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df = pd.read_csv(path2)
if df.shape[0] < max(28, 48, 14, 21):
    df_add = pd.read_csv(path1)
    df = df_add.append(df, ignore_index=True)

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df = df_add.append(df, ignore_index=True)

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df.append({'RSI': 100, 'EMA_UP': 50}, ignore_index=True)
print(df)

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df = pd.read_csv(path_storage('Historical-Data', 0, symbol, interval))
if df.shape[0] < max(period_l_t, period_l_a, period_u_a, period_u_t):
    df_add = pd.read_csv(path_storage('Historical-Data', 1, symbol, interval))
    df = df_add.append(df, ignore_index=True)


def on_message(wsapp, message):
	#   Receiving data from websocket request message (every ~~250ms).
    stream_data = json.loads(message)  # raw Data send back from websocket for the recent active candle.

    #   Process the data from the websocket stream.
    if stream_data['k']['x']:  # the send datapackage does contain the candle closing data.
        rsi_5m = shortterm_rsi(float(stream_data['k']['c']),
                               df['CLOSES'].iloc[-1],
                               period_length_5m_rsi,
                               df['EMA_UP'].iloc[-1],
                               df['EMA_DOWN'].iloc[-1])
        df = df.append({'DATE': datetime.fromtimestamp(int(((stream_data['k']['t']) * 0.001))),
                        'OPEN': stream_data['k']['o'],
                        'HIGH': stream_data['k']['h'],
                        'LOW': stream_data['k']['l'],
                        'CLOSES': float(stream_data['k']['c']),
                        'EMA_UP': rsi_5m[1],
                        'EMA_DOWN': rsi_5m[2],
                        'RSI': rsi_5m[0]
                        }, ignore_index=True)
                        
        df = df.drop([0])

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