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How to use the talib.SMA() on a DataFrame with multiple stocks?

Normally I use the talib on a single stock. I wonder how to use it on a DataFrame with multiple stocks as described in notebook.

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8 responses

Try this:

mySMA = data.rolling(window=10).mean()  
mySMA.tail(25)  

For SMA one can use the mean(). But if I want to calculate the EMA, MACD, etc? And if I do want to use the talib? Seems not possible? Assumed I have the 'open', 'low' etc.

I've tried using the pd. apply(), but it seems I can't overhand the paerameter such the preiod length.

Here the updated notebook.

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how to overhand the period 30 as argument/parameter?

Try this:

ma1_list = data.apply(myMA1).dropna()  
ma1_list  

Bit in this form the function myMA1 is not reusebal. I mean if I want to calculate the EMA with period of 50, 100? I can't overhand this parameter to the myMA1().

Try this:

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Arguments can be passed to an 'applied' function by using the args parameter. See the pandas 0.18 docs for the apply method https://pandas.pydata.org/pandas-docs/version/0.18/generated/pandas.DataFrame.apply.html .

So, the following will generate the 50 day and 100 day SMA for 'SSO' and 'SDS' using the talib library.

import talib

start = '2018-08-01'  
end = '2019-08-30'

assets = ['SSO', 'SDS']

data = get_pricing(assets, start_date=start, end_date=end, frequency='daily', fields='close_price')

sma_50 = data.apply(talib.SMA, args=(50,))  
sma_100 = data.apply(talib.SMA, args=(100,))


A few things to notice. The comma after the final arg is required (ie 50, ). Don't forget that. The apply method in ver 0.18 will create a new dataframe. One would need to manually merge it with the original dataframe if one wants all the data in one place. If one just wants the latest SMA as a number then use the tail or the ilocmethods. These will return the same values just formatted differently. tail returns a dataframe with securities as columns. iloc returns a series with the securities as the index.


# The following returns a dataframe of values with the date as the index  
sma_50.tail(1)  
sma_100.tail(1)

# The following returns a series of values with securities as the index  
sma_50.iloc[-1]  
sma_100.iloc[-1]

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Many thanks!