MACD_EMA_SHORT is only a class method

• you can't get it, unless you update the class
  • you need to return fast = df[ema_short]
• MACD_EMA_SHORT is a parameter used for a calculation in _get_macd
  • MACD_EMA_SHORT = 12
  • ema_short = 'close_{}_ema'.format(cls.MACD_EMA_SHORT)
  • ema_short = 'close_12_ema'

class StockDataFrame(pd.DataFrame):
    OPERATORS = ['le', 'ge', 'lt', 'gt', 'eq', 'ne']

    # Start of options.
    KDJ_PARAM = (2.0 / 3.0, 1.0 / 3.0)
    KDJ_WINDOW = 9

    BOLL_PERIOD = 20
    BOLL_STD_TIMES = 2

    MACD_EMA_SHORT = 12
    MACD_EMA_LONG = 26
    MACD_EMA_SIGNAL = 9

    @classmethod
    def _get_macd(cls, df):
        """ Moving Average Convergence Divergence
        This function will initialize all following columns.
        MACD Line (macd): (12-day EMA - 26-day EMA)
        Signal Line (macds): 9-day EMA of MACD Line
        MACD Histogram (macdh): MACD Line - Signal Line
        :param df: data
        :return: None
        """
        ema_short = 'close_{}_ema'.format(cls.MACD_EMA_SHORT)
        ema_long = 'close_{}_ema'.format(cls.MACD_EMA_LONG)
        ema_signal = 'macd_{}_ema'.format(cls.MACD_EMA_SIGNAL)
        fast = df[ema_short]
        slow = df[ema_long]
        df['macd'] = fast - slow
        df['macds'] = df[ema_signal]
        df['macdh'] = (df['macd'] - df['macds'])
        log.critical("NOTE: Behavior of MACDH calculation has changed as of "
                     "July 2017 - it is now 1/2 of previous calculated values")
        cls._drop_columns(df, [ema_short, ema_long, ema_signal])

Update:

• find stockstats.py, then in def _get_macd(cls, df), comment out cls._drop_columns(df, [ema_short, ema_long, ema_signal]) (e.g. put # in front of it)
• Then you can do stock['close_12_ema']

Code to get the table:

periods = '3600'
resp = requests.get('https://api.cryptowat.ch/markets/poloniex/ethusdt/ohlc', params={'periods': periods})
data = resp.json()
df = pd.DataFrame(data['result'][periods], columns=['date', 'open', 'high', 'low', 'close', 'volume', 'amount'])
df['date'] = pd.to_datetime(df['date'], unit='s')

stock = sdf.retype(df)
print(stock['macds'])

print(stock)

• The extra columns don't get added until you do stock['macds'].

OUtput:

                           open        high         low       close      volume        amount  close_12_ema  close_26_ema      macd  macd_9_ema     macds     macdh
date                                                                                                                                                               
2019-08-20 00:00:00  201.000000  203.379326  201.000000  202.138224  349.209128  70720.937575    202.138224    202.138224  0.000000    0.000000  0.000000  0.000000
2019-08-20 01:00:00  202.187160  202.650000  200.701061  200.778709  329.485014  66411.899720    201.401820    201.432322 -0.030502   -0.016946 -0.016946 -0.013556
2019-08-20 02:00:00  201.200000  201.558777  200.133667  200.338312   12.812929   2572.209909    200.986733    201.039255 -0.052522   -0.031526 -0.031526 -0.020996
2019-08-20 03:00:00  200.915590  201.177018  200.396571  200.440000   21.910910   4395.692727    200.814151    200.871730 -0.057579   -0.040352 -0.040352 -0.017227
2019-08-20 04:00:00  200.979999  200.979999  198.282603  198.644618  360.432424  71712.376256    200.224696    200.355253 -0.130557   -0.067186 -0.067186 -0.063371

Here you go, with explanation in comments.

import pandas as pd
from stockstats import StockDataFrame as Sdf

data   = pd.read_csv('data.csv')

stock  = Sdf.retype(data)

signal = stock['macds']        # Your signal line
macd   = stock['macd']         # The MACD that need to cross the signal line
#                                              to give you a Buy/Sell signal
listLongShort = ["No data"]    # Since you need at least two days in the for loop

for i in range(1, len(signal)):
    #                          # If the MACD crosses the signal line upward
    if macd[i] > signal[i] and macd[i - 1] <= signal[i - 1]:
        listLongShort.append("BUY")
    #                          # The other way around
    elif macd[i] < signal[i] and macd[i - 1] >= signal[i - 1]:
        listLongShort.append("SELL")
    #                          # Do nothing if not crossed
    else:
        listLongShort.append("HOLD")

stock['Advice'] = listLongShort

# The advice column means "Buy/Sell/Hold" at the end of this day or
#  at the beginning of the next day, since the market will be closed

print(stock['Advice'])