trying to assign the results to the 'table' variable, which you have initialized as a DataFrame.

Also, when the only parameter you can pass to a function is 'self', you do not include a parameter when you call the function.

Lastly, don't use reserved words like 'list' for variable names.

Try:

import pandas as pd
import numpy as np

list_values = pd.Series(np.ones(100))

sr = AroonIndicator(list_values)

sr = sr.aroon_up()

print(sr)