Get time series data for each constituent in an equity index

I'm trying to make a stock universe with historical price data for each constituent of the Euro Stoxx 50 equity index.

However, as I am a new user, I can't seem to figure out the process.

This is what I have so far.

I thus end up with 50 small dataframes, one for each constituent in the Euro Stoxx 50. I would like to merge all these into 1 dataframe, which I could use as a stock universe.

Would be great if anyone could help!

Thanks.

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python

index

time-series

constituents

datastream-api

dsws-api

Accepted answers

Jirapongse

@mathieu.debaets

From the "LDJES50I|L" request, you can get the list of items. Then, change the list of items to a comma-separated string which can be used in the second request.

The code looks like:

df = ds.get_data(tickers="LDJES50I|L", fields=["MNEM"], kind=0)
tickerList = df["Value"].tolist()
tickerString = ",".join(tickerList)
df1 = ds.get_data (tickers=tickerString, fields=['P'])
df1

The output is:

All comments

Pedro.Alexandre1

Hi Mathieu.debaets,

From the syntax that you are using, I would say that you are not using the Eikon Data API. But a Datastream library, what I suppose do not support the functionality you are looking for. You need to make the adjustment of your python code to handle the edition of the dataframes.

You want an Eikon version it would be:

value='0#.STOXX50E'
lista, err = ek.get_data(value,'RData')
lista=list(lista.Instrument[~lista.Instrument.isnull()].values)

df = ek.get_timeseries(lista,'CLOSE',
                        start_date="2019-08-01",   
                        end_date="2019-09-11",interval="daily",normalize=True)
df.head()

        Date   Security  Field   Value
0 2019-08-01  DPWGn.DE   CLOSE  29.400
1 2019-08-02  DPWGn.DE   CLOSE  28.350
2 2019-08-05  DPWGn.DE   CLOSE  27.880
3 2019-08-06  DPWGn.DE   CLOSE  28.510
4 2019-08-07  DPWGn.DE   CLOSE  28.685

Regards,

Pedro Alexandre

Jirapongse

@mathieu.debaets

From the "LDJES50I|L" request, you can get the list of items. Then, change the list of items to a comma-separated string which can be used in the second request.

The code looks like:

df = ds.get_data(tickers="LDJES50I|L", fields=["MNEM"], kind=0)
tickerList = df["Value"].tolist()
tickerString = ",".join(tickerList)
df1 = ds.get_data (tickers=tickerString, fields=['P'])
df1

The output is:

mathieu.debaets

Found this as well!

Thanks for the help.

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