Technical Analysis using embedPy

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https://learninghub.kx.com/forums/topic/technical-analysis-using-embedpy

Hello All,

I’m just starting out with embedPy and wondering if aoneone can help. I’m trying to use a module in python for some technical analysis.

I was trying to use this module

https://technical-analysis-library-in-python.readthedocs.io/en/latest/

I’ve just got some bar data something like

t:(sym:30#`A;open:30?50f;high:30?50f;low:30?50f;close:30?50f;vol:30?10000)

I’m having some difficulty passing the dataframe back and forth and can’t seem to get it to work. Wondering if someone could help me through this first example on their website, making this work properly from q.

import pandas as pd from ta.utils 
import dropna from ta.volatility 
import BollingerBands 
# Load datas 
df = pd.read_csv('ta/tests/data/datas.csv', sep=',') 
# Clean NaN values 
df = dropna(df) 
# Initialize Bollinger Bands Indicator 
indicator_bb = BollingerBands(close=df["Close"], window=20, window_dev=2) 
# Add Bollinger Bands features 
df['bb_bbm'] = indicator_bb.bollinger_mavg() 
df['bb_bbh'] = indicator_bb.bollinger_hband() 
df['bb_bbl'] = indicator_bb.bollinger_lband() 
# Add Bollinger Band high indicator 
df['bb_bbhi'] = indicator_bb.bollinger_hband_indicator() 
# Add Bollinger Band low indicator 
df['bb_bbli'] = indicator_bb.bollinger_lband_indicator()

 

Many thanks!

 

2

FYI if anyone is interested I was able to get this working now

py script

import pandas as pd from ta.utils 
import dropna from ta.volatility 
import BollingerBands 
def returnBB(df, window=20, window_dev=2): 
    indicator_bb = BollingerBands(close=df["close"], window=20, window_dev=2) 
    # Add Bollinger Bands features 
    df['bb_bbm'] = indicator_bb.bollinger_mavg() 
    df['bb_bbh'] = indicator_bb.bollinger_hband() 
    df['bb_bbl'] = indicator_bb.bollinger_lband() 
    # Add Bollinger Band high indicator 
    df['bb_bbhi'] = indicator_bb.bollinger_hband_indicator() 
    # Add Bollinger Band low indicator 
    df['bb_bbli'] = indicator_bb.bollinger_lband_indicator() 
return df

and then q script

//load above .p script l bb.p

//make returnBB py func callable in q

func:.p.get`returnBB

//conv t to dataframe, pass to the py func and then conv back to qtable .ml.df2tab[func[.ml.tab2df[t]]]